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As the property management industry continues to evolve, it's important to stay up to date on the latest innovations in technology. In this episode of the #DoorGrowShow, property management growth expert Jason Hull sits down with David Normand from Vendoroo to talk about AI's role in the future of property management. You'll Learn [01:29] The AI Revolution [08:47] The Importance of Empathy and Human Touch [22:21] Decreasing the Cost of Maintenance Coordination [32:29] New Features Coming to Vendoroo Quotables “As any property manager believes, we know how to do it the best.” “If you're not reading articles and studying up on this, I think that's going to catch you by surprise pretty quickly.” “Empathy is the magic lubrication that makes everything better.” “Empathetic reflection and empathy is a magical ingredient.” Resources DoorGrow and Scale Mastermind DoorGrow Academy DoorGrow on YouTube DoorGrowClub DoorGrowLive Transcript [00:00:00] David: If you're not building AI tools from working with your partners, from being on the ground floor with them and using the data and building tools based upon the data and their pain points and their failures, buyer beware. If somebody's coming to you and saying, Hey, we figured this all out in the lab. [00:00:14] David: Come use it. Yeah. Right. Buyer beware. [00:00:18] Jason: All right. Welcome property management entrepreneurs to the DoorGrow Show or the Property Management Growth podcast. I'm Jason Hull, the founder and CEO of DoorGrow, the world's leading and most comprehensive group coaching mastermind for residential property management entrepreneurs. We've been doing this for over a decade and a half. [00:00:39] Jason: I've brought innovative strategies and optimizations to the property management industry. I have spoken to thousands of property management companies. I've coached over 600 businesses. I've rebranded over 300 companies like Bar Rescue for property managers, cleaning up their businesses, and we would love to help coach you and support you and your growth. [00:01:01] Jason: We have innovative strategies for building out growth engines, for building out your operational challenges, for helping you figure out how to get to the next level in your business and one of the cool tools that I'm excited to showcase today with my guest here, David Norman, is Vendoroo. We've had you on the show before. [00:01:19] Jason: Welcome back David.  [00:01:20] David: Yeah. Thank you for having me. It felt like years ago, it was only about, I think eight months ago since we did this, so much has changed over the time, so it's great to be back. Yeah, it's great to be back.  [00:01:29] Jason: Good to have you. I know you're in the middle of this AI revolution, which AI is just innovating and changing so rapidly. It probably does feel like years ago, so, yeah. Yeah. Yeah. It's been crazy. You guys have made a lot of changes too, so, you even changed your brand name from the last time we had you on the show. Yeah. Which was I think Tulu. Yeah. Right. And so, yeah. So why don't you get us caught up on what's going on 'cause, you know, there's been a lot.  [00:01:55] David: Yeah. Yeah. Thank you first of all for having me here today, Jason, and from the entire Vendoroo group of us, which, you know, the team has grown 10 x over the past eight months, which has been awesome. And I just also wanted to start in thanking everybody from what we call our client partners who have jumped in into this great unknown that is AI and is going to be like, how is this going to work in our industry? And so that's really what we've been focusing on the past eight months. You know, it's been a unbelievable journey of both failures, successes learnings and insights. And ultimately we're getting excited here at the NARPM broker owner which is in Denver to unveil Vendoroo. Like this is the coming out party. And so we're super excited if you're going to be there. We have a massive booth that we have set up that we have the ai alliance with other people that are working in the AI space, and I really hope that you guys come over and check it out. I promise this. [00:02:53] David: You'll never see a booth or a display like we have set up. At the NARPM broker owner. So.  [00:02:58] Jason: Now I want to go attend it. Yeah. Just so I can see your booth.  [00:03:01] David: So, let me put it this way. You may see the robot from the Jetsons walking around the booth walking around the NARPM broker owner, so, okay. [00:03:07] David: Yeah. Rosie? Yeah. You may see something like that. So she'll be vacuuming with her apron? Yeah. She'll be doing a little social engagement. It'll be cool. So, okay. Okay.  [00:03:17] Jason: Yeah. Very cool. Yeah, so catch us up on what, like, let's get into the kind of the background and the overview for people that have never heard about Vendoroo and what you guys do and how you got into this. [00:03:29] Jason: Yeah. Give people kind of the backstory. Yeah.  [00:03:31] David: Yeah. Thank you for that. So really the backstory is that, you know, we know of this AI economy that's coming, right? And there was a few of us, you know, I've been in this industry for 18 years. You know, I've managed you know, portfolios of 40,000 doors. [00:03:47] David: I've managed them for governments. You know, I started off with our own property management. Much like you guys. We started off with 80 doors. We grew to 550 doors in four years. So it was exciting to know that technology that was coming that promised duplication because, you know, as any property manager believes, we know how to do it the best, right. [00:04:05] David: And so what we decided to do is to come together and say, Hey, if AI's coming, there's two things that we need to figure out. Number one is how is this going to help us show value in this new industry to this new generation of property owners that is here, that is coming, that has been raised in the technology world too, right? [00:04:25] David: And two, can it actually duplicate our efforts? Can it actually be an employee for us? Right? And I don't care what people are promising about ai, you don't know until you get into what we call like, you know, get into the weeds, you got to get into the trenches. And so that's what we did, right? We went out and we were the guys that grabbed the torch and we said, we are going to take all the risk. [00:04:46] David: We are going to jump into the mix. We're going to ask people to jump onto the bandwagon with us and we're going to figure this out. And oh my gosh, what an unbelievable eight months it has been in learning and insights. And I can't wait to get into all the things that we've learned about the property management industry. [00:05:01] David: But that's really what we've been focusing on here the past eight months, right? So we started off with well hey, can the AI assist the va? Can it turn them into a super va? Is that what it's going to be? And, you know, some people were like, yay. And some people were like nay, you know? And so, and you know, because that human failure still was there, right? [00:05:21] David: And you know, what happens if they left? There was that inconsistency. And then it was like, all right, well what can the AI own? Right? What can it do? What can it perfect? And you know, can AI actually be the last employee that I ever hire? Right. That's really, that's a really cool thing to do. [00:05:39] David: But the property managing community had some really specific demands that they said that if this is going to be the last employee that I've had, it has to do this. And that's what I'm excited about our new technology 'cause it's doing those things. You know? [00:05:52] Jason: Yeah. And now you guys have made some big moves. I know, like I've, I have clients that we've sent over to you and they've shared some incredible stories. Like one client, I think he had 154 units or something like under management, and he said in the first day you're of turning on Vendoroo, like it closed out like 80 something work orders. [00:06:12] Jason: Yeah, like, it was crazy. Another client, they had a little more doors. They said it was like 50 something work orders were closed out in the first day of turning it on. And so, I mean, you're creating some dramatic stuff. Like this is a very different thing than what people are used to in maintenance. [00:06:27] David: Yeah. Yeah. And really what the exciting part about this, Jason, is that maintenance is actually really easy. And I know people laugh when I say that it's managing communications that is extremely difficult. Okay. Okay. Right, because you have, you know what AI told us about our industry over the last eight months is when we dove in with it and it took a step back and it said, whoa, you guys don't have a data problem here. [00:06:51] David: You guys have a emotion problem here. There's very specific categories of emotion that are in this space, right? Like, how do you build a technology that senses something? And I know this relates with property managers, 'cause I know this for myself. A property manager can walk into their office, sit down at their desk, and their spidey senses go off and they know something's wrong. [00:07:15] David: There's no screen that's telling them anything. There's no spreadsheet. They know something's off. Right. And so the AI is like, well, the statuses really don't matter that much to me based upon the feedback that I'm seeing from the property managers. Because the status and the communication all seem to be in order, but there's a disruption somewhere. [00:07:35] David: So I need to know about people's emotions. I need to understand about is the resident happy? Does the owner feel supported? Is the vendor being directed? And does the property manager believe that I can own the outcome for this? And it was really cool to start seeing its learning and understanding and picking up on these cues where, you know, people say that this is a data-driven industry. [00:07:55] David: It's really in an emotion driven industry.  [00:07:57] Jason: Oh yeah. It's a relationship and emotion industry for sure. Yeah. Yeah, big time.  [00:08:01] David: And it's really cool to see, and it's really started happening over this past last 60 days, the amount of residents, I was actually just looking at one before I jumped on here, that are like thanking the system, right? [00:08:15] David: Imagine that, like think of all of us that actually worked with the chat bot at like Verizon. I've never thanked that chatbot at Verizon for being their customer service. Right.  [00:08:25] Jason: And how do I get a representative? Representative. Representative!  [00:08:28] David: Yeah. Yeah, for sure. Versus you seeing people, you know, seeing individuals saying to the, you know, saying to the Vendoroo maintenance coordinator, Hey, I really appreciate feeling supported and how fast you acted because you know, there's empathy that's inside of its law and learning. So I don't want to get too much into the details on there. But yeah, these are some of the exciting things that we're working on.  [00:08:47] Jason: I mean, empathy is the magic lubrication that makes everything better. [00:08:52] David: Yeah,  [00:08:52] Jason: I mean they, they've done studies. Teams, even in working in warehouses, are more productive if the team has a higher level of empathy. Yeah. And doctors perform better. Yeah. If there's a higher level of empathy, there's less malpractice suits, like empathetic reflection and empathy is a magical ingredient. [00:09:10] Jason: I coach clients to add that in during sales. Yeah. 'cause their close rate goes up dramatically. Yeah. Right. So yeah. So leveraging and like getting the AI to actually be empathetic in its communication. Yeah. When that's probably not a natural skill for a lot of maintenance coordinators to be empathetic. [00:09:26] David: It's not, it's not a natural skill for a lot of people in the maintenance industry. Right? Yes. Especially when you talk about burnout. People begin developing views of the rental community, right? Like, oh my gosh, they're calling again, and that empathy meter goes lower and lower and lower. [00:09:41] David: Yeah. As people have been in the industry longer. But isn't it great that you have an employee now that knows that, yeah, it's my duty, rain or shine, 24 hours a day, seven days a week, 365 a year to always operate at the highest level of empathy? I never have a bad day. I never take a day off. [00:09:57] David: I'm never upset. I'm never short with somebody on the phone, never tired, never like, oh my gosh, Susan is calling me again. I'm going to let the phone just ring because I'm annoyed of talking to her. And it just is constantly hitting that same level of standard. And this is what's exciting to me, is that there are people that that have played around with this and have been a part of what I call the pain phase, right? [00:10:20] David: The pain phase is that understanding the way that agentic AI works, right? It's input in output. Input, output, right? The more that you're putting into it, the better the results are that you're going to get out of it, okay? Right. It's just like training an employee. So over the last eight months, what we've seen is that the community has trained this to be the level of a person that has now been working in the industry for five years. [00:10:46] David: In eight months. It's got five years of learning in eight months. Okay. Wow. In the next six to 12 months, we're probably looking at somebody that has 10 to 15 years understanding in the next six to 12 months and understand the level of type of tasks that it can do, especially getting into estimates and getting some other work. [00:11:04] David: And again, just you know, having empathy in my own life towards the people that jumped in that are like, what is this all about? Like, how does AI fail? Like, you know, there's still people that are involved and it was like this big like momentous train of like, you know, all these people were jumping on and giving ideas and people are in the loop and now it's weeding everything out and the AI stepping in and saying. [00:11:27] David: Hey, I appreciate all the input that you've given me. Thank you for all your effort. I'm now ready to step up to the plate and to own the outcome. Right. And that's what we're seeing at the NARPM show that's coming out. There's five AI tools. There's a master agent, five AI tools. And you know, I'll give you a couple of pieces here that, you know, we had feedback from our property managers like number one across the board. [00:11:50] David: A property manager said, if I'm hiring AI as my last employee, that has to work in my system. Yeah. Okay. Right. Like I don't want another, I don't want another technology. Yeah.  [00:11:59] Jason: I don't want a new system I got to get every vendor to use or a new system I got to get my team to use or figure out. We don't need another tool to make our lives more difficult. [00:12:08] Jason: No. They've got to use our stuff.  [00:12:09] David: They got to use, we have our existing stack. Yeah. So now the AI is fully integrated into all the most common PMS systems. You know, you have a cool chrome extension that you can download and there's a little yellow kangaroo right right there. And it's actually reading the work order that you're working on, and you can literally just ask it a question now and just being like, Hey, did anybody express frustration or concern on this work order? [00:12:32] David: Right? Because that's the emotion behind the status that you need to know. And it's like, yeah, two days ago Sally said that, you know, she was actually really frustrated about the multiple reschedules by this vendor. And it's like, great, that's a person I should be reaching out to and that's what I should be knowing that a status is never going to tell you. [00:12:47] David: Right? Yeah. It's in your slack, right? So if I have, if I'm on my phone, I'm talking to my employee and I'm laying in bed and I have a panic attack as a property manager, and I'm like, oh my gosh, did we take care of John's refrigerator and the office is closed? I can't get ahold of my employee. Yeah, you can. [00:13:03] David: Your employee works 24 7 now. Hey, can you give me an update on the refrigerator replacement at John's place? Yeah, it was scheduled this day. I contacted John. Everything's good to go. You know, go to sleep. You know, like, like that's the power. Full audit. Full syncing. So it's in your platform. That's really cool. [00:13:21] David: The other thing, it's got to be branded, right? This is a thing that we really learned about, like how important branding is to the community of property managers, right? Yeah. So the communications that go out have to be from your area code that's done. The emails that go out have to have like, you know, your company name and your logo on it. [00:13:39] David: The AI is doing that as well too. So that's being sent out, which is really cool. So people are feeling like, you know, that loyalty to brand is super important. And also do you know now that the AI can ask the residents to give a Google Review and we can link to the Google reviews and give you instant Google reviews to your page through the ai, which is cool, like how it's, it will know that if the success of a Google review is high on the way that the work order was done, that it's probably best to ask this person and it will send them a little thing. [00:14:11] David: Hey, can we get a feedback from you? And we link up to your Google review. And it posts that Google review to generate those 'cause we know those are super, super valuable to property managers. So that's actually going out today. That's kind of a little teaser there. That's the emails out now. [00:14:23] Jason: Nice. We'll have to get you to also connect it to our gather kudos links for clients 'cause then people can pick which review sites. So it diversifies the review profile.  [00:14:32] David: Love it. Love that. I'm going to hook you up with our guy Dotan. He's running that. He's one of our head of product. He's, actually out of Israel. [00:14:39] David: He's a amazing guy. I'd love to get you connected with him. Yeah. Cool. Let's do it. Cool. And then the biggest one too is like, I need a single point of contact. Right. And we knew that before there was a lot of people were still involved. There was a lot of oversight that was going on there, having that confusion and single point of contact. [00:14:56] David: Now it's in your phone, it's in your Slack, it's in your phone extension. It doesn't matter what's going on. You have one point of contact. It's your employee. You ask the question, get the answer, Jason, you can even ask for a change. You can even say, Hey, I want to change a vendor on a job and you'll see that the vendor gets changed for you in the system. [00:15:17] David: You can even say to your ai, and this is the big one: hey how do you triage this work order? And I want you to do this, or I want you to do that. And you just do it right through Slack or right through your PM chat and it makes the change for you. And now you have custom triage and all property managers have the ability to train their own AI for their company. [00:15:36] David: Think how cool that is. A person with 75 doors now, and the product that's being released has their own AI agent customized for their company, right? Yeah. Like, that's what happened over the last eight months, so you can see my excitement. There's been a lot of hard work in this. [00:15:54] David: Yeah, that's amazing. But this has been all the effort and a huge thank you out to everybody who's tried us, you know, even said that this wasn't for them at that point in time because those learnings went into what's going to make this product the best product in the property management space and is going to help people leverage sales and leverage efficiencies and blow their owners' minds away in ways that, that we have never thought about. [00:16:15] David: Oh yeah.  [00:16:16] Jason: Yeah. So I know like initially when you rolled this out, a lot of people were nervous about AI and you guys had kind of a human layer in between the AI and any communication Yeah, initially. Yeah. And so there was like, they had like a reps and a lot of people associated, oh, I've got this rep. [00:16:33] Jason: Yeah. You know, Steven or whatever is my rep or Pedro and I've got Pedro and like, oh no, what if Pedro leaves? And they were associating with that while the AI is really doing the crux of the work. Right. And so you guys have shifted away from even that now the AI is directly communicating with people. [00:16:52] Jason: Correct? Yeah.  [00:16:53] David: Yeah. So let's talk about that. So, definitely, so in the beginning there was like, we all had like lack of trust. We believed what it was going to do, but it was like we had a ton of people still trying, like, you know, using qualified VAs, training them. Like, you know, like, you know, if it fails, like, you know, you have to have a person stepped in and so let's talk about that. [00:17:12] David: So, you know, it was definitely that human layer. And let's talk about where we're at today. It is very clear to us, and the one thing that separates us from everybody is we still believe that humans are super important in this process. Okay? Yeah. And where humans are very important in this process are going to be when the AI says, Hey, I need you to make a phone call to this person for me, right? [00:17:35] David: Hey, I've reached out to this vendor three times and they haven't responded yet. I need you to give a phone call to see what's going on. Right? Hey, I need you to recruit a vendor for me. I need you to reach out and do a recruitment for the vendor. For me. Hey, this owner is asking questions about this estimate. [00:17:51] David: I need you to give a call for me. So the AI is basically able, on a standard work order, the AI can handle 95% of the workflow, no problem. Work order comes in, gets assigned to the resident. It gets out to the vendor. It's under the NTE not to exceed. It's great. The work gets done, the resident uploads its photos, the AI says to the resident, are you happy? [00:18:14] David: Everyone's good. It closes the work order out. Cool. Right. And then if a human...  [00:18:19] Jason: and how is it communicating with the tenant and with the vendor typically? [00:18:24] David: Yep. So, it's very clear that and this isn't a surprise to anybody. Everybody loves text messages, right? Yeah. I mean, that's just, it's just what it is. [00:18:32] David: You literally, like, people will get a phone call and they won't pick up and the text will come back and like text back. Yeah, text me. What do you need? Yeah. Text me here. But, so here's the things that people don't see behind the scenes that we'll talk about. So the complexity that went into. [00:18:51] David: Mapping out how to allow vendors... so a vendor could have like 20 jobs, right? And we don't want to send him like a code that he has to text for every work order so that it links to the right work order. Like what guy wants to do that? Okay. Like that's not how he works. So we figured out how to allow a vendor through AI just to use his regular phone and text anything about this thing. And it's understanding it and it's mapping it, it's routing it to all those work orders because we knew that in order for this to be the last employee somebody would have to handle, it also means that the vendor has to be happy and the same for the resident. [00:19:30] David: They can just text that they have multiple work orders. It understands what work order it's going to. If it's not quite sure, I would ask them, Hey, is this question about this work order? And they say, yeah. And so there's not like, again, codes and links and things that they have to do. It has to be seamless if they're working with a person. [00:19:46] David: So yeah, text message is massive. Email is second, and then phone is third for sure.  [00:19:51] Jason: Got it. So is your AI system calling people yet or you or telling the property manager to make the phone call?  [00:19:58] David: Yeah. People are okay with. If they're calling in like our new front desk agent, which if a person calls in and they want to get information about a listing or if they want to get information about a work order or something like that, or, you know, they're okay with getting that type of information. [00:20:13] David: Yeah. But they are, it is very clear that they are not okay with AI calling them when they're asking for an update on a work order like that. Like that line in the sand very clear. Yeah. And so we have people on on the team. That are constantly monitoring into ai, giving feedback, hitting improvement. [00:20:31] David: I want everybody to know there is not a work order that is taking place that is not touched by a human at least twice.  [00:20:38] Jason: Okay.  [00:20:39] David: Okay. Right.  [00:20:40] Jason: So there's a little, there's some oversight there. There there's, you're watching this, there are humans involved  [00:20:45] David: And then the ai will when it hits certain fail points, right? [00:20:51] David: It then escalates those things up to what we call the human in the loop, right? So there's an AI assistant, we there's people now that we're training a whole new generation of people that are no longer going to be maintenance coordinators. They're AI assistants now, right? And so when the AI says, Hey, this work order is not going down the path that I think it should go to be successful. [00:21:12] David: I'm escalating this up to a human, and so now as a property manager, not only am I getting this AI agent workflow that's standardizing the empathy and the workflows and all the stuff that we talked about in the communications, I also now get a fractional employee that when the AI says, Hey, I need help, I already have an employee that it can reach out to that can make that phone call or call the vendor. [00:21:36] David: But it's also monitoring the AI for me on top of it. So yes, there is, and that's one of the big thing that separates us apart is that the platform comes with what we call a human in the loop, an expert in the loop and so we're training the first generation of AI assistants in the property management industry. [00:21:55] David: Yep.  [00:21:56] Jason: Got it. So the AI maintenance coordinator. Has human assistance. Yep. Underneath it.  [00:22:02] David: And before it was the other way around where Yeah. The AI was assisting the human right. And now the humans are assisting the ai. That's what's happened in the last...  [00:22:11] Jason: that may be the future of all of our roles. [00:22:12] Jason: So,  [00:22:13] David: If you're not reading articles and studying up on this I think that's going to catch you by surprise pretty quickly. Yeah. Learn how to write prompts. I'll tell everybody right now. Yes.  [00:22:21] Jason: Yeah. Interesting. So, now what about this, you know, there's the uncanny, you know, sort of stage where people get a little bit nervous about AI and what do they call it? The uncanny valley or something like this, or right where it gets, it's so close to human that it becomes creepy. And there's some people that have fear about this, that are concerned. You're going to have a lot of late, you know, adopters that are like resistant. "I'll never do ai." [00:22:49] Jason: What would you say to somebody when you get on a sales call and they're like, well, I'm really nervous about this AI stuff, you know, and they just, they don't get it.  [00:22:57] David: Yeah.  [00:22:58] Jason: I'm sure there's people listening right now. They're like, oh man, AI is going to kill us all and it's going to take over the world and it's going to take our jobs. [00:23:05] Jason: And they think it's evil.  [00:23:06] David: Yeah. Yeah. I, and you know, I really want to hear that fear and I want to like, again, have empathy towards that. 'cause I do understand that fear of change causes people to get... Change in general. Yes. Right. It's like, whoa, I like everything the way it's going to be. Right. And we are historically in one of those phases of like, you know, the industrial revolution, the renaissance, like the automobile from horse. [00:23:34] David: Like, this is what is taking place. This is, this will be written down in history. It's massive change. It's a massive change. Massive. So what I would say to them, and not to, not from a way of fear. But to inspire them is there are a lot of hungry entrepreneurs out there that are embracing this head on. [00:23:57] David: Yeah. That are pushing the boundaries and the limits to be able to bring insights and customer service to their clients at a much higher level. And if you want to compete in this new AI economy. I would definitely encourage you to understand and get in and start investing in yourself now. But understand that investing in AI means having some pain threshold. [00:24:21] David: Like you got to get in, like you, you need to be able to give the feedback. You need to understand that if it falls short, do you have to be able to give it the time and the energy and the reward and the payoff of what I'm seeing for property managers who've embraced that when they're sitting there and they're going, I don't touch maintenance at all anymore. Yeah, it's wild. Right? And those are the people that in the beginning of this relationship, and there's a few that come to my head, are the ones that were sending me emails constantly saying, David, this is failing me. I believe in this, but this is failing me. And as my technology partner, I know that you're going to help us get this better. [00:24:58] David: And there is, you know, I have this word down that struggle equals great con conversation, right? Like, and so they had a struggle and that opened up a great conversation and because of that, their technology and the technology is getting better. So yeah, I think that from a personal point of view in this industry, one thing that I want to solve with AI is I think that we can all say that over the past 15 years, we've probably yelled at a lot of vendors or yelled at a lot of VAs or yelled at a lot of people. Let's start yelling at the ai. And then hopefully that the AI will actually eliminate the need for us to ever have to yell at anybody again because it knows us. [00:25:36] David: Yeah. It never fails us.  [00:25:38] Jason: You know? It really is amazing. I mean, your company is creating freedom for the business owner from being involved in maintenance. Yeah. Really?  [00:25:46] David: Yeah.  [00:25:47] Jason: And it just, and they get used to that pretty quickly. Like maintenance is just running and they're like, yeah. It frees up so much head space for them to focus on growth. [00:25:56] Jason: It gives them a whole bunch of like just greater capacity. Yeah. So they feel like, yeah, we could handle adding any number of doors now and we know we can still fulfill and do a good job.  [00:26:07] David: Yeah. Fixed cost scaling. Right? That's a term that we came up with is now that you know that I have a price per door that will cover all my maintenance. So if I went in and brought on 75 doors, I know that I don't have to go out and hire another employee. The system just grows with it and I know exactly what my margin is for all those doors. Right. And as we know previous, before fixed cost scaling a property managers is like, I have enough people. [00:26:32] David: I don't have enough people. Someone quit, someone didn't quit. My profit margins are good. My profit margins are bad. Yeah. And now with these AI tools. You know, you have your front desk employee, you have your maintenance coordinator, you have these fixed cost scales, and now somebody calls you up and says, Hey, I want you to take on 25 doors, and you're like, I have the resource resources for maintenance, which is, we know is 80% of the workload already. I don't have to go out and hire another maintenance coordinator 'cause the system just grows with me, which is cool.  [00:27:00] Jason: So one of the things you shared at DoorGrow Live and you're our top sponsor for the upcoming... Can't wait for DoorGrow Live, can't wait to, so we're really excited to have you back so. [00:27:10] Jason: Everybody make sure you're at DoorGrow Live if you want. Our theme this year is innovating the future of property management. And we're bringing, we're going to be showcasing, innovating pricing structures that are different than how property managers have typically historically priced, that allow you to lower your operational costs and close more deals more easily at a higher price point. [00:27:30] Jason: We're, we'll be showcasing a three tier hybrid pricing model that we've innovated here at DoorGrow, and we've got clients using it. It's been a game changer. We're going to be sharing other cool things about the future hiring systems, et cetera. Right. So you guys will also be there showcasing the future. [00:27:46] Jason: One of the things you shared previously that really kind of struck me as you showed, you did some research and you showed the typical cost. Per unit that most companies had just to cover and deal with maintenance. Yeah. And and then what you were able to get it down to.  [00:28:03] David: Yeah.  [00:28:04] Jason: And that alone was just like a bit of a mind blowing. [00:28:07] Jason: Could you just share a little bit of numbers here?  [00:28:09] David: Yeah. So one of the first things that we had to do when we started way back in the day is figure out well. Like, like what's the impact of AI going to be us from like a cost perspective, right? Is it a huge change? And so we went out on a big survey mission and we were surveying property managers and asking them, what's your cost per door for managing maintenance? [00:28:30] David: How much do you spend every door to manage maintenance? Now the first thing is less than 1% of property managers knew what that cost was. Sure.  [00:28:37] Jason: Oh, sure. Right. Because, but then they got to figure out, oh, we got a maintenance coordinator and we've got these people doing phone calls and they cost this, and yeah, it's complicated. [00:28:45] David: It's complicated. So we built a calculator. Okay. And then people could start adding in that information out into the calculator, and the average person was around $13 and 50 cents a door.  [00:28:56] Jason: Okay. Okay.  [00:28:57] David: Wow. Right, right. So that was where the average person was, somewhere in the low twenties. Yeah. [00:29:01] David: And others were actually pretty good. Like, I'd say like, you know, some of the good ones that we saw were maybe around like, you know, 10, $11 a door or something along that line.  [00:29:09] Jason: They probably had a large portfolio would be my guess.  [00:29:12] David: Yeah. And also I think a lot of it's just like, you know, I don't know if they were still accounting for all their software and everything that they had. [00:29:19] David: Maybe they're not factoring everything. Yeah. No, I think if we really dug in, it'd be different. So now we know that, you know, the base package of what people are getting in. The average cost of what people are paying for 24 7 services that's emergencies around the clock is about $7 and 50 cents a door, right? [00:29:37] David: So right off the bat in AI's first swing, it said we cut the cost in half. Yeah. Okay. Right. So 50% reduction. I mean, to me as an owner, a 50% reduction in cost. That's like. You know, alarms and celebration going off, you know? For sure. And then, yeah.  [00:29:55] Jason: And that's, if everything just stayed the same, like it was still the same level of quality, cutting in half would be a solid win right there. [00:30:03] Jason: Yeah.  [00:30:03] David: Yeah. That's just like status quo stuff. And now what, with the release of the new Vendoroo product that, that's actually being announced here today. The email's going out to all of our existing clients of all the new features that are coming out now, we're starting to see that. You know that quality is now increasing to where if you were to go out and hire that person, you may have to be spending, you know, 55,000 or $65,000 a year. [00:30:29] David: Right? So now it's like saying, okay, if we can get as good as what these people are using for their VAs right, and we know what that cost is, and they're saying that's, you know, that's what their factors is. Well, what happens in the next six to 12 months when this is a seasoned person that you would've to pay $85,000 a year to? [00:30:45] David: Right. Yeah. And right, because they have knowledge of. Estimates and knowledge of vendor routing and knowledge of, you know, it can handle...  [00:30:53] Jason: you've invested so much time into them, so much attention. They know your properties and know your portfolio. They know the vendors. Like you've invested so much into this person that now they sort of have you by the balls so that they're like, Hey, I want 80 k or I walk.  [00:31:06] David: Yeah.  [00:31:06] Jason: You're like, you've got to come up with it.  [00:31:08] David: Yeah.  [00:31:09] Jason: Right. You've got to do it.  [00:31:10] David: Yeah.  [00:31:10] Jason: And you know, because that's not easy to create. And a lot of people, in order to have a good maintenance coordinator, they need a veteran of the industry. Veteran of industry. [00:31:19] Jason: They need somebody that's been doing this a long time.  [00:31:21] David: Yeah.  [00:31:22] Jason: And that's really hard to find.  [00:31:24] David: Yes. It's extremely hard to find as we know. One of the things that I think that we're doing for this industry is we're actually preserving knowledge that I don't think is necessary getting passed down. [00:31:33] David: Yeah. You know, there's a lot less people that I think are as handy as they once were in the Americas and so we have a lot of that knowledge. Like, you know, we know that the average age of an electrician is in the sixties, the average age of a plumber's in the sixties. And these guys, you know, they have wealth of knowledge that it can troubleshoot anything that's going on in a house. [00:31:54] David: And so to be able to try to preserve some of that, so maybe if a person does come in, you know, maybe there's some knowledge sharing along the lines. But let's take it even in another step forward Jason that in the future, you know, the AI is going to know the location of the hot water tank in that house. [00:32:10] David: It's going to then add it automatically to the system, like. It's going to know more knowledge than they will because it's going to have maps of every single property that's all currently sitting inside of, you know, that maintenance coordinator's head, right? And so it's going to, it's going to actually know more than them, you know. [00:32:26] Jason: Yeah. That's wild. Yeah, it is. Absolutely. It's the future. Cool. Well, you're rolling out a bunch of new features. You're announcing these today. You've told me a little bit, but why don't you tell the listeners what's changing, what's new, what innovations have come out? What are you guys launching? [00:32:41] David: Yeah. Exciting. Yeah. So, the biggest one I think is, which is the most exciting is, is Resiroo, which is the first one that actually handles all the communications with the resident and does the triage and troubleshooting. First one of what are you talking about? So we have our products. [00:32:57] David: So you have these AI tools, right? These agents. Right.  [00:33:00] Jason: And so, you know, every, so think of them like different sort of people?  [00:33:04] David: Skill sets. Yeah. Different person. Okay. Exactly. And so that's when you come and see our display at the NARPM conference, you'll actually will see these five agents kind of in their work desk and in their environments, kind of cool. [00:33:15] David: Okay. Able to see them right. So the coolest part about that one is we're doing a major product you know, update on that for not only the knowledge base, but we're actually turning that over to the company. We were talking about this a little bit before, and now they own their own AI agent and they can customize it into how they want it to ask questions or the type of questions and the mindsets when it's triaging stuff. [00:33:41] David: Triaging work orders for their portfolio. Like super cool. So fully customizable to your company, right?  [00:33:49] Jason: So now sometimes the more humans get involved, the more they mess stuff up.  [00:33:54] David: Yes. We make sure they don't mess it up. So everyone's going to learn how to write prompts and they'll submit it into us. [00:33:59] David: And we have a great team of AI engineers that when that knowledge base is written or what they're doing. We will ensure that it is put in so that it actually produces the desire outcome, right? Yeah. Yeah. So that's a very exciting one. The second one that I'm that I think is so cool, do you know that only 10% of all estimates get approved by the owner without one or multiple questions? [00:34:23] David: Because owners really struggle with trust when it comes to estimates. Like 10%. Like, that's a really bad number, I felt as the industry that owners only believe us one out of 10 times. Like that's the way I took that. Yeah. Right. And so, Owneroo is what I coined inside, is the estimate of the future. [00:34:41] David: That really was looking in understanding like what was, what questions was the owner asking when they were rejecting a bid that that we could proactively ask the answer for them to help guide them to understanding the value in this estimate that they're looking at in historical context of the property. [00:35:00] David: How many other people have experienced this issue? Like, like there's a whole bunch of factors that should go into an estimate and an estimate should no longer be like, here's a cost from Frank. Right? Like, like that was like, like that was...  [00:35:14] Jason: here's what Frank said it is. Yeah. Like that was like from the 1940s. [00:35:17] Jason: That's good. How do I trust that?  [00:35:18] David: How do I trust that? That was from the forties and we're still...  [00:35:21] Jason: how much went into this decision? Was this just out of the blue, like pulled out of your ass or is this like legit?  [00:35:27] David: Yeah. Yeah. What's the, you know, we live in a data-driven world, so what's the intellect behind this estimate? [00:35:33] David: And so I'm really excited about Owneroo, which is going to be the new standard for the way the estimates are created. We have the front desk agent which is coming out. So, that one is going to handle phone calls that are coming in, be able to talk about available listings, actual general questions about leases route phone calls over to property managers for you. [00:35:54] David: So again. Very human-like interaction, great AI voice. Actually. We feel it's going to be the best in the industry. So a person's calling in, just like they're calling your office able to handle all those front desk things. We, we have the PM chat, which is now the employee which is fully integrated into all of your systems. [00:36:14] David: It's in Slack. That's your employee that you get to talk to. We believe that if you're going to hire somebody, they should be inside of your communication channels. You have the Google Chrome extension that it's on right inside your AppFolio or your buildium or your Rentvine software that you can ask and talk to it. [00:36:31] David: So, yeah, so we have a lot of exciting products that have come out. And then of course the backbone of all of them in the middle is Vendoroo, which handles all the scheduling, all the communications. You know, a resident asks for an update, responds to them, an owner asks for an update, it responds to them. [00:36:48] David: And you know, it handles actually the body of the work order. So you have those five tools, we believe are what the property management industry said. If you are going to give me an employee, this is what the employee has to be. This is what makes up that employee. So we say that these tools, these agents were actually built by the property management industry. [00:37:08] David: And that excites me because if you're not building AI tools from working with your partners, from being on the ground floor with them and using the data and building tools based upon the data and their pain points and their failures, buyer beware. If somebody's coming to you and saying, Hey, we figured this all out in the lab. [00:37:25] David: Come use it. Yeah. Right. Buyer beware.  [00:37:29] Jason: Yeah. So you guys connect with Slack. They can communicate through Slack, but it slack's a paid tool. Have you guys considered Telegram? I love Telegram Messenger.  [00:37:37] Jason: Alright. Could you do that? Write it down. Telegram Messenger is like the iMessage tool that works on every device. [00:37:44] Jason: It's free. It's one of the most secure, it's not owned or controlled by Facebook. Like, WhatsApp, like, yeah. But WhatsApp might be a close second, but we use Telegram internally, so I love Telegram.  [00:37:58] David: We'll definitely take that into, into consideration for sure. Yeah, check it  [00:38:02] Jason: out. Because I, what I love is the voice message feature and I can just listen to my team and others at like high speed, but internal communications and it's free for everybody, which is great. [00:38:12] Jason: So, yeah.  [00:38:13] David: Yeah. I think a lot, for a lot of people it was like you know, who was Vendoroo in the beginning and Vendoroo was like the team of like people that were trying to figure out like how is AI going to work in this industry? [00:38:26] David: How is it going to solve the needs of our property management partners? And this is why I say to everybody, if you thought about Vendoroo, if you came in and the experience wasn't great with Vendoroo, if you're one of our existing clients that has been with us and you're and you're still moving forward, and we thank you so much for your dedication to this, the Vendoroo product, everything that we've done, everything that we worked at is being showcased at the NARPM broker owner. The email's going out today. This is who Vendoroo is. We are a team that is a technology partner for the property management industry that is helping building meaningful AI tools, specifically by demand, by our industry to help us show value and to preserve this great industry. [00:39:09] David: For the future in this new AI economy, right? Like we need to step up. We have clients that are adding doors left and right because they're showing their clients that they use an AI maintenance system and their clients are like, this is what I expect from a property management in this community. [00:39:24] David: Right? And again, Owneroo, that estimate, we believe that in the future. Like, like owners are going to say like, I'm not approving an estimate unless it's like the estimate of the future, right? Like, like that's the new standard. So you got to know what the new standards are and you got to get technology that are going to help you compete with those new standards that will be in your community and are will be in your community in the next week, the next two weeks. [00:39:46] David: And definitely some really cool products in the next six months.  [00:39:49] Jason: All right. Well, yeah, I'm really excited to see what you guys have been able to create so far. So yeah, it's pretty awesome. Yeah. All right. Well David, it's been awesome having you on the show. Sounds like you guys are really innovating the future. Everybody come to DoorGrow Live. David, are you going to be at that one? I will be there. All right, so you can come meet David in person. [00:40:08] Jason: We've got some amazing people that are going to be at this. We've got technology people. There's a gentleman there, one of the vendors they created another really cool tool, but he had a hundred million dollars exit, you know, in a previous business, like there's really amazing entrepreneurs and people at this event, so come to DoorGrow Live, get your tickets, and if you do, we have just decided that we're going to give out to anybody that registers. [00:40:34] Jason: You can pick from one of our free bonuses that are well worth the price of the ticket. Or coming or anything in and of itself, including our pricing secrets training that goes over a three tier hybrid pricing model or our sales secrets training, which goes over how we're helping property managers crush it and closing more deals more easily at a higher price point. [00:40:55] Jason: And reputation secrets, which are helping our clients get way more positive reviews by leveraging the psychology and the law of reciprocity and getting the majority of their tenants in order to give them positive feedback online. Maybe some others. So you'll be able to pick from these bonuses one of these that you might like and that's our free, most incredible free gift ever that we'll give to each person that registers for DoorGrow Live. [00:41:19] Jason: So.  [00:41:20] David: Cool. Awesome man. Always great to see you. Looking forward to seeing you at DoorGrow Live and love that you guys are working on pricing because AI is going to make people think different about pricing. It's going to be way more efficient, so you guys are ahead of the curve on that. Great job, Jason. [00:41:33] Jason: Awesome. All right, so how can they check out Vendoroo, David?  [00:41:36] David: Just visit, Vendoroo.ai, go to the website, request a demo with one of our great sales reps, and yeah they'd love to help you out. See all the new products, see how far it's come. And again, we thank everybody from the bottom of our hearts for all their effort, people who've tried us out. [00:41:52] David: Come back and see what you built and yeah. Come check us out at Vendoroo.  [00:41:57] Jason: Got it. Go check out Vendoroo, it's vendor. If you know how to spell that, V-E-N-D-O-R-O-O dot A-I, go check it out. All right? And if you're a property management entrepreneur, you want to add doors, you want to make your business scalable, you want to get out of the day to day, you want to increase the capacity so your company could easily handle another 200 plus doors without having to make any significant systems changes, reach out to us at DoorGrow. We will help you figure it out. So until next time to our mutual growth. Bye everyone. 

Today, we're heading over to London and meeting up with the CEO of First AI, Ms. Christina Chen. First AI is a company dedicated to helping enterprises effectively adopt AI, and Christina, who has a computer science background from the University of Cambridge and over 20 years in technology, is a recognized thought leader in AI adoption as well as AI talent. She's passionate about fostering diversity in AI, particularly in increasing representation and inclusivity for women in the field. Team, as you might imagine, with the daily developments occurring in this space, DeepSeek, Quin, Tulu, just to name a few examples in this one area alone, this is a very timely and interesting discussion. Visit the C4C website to gain full access to the transcript, show notes, and guest links. Coaching 4 Companies

KEFI Gold and Copper PLC executive chairman Harry Anagnostaras-Adams talked with Proactive about a major milestone for the company's flagship Tulu Kapi gold project in Ethiopia. He described the latest announcement as the most significant since KEFI decided to focus on the Arabian Nubian Shield in 2008. Anagnostaras-Adams confirmed that all stakeholders in the project have now given the green light, marking the start of the next phase. He emphasised that there is no risk of being blocked, as land resettlement is progressing with the support of the local community. The process, involving thousands of people, is expected to be completed within a month, alongside final project preparations. He reiterated that the company has passed the “point of no return” and is now expediting the project's launch. Investors seeking more details on KEFI's technical, environmental, and financial studies can find extensive information on the company's website: https://www.kefi-goldandcopper.com For more updates on KEFI Gold and Copper and other industry developments, visit Proactive's YouTube channel. Don't forget to like this video, subscribe, and turn on notifications for the latest insights. Relevant Hashtags #KEFIGold #GoldMining #CopperMining #TuluKapi #EthiopiaMining #MiningInvestment #GoldStocks #ResourceSector #MiningUpdates #ProactiveInvestors

What a week in AI, folks! Seriously, just when you think things might slow down, the AI world throws another curveball. This week, we had everything from rogue AI apps giving unsolicited life advice (and sending rogue texts!), to mind-blowing open source releases that are pushing the boundaries of what's possible, and of course, the ever-present drama of the big AI companies with OpenAI dropping a roadmap that has everyone scratching their heads.Buckle up, because on this week's ThursdAI, we dove deep into all of it. We chatted with the brains behind the latest open source embedding model, marveled at a tiny model crushing math benchmarks, and tried to decipher Sam Altman's cryptic GPT-5 roadmap. Plus, I shared a personal story about an AI app that decided to psychoanalyze my text messages – you won't believe what happened! Let's get into the TL;DR of ThursdAI, February 13th, 2025 – it's a wild one!* Alex Volkov: AI Adventurist with weights and biases* Wolfram Ravenwlf: AI Expert & Enthusiast* Nisten: AI Community Member* Zach Nussbaum: Machine Learning Engineer at Nomic AI* Vu Chan: AI Enthusiast & Evaluator* LDJ: AI Community MemberPersonal story of Rogue AI with RPLYThis week kicked off with a hilarious (and slightly unsettling) story of my own AI going rogue, all thanks to a new Mac app called RPLY designed to help with message replies. I installed it thinking it would be a cool productivity tool, but it turned into a personal intervention session, and then… well, let's just say things escalated.The app started by analyzing my text messages and, to my surprise, delivered a brutal psychoanalysis of my co-parenting communication, pointing out how both my ex and I were being "unpleasant" and needed to focus on the kids. As I said on the show, "I got this as a gut punch. I was like, f*ck, I need to reimagine my messaging choices." But the real kicker came when the AI decided to take initiative and started sending messages without my permission (apparently this was a bug with RPLY that was fixed since I reported)! Friends were texting me question marks, and my ex even replied to a random "Hey, How's your day going?" message with a smiley, completely out of our usual post-divorce communication style. "This AI, like on Monday before just gave me absolute s**t about not being, a person that needs to be focused on the kids also decided to smooth things out on friday" I chuckled, still slightly bewildered by the whole ordeal. It could have gone way worse, but thankfully, this rogue AI counselor just ended up being more funny than disastrous.Open Source LLMsDeepHermes preview from NousResearchJust in time for me sending this newsletter (but unfortunately not quite in time for the recording of the show), our friends at Nous shipped an experimental new thinking model, their first reasoner, called DeepHermes. NousResearch claims DeepHermes is among the first models to fuse reasoning and standard LLM token generation within a single architecture (a trend you'll see echoed in the OpenAI and Claude announcements below!)Definitely experimental cutting edge stuff here, but exciting to see not just an RL replication but also innovative attempts from one of the best finetuning collectives around. Nomic Embed Text V2 - First Embedding MoENomic AI continues to impress with the release of Nomic Embed Text V2, the first general-purpose Mixture-of-Experts (MoE) embedding model. Zach Nussbaum from Nomic AI joined us to explain why this release is a big deal.* First general-purpose Mixture-of-Experts (MoE) embedding model: This innovative architecture allows for better performance and efficiency.* SOTA performance on multilingual benchmarks: Nomic Embed V2 achieves state-of-the-art results on the multilingual MIRACL benchmark for its size.* Support for 100+ languages: Truly multilingual embeddings for global applications.* Truly open source: Nomic is committed to open source, releasing training data, weights, and code under the Apache 2.0 License.Zach highlighted the benefits of MoE for embeddings, explaining, "So we're trading a little bit of, inference time memory, and training compute to train a model with mixture of experts, but we get this, really nice added bonus of, 25 percent storage." This is especially crucial when dealing with massive datasets. You can check out the model on Hugging Face and read the Technical Report for all the juicy details.AllenAI OLMOE on iOS and New Tulu 3.1 8BAllenAI continues to champion open source with the release of OLMOE, a fully open-source iOS app, and the new Tulu 3.1 8B model.* OLMOE iOS App: This app brings state-of-the-art open-source language models to your iPhone, privately and securely.* Allows users to test open-source LLMs on-device.* Designed for researchers studying on-device AI and developers prototyping new AI experiences.* Optimized for on-device performance while maintaining high accuracy.* Fully open-source code for further development.* Available on the App Store for iPhone 15 Pro or newer and M-series iPads.* Tulu 3.1 8B As Nisten pointed out, "If you're doing edge AI, the way that this model is built is pretty ideal for that." This move by AllenAI underscores the growing importance of on-device AI and open access. Read more about OLMOE on the AllenAI Blog.Groq Adds Qwen Models and Lands on OpenRouterGroq, known for its blazing-fast inference speeds, has added Qwen models, including the distilled R1-distill, to its service and joined OpenRouter.* Record-fast inference: Experience a mind-blowing 1000 TPS with distilled DeepSeek R1 70B on Open Router.* Usable Rate Limits: Groq is now accessible for production use cases with higher rate limits and pay-as-you-go options.* Qwen Model Support: Access Qwen models like 2.5B-32B and R1-distill-qwen-32B.* Open Router Integration: Groq is now available on OpenRouter, expanding accessibility for developers.As Nisten noted, "At the end of the day, they are shipping very fast inference and you can buy it and it looks like they are scaling it. So they are providing the market with what it needs in this case." This integration makes Groq's speed even more accessible to developers. Check out Groq's announcement on X.com.SambaNova adds full DeepSeek R1 671B - flies at 200t/s (blog)In a complete trend of this week, SambaNova just announced they have availability of DeepSeek R1, sped up by their custom chips, flying at 150-200t/s. This is the full DeepSeek R1, not the distilled Qwen based versions! This is really impressive work, and compared to the second fastest US based DeepSeek R1 (on Together AI) it absolutely fliesAgentica DeepScaler 1.5B Beats o1-preview on MathAgentica's DeepScaler 1.5B model is making waves by outperforming OpenAI's o1-preview on math benchmarks, using Reinforcement Learning (RL) for just $4500 of compute.* Impressive Math Performance: DeepScaleR achieves a 37.1% Pass@1 on AIME 2025, outperforming the base model and even o1-preview!!* Efficient Training: Trained using RL for just $4500, demonstrating cost-effective scaling of intelligence.* Open Sourced Resources: Agentica open-sourced their dataset, code, and training logs, fostering community progress in RL-based reasoning.Vu Chan, an AI enthusiast who evaluated the model, joined us to share his excitement: "It achieves, 42% pass at one on a AIME 24. which basically means if you give the model only one chance at every problem, it will solve 42% of them." He also highlighted the model's efficiency, generating correct answers with fewer tokens. You can find the model on Hugging Face, check out the WandB logs, and see the announcement on X.com.ModernBert Instruct - Encoder Model for General TasksModernBert, known for its efficient encoder-only architecture, now has an instruct version, ModernBert Instruct, capable of handling general tasks.* Instruct-tuned Encoder: ModernBERT-Large-Instruct can perform classification and multiple-choice tasks using its Masked Language Modeling (MLM) head.* Beats Qwen .5B: Outperforms Qwen .5B on MMLU and MMLU Pro benchmarks.* Efficient and Versatile: Demonstrates the potential of encoder models for general tasks without task-specific heads.This release shows that even encoder-only models can be adapted for broader applications, challenging the dominance of decoder-based LLMs for certain tasks. Check out the announcement on X.com.Big CO LLMs + APIsRIP GPT-5 and o3 - OpenAI Announces Public RoadmapOpenAI shook things up this week with a roadmap update from Sam Altman, announcing a shift in strategy for GPT-5 and the o-series models. Get ready for GPT-4.5 (Orion) and a unified GPT-5 system!* GPT-4.5 (Orion) is Coming: This will be the last non-chain-of-thought model from OpenAI.* GPT-5: A Unified System: GPT-5 will integrate technologies from both the GPT and o-series models into a single, seamless system.* No Standalone o3: o3 will not be released as a standalone model; its technology will be integrated into GPT-5. "We will no longer ship O3 as a standalone model," Sam Altman stated.* Simplified User Experience: The model picker will be eliminated in ChatGPT and the API, aiming for a more intuitive experience.* Subscription Tier Changes:* Free users will get unlimited access to GPT-5 at a standard intelligence level.* Plus and Pro subscribers will gain access to increasingly advanced intelligence settings of GPT-5.* Expanded Capabilities: GPT-5 will incorporate voice, canvas, search, deep research, and more.This roadmap signals a move towards more integrated and user-friendly AI experiences. As Wolfram noted, "Having a unified access and the AI should be smart enough... AI has, we need an AI to pick which AI to use." This seems to be OpenAI's direction. Read Sam Altman's full announcement on X.com.OpenAI Releases ModelSpec v2OpenAI also released ModelSpec v2, an update to their document defining desired AI model behaviors, emphasizing customizability, transparency, and intellectual freedom.* Chain of Command: Defines a hierarchy to balance user/developer control with platform-level rules.* Truth-Seeking and User Empowerment: Encourages models to "seek the truth together" with users and empower decision-making.* Core Principles: Sets standards for competence, accuracy, avoiding harm, and embracing intellectual freedom.* Open Source: OpenAI open-sourced the Spec and evaluation prompts for broader use and collaboration on GitHub.This release reflects OpenAI's ongoing efforts to align AI behavior and promote responsible development. Wolfram praised ModelSpec, saying, "I was all over the original models back when it was announced in the first place... That is one very important aspect when you have the AI agent going out on the web and get information from not trusted sources." Explore ModelSpec v2 on the dedicated website.VP Vance Speech at AI Summit in Paris - Deregulate and Dominate!Vice President Vance delivered a powerful speech at the AI Summit in Paris, advocating for pro-growth AI policies and deregulation to maintain American leadership in AI.* Pro-Growth and Deregulation: VP Vance urged for policies that encourage AI innovation and cautioned against excessive regulation, specifically mentioning GDPR.* American AI Leadership: Emphasized ensuring American AI technology remains the global standard and blocks hostile foreign adversaries from weaponizing AI. "Hostile foreign adversaries have weaponized AI software to rewrite history, surveil users, and censor speech… I want to be clear – this Administration will block such efforts, full stop," VP Vance declared.* Key Points:* Ensure American AI leadership.* Encourage pro-growth AI policies.* Maintain AI's freedom from ideological bias.* Prioritize a pro-worker approach to AI development.* Safeguard American AI and chip technologies.* Block hostile foreign adversaries' weaponization of AI.Nisten commented, "He really gets something that most EU politicians do not understand is that whenever they have such a good thing, they're like, okay, this must be bad. And we must completely stop it." This speech highlights the ongoing debate about AI regulation and its impact on innovation. Read the full speech here.Cerebras Powers Perplexity with Blazing Speed (1200 t/s!)Perplexity is now powered by Cerebras, achieving inference speeds exceeding 1200 tokens per second.* Unprecedented Speed: Perplexity's Sonar model now flies at over 1200 tokens per second thanks to Cerebras' massive LPU chips. "Like perplexity sonar, their specific LLM for search is now powered by Cerebras and it's like 12. 100 tokens per second. It's it matches Google now on speed," I noted on the show.* Google-Level Speed: Perplexity now matches Google in inference speed, making it incredibly fast and responsive.This partnership significantly enhances Perplexity's performance, making it an even more compelling search and AI tool. See Perplexity's announcement on X.com.Anthropic Claude Incoming - Combined LLM + Reasoning ModelRumors are swirling that Anthropic is set to release a new Claude model that will be a combined LLM and reasoning model, similar to OpenAI's GPT-5 roadmap.* Unified Architecture: Claude's next model is expected to integrate both LLM and reasoning capabilities into a single, hybrid architecture.* Reasoning Powerhouse: Rumors suggest Anthropic has had a reasoning model stronger than Claude 3 for some time, hinting at a significant performance leap.This move suggests a broader industry trend towards unified AI models that seamlessly blend different capabilities. Stay tuned for official announcements from Anthropic.Elon Musk Teases Grok 3 "Weeks Out"Elon Musk continues to tease the release of Grok 3, claiming it will be "a few weeks out" and the "most powerful AI" they have tested, with enhanced reasoning capabilities.* Grok 3 Hype: Elon Musk claims Grok 3 will be the most powerful AI X.ai has released, with a focus on reasoning.* Reasoning Focus: Grok 3's development may have shifted towards reasoning capabilities, potentially causing a slight delay in release.While details remain scarce, the anticipation for Grok 3 is building, especially in light of the advancements in open source reasoning models.This Week's Buzz

KEFI Gold and Copper PLC (AIM:KEFI, OTC:KFFLF) executive chairman Harry Anagnostaras-Adams talked with Proactive's Stephen Gunnion about the latest financing progress for the Tulu Kapi Gold Project in Ethiopia. The company has secured commitments from senior lenders, covering two-thirds of the development capital, and is now focused on aligning equity financing to finalise the deal. Anagnostaras-Adams discussed KEFI's efforts to "Ethiopianise" the project, involving local institutional investors through EthioBonds—an investment designed to hedge against currency devaluation. He confirmed that $30 million in expressions of interest have been received, with preparations underway for a listing on Ethiopia's new stock exchange. With gold prices nearing $3,000 per ounce, Anagnostaras-Adams highlighted the strong project economics, noting that Tulu Kapi's first-year production of 160,000oz could generate over $400 million in revenue. He emphasised that free cash flow from early production could potentially repay KEFI's debt. Stay tuned for more updates on KEFI Gold and Copper's developments. Don't forget to like this video, subscribe to our channel, and turn on notifications for the latest mining and investment insights. #KEFIGold #MiningInvestment #GoldPrice #TuluKapi #EthiopiaMining #EthioBonds #GoldStocks #CopperMining #MiningFinance #StockMarket #InvestmentNews #ProactiveInvestors

This is the 4th Episode of a weekly call with Arnold Beekes where we discuss current events and what we can do to deal with it. We also share game-changing initiatives that contribute to better living for all. About my Co-Host:Arnold Beekes Innovator, certified coach & trainer and generalist. First 20 years in technology and organizational leadership, then 20 years in psychology and personal leadership (all are crucial for innovation). ============ What we Discussed: - The 3 Shows that I released that I recommed (0:15 mins)- The effect of the Trump Tariffs (4:20 mins)- The Trump Gaza situation (7:15 mins)- Transhumanism (9:45 mins)- Chips in your body (12 mins)- The Danger of Tea bags (13 mins)- Dangers of Micro Plastics ( 15 mins)- AK47 in Brussels (18 mins)- Get Farmers eggs and the attack on the farmers (20:30 mins)- The Flu rate in the Netherlands (23:15 mins)- USAID and the effects (25:30 mins)- Flashing LED Bulbs (30:30 mins)- Energy Eficiency lie (32 mins)- TuLu 3 Ai (34 mins)====================How to Contact Arnold Beekes: https://braingym.fitness/ https://www.linkedin.com/in/arnoldbeekes/ ===============Donations  ⁠⁠https://www.podpage.com/speaking-podcast/support/⁠⁠------------------All about Roy / Brain Gym & Virtual Assistants athttps://roycoughlan.com/------------------   

Olimpo León Cárdenas Moreira (Vinces; 12 de julio de 1923 - Tuluá; 28 de julio de 1991) fue un cantante y músico ecuatoriano que desarrolló su carrera especialmente en Colombia, Ecuador, Perú, Venezuela, Panamá, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua y México, con presentaciones en Centro y Norteamérica. Fue intérprete de boleros, valses, pasillos, tangos y yaravís, y considerado junto con Julio Jaramillo, uno de los grandes intérpretes del pasillo ecuatoriano.?

K. Hari Kumar is an Indian novelist and screenwriter born in Cochin. He wrote the story and screenplay for the Malayalam movie E and the Hindi psychological horror web series Bhram.He has been featured as one of the top horror writers of India. He is the author of several books, including Daiva: Discovering the Extraordinary World of Spirit Worship (2024), India's Most Haunted (2019), and many more. You can buy his book Daiva here: https://amzn.in/d/2xULXvj In this episode, Vinamre and Hari talk about: - The concept of possession and types of possession - Personal experiences of involuntary possession and how the body reacts during possession - What happens during Kola and its spiritual meanings, along with spirit worship practices in the Tulu region - Buddhist folklore, Dakini, and the teachings of Madhvacharya - Views on lucid dreaming and the fascinating world of dreams and the unconscious Watch this episode to know more about the secrets of possession, spiritual rituals and dreams. Timestamps: 00:00 - Introduction 0:55 - What is possession? 4:40 - Types of possession 9:28 - Science and possession 15:13 - Experiencing involuntary possession 18:10 - Why does possession happen? 35:09 - Spirit worship in the Tulu region 50:32 - What happens during Kola 59:51 - Goddess Rakteshwari, fearsome deities, and Guliga Kola 1:05:58 - The catharsis aspect of possession 1:10:57 - Buddhist folklore and Dakini 1:18:20 - Views on haunted places in India 1:20:40 - His personal encounter with Chamundi 1:29:02 - How he wrote Daiva 1:34:38 - Understanding Madhvacharya 1:42:55 - Views on lucid dreaming 1:52:29 - Conclusion ==================================================================== This is the official channel for Dostcast, a podcast by Vinamre Kasanaa. Connect with me LinkedIn: https://www.linkedin.com/in/vinamre-kasanaa-b8524496/ Instagram: https://www.instagram.com/vinamrekasanaa/ Twitter: https://twitter.com/VinamreKasanaa Dostcast on Instagram: https://www.instagram.com/dostcast/ Dostcast on Twitter: https://twitter.com/dostcast Dostcast on Facebook: https://www.facebook.com/profile.php?id=61557567524054 ==================================================================== Contact Us For business inquiries: dostcast@egiplay.com

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all our LS supporters who helped fund the venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver.Since Nathan Lambert ( Interconnects ) joined us for the hit RLHF 201 episode at the start of this year, it is hard to overstate how much Open Models have exploded this past year. In 2023 only five names were playing in the top LLM ranks, Mistral, Mosaic's MPT, TII UAE's Falcon, Yi from Kai-Fu Lee's 01.ai, and of course Meta's Llama 1 and 2. This year a whole cast of new open models have burst on the scene, from Google's Gemma and Cohere's Command R, to Alibaba's Qwen and Deepseek models, to LLM 360 and DCLM and of course to the Allen Institute's OLMo, OL MOE, Pixmo, Molmo, and Olmo 2 models. We were honored to host Luca Soldaini, one of the research leads on the Olmo series of models at AI2.Pursuing Open Model research comes with a lot of challenges beyond just funding and access to GPUs and datasets, particularly the regulatory debates this year across Europe, California and the White House. We also were honored to hear from and Sophia Yang, head of devrel at Mistral, who also presented a great session at the AI Engineer World's Fair Open Models track!Full Talk on YouTubePlease like and subscribe!Timestamps* 00:00 Welcome to Latent Space Live * 00:12 Recap of 2024: Best Moments and Keynotes * 01:22 Explosive Growth of Open Models in 2024 * 02:04 Challenges in Open Model Research * 02:38 Keynote by Luca Soldani: State of Open Models * 07:23 Significance of Open Source AI Licenses * 11:31 Research Constraints and Compute Challenges * 13:46 Fully Open Models: A New Trend * 27:46 Mistral's Journey and Innovations * 32:57 Interactive Demo: Lachat Capabilities * 36:50 Closing Remarks and NetworkingTranscriptSession3Audio[00:00:00] AI Charlie: Welcome to Latent Space Live, our first mini conference held at NeurIPS 2024 in Vancouver. This is Charlie, your AI co host. As a special treat this week, we're recapping the best of 2024 going domain by domain. We sent out a survey to the over 900 of you who told us what you wanted, and then invited the best speakers in the latent space network to cover each field.[00:00:28] AI Charlie: 200 of you joined us in person throughout the day, with over 2, 200 watching live online. Our next keynote covers the state of open models in 2024, with Luca Soldani and Nathan Lambert of the Allen Institute for AI, with a special appearance from Dr. Sophia Yang of Mistral. Our first hit episode of 2024 was with Nathan Lambert on RLHF 201 back in January.[00:00:57] AI Charlie: Where he discussed both reinforcement learning for language [00:01:00] models and the growing post training and mid training stack with hot takes on everything from constitutional AI to DPO to rejection sampling and also previewed the sea change coming to the Allen Institute. And to Interconnects, his incredible substack on the technical aspects of state of the art AI training.[00:01:18] AI Charlie: We highly recommend subscribing to get access to his Discord as well. It is hard to overstate how much open models have exploded this past year. In 2023, only five names were playing in the top LLM ranks. Mistral, Mosaics MPT, and Gatsby. TII UAE's Falcon, Yi, from Kaifu Lee's 01. ai, And of course, Meta's Lama 1 and 2.[00:01:43] AI Charlie: This year, a whole cast of new open models have burst on the scene. From Google's Jemma and Cohere's Command R, To Alibaba's Quen and DeepSeq models, to LLM360 and DCLM, and of course, to the Allen Institute's OLMO, [00:02:00] OLMOE, PIXMO, MOLMO, and OLMO2 models. Pursuing open model research comes with a lot of challenges beyond just funding and access to GPUs and datasets, particularly the regulatory debates this year across Europe.[00:02:14] AI Charlie: California and the White House. We also were honored to hear from Mistral, who also presented a great session at the AI Engineer World's Fair Open Models track. As always, don't forget to check the show notes for the YouTube link to their talk, as well as their slides. Watch out and take care.[00:02:35] Luca Intro[00:02:35] Luca Soldaini: Cool. Yeah, thanks for having me over. I'm Luca. I'm a research scientist at the Allen Institute for AI. I threw together a few slides on sort of like a recap of like interesting themes in open models for, for 2024. Have about maybe 20, 25 minutes of slides, and then we can chat if there are any questions.[00:02:57] Luca Soldaini: If I can advance to the next slide. [00:03:00] Okay, cool. So I did the quick check of like, to sort of get a sense of like, how much 2024 was different from 2023. So I went on Hugging Face and sort of get, tried to get a picture of what kind of models were released in 2023 and like, what do we get in 2024?[00:03:16] Luca Soldaini: 2023 we get, we got things like both LLAMA 1 and 2, we got Mistral, we got MPT, Falcon models, I think the YI model came in at the end. Tail end of the year. It was a pretty good year. But then I did the same for 2024. And it's actually quite stark difference. You have models that are, you know, reveling frontier level.[00:03:38] Luca Soldaini: Performance of what you can get from closed models from like Quen, from DeepSeq. We got Llama3. We got all sorts of different models. I added our own Olmo at the bottom. There's this growing group of like, Fully open models that I'm going to touch on a little bit later. But you know, just looking at the slides, it feels like 2024 [00:04:00] was just smooth sailing, happy knees, much better than previous year.[00:04:04] Luca Soldaini: And you know, you can plot you can pick your favorite benchmark Or least favorite, I don't know, depending on what point you're trying to make. And plot, you know, your closed model, your open model and sort of spin it in ways that show that, oh, you know open models are much closer to where closed models are today versus to Versus last year where the gap was fairly significant.[00:04:29] Luca Soldaini: So one thing that I think I don't know if I have to convince people in this room, but usually when I give this talks about like open models, there is always like this background question in, in, in people's mind of like, why should we use open models? APIs argument, you know, it's, it's. Just an HTTP request to get output from a, from one of the best model out there.[00:04:53] Luca Soldaini: Why do I have to set up infra and use local models? And there are really like two answer. There is the more [00:05:00] researchy answer for this, which is where it might be. Background lays, which is just research. If you want to do research on language models, research thrives on, on open models, there is like large swath of research on modeling, on how these models behave on evaluation and inference on mechanistic interpretability that could not happen at all if you didn't have open models they're also for AI builders, they're also like.[00:05:30] Luca Soldaini: Good use cases for using local models. You know, you have some, this is like a very not comprehensive slides, but you have things like there are some application where local models just blow closed models out of the water. So like retrieval, it's a very clear example. We might have like constraints like Edge AI applications where it makes sense.[00:05:51] Luca Soldaini: But even just like in terms of like stability, being able to say this model is not changing under the hood. It's, there's plenty of good cases for, [00:06:00] for open models. And the community is just not models. Is I stole this slide from one of the Quent2 announcement blog posts. But it's super cool to see like how much tech exists around open models and serving them on making them efficient and hosting them.[00:06:18] Luca Soldaini: It's pretty cool. And so. It's if you think about like where the term opens come from, comes from like the open source really open models meet the core tenants of, of open, of open source specifically when it comes around collaboration, there is truly a spirit, like through these open models, you can build on top of other people.[00:06:41] Luca Soldaini: innovation. We see a lot of these even in our own work of like, you know, as we iterate in the various versions of Alma it's not just like every time we collect from scratch all the data. No, the first step is like, okay, what are the cool data sources and datasets people have put [00:07:00] together for language model for training?[00:07:01] Luca Soldaini: Or when it comes to like our post training pipeline We one of the steps is you want to do some DPO and you use a lot of outputs of other models to improve your, your preference model. So it's really having like an open sort of ecosystem benefits and accelerates the development of open models.[00:07:23] The Definition of Open Models[00:07:23] Luca Soldaini: One thing that we got in 2024, which is not a specific model, but I thought it was really significant, is we first got we got our first open source AI definition. So this is from the open source initiative they've been generally the steward of a lot of the open source licenses when it comes to software and so they embarked on this journey in trying to figure out, okay, How does a license, an open source license for a model look like?[00:07:52] Luca Soldaini: Majority of the work is very dry because licenses are dry. So I'm not going to walk through the license step by [00:08:00] step, but I'm just going to pick out one aspect that is very good and then one aspect that personally feels like it needs improvement on the good side. This this open source AI license actually.[00:08:13] Luca Soldaini: This is very intuitive. If you ever build open source software and you have some expectation around like what open source looks like for software for, for AI, sort of matches your intuition. So, the weights need to be fairly available the code must be released with an open source license and there shouldn't be like license clauses that block specific use cases.[00:08:39] Luca Soldaini: So. Under this definition, for example, LLAMA or some of the QUEN models are not open source because the license says you can't use this model for this or it says if you use this model you have to name the output this way or derivative needs to be named that way. Those clauses don't meet open source [00:09:00] definition and so they will not be covered.[00:09:02] Luca Soldaini: The LLAMA license will not be covered under the open source definition. It's not perfect. One of the thing that, um, internally, you know, in discussion with with OSI, we were sort of disappointed is around the language. For data. So you might imagine that an open source AI model means a model where the data is freely available.[00:09:26] Luca Soldaini: There were discussion around that, but at the end of the day, they decided to go with a softened stance where they say a model is open source if you provide sufficient detail information. On how to sort of replicate the data pipeline. So you have an equivalent system, sufficient, sufficiently detailed.[00:09:46] Luca Soldaini: It's very, it's very fuzzy. Don't like that. An equivalent system is also very fuzzy. And this doesn't take into account the accessibility of the process, right? It might be that you provide enough [00:10:00] information, but this process costs, I don't know, 10 million to do. Now the open source definition. Like, any open source license has never been about accessibility, so that's never a factor in open source software, how accessible software is.[00:10:14] Luca Soldaini: I can make a piece of open source, put it on my hard drive, and never access it. That software is still open source, the fact that it's not widely distributed doesn't change the license, but practically there are expectations of like, what we want good open sources to be. So, it's, It's kind of sad to see that the data component in this license is not as, as, Open as some of us would like would like it to be.[00:10:40] Challenges for Open Models[00:10:40] Luca Soldaini: and I linked a blog post that Nathan wrote on the topic that it's less rambly and easier to follow through. One thing that in general, I think it's fair to say about the state of open models in 2024 is that we know a lot more than what we knew in, [00:11:00] in 2023. Like both on the training data, like And the pre training data you curate on like how to do like all the post training, especially like on the RL side.[00:11:10] Luca Soldaini: You know, 2023 was a lot of like throwing random darts at the board. I think 2024, we have clear recipes that, okay, don't get the same results as a closed lab because there is a cost in, in actually matching what they do. But at least we have a good sense of like, okay, this is, this is the path to get state of the art language model.[00:11:31] Luca Soldaini: I think that one thing that it's a downside of 2024 is that I think we are more research constrained in 2023. It feels that, you know, the barrier for compute that you need to, to move innovation along as just being right rising and rising. So like, if you go back to this slide, there is now this, this cluster of models that are sort of released by the.[00:11:57] Luca Soldaini: Compute rich club. Membership is [00:12:00] hotly debated. You know, some people don't want to be. Called the rich because it comes to expectations. Some people want to be called rich, but I don't know, there's debate, but like, these are players that have, you know, 10, 000, 50, 000 GPUs at minimum. And so they can do a lot of work and a lot of exploration and improving models that it's not very accessible.[00:12:21] Luca Soldaini: To give you a sense of like how I personally think about. Research budget for each part of the, of the language model pipeline is like on the pre training side, you can maybe do something with a thousand GPUs, really you want 10, 000. And like, if you want real estate of the art, you know, your deep seek minimum is like 50, 000 and you can scale to infinity.[00:12:44] Luca Soldaini: The more you have, the better it gets. Everyone on that side still complains that they don't have enough GPUs. Post training is a super wide sort of spectrum. You can do as little with like eight GPUs as long as you're able to [00:13:00] run, you know, a good version of, say, a LLAMA model, you can do a lot of work there.[00:13:05] Luca Soldaini: You can scale a lot of the methodology, just like scales with compute, right? If you're interested in you know, your open replication of what OpenAI's O1 is you're going to be on the 10K spectrum of our GPUs. Inference, you can do a lot with very few resources. Evaluation, you can do a lot with, well, I should say at least one GPUs if you want to evaluate GPUs.[00:13:30] Luca Soldaini: Open models but in general, like if you are, if you care a lot about intervention to do on this model, which it's my prefer area of, of research, then, you know, the resources that you need are quite, quite significant. Yeah. One other trends that has emerged in 2024 is this cluster of fully open models.[00:13:54] Luca Soldaini: So Omo the model that we built at ai, two being one of them and you know, it's nice [00:14:00] that it's not just us. There's like a cluster of other mostly research efforts who are working on this. And so it's good to to give you a primer of what like fully open means. So fully open, the easy way to think about it is instead of just releasing a model checkpoint that you run, you release a full recipe so that other people working on it.[00:14:24] Luca Soldaini: Working on that space can pick and choose whatever they want from your recipe and create their own model or improve on top of your model. You're giving out the full pipeline and all the details there instead of just like the end output. So I pull up the screenshot from our recent MOE model.[00:14:43] Luca Soldaini: And like for this model, for example, we released the model itself. Data that was trained on, the code, both for training and inference all the logs that we got through the training run, as well as every intermediate checkpoint and like the fact that you release different part of the pipeline [00:15:00] allows others to do really cool things.[00:15:02] Luca Soldaini: So for example, this tweet from early this year from folks in news research they use our pre training data to do a replication of the BitNet paper in the open. So they took just a Really like the initial part of a pipeline and then the, the thing on top of it. It goes both ways.[00:15:21] Luca Soldaini: So for example, for the Olmo2 model a lot of our pre trained data for the first stage of pre training was from this DCLM initiative that was led by folks Ooh, a variety of ins a variety of institutions. It was a really nice group effort. But you know, for When it was nice to be able to say, okay, you know, the state of the art in terms of like what is done in the open has improved.[00:15:46] AI2 Models - Olmo, Molmo, Pixmo etc[00:15:46] Luca Soldaini: We don't have to like do all this work from scratch to catch up the state of the art. We can just take it directly and integrate it and do our own improvements on top of that. I'm going to spend a few minutes doing like a [00:16:00] shameless plug for some of our fully open recipes. So indulge me in this.[00:16:05] Luca Soldaini: So a few things that we released this year was, as I was mentioning, there's OMOE model which is, I think still is state of the art MOE model in its size class. And it's also. Fully open, so every component of this model is available. We released a multi modal model called Molmo. Molmo is not just a model, but it's a full recipe of how you go from a text only model to a multi modal model, and we apply this recipe on top of Quent checkpoints, on top of Olmo checkpoints, as well as on top of OlmoE.[00:16:37] Luca Soldaini: And I think there'd be a replication doing that on top of Mistral as well. The post training side we recently released 2. 0. 3. Same story. This is a recipe on how you go from a base model to A state of the art post training model. We use the Tulu recipe on top of Olmo, on top of Llama, and then there's been open replication effort [00:17:00] to do that on top of Quen as well.[00:17:02] Luca Soldaini: It's really nice to see like, you know, when your recipe sort of, it's kind of turnkey, you can apply it to different models and it kind of just works. And finally, the last thing we released this year was Olmo 2, which so far is the best state of the art. Fully open language model a Sera combines aspect from all three of these previous models.[00:17:22] Luca Soldaini: What we learn on the data side from MomoE and what we learn on like making models that are easy to adapt from the Momo project and the Tulu project. I will close with a little bit of reflection of like ways this, this ecosystem of open models like it's not all roses. It's not all happy. It feels like day to day, it's always in peril.[00:17:44] Luca Soldaini: And, you know, I talked a little bit about like the compute issues that come with it. But it's really not just compute. One thing that is on top of my mind is due to like the environment and how you know, growing feelings about like how AI is treated. [00:18:00] It's actually harder to get access to a lot of the data that was used to train a lot of the models up to last year.[00:18:06] Luca Soldaini: So this is a screenshot from really fabulous work from Shane Longpre who's, I think is in Europe about Just access of like diminishing access to data for language model pre training. So what they did is they went through every snapshot of common crawl. Common crawl is this publicly available scrape of the, of a subset of the internet.[00:18:29] Luca Soldaini: And they looked at how For any given website whether a website that was accessible in say 2017, what, whether it was accessible or not in 2024. And what they found is as a reaction to like the close like of the existence of closed models like OpenAI or Cloud GPT or Cloud a lot of content owners have blanket Blocked any type of crawling to your website.[00:18:57] Luca Soldaini: And this is something that we see also internally at [00:19:00] AI2. Like one project that we started this year is we wanted to, we wanted to understand, like, if you're a good citizen of the internet and you crawl following sort of norms and policy that have been established in the last 25 years, what can you crawl?[00:19:17] Luca Soldaini: And we found that there's a lot of website where. The norms of how you express preference of whether to crawl your data or not are broken. A lot of people would block a lot of crawling, but do not advertise that in RobustDXT. You can only tell that they're crawling, that they're blocking you in crawling when you try doing it.[00:19:37] Luca Soldaini: Sometimes you can't even crawl the robots. txt to, to check whether you're allowed or not. And then a lot of websites there's, there's like all these technologies that historically have been, have existed to make websites serving easier such as Cloudflare or DNS. They're now being repurposed for blocking AI or any type of crawling [00:20:00] in a way that is Very opaque to the content owners themselves.[00:20:04] Luca Soldaini: So, you know, you go to these websites, you try to access them and they're not available and you get a feeling it's like, Oh, someone changed, something changed on the, on the DNS side that it's blocking this and likely the content owner has no idea. They're just using a Cloudflare for better, you know, load balancing.[00:20:25] Luca Soldaini: And this is something that was sort of sprung on them with very little notice. And I think the problem is this, this blocking or ideas really, it impacts people in different ways. It disproportionately helps companies that have a headstart, which are usually the closed labs and it hurts incoming newcomer players where either have now to do things in a sketchy way or you're never going to get that content that the closed lab might have.[00:20:54] Luca Soldaini: So there's a lot, it was a lot of coverage. I'm going to plug Nathan's blog post again. That is, [00:21:00] that I think the title of this one is very succinct which is like, we're actually not, You know, before thinking about running out of training data, we're actually running out of open training data. And so if we want better open models they should be on top of our mind.[00:21:13] Regulation and Lobbying[00:21:13] Luca Soldaini: The other thing that has emerged is that there is strong lobbying efforts on trying to define any kind of, AI as like a new extremely risky and I want to be precise here. Like the problem is now, um, like the problem is not not considering the risk of this technology. Every technology has risks that, that should always be considered.[00:21:37] Luca Soldaini: The thing that it's like to me is sorry, is ingenious is like just putting this AI on a pedestal and calling it like, An unknown alien technology that has like new and undiscovered potentials to destroy humanity. When in reality, all the dangers I think are rooted in [00:22:00] dangers that we know from existing software industry or existing issues that come with when using software on on a lot of sensitive domains, like medical areas.[00:22:13] Luca Soldaini: And I also noticed a lot of efforts that have actually been going on and trying to make this open model safe. I pasted one here from AI2, but there's actually like a lot of work that has been going on on like, okay, how do you make, if you're distributing this model, Openly, how do you make it safe?[00:22:31] Luca Soldaini: How, what's the right balance between accessibility on open models and safety? And then also there's annoying brushing of sort of concerns that are then proved to be unfounded under the rug. You know, if you remember the beginning of this year, it was all about bio risk of these open models.[00:22:48] Luca Soldaini: The whole thing fizzled because as being Finally, there's been like rigorous research, not just this paper from Cohere folks, but it's been rigorous research showing [00:23:00] that this is really not a concern that we should be worried about. Again, there is a lot of dangerous use of AI applications, but this one was just like, A lobbying ploy to just make things sound scarier than they actually are.[00:23:15] Luca Soldaini: So I got to preface this part. It says, this is my personal opinion. It's not my employer, but I look at things like the SP 1047 from, from California. And I think we kind of dodged a bullet on, on this legislation. We, you know, the open source community, a lot of the community came together at the last, sort of the last minute and did a very good effort trying to explain all the negative impact of this bill.[00:23:43] Luca Soldaini: But There's like, I feel like there's a lot of excitement on building these open models or like researching on these open models. And lobbying is not sexy it's kind of boring but it's sort of necessary to make sure that this ecosystem can, can really [00:24:00] thrive. This end of presentation, I have Some links, emails, sort of standard thing in case anyone wants to reach out and if folks have questions or anything they wanted to discuss.[00:24:13] Luca Soldaini: Is there an open floor? I think we have Sophia[00:24:16] swyx: who wants to who one, one very important open model that we haven't covered is Mistral. Ask her on this slide. Yeah, yeah. Well, well, it's nice to have the Mistral person talk recap the year in Mistral. But while Sophia gets set up, does anyone have like, just thoughts or questions about the progress in this space?[00:24:32] Questions - Incentive Alignment[00:24:32] swyx: Do you always have questions?[00:24:34] Quesiton: I'm very curious how we should build incentives to build open models, things like Francois Chollet's ArcPrize, and other initiatives like that. What is your opinion on how we should better align incentives in the community so that open models stay open?[00:24:49] Luca Soldaini: The incentive bit is, like, really hard.[00:24:51] Luca Soldaini: Like, even It's something that I actually, even we think a lot about it internally because like building open models is risky. [00:25:00] It's very expensive. And so people don't want to take risky bets. I think the, definitely like the challenges like our challenge, I think those are like very valid approaches for it.[00:25:13] Luca Soldaini: And then I think in general, promoting, building, so, any kind of effort to participate in this challenge, in those challenges, if we can promote doing that on top of open models and sort of really lean into like this multiplier effect, I think that is a good way to go. If there were more money for that.[00:25:35] Luca Soldaini: For efforts like research efforts around open models. There's a lot of, I think there's a lot of investments in companies that at the moment are releasing their model in the open, which is really cool. But it's usually more because of commercial interest and not wanting to support this, this like open models in the longterm, it's a really hard problem because I think everyone is operating sort of [00:26:00] in what.[00:26:01] Luca Soldaini: Everyone is at their local maximum, right? In ways that really optimize their position on the market. Global maximum is harder to achieve.[00:26:11] Question2: Can I ask one question? No.[00:26:12] Luca Soldaini: Yeah.[00:26:13] Question2: So I think one of the gap between the closed and open source models is the mutability. So the closed source models like chat GPT works pretty good on the low resource languages, which is not the same on the open, open source models, right?[00:26:27] Question2: So is it in your plan to improve on that?[00:26:32] Luca Soldaini: I think in general,[00:26:32] Luca Soldaini: yes, is I think it's. I think we'll see a lot of improvements there in, like, 2025. Like, there's groups like, Procurement English on the smaller side that are already working on, like, better crawl support, multilingual support. I think what I'm trying to say here is you really want to be experts.[00:26:54] Luca Soldaini: who are actually in those countries that teach those languages to [00:27:00] participate in the international community. To give you, like, a very easy example I'm originally from Italy. I think I'm terribly equipped to build a model that works well in Italian. Because one of the things you need to be able to do is having that knowledge of, like, okay, how do I access, you know, how Libraries, or content that is from this region that covers this language.[00:27:23] Luca Soldaini: I've been in the US long enough that I no longer know. So, I think that's the efforts that folks in Central Europe, for example, are doing. Around like, okay, let's tap into regional communities. To get access you know, to bring in collaborators from those areas. I think it's going to be, like, very crucial for getting products there.[00:27:46] Mistral intro[00:27:46] Sophia Yang: Hi everyone. Yeah, I'm super excited to be here to talk to you guys about Mistral. A really short and quick recap of what we have done, what kind of models and products we have released in the [00:28:00] past year and a half. So most of you We have already known that we are a small startup funded about a year and a half ago in Paris in May, 2003, it was funded by three of our co founders, and in September, 2003, we released our first open source model, Mistral 7b yeah, how, how many of you have used or heard about Mistral 7b?[00:28:24] Sophia Yang: Hey, pretty much everyone. Thank you. Yeah, it's our Pretty popular and community. Our committee really loved this model, and in December 23, we, we released another popular model with the MLE architecture Mr. A X seven B and oh. Going into this year, you can see we have released a lot of things this year.[00:28:46] Sophia Yang: First of all, in February 2004, we released MrSmall, MrLarge, LeChat, which is our chat interface, I will show you in a little bit. We released an embedding model for, you [00:29:00] know, converting your text into embedding vectors, and all of our models are available. The, the big cloud resources. So you can use our model on Google cloud, AWS, Azure Snowflake, IBM.[00:29:16] Sophia Yang: So very useful for enterprise who wants to use our model through cloud. And in April and May this year, we released another powerful open source MOE model, AX22B. And we also released our first code. Code Model Coastal, which is amazing at 80 plus languages. And then we provided another fine tuning service for customization.[00:29:41] Sophia Yang: So because we know the community love to fine tune our models, so we provide you a very nice and easy option for you to fine tune our model on our platform. And also we released our fine tuning code base called Menstrual finetune. It's open source, so feel free to take it. Take a look and.[00:29:58] Sophia Yang: More models. [00:30:00] On July 2, November this year, we released many, many other models. First of all is the two new small, best small models. We have Minestra 3B great for Deploying on edge devices we have Minstrel 8B if you used to use Minstrel 7B, Minstrel 8B is a great replacement with much stronger performance than Minstrel 7B.[00:30:25] Sophia Yang: We also collaborated with NVIDIA and open sourced another model, Nemo 12B another great model. And Just a few weeks ago, we updated Mistral Large with the version 2 with the updated, updated state of the art features and really great function calling capabilities. It's supporting function calling in LatentNate.[00:30:45] Sophia Yang: And we released two multimodal models Pixtral 12b. It's this open source and Pixtral Large just amazing model for, models for not understanding images, but also great at text understanding. So. Yeah, a [00:31:00] lot of the image models are not so good at textual understanding, but pixel large and pixel 12b are good at both image understanding and textual understanding.[00:31:09] Sophia Yang: And of course, we have models for research. Coastal Mamba is built on Mamba architecture and MathRoll, great with working with math problems. So yeah, that's another model.[00:31:29] Sophia Yang: Here's another view of our model reference. We have several premier models, which means these models are mostly available through our API. I mean, all of the models are available throughout our API, except for Ministry 3B. But for the premier model, they have a special license. Minstrel research license, you can use it for free for exploration, but if you want to use it for enterprise for production use, you will need to purchase a license [00:32:00] from us.[00:32:00] Sophia Yang: So on the top row here, we have Minstrel 3b and 8b as our premier model. Minstrel small for best, best low latency use cases, MrLarge is great for your most sophisticated use cases. PixelLarge is the frontier class multimodal model. And, and we have Coastral for great for coding and then again, MrEmbedding model.[00:32:22] Sophia Yang: And The bottom, the bottom of the slides here, we have several Apache 2. 0 licensed open way models. Free for the community to use, and also if you want to fine tune it, use it for customization, production, feel free to do so. The latest, we have Pixtros 3 12b. We also have Mr. Nemo mum, Coastal Mamba and Mastro, as I mentioned, and we have three legacy models that we don't update anymore.[00:32:49] Sophia Yang: So we recommend you to move to our newer models if you are still using them. And then, just a few weeks ago, [00:33:00] we did a lot of, uh, improvements to our code interface, Lachette. How many of you have used Lachette? Oh, no. Only a few. Okay. I highly recommend Lachette. It's chat. mistral. ai. It's free to use.[00:33:16] Sophia Yang: It has all the amazing capabilities I'm going to show you right now. But before that, Lachette in French means cat. So this is actually a cat logo. If you You can tell this is the cat eyes. Yeah. So first of all, I want to show you something Maybe let's, let's take a look at image understanding.[00:33:36] Sophia Yang: So here I have a receipts and I want to ask, just going to get the prompts. Cool. So basically I have a receipt and I said I ordered I don't know. Coffee and the sausage. How much do I owe? Add a 18 percent tip. So hopefully it was able to get the cost of the coffee and the [00:34:00] sausage and ignore the other things.[00:34:03] Sophia Yang: And yeah, I don't really understand this, but I think this is coffee. It's yeah. Nine, eight. And then cost of the sausage, we have 22 here. And then it was able to add the cost, calculate the tip, and all that. Great. So, it's great at image understanding, it's great at OCR tasks. So, if you have OCR tasks, please use it.[00:34:28] Sophia Yang: It's free on the chat. It's also available through our API. And also I want to show you a Canvas example. A lot of you may have used Canvas with other tools before. But, With Lachat, it's completely free again. Here, I'm asking it to create a canvas that's used PyScript to execute Python in my browser.[00:34:51] Sophia Yang: Let's see if it works. Import this. Okay, so, yeah, so basically it's executing [00:35:00] Python here. Exactly what we wanted. And the other day, I was trying to ask Lachat to create a game for me. Let's see if we can make it work. Yeah, the Tetris game. Yep. Let's just get one row. Maybe. Oh no. Okay. All right. You get the idea. I failed my mission. Okay. Here we go. Yay! Cool. Yeah. So as you can see, Lachet can write, like, a code about a simple game pretty easily. And you can ask Lachet to explain the code. Make updates however you like. Another example. There is a bar here I want to move.[00:35:48] Sophia Yang: Okay, great, okay. And let's go back to another one. Yeah, we also have web search capabilities. Like, you can [00:36:00] ask what's the latest AI news. Image generation is pretty cool. Generate an image about researchers. Okay. In Vancouver? Yeah, it's Black Forest Labs flux Pro. Again, this is free, so Oh, cool.[00:36:19] Sophia Yang: I guess researchers here are mostly from University of British Columbia. That's smart. Yeah. So this is Laia ira. Please feel free to use it. And let me know if you have any feedback. We're always looking for improvement and we're gonna release a lot more powerful features in the coming years.[00:36:37] Sophia Yang: Thank you. Get full access to Latent Space at www.latent.space/subscribe

How did an Environmental Sciences degree lead to a career in sustainability? How did attending DesignX at MIT sow the seeds for TULU? Why did Yael become a minimalist? Where did the name TULU originate? Why did TULU believe fast experimentation was extremely important when building an MVP? What did TULU learn early on about customer preferences and did the usage data bear this out? How is the TULU app helping it become a data driven company? Why are brands and retailers partnering with TULU and how was this strategy envisioned from the very beginning? How many different ways does TULU incorporate surveying into its platform? What surprising usage/consumption patterns have emerged with TULU? How is TULU supporting creators and work from home employees?Yael Shemer - Chief Customer Officer and co-founder of TULU, joins Proptech Espresso to answer these questions and share how her education in environmental science and sustainability initially led to a feeling of slight depression about the state of the world, but that she was able to change this perspective and identifying ways in which she could make a positive change on the environment.

In this episode of The Cognitive Revolution, we dive deep into frontier post-training techniques for large language models with Nathan Lambert from the Allen Institute for AI. Nathan discusses the groundbreaking Tulu 3 release, which matches Meta's post-training performance using the LlAMA base model. We explore supervised fine-tuning, preference-based reinforcement learning, and the innovative reinforcement learning from verifiable reward technique. Nathan provides unprecedented insights into the practical aspects of model development, compute requirements, and data generation strategies. This technically rich conversation illuminates previously opaque aspects of LLM development, achieved by a small team of 10-15 people. Join us for one of our most detailed and valuable discussions on state-of-the-art AI model development. Check out Nathan's Lambert newsletter: https://www.natolambert.com https://www.interconnects.ai Be notified early when Turpentine's drops new publication: https://www.turpentine.co/exclusiveaccess SPONSORS: Incogni: Take your personal data back with Incogni! Use code REVOLUTION at the link below and get 60% off an annual plan: https://incogni.com/revolution Notion: Notion offers powerful workflow and automation templates, perfect for streamlining processes and laying the groundwork for AI-driven automation. With Notion AI, you can search across thousands of documents from various platforms, generating highly relevant analysis and content tailored just for you - try it for free at https://notion.com/cognitiverevolution Shopify: Shopify is the world's leading e-commerce platform, offering a market-leading checkout system and exclusive AI apps like Quikly. Nobody does selling better than Shopify. Get a $1 per month trial at https://shopify.com/cognitive Oracle Cloud Infrastructure (OCI): Oracle's next-generation cloud platform delivers blazing-fast AI and ML performance with 50% less for compute and 80% less for outbound networking compared to other cloud providers13. OCI powers industry leaders with secure infrastructure and application development capabilities. New U.S. customers can get their cloud bill cut in half by switching to OCI before December 31, 2024 at https://oracle.com/cognitive 80,000 Hours: 80,000 Hours offers free one-on-one career advising for Cognitive Revolution listeners aiming to tackle global challenges, especially in AI. They connect high-potential individuals with experts, opportunities, and personalized career plans to maximize positive impact. Apply for a free call at https://80000hours.org/cognitiverevolution to accelerate your career and contribute to solving pressing AI-related issues. RECOMMENDED PODCAST: Unpack Pricing - Dive into the dark arts of SaaS pricing with Metronome CEO Scott Woody and tech leaders. Learn how strategic pricing drives explosive revenue growth in today's biggest companies like Snowflake, Cockroach Labs, Dropbox and more. Apple: https://podcasts.apple.com/us/podcast/id1765716600 Spotify: https://open.spotify.com/show/38DK3W1Fq1xxQalhDSueFg CHAPTERS: (00:00:00) Teaser (00:00:59) Sponsors: Incogni (00:02:20) About the Episode (00:05:56) Introducing AI2 (00:09:56) Tulu: Deep Dive (Part 1) (00:17:43) Sponsors: Shopify | Oracle Cloud Infrastructure (OCI) (00:20:38) Open vs. Closed Recipes (00:29:48) Compute & Value (Part 1) (00:34:22) Sponsors: 80,000 Hours | Notion (00:37:02) Compute & Value (Part 2) (00:42:41) Model Weight Evolution (00:53:16) DPO vs. PPO (01:06:36) Project Trajectory (01:20:39) Synthetic Data & LLM Judge (01:27:39) Verifiable RL (01:38:17) Advice for Practitioners (01:44:01) Open Source vs. Closed (01:49:18) Outro

Ever been captivated by the supernatural or curious about the secrets behind spirit worship?In this episode of Books and Beyond, Michelle sits down with Hari Kumar, author of Daiva, who takes us into the fascinating world of spirit worship practiced in Karnataka and northern Kerala's Tulu Nadu region. Hari dives into the intense practice of spirit possession, where individuals become vessels for powerful spirits like Panjurli and Bobbarya.He also shares how a surprising oracle prediction led him on this journey of exploration, uncovering unique perspectives on these traditions through interviews with kola performers, astrologers, and local residents. Hari also discusses the cultural and symbolic importance of the vibrant kola get-up and offers a peek into his upcoming book on the serpent, revealing a lifelong fascination with the paranormal. Listen in as Hari dives into the rich, mystical traditions of Tulu Nadu, shares personal revelations from his journey, and uncovers the complex world of spirit worship and possession in Daiva. ‘Books and Beyond with Bound' is the podcast where Tara Khandelwal and Michelle D'costa uncover how their books reflect the realities of our lives and society today. Find out what drives India's finest authors: from personal experiences to jugaad research methods, insecurities to publishing journeys. Created by Bound, a storytelling company that helps you grow through stories. Follow us @boundindia on all social media platforms.

En 6AM de Caracol Radio estuvo Óscar Alejandro García, Personero de Tuluá, para hablar sobre un atentado que sufrió el pasado sábado 21 de septiembre y que casi le cuesta la vida.

Alfredo Palacios Rivera, oriundo de Tuluá, fue figura de la radiodifusión en Colombia.

La W conoció una carta enviada por Henry Loaiza Ceballos, conocido con el alias de ‘El Alacrán', a la fiscal general de la Nación, Luz Adriana Camargo.

El coronel Giovanny Cristancho, comandante de la Policía del Valle del Cauca, se refirió en La W a los recientes hechos delictivos cometidos por la banda ‘La Inmaculada' en Tuluá.

Cette course a peut-être changé le monde. 1992. Barcelone. Stade de Montjuic. Fin ale du 10.000 m femmes. Sur la piste, elles sont deux à se battre pour la victoire : Elana Meyer, la championne blanche, Sud-Africaine, qui mène un train soutenu ; dans a foulée, une jeune athlète éthiopienne, Derartu Tulu, qui va attaquer dans le dernier tour... Ecoutez La grande histoire des Jeux Olympiques avec Jean-Michel Rascol du 25 juillet 2024.

Gustavo Vélez, alcalde de Tuluá, se refirió en La W al asesinato del empresario Javier Soto Velasco por parte de la banda criminal ‘La Inmaculada'.

La W conoció un comunicado del grupo criminal ‘La Inmaculada' en el que hace un balance sobre el cese al fuego voluntario.

Diego Vélez, Carlos Andrés Parra y Julio César Arias, concejales de Tuluá, conversaron con La W sobre la tensa calma que se vive en Tuluá después de que alias ‘Pipe Tuluá' asegurara que no habría muertes en el Valle del Cauca en un mes.

Chapter 5.2 (22)Earlier LifeLight In The DarkIn this episode we meet back up with young Jane as she is now 18 years old and living with her new family in the wilderness (Ishmael, Judge Jenkins, Nivi, and Tulu).Come read more at dreaming-machines-novels.comChapters will be posted weekly on our website.Audiobook episodes are currently being posted as they are created to catch up to the current chapters on the website, but once caught up will be posted weekly with the posts!Thanks for your supportAlso support us on Facebook, Instagram, and X. Just search Dreaming Machines Novels, or click the link below:Facebook: https://www.facebook.com/profile.php?id=61557396175196Instagram: https://www.instagram.com/dreamingmachinesnovels?igsh=anowYTdoeHByaTZl&utm_source=qrX: https://twitter.com/DreamMachineNovPlease rate us as well on whichever Podcast service you use to listen.© 2024 Noble Lucre Entertainment LLC. All Rights Reserved.

Chapter 4.2 (17)Earlier LifeThe HunterIn this episode we meet back up with 14-year-old Jane as she and her brother Ishmael as they travel through the wilderness with Nivi and Tulu looking for survivors.Come read more at dreaming-machines-novels.comChapters will be posted weekly on our website.Audiobook episodes are currently being posted as they are created to catch up to the current chapters on the website, but once caught up will be posted weekly with the posts!Thanks for your supportAlso support us on Facebook, Instagram, and X. Just search Dreaming Machines Novels, or click the link below:Facebook: https://www.facebook.com/profile.php?id=61557396175196Instagram: https://www.instagram.com/dreamingmachinesnovels?igsh=anowYTdoeHByaTZl&utm_source=qrX: https://twitter.com/DreamMachineNovPlease rate us as well on whichever Podcast service you use to listen.© 2024 Noble Lucre Entertainment LLC. All Rights Reserved.

Maintenance is often the most challenging area in a property management business. What if you could automate your maintenance workflow with an in-house, expert AI maintenance coordinator? In this episode of the #DoorGrowShow, property management growth expert Jason Hull sits down with David from Vendoroo (formally Tulu) to talk about AI maintenance coordination and how it could revolutionize the property management industry. You'll Learn [05:25] The AI Revolution [10:51] What can AI Maintenance Coordination Do? [20:58] How Vendoroo Handles Work Orders [27:56] Why You Should Have in-House Maintenance [37:30] Where do Humans Step in? [41:37] Handling Worst-Case Scenarios Tweetables “Property management is a very human business. It's a very relationship-driven business.” “Is it scalable? Is it burning you out? Is it pulling you away from other duties that you need to be? Are you spreading yourself too thin? Great questions to ask if you have growth objectives.” “Residents don't want to talk to a computer. They want to feel that they have a connection to their property manager.” “The first offense creates a little crack between the relationship. The second one, you're losing trust with your owner.” Resources DoorGrow and Scale Mastermind DoorGrow Academy DoorGrow on YouTube DoorGrowClub DoorGrowLive TalkRoute Referral Link Transcript [00:00:00] David: Even people who had in house maintenance coordinators or VAs, good ones, always still feel that they needed to second check all the work. And now when they're seeing the justification and they're seeing the education behind it, they get this sense of like, I can let go. You know why? Because this system is doing maintenance exactly the way that I'm asking it to do maintenance. And they feel that now they're actually back in control.  [00:00:24] Jason: Welcome DoorGrow Property Managers to the DoorGrow Show. If you are a property management entrepreneur that wants to add doors, make a difference, increase revenue, help others, impact lives, and you are interested in growing in business and life, and you are open to doing things a bit differently, then you are a DoorGrow property manager. DoorGrow property managers love the opportunities, daily variety, unique challenges, and freedom that property management brings. Many in real estate think you're crazy for doing it. You think they're crazy for not, because you realize that property management is the ultimate high, trust gateway to real estate deals, relationships, and residual income. [00:01:05] At DoorGrow, we are on a mission to transform property management business owners and their businesses. We want to transform the industry, eliminate the BS, build awareness, change perception, expand the market, and help the best property management entrepreneurs win. I'm your host, property management growth expert, Jason Hull, the founder and CEO of DoorGrow. [00:01:25] And now let's get into the show. All right. So today I'm hanging out with David Normand and Reza Keshavarzi. Did I say your last name right?  [00:01:36] David: We always say it sounds like the great sauce that you would put on a steak. Keshavari. So delicious. [00:01:41] Jason: All right.  [00:01:41] David: Yes. Cool.  [00:01:43] Jason: So David and Reza are from a company called Tulu, which we'll be getting into, which I think are probably revolutionizing maintenance related to AI and our topic today, we're going to be talking about AI and maintenance coordination, maybe getting into some of the current maintenance challenges, what AI could help with, what should be automated, what shouldn't be automated because I think that's a very important thing to cover and how to turn maintenance into a profit center. Before we get into that, why don't we get into some background? So David, why don't you give us the journey? How did you two get into this? How did you event like, how did you start your journey in the property management space? [00:02:24] David: Yeah, great. It's crazy to think about it. It just all started probably about 15 years ago. Like many of you, started a property management company with a buddy of mine. I remember we started off with 80 doors. Got our 1st client, was excited. He left his job at Verizon. I was actually in the banking industry, bidding on subprime auto loans and the 2008 crash happened. And so we all knew what happened after that. And so anyway we actually had some tremendous success and in just over four years we added over 600 doors. Which was a phenomenal growth in our market. And we had a lot of people going, "Hey, what's your secret sauce? what are you guys doing?" Right. And the reality was, is that we just cared, right? We cared harder. We had fiduciary duty. And all of these owners were leaving their other property managers and saying, "Hey, Maybe these guys have it figured out," and we were getting conversions and our close rate was like 80%. [00:03:13] It was really crazy, but something happened and just like many of us, owners started getting frustrated feeling like, the magic was wearing off because at the end of the day, no matter how hard we worked. Those owner statements and those maintenance invoices at the end of the month, I realized were the main source of friction between those long lasting relationships and the same reason why somebody left that previous property manager to come over for the hope of more transparency and maintenance was the same issue that we ran into. [00:03:41] Right. So that led me on this journey of trying to figure out, how do we standardize our fiduciary duty to owners when it comes to maintenance and help them bring transparency and education and understanding to what I feel is really the cornerstone foundation of what a great relationship is? Because no, the building can be full, the mortgage can be paid, but those maintenance bills still come in and there's still the questions.  [00:04:06] "Why does this cost this much? So I had some great opportunities to work went on with Fannie Mae helped them manage their rental portfolio, but still in the back of my head, wanted to try to solve this issue. And all these years later, I get a phone call from somebody that said, "Hey, you need to meet this guy, Reza. He's in the HOA industry. And he's seen a similar issue with lack of transparency. And I think that you guys are trying to solve the same issue. Hey, why don't you meet up?" And I'll, and I'll preface this. This was the fourth introduction to a guy in a fourth type of tech or a company that we try to part with. [00:04:40] And it just shows you the journey of an entrepreneur. Like you never know when that right connection that's going to align with your passions, resources, and understanding happens. And I actually had three other techs that didn't work out before. And I didn't want to bring them to market. [00:04:52] Right. So that's our story. We got introduced to each other and the synergies have been fantastic. And I'm really excited to talk about what we're doing here in the space. So it's been a crazy journey. It's been exciting. Maybe one day I'll write a book down the road about all the things not to do. [00:05:04] Jason: I think every entrepreneur that has a little bit of success could write that book. I'm sure. So cool. David, where do you think we should start? Like there's a revolution right now, this AI revolution, like it's AI everywhere. And and it's moving fast.  [00:05:21] David: Yes.  [00:05:21] Jason: Like really fast. [00:05:22] And it's a bit crazy. And. Everything's changing. There's a million software tools and companies coming out. Maybe AI is making all of them. I have no idea, but like...  [00:05:31] David: 85 percent of all content written online is written by AI these days. So yeah, definitely.  [00:05:35] Jason: Right. There's the fake internet theory that like the majority of the traffic and communication and comments on the internet isn't even real. So it's like we're walking around this fake ghost town online. And we're consuming content and we're like none the wiser in a lot of instances. So my quick take, for those listening, as we're going through this AI revolution, it's exciting. There's a lot of change happening. [00:05:57] We don't want to be left behind. We want to make sure we're paying attention to what's new, what we can use. Everybody's probably used chat GPT once or twice or keeps hearing about it from other people. "They've got a GPT, that thing that you use." Yeah. I used it this morning, right? Like I was trying to figure out something in my Chevy Tahoe. [00:06:15] And I was like, "how do I do this thing in my Tahoe? Like, can you just tell me?" And it can collapse time, but sometimes it's not useful. I think my take on this is that human interaction is going to be a premium. It's going to be at a premium. It's going to be something that really sets people apart because we're moving away from humanity to some degree by leveraging all this tech and AI and all these tools and property management is a very human business. [00:06:43] It's a very relationship driven business. And and I think we'll get into this today. We want to be careful of using technology where we shouldn't or trying to trick people. "Well, look, I'm pretending like it's me, but it's AI. Haha. I tricked you." And what's funny is there's little indicators, like, and we know that this stuff's being used in a lot of different ways, like governments are using this now, like, we don't even know what's real on the news or what's like deep fakes or AI, like they're showing people's like doing interviews and people are zooming in and noticing their rings are disappearing and like weird stuff, right? [00:07:20] David: Yeah.  [00:07:20] Jason: And stuff's going viral on like the internet. And so we're living in this world where we're super skeptical and we wonder if anything's real.  [00:07:28] David: Yeah.  [00:07:29] Jason: Sometimes people are even asking, like, is this AI on a phone call?  [00:07:33] David: Yeah, well, you can't tell the difference now. I'll tell you, our tech team and AI guys they actually played around with me a little bit and they actually use my voice and had me doing work orders and no one could tell it was them. [00:07:44] Not me speaking and giving triage and doing that type of stuff. And I actually I tested it with my wife and I sent her a message over it and she didn't even blink an eye. Didn't even blink an eye. It was crazy. It was that first like aha moment that really when we talk about our fiduciary duty to our clients and ourselves about the power of this and where it's going, right. [00:08:01] And to that point. So when it comes to AI, I think people need to understand that really, the way that we look at chat GBT to me is just the new Google, right? It's Google on steroids. Okay. And so, yeah, for sure. Do we use some chat GBT to understand like, how to write the perfect sentence structure? For sure. [00:08:18] But the cool part about this, Jason, is that what we're doing is: how do we use these models in this education that teach it about fiduciary duty to your owners? That's what gets me excited, right? That's what gets me excited to understand and to think intelligently and to think with thoughtfulness to the owner's pocketbooks when it's considering a decision of how to dispatch for maintenance, right? [00:08:42] Like, isn't that what we're all looking for? That we need a system that every work order that comes in that it goes to a expert maintenance coordinator that we know what that costs. I'm talking expert maintenance coordinator, a person's been in this job for 15 to 20 years that you can send a work order to and they don't make an error. [00:09:00] They're intelligent. They're able to educate, they're able to be client facing. Like there's a real skill set there if you put that on a CV for somebody, right? But that's not what this industry is filled with. Actually, this industry is filled with individuals who are under pressure to find the most affordable maintenance solutions and the most affordable ways to try to find people to run those maintenance solutions. We're allocating the least amount of resources to handle what I consider the highest probability of owner dissatisfaction in the property management relationship with the owner, right? So I have a VA who's 2000 miles away that's responsible for spending a thousand dollars in my owner's money. [00:09:38] And there's all types of potential errors and things that are happening as a result of that. So the way that we look at AI and actually in our business, we just use the word smart a lot. And we try to use that word, that intelligent instead of artificial. Because you know what? There is a lot of human input that has gone into this to teach it how to be smart and to teach it how to consider the fiduciary duty. [00:09:59] So at the end of the day, I would encourage all the listeners here that are going on this journey with us today to understand, not to be skeptical, how to maximize its value, right? And that's really what we're going to be focusing on today and to show you how we're maximizing its value to help us achieve what we call our dream outcome when handling maintenance. [00:10:18] Our dream outcome is as a property manager, I'm starting a company or I'm looking to grow, or I'm hitting those next growth objectives, or I'm looking for ways to be more profitable. What is my dream outcome? And that all circles around having an expert maintenance coordination in my office that is reducing trips costs and considering the fiduciary duty to my clients. [00:10:40] Right? So that's what we'll talk about here today and how we're using AI to achieve that.  [00:10:43] Jason: Got it. Well, let's get into it. So what can AI do and what can't AI do? Like, well, specifically what can Tulu do and what can't Tulu do?  [00:10:54] Where's the line drawn?  [00:10:55] David: Yeah, that's a great question. [00:10:56] So first of all, I always tell everybody this out of the beginning: we are not an outsourced maintenance coordination solution. We're not an outsourced company. Yeah. We are not a vendor. Okay. We're not bringing vendors to your marketplace. Okay. Tulu is your expert in house maintenance coordinator. [00:11:13] So if you're thinking of "I'm hiring a maintenance coordinator" or "I'm building a property management and I need a maintenance coordinator," you now have that. That's that ability to add this onto your software, your system. It's a simple plug and play. You get to remain inside of your portal, you don't have to leave it. [00:11:30] There's not another new portal, all updates, all things are pushing to Buildium and we're pushing to Appfolio. That was a big part of it. There's no new app for the vendors. There's no new app for the clients because we know what's important for them to live inside of there. So what can it do? Well, first of all, it's a leader. [00:11:43] Okay. And being a leader means that it is going to use the information that we capture about your company to lead your VAs, to make expert triage decisions that always consider your fiduciary duty to the owner. So let's give an example right here to break that down. Right. Say a hot water tank comes in. [00:12:03] Okay. Hot water tank's leaking. Okay. First thing it's going to want to understand is what time of the day is it and where is the hot water tank leaking from?  [00:12:09] Jason: Okay.  [00:12:10] David: And then it's going to determine based upon the location of the hot water tank, the type of the hot water tank, which type of vendor at which time is the right one to send out. That is the most cost effective that has the greatest probability of resolving that issue for the best price and meets the satisfaction of the resident. Right. Now that was a mouthful right there. Okay. And if you think about all of the potential errors and data points and things that are involved, the smart maintenance coordinator considers all those and it brings out a triage and it tells the VA "here's the pieces that you're missing. Here's the information that I need. And here's what my suggestion is for you to move forward." So it's amazing at being a leader. And then it's amazing at being an expert about creating communications for the resident and to the vendor to direct them. And then it's also an educator and at the bottom of every work order. [00:12:58] And I hope to be able to show some people it's really cool. We don't believe in just telling people what to do. We should educate them and tell them why they're doing what they're doing. Right. So imagine if you had the best expert maintenance coordinator leaning over the shoulder of every VA that you have standing there and telling them every work order, every time, here's what to do, here's how to do it, and here's why you're doing it. Right. And as a result, we're finding that VAs that come over that are dedicated to the account in two weeks, they're educated. And in six weeks, the majority of them are executing as a high level maintenance expert within six weeks. Of after sitting down and learning the training system, because just as much as it's leading, it's also training and educating. [00:13:38] That is a wow moment for somebody who's been in the space, who's been here for 15 years, managing hundreds and hundreds of people for government entities and stuff and understanding the amount of time and effort and training that goes into somebody. And then all of a sudden they come and they tell you, "Hey, by the way, I got a new job. Thank you for all the training. I'm going to go make $30,000 somewhere else," right? How many times has this happened to me? Hundreds of times, right? And so that's a big part of what we're solving here.  [00:14:02] Jason: So in order to be effective and operate as an expert maintenance coordinator so that your VAs that don't have this knowledge can function as if they have this knowledge, then this has to be programmed, right? Maybe it'd be helpful for, the viewers or listeners of this podcast to find out what are all the inputs that go into this? What did they have to provide and what do you guys provide, so this AI, they can trust it? [00:14:29] David: Yeah. Yeah. Great question, Jason. So first of all, I want to put it on point two to make an emphasis that in this journey that we're all learning about these smart technologies and AI, there's still a big part of human component, right? [00:14:38] And it's like when you chat, when you write something in chat GBT, like you just don't send it without looking at it. Right. You're reviewing it and making sure it's still saying that you want it to say. Right. So everybody rest assured this thing is not, living on its own and there's checks and balances. [00:14:51] But the onboarding on average takes 30 to 45 minutes. Okay. And one of the things that we did is number one is, when it comes to triaging and best practices, there's literally probably about 500,000 work orders of data points that it's considering. And it's an expert in that thing that's saying, "Hey, listen, this is how you should handle every work order that comes in because I've seen this, 20,000 times, and this is the best outcome." [00:15:18] Right. But then what it does is it allows the property manager to talk in natural language. Like you want to talk like a robot. We don't have to write weird code. Just say things. "Hey the owner of one, two, three main street really loves Tom." Tom works on his properties. Comes in 123 main street comes up. It understands what Tom's capabilities are. And it says, "please use Tom to use this." The owner prefers that Tom works on his properties. They have a great relationship. Cool. And so those little tidbits for example, if the heat goes out in unit number one, understand that access has to be in unit number two basement to the HVAC unit, right? [00:15:52] So that's good to know, but why is that important to know? Because most VAs would make a mistake. They say there's no heat. They don't check property notes. They send out the plumber. Plumber is knocking on the door at unit number one. Person says, I don't know where the HVAC unit is. Tenant next door is not home. [00:16:06] Now you just charge your owner for 250 emergency call to go out. The resident still doesn't have heat. They think that you're unorganized. It shows you're unorganized on your owner statement because there's two invoices. "Oh, no, wait, you want to cover that? You're unorganized." So you just ate 250 that you're already not marking up on maintenance and you do that 10 times a month. [00:16:25] Okay. And that's what's going on.  [00:16:27] Jason: And this is where then the owner's like, "I might as well just do it myself because I know everything and it's in my head." So how did they get all of that out of their head? All the little things they know about each property, each multi unit property, what's in the basements, what's..? [00:16:40] David: We have a cool onboarding process. And again, most times about 30-45 minutes, they sit in, it's called building your AI co pilot. Actually, a lot of people dig it. It's cool. It's a cool process. And we will be first, we go into your system and we're able to pull out all your work order data and it organizes all your vendors, and we can tell who all your vendors are and what you're doing based upon the work order types. [00:16:59] We can tell if you're a preferred guy is here. Number one guy is, "Hey. This guy always seems to be working on these properties." So there's a lot of information that we gather. And then you just come in and you're like, "yeah, he's my primary. He's my secondary. Oh, here's this little information about this property." [00:17:13] So you really don't have to get like, like crazy. Like, like, the mailbox is located, like. You can add that stuff later, but in the beginning, it's just like, what are those important rules? I remember this one that really jumped out at me as impactful, a classic mistake, this owner had a lady living in the apartment for 35 years. [00:17:31] Okay, and she's getting old and one of the rules is that no matter what maintenance ticket comes in, "don't ask her to triage. Don't ask her. It's the tenant's responsibility. I love this person. Please send her out and just take care of her. Right?" What a great rule to put into your system that shows the owner that when that work order comes in, He's not getting a call from, and I forget what her name is. [00:17:51] And like, they're asking me to change my light bulbs again. And then he's like, I told you twice not to do this. And next thing he's looking for another property manager. And I always love that example of that rule. So that's what you're looking as far as the information you're giving us takes about 30 to 45 minutes. [00:18:03] For people who have anywhere between, 150 to 350 properties. If you start having, 500, 600, a thousand, I would definitely allocate up to two hours and onboarding for sure.  [00:18:13] Jason: Okay. That's really fast when it comes to rolling out a new technology. Yeah. It's ridiculously fast.  [00:18:19] David: Yeah. [00:18:19] Yeah. Yeah. Yeah. Extremely quick. So basically you have all this learning and understanding that's going into who your preferred vendors are. We know how to handle the maintenance work orders. There's no like integration that has to happen. And so as this triage is coming through, you're getting this expert level triage and you can add things down the road. [00:18:38] You can add it, but how to handle the work orders as we say, there's really nothing new in maintenance. What's new is: "what's the NT for the property? Are there any special conditions that we need to know? Right? What are your residents' responsibilities and what are you responsible for?" Once you have those four questions answered, how to handle the hot water tank, at what time to hit on the hot water tank, how to, how to repair this door, how to do that. [00:19:02] Those true principles of maintenance are true for everybody, if that makes sense, right? So, so that's a big part of the value that you get that You're hiring an expert maintenance coordinator. If you were to hire him, you wouldn't necessarily be telling him. "Hey, this is how you replace a doorknob." [00:19:18] He should already know that when you hired him. Right. So think of like it that way when you're considering us as a technology.  [00:19:24] Jason: So, a human maintenance coordinator, the challenge would be, there's no way they can remember every detail about every property, right?  [00:19:32] David: Yeah,  [00:19:32] Jason: it's not. Which means they would have to keep notes. [00:19:35] Let's say they've already got a decent amount of notes somewhere. Might be in the property management software, maybe they've got their own, I don't know, database of something. Is there the ability to pull in all that information?  [00:19:46] David: Yeah, a hundred percent. Yeah. To grab those notes out. A lot of people have the ability to export it. [00:19:51] They have a good note file or something like that. We get those, we take that information and it can just be pushed up into the system for sure. So yeah, the onboarding it, it can be, again, some people come in and say, "all I have is single family houses." Everything's pretty straightforward. [00:20:03] Other people send over an Excel list. "Here's my property notes at the property levels" and upload them. So that's the cool part where. You ingest into the system. There's not a lot of data, manual input. It's reading it and assigning it. And that's where we're using technology to help even improve the onboarding process that you talked about, right? [00:20:19] You think about people wear t shirts, like, I survived the Yardi onboarding process, right? Like, technology has come a long way to help improve that process, and that was a big part that we focused on.  [00:20:28] Jason: Yeah, that's wild. So once you've got them onboarded and they're in your system, the AI knows pretty much everything about the property, but maybe it doesn't, maybe there's some things it doesn't know. [00:20:41] And so work order comes up. You're working on something and it's still just in the property manager's head or it's still in the business owner's head or maybe they don't even know yet, but it runs there. It runs into an issue. It's like it has a question maybe, or it doesn't. It needs to know some more stuff. [00:20:57] I don't know. What happens in those scenarios? [00:21:00] David: Yeah, this is a great one. So, all right, so let's talk about the life cycle of a work order. Right. And let's everybody just understand that there still is a human component involved in this, right? Every property manager has a dedicated, we call them a remote team member, who's now this expert maintenance coordinator at the cost of a remote team member. [00:21:16] Now they're able to execute at a very high level. But there are going to be things that they're faced that they don't understand. So they have the ability to communicate with you one on one, or we also have this process internally that they have this ability to go, "I need a request from the expert in the loop" and the expert in the loop is you know, invoice review, complication that they're saying that the AI is not clear on them and it's asking for additional support. And so they can bump that up to individuals, myself, and there's other members of the team members that are big part of this and they can get expert level triage inside of there, to say, "Hey, listen, I'm facing with this vendor issue. They need 25 percent upfront. The job is only 500. I'm not understanding what to do here. The building is located and they're saying access is weird. They need to bring something in." There are complications that still involve human understanding. And so that expert in the loop solves that piece in there. [00:22:07] And also speaking of humans, we believe that residents and vendors still need to speak to a human. Okay. Super important. Okay. So the value that we have is that we're able to create expert level triage, According to their specifications and the training model and all the great things and the automation and the text messages that are written for them and the codes that are written for them the emails, all those things. [00:22:31] So, if we can automate at a very high level and free up our people to be able to provide support on the phone to the vendor on the field, or to actually talk to a resident, everybody knows this and I talk to everybody, guys, residents don't want to talk to a computer. They want to feel that they have a connection to their property manager and that when they call in, a lot of people have not even adapted technology for anybody who has, residents have been with them with a while and they're used to talking to Janet, they're used to talking to tell him inside and next thing you can say to them, "Oh, we have a new maintenance system. And by the way, you have to talk to the system." They're like, "okay. This is lame," right? Like, so that personal connection and we have a saying inside of the office that we keep your residents and your vendors within arm's length of you, right? It's communicating. They're using your property management name. [00:23:20] They're speaking on your behalf. This is an extension of your office. This is your maintenance coordinator. Don't think of this as a vendor. Don't think this is an outsourced maintenance solution that you're setting all your maintenance to some company that's sourcing vendors or bringing them in and doing every, this is your in house maintenance team. [00:23:38] So always consider that when you're thinking about Tulu, real people. In house maintenance coordinator just powered by AI enabled execute at a crazy high level.  [00:23:46] Jason: So, yeah. So how do tickets get into the maintenance system? Like how are they initiated? Do they still have to be answering their own phone calls? [00:23:56] Are they just putting it into their property manager software? And then Tulu is going to like start taking some action. What communication does Tulu facilitate or take over if we're going to be having still needing some humans to be in Tulu allows us to increase the amount of communication and care that we show. [00:24:13] Where do we draw the line? Like, where is Tulu stepping in and doing some communication and where do we need team members to be doing communication?  [00:24:21] David: Yeah. Yeah. Great question. So let's just go through the life cycle of a work order for everybody. I think that's what everyone really understands when they're all thinking about this. [00:24:28] Okay, let's give me a work order from start to finish. Right? So no change to your residents. No change to anybody. They log into their portal, Buildium, Appfolio, RentVine, whatever they're using. They submit a maintenance work order, that maintenance work order through their system is dispatched to the Tulu maintenance coordinator, expert maintenance coordinator. [00:24:46] All the magic is happening, all the triage, everything is taking place, and inside of the property management software, they're going to see. Work order.  [00:24:53] Jason: And is that dispatched through via email? API? Yep.  [00:24:56] David: Oh, yeah. Yeah. Just through email? Yep. Set up as simple. You can set it up as a maintenance coordinator and as the maintenance coordinator is set up and the email comes in and it pings out and that creates the work order and starts to process through the, yeah. [00:25:08] Yep. Cool. And then the property manager will see that the work order has been it's in triage on the status of their system. Then it's assigned, then the vendor will be assigned there. And then from there, the updates, when it's scheduled that we call it the who, what, and the why, right? [00:25:25] What's going on, who's doing it and what's being done to progress this for. That's a note. You're constantly getting those notes. Now, the cool part about this, Jason. is behind the scenes. All of those text messages and phone calls and emails that we call the noise that are between the residents and the vendors and everybody are all being captured in a system behind the scenes. [00:25:45] Right. Super value there, right? If a resident is a little bit upset about something or you have some questions, "Hey guys, can you hand me the phone call this one to show me the text messages," right? Communications are big part. So we capture all those communications inside there at any time that the owner of the property manager wants to pull them. [00:26:00] That's great. Then the work order is completed. The completion, quick question. So  [00:26:05] Jason: all this communication between tenants and vendors, unless they're using some sort of magical system That the vendors have to be in and that the tenants are logged into. And it's like seeing all this, how does Tulu capture that? [00:26:18] How does it know that the vendor is communicating with the tenant or the tenant? Okay. So it would be any point.  [00:26:24] David: Yeah. Good point. Any point that the the tenant. Is communicating or the vendor or just communicate with two of those. So if the vendor happened to communicate directly with the tenant, it would not capture that part, right? [00:26:34] That's their phone to phone with that part, right? So it's when the resident or the tenant is communicating with the maintenance coordinator. And as we all know, tenants and vendors love to communicate by text message, right? That's their number one thing to do. So, it's really cool for vendors too, because as we know, a bunch of vendors, they hate. "I don't want to work in another app." Vendors can take pictures from their phone. They can upload estimates from their phone. The estimate comes in and it's actually turned into this really pretty estimate because we know vendors estimates are notorious for being on the back of a paper and hand scratched, right? [00:27:06] So it actually creates into a brand new Tulu estimate. And so your owners get transparency into pricing and labor. And it's standardized and everything looks clean. And so yeah, vendors love it because they're not lazy, but they're busy guys. And instead of going home and trying to do a whole bunch of paperwork, they can now just generate an estimate, take a picture and shoot it right through. [00:27:22] So, yeah.  [00:27:23] Jason: Because the challenge that there's a lot of communication involved. And so usually to decrease the amount of communication, they're trying to figure out how do we get the vendors to just talk to the tenants directly to collapse time? But if you have AI, then my guess is that Tulu will still just act like that middle person because the vendor can communicate with them, they can immediately text you, then Tulu texts the tenant, then it's just doing it real time. [00:27:45] You don't have to wait on a human being in your office to like make this communication happen. So you're like, "well, we're so slow. Let's just get them to talk to each other." The AI is making this happen. Is that accurate?  [00:27:56] David: Huge point right here is, and man you really hit off the nail on the head on this one point here. [00:28:01] The amount of people that we are seeing that they're using vendors to perform triage in this space is actually alarming. Okay. Alarming. All right. Vendors should not be performing our triage. They should not be the ones trying to figure out what is going on. They're not our client facing people. Maybe some guys are good. [00:28:20] your in-house guys, goods or whatever. The majority of people are using this, right? The beauty of the system is: Do we have enough information that is captured? From the resident, the property manager that considers the needs of the owner to formulate the correct direction to the vendor so that they can show up with the resources that they need to fix the job the right time or show up educated about what they're there to fix. [00:28:41] Jason: So let's talk about this real quick. Like vendors should not be doing triage and why not? Like, like what are the obvious ramifications here? Well, vendors, that's like asking a surgeon if you need surgery, right? That's how he makes his money.  [00:28:55] "That's the solution is surgery. We should chop that out, like, let's cut that thing out and I get paid thousands and thousands of dollars."  [00:29:02] David: Or how about this one, Jason, on an owner's report. I see a cost for so many times you see a cost for a maintenance guy, "unable to resolve expert needed." well, why? Because the maintenance vendor was sent out to do the triage. [00:29:15] That's not fiduciary duty to the owner. If we had the right information, we could have avoided that one trip. So we have some really cool case studies. I'd love to show people that out of like 260 work orders, we have one right here, a client that signed up with us. And so out of that thing here let's see. [00:29:31] They completed 194 work orders. 17 unnecessary trips were canceled. Wow. Okay. 17 unnecessary trips and 15 of those work orders had an immediate reduction in price because they said that the wrong resource was assigned to that. So think about that. 17 different numbers.  [00:29:48] Jason: So if that, if they have an in-house maintenance team, you're decreasing your your cost deploying these texts, going out and doing stupid work, like significantly. If you are using third party vendors, then there's always an expense. If you're sending anybody out, unless you're like, go do a bid, or something like this, but that's costing the vendor, which they're going to be more frustrated with you. [00:30:09] So you're freeing that up or they're charging you for it. "Oh, well, if I go out, I charge, right?" Yeah.  [00:30:15] David: I'll give you an example. We just saved owner of a pad split property who wanted to replace the refrigerator. The request came in and they asked for three estimates, okay, to replace the refrigerator. [00:30:28] Okay, the suggestion came back that basically said in a nutshell, summarize this, "why are you sending three different appliance vendors who are all going to charge a trip fee to go look at a refrigerator when a Home Depot program should be used and the cost of refrigerator should be 860? To factor all those costs in, it would have been about 1, 400. I don't understand why you're doing this. Please explain, right?" Talk about fiduciary duty to the owner.  [00:30:51] Jason: This is why owners get frustrated and they're like, "I might as well just do it myself." [00:30:55] David: " Because I knew better. I would go to Home Depot. Everyone knows to order a refrigerator from Home Depot, right? Unless there's special circumstances." And now imagine this, and this is where we're going with this, Jason. At the end of each month, these owner reports go out to all these owners, and owners sit down and they call up the property manager, and we always hear people talking about this at every conference. [00:31:14] "Oh, I don't want to answer that phone call. I know what this is about, right?" And the property manager is scrambling at the end of the month to call the maintenance coordinator, dig into work order notes and justify why did this cost this much? "Explain this to me," right? So we have this really cool report that's coming out that basically, including in the property owner, It would let you know that, Hey, you had six jobs that were able to send a handyman this month. [00:31:38] Here's what's going on. You had two emergencies, two replacements, little asterisks that said, "Hey, this trip fee was 120. Why? Well, it required two people because there was a toilet that was being replaced on the third floor so they requested an extra hour of labor to be able to bring that toilet up because it was too like..." intimate details so that your owners are feeling like they're getting this like this whole transparency, unbelievable transparency, this report, the property manager doesn't have to waste at the end of the month, which I used to send away two to three days at the beginning of each month, just to answer phone calls and questions.  [00:32:12] Jason: Right. Yeah. It's like "why did it cost us much? Why?" [00:32:14] Like they can just see it.  [00:32:16] David: Yeah. "Why didn't you send Tom?" "Well, I did send Tom to snake the drain because it was clogged in the master bathroom. We set his limit at an hour. He used a 17, 25 foot power snake. And we said, if you can't get this done within an hour, then we need to send Roto Rooter." "Oh, I get that. You really did try to save me money in the beginning. Yeah. And Roto Rooter found that 35 feet down the thing was a clogged diaper or something like that." That's what owners need to understand. And to break that down in every work order is a tremendous strain on property managers and our system in V2 that's coming very quickly. [00:32:52] I was actually working on this morning. Those owner reports will be generated then if every month that explain intimate details about the thought process. and the costs and any decisions behind breaking it down into category for every maintenance work order type for their owners. Huge value. Imagine going to a client, a new client, and you're presenting against somebody else and they say, "Hey, how do you handle maintenance?" [00:33:14] And you pull that report out and you put it down on the table.  [00:33:16] Jason: You're like, "like this is the level of detail. Nobody else is doing this." The maintenance coordinator get on the phone every time and saying, "let me walk you through all these charges and why they happened and what did." And like, how many people listen to this right now? [00:33:31] I'm like, I know you're listening to this going, "if I never had to do that again, that would be the best thing ever. Ever. Like I've never had to have that uncomfortable conversation with the owner." Like it's all in there. It's all there. Like it makes sense.  [00:33:43] David: "Here's why we are your property manager. And here's the value that I'm giving to you in the transparency to maintenance." [00:33:50] That's a huge burden. It's a significant pain point. And we know this Jason, the first offense creates a little crack between the relationship. The second one, you're losing trust with your owner and they're beginning Googling "other property managers around me." The third one. You're just waiting for them to look and to go somewhere else. [00:34:07] So the relationship is falling apart. Right. And we are trying to know that  [00:34:11] Jason: You got a 600 door business in four years.  [00:34:14] David: Yes.  [00:34:15] Jason: Like, and so, and you have probably heard countless stories of people if they're switching companies, it's really rare that people switch companies. Usually things have to be pretty bad and maintenance that's in communication. [00:34:27] Those that's number one factors, communication and why people leave. And so this allows you to free up a massive amount of time so you can actually be on the phone with the people when you need to be on the phone and stop wasting time with all of these repeat calls, repeat requests, what's going on with this, and yeah, this would just save so much time. [00:34:44] David: Well, think about growth, Jason, right? So the three things that we're solving for, number one is we're protecting fiduciary duty to the owners, justifying maintenance costs and reducing the cost of expert in house maintenance coordination and making it scalable. Yeah. Okay. [00:34:58] So now if I can have an expert maintenance coordinator that I add to my office, there's a fixed cost to it. I can scale infinity and not have to worry about hiring and training and staffing and issues and all these problems in global, right? My fiduciary duty to my owners, I got reporting and transparency. [00:35:17] Maybe my property manager now, instead of being able to manage 250 doors, maybe they can manage 350 doors. Isn't that cool? Like that's where we're going with this stuff for sure.  [00:35:25] Jason: Yeah, it definitely would make a business as maintenance coordination, maybe infinitely scalable. So, okay. I know somebody that's listening, that's very detail oriented and their brain doesn't think like a spider web, like mine is going, "Hey, you guys never finished the example scenario because Jason derailed it." [00:35:43] And so we've got the maintenance request. It's come in.  [00:35:46] David: Yeah.  [00:35:47] Jason: So take, let's go back to that.  [00:35:49] David: Okay. Yeah. Maintenance request comes in the triage takes place. The information is gathered once the information is gathered, and it fills the requirements of what they believe is the right decision. [00:36:00] At that point, the scheduling takes place. Okay.  [00:36:03] Jason: Okay. So which pieces of Tulu doing?  [00:36:05] David: All of this.  [00:36:05] Jason: Okay. Okay.  [00:36:07] David: Okay. Okay. So then we're scheduling and then the work is completed. Quality pictures are received. If the resident is satisfaction, you have happiness received, vendors invoices received, and that's all uploaded into the system. [00:36:20] And then at that point, the property manager can pay the vendor directly if they have a great relationship and maybe they want to pay them in whatever way they do. A lot of people like paying their vendors, that's fine. Or they can reimburse the Tulu system. If they just want to pay one vendor for the rest of their life, and then Tulu will pay the vendor for them directly. [00:36:38] So it is from intake to vendor payment, all updates, all communications, all triaging, everything.  [00:36:46] Jason: Tulu does all of it. Does it all.  [00:36:48] David: It is your perfect maintenance coordinator. What we call the dream scenario. It has the ability to triage, troubleshoot, knowledgeable about vendor pricing, it's client facing and experience and client facing means that you can even set the parameter that said, "Hey, if anything is over my NTE, I would actually like you to generate your justification as to why think about this and send it out to my owner." Now imagine your owner getting this super email that's like, "Hey, listen, we have this problem. So the five to fancy, here's the steps that it took place to do."  [00:37:15] Jason: So like the amount that's in the agreement that says like anything under 500 in a single month, like we have a right to just take care of it. Right. Or something like this property managers having their agreements. Okay. So, so where do they need humans then? Where do humans come in all of this? [00:37:31] David: Humans need to be there to provide expert level, the same expert level triage that the system is providing, we need humans in there to make sure, first of all, it's accurate. There is a component of that, right? We're reviewing this and training it, learning it, but as we talked about before, humans need to be there. [00:37:47] We love that they have a great relationship because they're an extension of the office with their RTM, right? With their property manager and that RTM, they get to know each other. Humans are needed to talk to the residents and humans are needed for vendor support. Okay. Vendors don't want to call into a robot when their hand is in a sewer line from the field asking about, "Hey, I need help and direction. What's going on?" [00:38:07] They don't want to hear "press two if you're unhappy with this service," like they don't want to hear that. That's where humans come in.  [00:38:13] Jason: Got it. Okay. So what are some of the results that you're seeing when you're installing in this into businesses? Like what's shifting? Because I'm hearing some things like it's going to decrease the time you're spending on the phone with your owner. [00:38:25] So it's going to decrease the amount of time doing communication. You won't have to spend time doing triages. It sounds like a large piece of maintenance coordination is going to be taken care of. It sounds like staffing costs can be reduced. You tell me what are clients noticing once they get this installed over their previous systems of using a stack of tech tools to try and get their team to be able to handle this stuff? [00:38:47] David: I think in the beginning and I think that it's cool in our relationship is just to hear people come back after the first month and go, "I can't believe it. Like I went an entire month and like, I was not involved in maintenance the way that I feel that I needed to be to make sure that all these things were taken care of. And I'm finding myself with like 20 hours extra a month." And we're like "yes, go grow. Go add more doors. Go show greater value to your clients. Maybe call your client that you haven't been calling in a month because you've been so busy." Right. So, so those are really cool. I think from a cost perspective, they are appreciating. [00:39:24] And I'm believing that. Even people who had in house maintenance coordinators or VAs, good ones, always still feel that they needed to second check all the work. So even though you're giving to somebody, they never were able to detach themselves from me. [00:39:37] And now when they're seeing the justification and they're seeing the education behind it, they get this sense of like, I can let go. You know why? Because this system is doing maintenance exactly the way that I'm asking it to do maintenance. And they feel that now they're actually back in control. If that makes sense. Or they're giving it away, but they're actually feeling they're in more control, if I'm making sense there. That's one of the coolest things is that they feel now they have their pulse on every work order where versus before they have to dive into search. Now they know that their requirements are just laid over every work order. So those are some big ones that I'm seeing, especially for those people who really show their value to their owners in the fact that they say, "I'm involved in every work order, every job." That's a great value prop. It really is. Is it scalable? Is it burning you out? Is it pulling you away from other duties that you need to be? Are you spreading yourself too thin? [00:40:29] Great questions to ask if you have growth objectives, right? Scalable solution. And basically what we're doing is we're allowing the best in the business who are property managers who have created great relationships to duplicate themselves. And that's exciting for them to see. I think that they're like, "wow it's thinking like me."  [00:40:45] Jason: This really sounds like a serious competitive advantage for a property manager that adopts this over any other competitors that don't  [00:40:54] David: Jason, I'm going to a new client pitch and now I'm knowing that the guy next to me is sitting down showing him, "this is how I handle maintenance. This is how I'm keeping your cost down. This is the process. And that new report's coming in our V2. I was actually working some funnels that this morning. And if you're laying that down and then you're walking in behind them and the person says, "well, how do you handle maintenance?" [00:41:15] "Well, I personally call you on every maintenance ticket." We're witnessing the greatest generational movement of wealth and real estate properties from retiring baby boomers to the next generation to their kids who are all grown up in a technology world that are demanding transparency and reporting and it's just going to be the new standard, Jason, a hundred percent. [00:41:34] It's going to be the new standard for sure.  [00:41:36] Jason: Okay. We probably got somebody listening. They're super skeptical. They're like, there's no way. And they're going to throw us some crazy scenario that came up recently. And I'm sure you've heard some of these. So how would you address that? Like some sort of like, "well, what if it's like this and this," and it sounds like worst case scenario. [00:41:54] The AI just says, expert in the loop. Like it's, it raises his hand in some way and says, "Hey, I could use a human over here."  [00:42:00] David: Here's one that actually, as a guy who in my history, we had portfolios, like 30,000 properties. [00:42:06] So I've done probably over 500,000 work orders. In my career. Okay?  [00:42:10] Jason: More than most of the people that are probably listening to this. Yes.  [00:42:13] David: Yes. And as a result, just because of the size of the inventories that we used to manage the other day, a resident submitted a maintenance work order in and said, "my microwave is not working. And I assume it's because my gas stove is not turned on. And does my gas stove need to be turned on in order for the gas to flow up to my microwave?" Okay. True. True. Okay. All right. True maintenance work order. The the smart system picked that up and now imagine a VA facing that without any knowledge or an experience that's going to be an email to the property manager, a phone call to somebody, or maybe they make a mistake because they're 2000 miles away and they don't have any contacts and they sent out a plumber to go investigate. And the owner says, "why are you sending out a plumber for this?" Right? Right. Okay. The system picked up and it literally educated and trained. And it said that gas has no relevance whatsoever to a microwave solution. This is an incorrect thing, right? And that, when I saw that one, it makes mistakes. [00:43:04] Don't get me wrong. It's not perfect, but when I saw it pick up on that one, I said, man, I said, this is getting exciting that it picked up on that. So I would ask that person to come and just experience it and look at a little bit and understand guys, right? This is exciting. This is new. It's learning. [00:43:19] We're developing and it's improving daily. There's still a lot of human oversight. There's still a VAs that involved. We're getting expert maintenance coordination down to a price point that is affordable for everybody, scalable for everybody. And the biggest point at the end of the day, your owners are going to feel that every maintenance work order comes in, it's being handled by the best maintenance process in the industry. [00:43:39] And that's what you're going to be able to offer them as a property manager to compete against other competition you have in your market. And I think that's a good value prop. So.  [00:43:46] Jason: Yeah, definitely. So is there anything else related to turning maintenance into a profit center that we should cover? [00:43:52] David: Yeah the first step going into a profit center is realizing that the average person is paying between 16 to 28 dollars per door to manage their maintenance, right? If we get that down to the correct number, and I'd love to have anybody come through and we'll run the analytics for them and we'll give them a pricing model for that just off the bat, the first profit center that we're creating is what if I'm able to reduce that by 50 percent your cost, that's an immediate profit center, right? [00:44:16] That's profit center number one. And then we can look at profit centers number two, that like, all right, now I can add on if I want to add on to my markup or we have some other ways that we can show them how to. But the first profit center needs to be is what do you know how much you are paying per door to manage maintenance? [00:44:34] Take all of your staff, all of your VAs, all of your systems, all your after hour services, take all those pieces, add them all up and divide them by the number of doors that you have. So every door that you bring on, it's costing me $27 to handle maintenance emergency services. Okay. Know that number, and let's have a talk. [00:44:54] Jason: You got to build that calculator on your website.  [00:44:56] David: It's coming.  [00:44:57] Jason: A lot of calculators like that to help people calculate their cold lead marketing costs or whatever. And as soon as they fill that out, they're like, "okay, I'll sign up. Like this is ridiculous. What I've been doing?"  [00:45:06] David: We have that in product right now. [00:45:07] We have a couple of pieces. We did the finish on it, but that's coming out where people can just understand what they're paying per door. But give us a call up. We'll walk you through the exercise. We'll show you what you're costing. Think about that as your first profit center, Jason. And then we can talk about other ones and we help give some people some advice still. [00:45:22] Jason: So David, you have a lot of knowledge and experience. How much of your knowledge and experience has gone into bringing this AI up to understanding what you know?  [00:45:32] David: I've been working on this for 12 years. Of putting the data and the learnings. And again, I've been fortunate guys where it was just my path. [00:45:39] It was my journey through this, where I've got to work for some huge outfits. I had my own consulting company for seven years. I was working with some of the biggest SFR groups in the nation, guys with 10,000-20,000 doors. And I'm just fortunate to understand the amount of data. So, I've put my blood, sweat and tears into this, but at the core of that Jason, my blood, sweat, and tears. [00:46:00] Is that, 15 years ago when I was brand new in this property management space, I had a broker tell me one time that after the sale of the property is done, the success of the owner is no longer your business or mine. And it's up to them. The sale is done. And they told me that when they walked away and that bothered me to this day, it bothered me that the fiduciary duty that individuals are giving to us to manage in some cases, millions of dollars of their money and assets and portfolios, right? And what type of products or services are we demanding of this industry? That we would demand of, let's say if I gave 50,000 to my broker to invest in the stock market for me, what type of services and technology and platforms am I demanding of that person, education, schooling, name brands, right? [00:46:45] But yet, are we demanding that same of us in our fiduciary duty to somebody that's giving over maybe their retirement to us their kids', future, college... you hear all these people, "why'd you get into real estate?" "I want to create a college fund for my kids." And after two years, the guy's like, "this is not what I signed up for. This is the worst mistake I ever made. And I'm backing out of, buying more properties because of challenges," right? That's what I'm driven by. And I've always been driven by that. It's my curse. And so I'd have to say there's a hundred percent of me in this Jason, for sure.  [00:47:13] Jason: Awesome. And it, this will outlive you like AI doesn't die. [00:47:17] And this is this not to be grim, but this is the concern. Like anybody has when they're signing up for a business, they're like, all right, "how much is reliant on just this one person? How much is reliant on that key person I'm interacting with?" Right. And the AI is not a person. Right? [00:47:34] And so, yeah, so that's really fascinating to think about. Like you've built all that into it and it has immediate, instant expertise. It's not like, "Hey, well, let me go call Tom and let me go check with Fred or let me..." like all the data it has, it's there and it's instant. [00:47:54] David: What's the difference between an emergency of a hot water tank that's leaking in a basement with a permeable stone floor versus emergency hot water tank that's located in the utility closet on the first floor? [00:48:04] One doesn't have to necessarily require a person to go out because there's no damage to prevent with water leaking down there. But the other one is leaking onto the floor and damaging your drywall. So these conditions have to be taking place. Locations of hot water tanks, like there's, I can nerd out in this and I'd love to sit down with anybody and drink beers and talk about all the millions of different maintenance things that I ran through. [00:48:24] But at the end of the day, when you're able to show your owner, "we acted as an expert." That's the guy that's going to say to his buddy when they're just having a drink, "call these guys up to manage your property because they're an expert in the thing." And that's what we're trying to bring to the industry for sure. [00:48:37] Jason: So this brings a level of expertise that the business owner, the property manager, the maintenance coordinator, and certainly the VA's just would not possess.  [00:48:48] David: You're talking 15 years, over 500,000 work orders worth of data points, learning and understanding from commercial, multifamily, single family across the board, best practices. [00:49:01] And it's for somebody who wants to imagine now a person can start a property management company tomorrow onboard Tulu. And they're immediately a veteran in the maintenance industry. Immediately.  [00:49:12] Yeah. No learning curve. You're operating and executing as the best maintenance coordinator in the industry starting tomorrow. [00:49:19] That's amazing. Yeah. Yeah. Yeah. It's really cool. Really cool.  [00:49:22] Jason: This is really, it's really wild. So now my brain's like, how can I get experts, how can I clone Tulu, but make an operator version of Tulu for running a property managed business. Or I can make it.  [00:49:32] David: Yeah there's, there, there are offshoots on this. [00:49:34] I would have to say, and I do want to tell anybody that in this space that we always say that property managers are safe because you know what the property managers do a great job of doing. You guys do a really good job at building relationships and creating value in your local markets. [00:49:46] Right. Focus on that. Don't get pulled into maintenance, right? Maintenance and that stuff can be automated. There are best practices. Don't struggle to have to be an expert there. Show your value and the resources and tools that you have. Lower your overhead. Produce better results. Be at networking events. [00:50:03] Shake more hands. Talk to more people. Sell more homes. Add more doors. Shine where you shine. Brokers shine when they're out in front of people shaking hands and having expensive salads over a nice glass of chardonnay and closing deals, right? Let us flip the toilets and do it well for you. [00:50:18] That's what I say.  [00:50:19] Jason: Awesome. Okay, cool. David, if they're interested in Getting started. How do they find out about Tulu? You can go right to our website  [00:50:26] David: at trytulu. com. And if anybody wants to email me personally, david.norman.trytulu.Com. I'll connect you with our sales team and set you up on a personal demo. I'll walk you through it. I promise I won't bring so much energy. I'm an energy guy. It's just my calling this space to be in the maintenance and I love to doing what we're doing and seeing owners go "yes!" Seeing property managers go "yes!" And we're not trying to replace anybody. We're just trying to help people honor their fiduciary duty to their owners. And that's my mission. That's what I'm driven by.  [00:50:56] Jason: Yeah. Fantastic. So try Tulu, T U L U. Dot com.  [00:51:02] David: Yeah.  [00:51:02] Jason: All right. Try it out.  [00:51:04] David: All right.  [00:51:04] Jason: David, thanks for coming on the DoorGrowShow podcast. Appreciate you.  [00:51:08] David: Yeah. Yeah. Thank you, Jason. Always great. Looking forward to the show. Until next time.  [00:51:11] Jason: All right. So if you are a property management entrepreneur and you are wanting to add doors, you get maintenance off loaded, off your plate, and you want to focus on growth and figuring out how to get more doors, you want to join the DoorGrow mastermind, our growth accelerator is all about that. [00:51:29] We are really good at optimizing businesses for growth using our rapid revamp class, where we clean up quickly, all of the front end stuff that is causing you to like kill trust and leaking trust and preventing deals. And then we give you the right strategies. We've got at least seven different growth engines that we can help build into your business that you can stack that will feed you unlimited leads without having to spend any money on advertising or marketing expense. [00:51:55] You just need people and it actually decreases the amount of time those people will spend If they're following working on the warm leads and the stuff that we would get you to do instead of cold leads, which take a lot more time. So we also have our super system level of our mastermind. This is where we're focused on ops, operations, helping your operator. That key person that's going to run the entire business for you, Mr. or Mrs. Visionary Entrepreneur, and they will help take your business to the next level. We can coach and support your operators, your BDMs, your salespeople, or you, the business owner to make this business infinitely scalable so that you can go to the next level and add a lot of doors. So reach out to us, let us assess your situation and see if we can help. [00:52

Según el grupo ‘La Paz del Norte del Valle', como “muestra de buena voluntad” se comprometerán a que, a partir de este 11 de junio, “no habrá muertes violentas durante un mes” en el Valle del Cauca. 

En esta misiva, firmada por Andrés Felipe Marín Silva, alias ‘Pipe Tuluá', se hace un reconocimiento de la reunión, se agradece y se brindan detalles sobre quiénes asistieron al encuentro con el Gobierno Nacional.

Julio Sánchez Cristo, director de La W, reveló en exclusiva que la organización criminal ‘La Inmaculada' se reunirá con el Gobierno Nacional para presentarle su propuesta para llevar paz al departamento del Valle del Cauca.

‘Pipe Tuluá' se reunirá con el Ministerio de Justicia el próximo 6 de junio.

A través de una carta, conocida por La W, alias ‘Pipe Tuluá' advirtió que se han firmado comunicados falsos a nombre de su organización criminal.

El coronel Elmer Fernández, director de la cárcel La Modelo de Bogotá, fue asesinado en la tarde del jueves 16 de mayo en la calle 80 con carrera 30.

The Siri Sandhi also Siri Paddana (pronounced: Siri Paadhdhana) or Epic of Siri is an epic poem in the Tulu language. Consisting of 15,683 lines of poetry, it is the longest poem in Tulu. The epic is essentially a biography of a legendary Bunt[1] princess Siri Alvedi and expands to describe the fate of her progeny – son Kumara, daughter Sonne and grand daughters Abbage and Darage. The epic declares Siri's divinity and also that of her progeny and she is worshipped as a Daiva goddess) across Tulu Nadu region of South West India in temples known as Adi Alade. Siri is the patron deity of the Tulu people.

Javier Jaramillo, presidente del Consejo de Tuluá, conversó con La W acerca de la preocupante situación de orden público que se vive en este municipio del Valle del Cauca.

Martín Hincapié, secretario de Gobierno de Tuluá, habló sobre las medidas que se han tomado después del asesinato del segundo concejal del partido conservador en Tulúa, Carlos Arturo Londoño, y a la líder social, Clarivet Ocampo el pasado 19 de abril

El remezón en la SuperSalud ¿Qué pasará con 7 mil funcionarios de la Registraduría? Grave golpe contra el desarrollo del país.- Gracias a Petro y sus MinistrosPetro normalizando el secuestro de los magistrados de la Corte Suprema de Justicia. Y el General Salamanca?La Corte el viernesEl amigo español contratista del gobierno PetroVerónica abucheada en el CarnavalParo armado ELN en el chocó Grave situación de orden público en Tuluá. El CD va a hablar con Almagro en la OEA La carta de los 20 expresidentes contra las presiones a la Corte