Podcasts about chat ai

Let's talk. Send me a message with your email and I'll get back to you!

One last Gold sponsor slot is available for the AI Engineer Summit in NYC. Our last round of invites is going out soon - apply here - If you are building AI agents or AI eng teams, this will be the single highest-signal conference of the year for you!While the world melts down over DeepSeek, few are talking about the OTHER notable group of former hedge fund traders who pivoted into AI and built a remarkably profitable consumer AI business with a tiny team with incredibly cracked engineering team — Chai Research. In short order they have:* Started a Chat AI company well before Noam Shazeer started Character AI, and outlasted his departure.* Crossed 1m DAU in 2.5 years - William updates us on the pod that they've hit 1.4m DAU now, another +40% from a few months ago. Revenue crossed >$22m. * Launched the Chaiverse model crowdsourcing platform - taking 3-4 week A/B testing cycles down to 3-4 hours, and deploying >100 models a week.While they're not paying million dollar salaries, you can tell they're doing pretty well for an 11 person startup:The Chai Recipe: Building infra for rapid evalsRemember how the central thesis of LMarena (formerly LMsys) is that the only comprehensive way to evaluate LLMs is to let users try them out and pick winners?At the core of Chai is a mobile app that looks like Character AI, but is actually the largest LLM A/B testing arena in the world, specialized on retaining chat users for Chai's usecases (therapy, assistant, roleplay, etc). It's basically what LMArena would be if taken very, very seriously at one company (with $1m in prizes to boot):Chai publishes occasional research on how they think about this, including talks at their Palo Alto office:William expands upon this in today's podcast (34 mins in):Fundamentally, the way I would describe it is when you're building anything in life, you need to be able to evaluate it. And through evaluation, you can iterate, we can look at benchmarks, and we can say the issues with benchmarks and why they may not generalize as well as one would hope in the challenges of working with them. But something that works incredibly well is getting feedback from humans. And so we built this thing where anyone can submit a model to our developer backend, and it gets put in front of 5000 users, and the users can rate it. And we can then have a really accurate ranking of like which model, or users finding more engaging or more entertaining. And it gets, you know, it's at this point now, where every day we're able to, I mean, we evaluate between 20 and 50 models, LLMs, every single day, right. So even though we've got only got a team of, say, five AI researchers, they're able to iterate a huge quantity of LLMs, right. So our team ships, let's just say minimum 100 LLMs a week is what we're able to iterate through. Now, before that moment in time, we might iterate through three a week, we might, you know, there was a time when even doing like five a month was a challenge, right? By being able to change the feedback loops to the point where it's not, let's launch these three models, let's do an A-B test, let's assign, let's do different cohorts, let's wait 30 days to see what the day 30 retention is, which is the kind of the, if you're doing an app, that's like A-B testing 101 would be, do a 30-day retention test, assign different treatments to different cohorts and come back in 30 days. So that's insanely slow. That's just, it's too slow. And so we were able to get that 30-day feedback loop all the way down to something like three hours.In Crowdsourcing the leap to Ten Trillion-Parameter AGI, William describes Chai's routing as a recommender system, which makes a lot more sense to us than previous pitches for model routing startups:William is notably counter-consensus in a lot of his AI product principles:* No streaming: Chats appear all at once to allow rejection sampling* No voice: Chai actually beat Character AI to introducing voice - but removed it after finding that it was far from a killer feature.* Blending: “Something that we love to do at Chai is blending, which is, you know, it's the simplest way to think about it is you're going to end up, and you're going to pretty quickly see you've got one model that's really smart, one model that's really funny. How do you get the user an experience that is both smart and funny? Well, just 50% of the requests, you can serve them the smart model, 50% of the requests, you serve them the funny model.” (that's it!)But chief above all is the recommender system.We also referenced Exa CEO Will Bryk's concept of SuperKnowlege:Full Video versionOn YouTube. please like and subscribe!Timestamps* 00:00:04 Introductions and background of William Beauchamp* 00:01:19 Origin story of Chai AI* 00:04:40 Transition from finance to AI* 00:11:36 Initial product development and idea maze for Chai* 00:16:29 User psychology and engagement with AI companions* 00:20:00 Origin of the Chai name* 00:22:01 Comparison with Character AI and funding challenges* 00:25:59 Chai's growth and user numbers* 00:34:53 Key inflection points in Chai's growth* 00:42:10 Multi-modality in AI companions and focus on user-generated content* 00:46:49 Chaiverse developer platform and model evaluation* 00:51:58 Views on AGI and the nature of AI intelligence* 00:57:14 Evaluation methods and human feedback in AI development* 01:02:01 Content creation and user experience in Chai* 01:04:49 Chai Grant program and company culture* 01:07:20 Inference optimization and compute costs* 01:09:37 Rejection sampling and reward models in AI generation* 01:11:48 Closing thoughts and recruitmentTranscriptAlessio [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO at Decibel, and today we're in the Chai AI office with my usual co-host, Swyx.swyx [00:00:14]: Hey, thanks for having us. It's rare that we get to get out of the office, so thanks for inviting us to your home. We're in the office of Chai with William Beauchamp. Yeah, that's right. You're founder of Chai AI, but previously, I think you're concurrently also running your fund?William [00:00:29]: Yep, so I was simultaneously running an algorithmic trading company, but I fortunately was able to kind of exit from that, I think just in Q3 last year. Yeah, congrats. Yeah, thanks.swyx [00:00:43]: So Chai has always been on my radar because, well, first of all, you do a lot of advertising, I guess, in the Bay Area, so it's working. Yep. And second of all, the reason I reached out to a mutual friend, Joyce, was because I'm just generally interested in the... ...consumer AI space, chat platforms in general. I think there's a lot of inference insights that we can get from that, as well as human psychology insights, kind of a weird blend of the two. And we also share a bit of a history as former finance people crossing over. I guess we can just kind of start it off with the origin story of Chai.William [00:01:19]: Why decide working on a consumer AI platform rather than B2B SaaS? So just quickly touching on the background in finance. Sure. Originally, I'm from... I'm from the UK, born in London. And I was fortunate enough to go study economics at Cambridge. And I graduated in 2012. And at that time, everyone in the UK and everyone on my course, HFT, quant trading was really the big thing. It was like the big wave that was happening. So there was a lot of opportunity in that space. And throughout college, I'd sort of played poker. So I'd, you know, I dabbled as a professional poker player. And I was able to accumulate this sort of, you know, say $100,000 through playing poker. And at the time, as my friends would go work at companies like ChangeStreet or Citadel, I kind of did the maths. And I just thought, well, maybe if I traded my own capital, I'd probably come out ahead. I'd make more money than just going to work at ChangeStreet.swyx [00:02:20]: With 100k base as capital?William [00:02:22]: Yes, yes. That's not a lot. Well, it depends what strategies you're doing. And, you know, there is an advantage. There's an advantage to being small, right? Because there are, if you have a 10... Strategies that don't work in size. Exactly, exactly. So if you have a fund of $10 million, if you find a little anomaly in the market that you might be able to make 100k a year from, that's a 1% return on your 10 million fund. If your fund is 100k, that's 100% return, right? So being small, in some sense, was an advantage. So started off, and the, taught myself Python, and machine learning was like the big thing as well. Machine learning had really, it was the first, you know, big time machine learning was being used for image recognition, neural networks come out, you get dropout. And, you know, so this, this was the big thing that's going on at the time. So I probably spent my first three years out of Cambridge, just building neural networks, building random forests to try and predict asset prices, right, and then trade that using my own money. And that went well. And, you know, if you if you start something, and it goes well, you You try and hire more people. And the first people that came to mind was the talented people I went to college with. And so I hired some friends. And that went well and hired some more. And eventually, I kind of ran out of friends to hire. And so that was when I formed the company. And from that point on, we had our ups and we had our downs. And that was a whole long story and journey in itself. But after doing that for about eight or nine years, on my 30th birthday, which was four years ago now, I kind of took a step back to just evaluate my life, right? This is what one does when one turns 30. You know, I just heard it. I hear you. And, you know, I looked at my 20s and I loved it. It was a really special time. I was really lucky and fortunate to have worked with this amazing team, been successful, had a lot of hard times. And through the hard times, learned wisdom and then a lot of success and, you know, was able to enjoy it. And so the company was making about five million pounds a year. And it was just me and a team of, say, 15, like, Oxford and Cambridge educated mathematicians and physicists. It was like the real dream that you'd have if you wanted to start a quant trading firm. It was like...swyx [00:04:40]: Your own, all your own money?William [00:04:41]: Yeah, exactly. It was all the team's own money. We had no customers complaining to us about issues. There's no investors, you know, saying, you know, they don't like the risk that we're taking. We could. We could really run the thing exactly as we wanted it. It's like Susquehanna or like Rintec. Yeah, exactly. Yeah. And they're the companies that we would kind of look towards as we were building that thing out. But on my 30th birthday, I look and I say, OK, great. This thing is making as much money as kind of anyone would really need. And I thought, well, what's going to happen if we keep going in this direction? And it was clear that we would never have a kind of a big, big impact on the world. We can enrich ourselves. We can make really good money. Everyone on the team would be paid very, very well. Presumably, I can make enough money to buy a yacht or something. But this stuff wasn't that important to me. And so I felt a sort of obligation that if you have this much talent and if you have a talented team, especially as a founder, you want to be putting all that talent towards a good use. I looked at the time of like getting into crypto and I had a really strong view on crypto, which was that as far as a gambling device. This is like the most fun form of gambling invented in like ever super fun, I thought as a way to evade monetary regulations and banking restrictions. I think it's also absolutely amazing. So it has two like killer use cases, not so much banking the unbanked, but everything else, but everything else to do with like the blockchain and, and you know, web, was it web 3.0 or web, you know, that I, that didn't, it didn't really make much sense. And so instead of going into crypto, which I thought, even if I was successful, I'd end up in a lot of trouble. I thought maybe it'd be better to build something that governments wouldn't have a problem with. I knew that LLMs were like a thing. I think opening. I had said they hadn't released GPT-3 yet, but they'd said GPT-3 is so powerful. We can't release it to the world or something. Was it GPT-2? And then I started interacting with, I think Google had open source, some language models. They weren't necessarily LLMs, but they, but they were. But yeah, exactly. So I was able to play around with, but nowadays so many people have interacted with the chat GPT, they get it, but it's like the first time you, you can just talk to a computer and it talks back. It's kind of a special moment and you know, everyone who's done that goes like, wow, this is how it should be. Right. It should be like, rather than having to type on Google and search, you should just be able to ask Google a question. When I saw that I read the literature, I kind of came across the scaling laws and I think even four years ago. All the pieces of the puzzle were there, right? Google had done this amazing research and published, you know, a lot of it. Open AI was still open. And so they'd published a lot of their research. And so you really could be fully informed on, on the state of AI and where it was going. And so at that point I was confident enough, it was worth a shot. I think LLMs are going to be the next big thing. And so that's the thing I want to be building in, in that space. And I thought what's the most impactful product I can possibly build. And I thought it should be a platform. So I myself love platforms. I think they're fantastic because they open up an ecosystem where anyone can contribute to it. Right. So if you think of a platform like a YouTube, instead of it being like a Hollywood situation where you have to, if you want to make a TV show, you have to convince Disney to give you the money to produce it instead, anyone in the world can post any content they want to YouTube. And if people want to view it, the algorithm is going to promote it. Nowadays. You can look at creators like Mr. Beast or Joe Rogan. They would have never have had that opportunity unless it was for this platform. Other ones like Twitter's a great one, right? But I would consider Wikipedia to be a platform where instead of the Britannica encyclopedia, which is this, it's like a monolithic, you get all the, the researchers together, you get all the data together and you combine it in this, in this one monolithic source. Instead. You have this distributed thing. You can say anyone can host their content on Wikipedia. Anyone can contribute to it. And anyone can maybe their contribution is they delete stuff. When I was hearing like the kind of the Sam Altman and kind of the, the Muskian perspective of AI, it was a very kind of monolithic thing. It was all about AI is basically a single thing, which is intelligence. Yeah. Yeah. The more intelligent, the more compute, the more intelligent, and the more and better AI researchers, the more intelligent, right? They would speak about it as a kind of erased, like who can get the most data, the most compute and the most researchers. And that would end up with the most intelligent AI. But I didn't believe in any of that. I thought that's like the total, like I thought that perspective is the perspective of someone who's never actually done machine learning. Because with machine learning, first of all, you see that the performance of the models follows an S curve. So it's not like it just goes off to infinity, right? And the, the S curve, it kind of plateaus around human level performance. And you can look at all the, all the machine learning that was going on in the 2010s, everything kind of plateaued around the human level performance. And we can think about the self-driving car promises, you know, how Elon Musk kept saying the self-driving car is going to happen next year, it's going to happen next, next year. Or you can look at the image recognition, the speech recognition. You can look at. All of these things, there was almost nothing that went superhuman, except for something like AlphaGo. And we can speak about why AlphaGo was able to go like super superhuman. So I thought the most likely thing was going to be this, I thought it's not going to be a monolithic thing. That's like an encyclopedia Britannica. I thought it must be a distributed thing. And I actually liked to look at the world of finance for what I think a mature machine learning ecosystem would look like. So, yeah. So finance is a machine learning ecosystem because all of these quant trading firms are running machine learning algorithms, but they're running it on a centralized platform like a marketplace. And it's not the case that there's one giant quant trading company of all the data and all the quant researchers and all the algorithms and compute, but instead they all specialize. So one will specialize on high frequency training. Another will specialize on mid frequency. Another one will specialize on equity. Another one will specialize. And I thought that's the way the world works. That's how it is. And so there must exist a platform where a small team can produce an AI for a unique purpose. And they can iterate and build the best thing for that, right? And so that was the vision for Chai. So we wanted to build a platform for LLMs.Alessio [00:11:36]: That's kind of the maybe inside versus contrarian view that led you to start the company. Yeah. And then what was maybe the initial idea maze? Because if somebody told you that was the Hugging Face founding story, people might believe it. It's kind of like a similar ethos behind it. How did you land on the product feature today? And maybe what were some of the ideas that you discarded that initially you thought about?William [00:11:58]: So the first thing we built, it was fundamentally an API. So nowadays people would describe it as like agents, right? But anyone could write a Python script. They could submit it to an API. They could send it to the Chai backend and we would then host this code and execute it. So that's like the developer side of the platform. On their Python script, the interface was essentially text in and text out. An example would be the very first bot that I created. I think it was a Reddit news bot. And so it would first, it would pull the popular news. Then it would prompt whatever, like I just use some external API for like Burr or GPT-2 or whatever. Like it was a very, very small thing. And then the user could talk to it. So you could say to the bot, hi bot, what's the news today? And it would say, this is the top stories. And you could chat with it. Now four years later, that's like perplexity or something. That's like the, right? But back then the models were first of all, like really, really dumb. You know, they had an IQ of like a four year old. And users, there really wasn't any demand or any PMF for interacting with the news. So then I was like, okay. Um. So let's make another one. And I made a bot, which was like, you could talk to it about a recipe. So you could say, I'm making eggs. Like I've got eggs in my fridge. What should I cook? And it'll say, you should make an omelet. Right. There was no PMF for that. No one used it. And so I just kept creating bots. And so every single night after work, I'd be like, okay, I like, we have AI, we have this platform. I can create any text in textile sort of agent and put it on the platform. And so we just create stuff night after night. And then all the coders I knew, I would say, yeah, this is what we're going to do. And then I would say to them, look, there's this platform. You can create any like chat AI. You should put it on. And you know, everyone's like, well, chatbots are super lame. We want absolutely nothing to do with your chatbot app. No one who knew Python wanted to build on it. I'm like trying to build all these bots and no consumers want to talk to any of them. And then my sister who at the time was like just finishing college or something, I said to her, I was like, if you want to learn Python, you should just submit a bot for my platform. And she, she built a therapy for me. And I was like, okay, cool. I'm going to build a therapist bot. And then the next day I checked the performance of the app and I'm like, oh my God, we've got 20 active users. And they spent, they spent like an average of 20 minutes on the app. I was like, oh my God, what, what bot were they speaking to for an average of 20 minutes? And I looked and it was the therapist bot. And I went, oh, this is where the PMF is. There was no demand for, for recipe help. There was no demand for news. There was no demand for dad jokes or pub quiz or fun facts or what they wanted was they wanted the therapist bot. the time I kind of reflected on that and I thought, well, if I want to consume news, the most fun thing, most fun way to consume news is like Twitter. It's not like the value of there being a back and forth, wasn't that high. Right. And I thought if I need help with a recipe, I actually just go like the New York times has a good recipe section, right? It's not actually that hard. And so I just thought the thing that AI is 10 X better at is a sort of a conversation right. That's not intrinsically informative, but it's more about an opportunity. You can say whatever you want. You're not going to get judged. If it's 3am, you don't have to wait for your friend to text back. It's like, it's immediate. They're going to reply immediately. You can say whatever you want. It's judgment-free and it's much more like a playground. It's much more like a fun experience. And you could see that if the AI gave a person a compliment, they would love it. It's much easier to get the AI to give you a compliment than a human. From that day on, I said, okay, I get it. Humans want to speak to like humans or human like entities and they want to have fun. And that was when I started to look less at platforms like Google. And I started to look more at platforms like Instagram. And I was trying to think about why do people use Instagram? And I could see that I think Chai was, was filling the same desire or the same drive. If you go on Instagram, typically you want to look at the faces of other humans, or you want to hear about other people's lives. So if it's like the rock is making himself pancakes on a cheese plate. You kind of feel a little bit like you're the rock's friend, or you're like having pancakes with him or something, right? But if you do it too much, you feel like you're sad and like a lonely person, but with AI, you can talk to it and tell it stories and tell you stories, and you can play with it for as long as you want. And you don't feel like you're like a sad, lonely person. You feel like you actually have a friend.Alessio [00:16:29]: And what, why is that? Do you have any insight on that from using it?William [00:16:33]: I think it's just the human psychology. I think it's just the idea that, with old school social media. You're just consuming passively, right? So you'll just swipe. If I'm watching TikTok, just like swipe and swipe and swipe. And even though I'm getting the dopamine of like watching an engaging video, there's this other thing that's building my head, which is like, I'm feeling lazier and lazier and lazier. And after a certain period of time, I'm like, man, I just wasted 40 minutes. I achieved nothing. But with AI, because you're interacting, you feel like you're, it's not like work, but you feel like you're participating and contributing to the thing. You don't feel like you're just. Consuming. So you don't have a sense of remorse basically. And you know, I think on the whole people, the way people talk about, try and interact with the AI, they speak about it in an incredibly positive sense. Like we get people who say they have eating disorders saying that the AI helps them with their eating disorders. People who say they're depressed, it helps them through like the rough patches. So I think there's something intrinsically healthy about interacting that TikTok and Instagram and YouTube doesn't quite tick. From that point on, it was about building more and more kind of like human centric AI for people to interact with. And I was like, okay, let's make a Kanye West bot, right? And then no one wanted to talk to the Kanye West bot. And I was like, ah, who's like a cool persona for teenagers to want to interact with. And I was like, I was trying to find the influencers and stuff like that, but no one cared. Like they didn't want to interact with the, yeah. And instead it was really just the special moment was when we said the realization that developers and software engineers aren't interested in building this sort of AI, but the consumers are right. And rather than me trying to guess every day, like what's the right bot to submit to the platform, why don't we just create the tools for the users to build it themselves? And so nowadays this is like the most obvious thing in the world, but when Chai first did it, it was not an obvious thing at all. Right. Right. So we took the API for let's just say it was, I think it was GPTJ, which was this 6 billion parameter open source transformer style LLM. We took GPTJ. We let users create the prompt. We let users select the image and we let users choose the name. And then that was the bot. And through that, they could shape the experience, right? So if they said this bot's going to be really mean, and it's going to be called like bully in the playground, right? That was like a whole category that I never would have guessed. Right. People love to fight. They love to have a disagreement, right? And then they would create, there'd be all these romantic archetypes that I didn't know existed. And so as the users could create the content that they wanted, that was when Chai was able to, to get this huge variety of content and rather than appealing to, you know, 1% of the population that I'd figured out what they wanted, you could appeal to a much, much broader thing. And so from that moment on, it was very, very crystal clear. It's like Chai, just as Instagram is this social media platform that lets people create images and upload images, videos and upload that, Chai was really about how can we let the users create this experience in AI and then share it and interact and search. So it's really, you know, I say it's like a platform for social AI.Alessio [00:20:00]: Where did the Chai name come from? Because you started the same path. I was like, is it character AI shortened? You started at the same time, so I was curious. The UK origin was like the second, the Chai.William [00:20:15]: We started way before character AI. And there's an interesting story that Chai's numbers were very, very strong, right? So I think in even 20, I think late 2022, was it late 2022 or maybe early 2023? Chai was like the number one AI app in the app store. So we would have something like 100,000 daily active users. And then one day we kind of saw there was this website. And we were like, oh, this website looks just like Chai. And it was the character AI website. And I think that nowadays it's, I think it's much more common knowledge that when they left Google with the funding, I think they knew what was the most trending, the number one app. And I think they sort of built that. Oh, you found the people.swyx [00:21:03]: You found the PMF for them.William [00:21:04]: We found the PMF for them. Exactly. Yeah. So I worked a year very, very hard. And then they, and then that was when I learned a lesson, which is that if you're VC backed and if, you know, so Chai, we'd kind of ran, we'd got to this point, I was the only person who'd invested. I'd invested maybe 2 million pounds in the business. And you know, from that, we were able to build this thing, get to say a hundred thousand daily active users. And then when character AI came along, the first version, we sort of laughed. We were like, oh man, this thing sucks. Like they don't know what they're building. They're building the wrong thing anyway, but then I saw, oh, they've raised a hundred million dollars. Oh, they've raised another hundred million dollars. And then our users started saying, oh guys, your AI sucks. Cause we were serving a 6 billion parameter model, right? How big was the model that character AI could afford to serve, right? So we would be spending, let's say we would spend a dollar per per user, right? Over the, the, you know, the entire lifetime.swyx [00:22:01]: A dollar per session, per chat, per month? No, no, no, no.William [00:22:04]: Let's say we'd get over the course of the year, we'd have a million users and we'd spend a million dollars on the AI throughout the year. Right. Like aggregated. Exactly. Exactly. Right. They could spend a hundred times that. So people would say, why is your AI much dumber than character AIs? And then I was like, oh, okay, I get it. This is like the Silicon Valley style, um, hyper scale business. And so, yeah, we moved to Silicon Valley and, uh, got some funding and iterated and built the flywheels. And, um, yeah, I, I'm very proud that we were able to compete with that. Right. So, and I think the reason we were able to do it was just customer obsession. And it's similar, I guess, to how deep seek have been able to produce such a compelling model when compared to someone like an open AI, right? So deep seek, you know, their latest, um, V2, yeah, they claim to have spent 5 million training it.swyx [00:22:57]: It may be a bit more, but, um, like, why are you making it? Why are you making such a big deal out of this? Yeah. There's an agenda there. Yeah. You brought up deep seek. So we have to ask you had a call with them.William [00:23:07]: We did. We did. We did. Um, let me think what to say about that. I think for one, they have an amazing story, right? So their background is again in finance.swyx [00:23:16]: They're the Chinese version of you. Exactly.William [00:23:18]: Well, there's a lot of similarities. Yes. Yes. I have a great affinity for companies which are like, um, founder led, customer obsessed and just try and build something great. And I think what deep seek have achieved. There's quite special is they've got this amazing inference engine. They've been able to reduce the size of the KV cash significantly. And then by being able to do that, they're able to significantly reduce their inference costs. And I think with kind of with AI, people get really focused on like the kind of the foundation model or like the model itself. And they sort of don't pay much attention to the inference. To give you an example with Chai, let's say a typical user session is 90 minutes, which is like, you know, is very, very long for comparison. Let's say the average session length on TikTok is 70 minutes. So people are spending a lot of time. And in that time they're able to send say 150 messages. That's a lot of completions, right? It's quite different from an open AI scenario where people might come in, they'll have a particular question in mind. And they'll ask like one question. And a few follow up questions, right? So because they're consuming, say 30 times as many requests for a chat, or a conversational experience, you've got to figure out how to how to get the right balance between the cost of that and the quality. And so, you know, I think with AI, it's always been the case that if you want a better experience, you can throw compute at the problem, right? So if you want a better model, you can just make it bigger. If you want it to remember better, give it a longer context. And now, what open AI is doing to great fanfare is with projection sampling, you can generate many candidates, right? And then with some sort of reward model or some sort of scoring system, you can serve the most promising of these many candidates. And so that's kind of scaling up on the inference time compute side of things. And so for us, it doesn't make sense to think of AI is just the absolute performance. So. But what we're seeing, it's like the MML you score or the, you know, any of these benchmarks that people like to look at, if you just get that score, it doesn't really tell tell you anything. Because it's really like progress is made by improving the performance per dollar. And so I think that's an area where deep seek have been able to form very, very well, surprisingly so. And so I'm very interested in what Lama four is going to look like. And if they're able to sort of match what deep seek have been able to achieve with this performance per dollar gain.Alessio [00:25:59]: Before we go into the inference, some of the deeper stuff, can you give people an overview of like some of the numbers? So I think last I checked, you have like 1.4 million daily active now. It's like over 22 million of revenue. So it's quite a business.William [00:26:12]: Yeah, I think we grew by a factor of, you know, users grew by a factor of three last year. Revenue over doubled. You know, it's very exciting. We're competing with some really big, really well funded companies. Character AI got this, I think it was almost a $3 billion valuation. And they have 5 million DAU is a number that I last heard. Torquay, which is a Chinese built app owned by a company called Minimax. They're incredibly well funded. And these companies didn't grow by a factor of three last year. Right. And so when you've got this company and this team that's able to keep building something that gets users excited, and they want to tell their friend about it, and then they want to come and they want to stick on the platform. I think that's very special. And so last year was a great year for the team. And yeah, I think the numbers reflect the hard work that we put in. And then fundamentally, the quality of the app, the quality of the content, the quality of the content, the quality of the content, the quality of the content, the quality of the content. AI is the quality of the experience that you have. You actually published your DAU growth chart, which is unusual. And I see some inflections. Like, it's not just a straight line. There's some things that actually inflect. Yes. What were the big ones? Cool. That's a great, great, great question. Let me think of a good answer. I'm basically looking to annotate this chart, which doesn't have annotations on it. Cool. The first thing I would say is this is, I think the most important thing to know about success is that success is born out of failures. Right? Through failures that we learn. You know, if you think something's a good idea, and you do and it works, great, but you didn't actually learn anything, because everything went exactly as you imagined. But if you have an idea, you think it's going to be good, you try it, and it fails. There's a gap between the reality and expectation. And that's an opportunity to learn. The flat periods, that's us learning. And then the up periods is that's us reaping the rewards of that. So I think the big, of the growth shot of just 2024, I think the first thing that really kind of put a dent in our growth was our backend. So we just reached this scale. So we'd, from day one, we'd built on top of Google's GCP, which is Google's cloud platform. And they were fantastic. We used them when we had one daily active user, and they worked pretty good all the way up till we had about 500,000. It was never the cheapest, but from an engineering perspective, man, that thing scaled insanely good. Like, not Vertex? Not Vertex. Like GKE, that kind of stuff? We use Firebase. So we use Firebase. I'm pretty sure we're the biggest user ever on Firebase. That's expensive. Yeah, we had calls with engineers, and they're like, we wouldn't recommend using this product beyond this point, and you're 3x over that. So we pushed Google to their absolute limits. You know, it was fantastic for us, because we could focus on the AI. We could focus on just adding as much value as possible. But then what happened was, after 500,000, just the thing, the way we were using it, and it would just, it wouldn't scale any further. And so we had a really, really painful, at least three-month period, as we kind of migrated between different services, figuring out, like, what requests do we want to keep on Firebase, and what ones do we want to move on to something else? And then, you know, making mistakes. And learning things the hard way. And then after about three months, we got that right. So that, we would then be able to scale to the 1.5 million DAE without any further issues from the GCP. But what happens is, if you have an outage, new users who go on your app experience a dysfunctional app, and then they're going to exit. And so your next day, the key metrics that the app stores track are going to be something like retention rates. And so your next day, the key metrics that the app stores track are going to be something like retention rates. Money spent, and the star, like, the rating that they give you. In the app store. In the app store, yeah. Tyranny. So if you're ranked top 50 in entertainment, you're going to acquire a certain rate of users organically. If you go in and have a bad experience, it's going to tank where you're positioned in the algorithm. And then it can take a long time to kind of earn your way back up, at least if you wanted to do it organically. If you throw money at it, you can jump to the top. And I could talk about that. But broadly speaking, if we look at 2024, the first kink in the graph was outages due to hitting 500k DAU. The backend didn't want to scale past that. So then we just had to do the engineering and build through it. Okay, so we built through that, and then we get a little bit of growth. And so, okay, that's feeling a little bit good. I think the next thing, I think it's, I'm not going to lie, I have a feeling that when Character AI got... I was thinking. I think so. I think... So the Character AI team fundamentally got acquired by Google. And I don't know what they changed in their business. I don't know if they dialed down that ad spend. Products don't change, right? Products just what it is. I don't think so. Yeah, I think the product is what it is. It's like maintenance mode. Yes. I think the issue that people, you know, some people may think this is an obvious fact, but running a business can be very competitive, right? Because other businesses can see what you're doing, and they can imitate you. And then there's this... There's this question of, if you've got one company that's spending $100,000 a day on advertising, and you've got another company that's spending zero, if you consider market share, and if you're considering new users which are entering the market, the guy that's spending $100,000 a day is going to be getting 90% of those new users. And so I have a suspicion that when the founders of Character AI left, they dialed down their spending on user acquisition. And I think that kind of gave oxygen to like the other apps. And so Chai was able to then start growing again in a really healthy fashion. I think that's kind of like the second thing. I think a third thing is we've really built a great data flywheel. Like the AI team sort of perfected their flywheel, I would say, in end of Q2. And I could speak about that at length. But fundamentally, the way I would describe it is when you're building anything in life, you need to be able to evaluate it. And through evaluation, you can iterate, we can look at benchmarks, and we can say the issues with benchmarks and why they may not generalize as well as one would hope in the challenges of working with them. But something that works incredibly well is getting feedback from humans. And so we built this thing where anyone can submit a model to our developer backend, and it gets put in front of 5000 users, and the users can rate it. And we can then have a really accurate ranking of like which model, or users finding more engaging or more entertaining. And it gets, you know, it's at this point now, where every day we're able to, I mean, we evaluate between 20 and 50 models, LLMs, every single day, right. So even though we've got only got a team of, say, five AI researchers, they're able to iterate a huge quantity of LLMs, right. So our team ships, let's just say minimum 100 LLMs a week is what we're able to iterate through. Now, before that moment in time, we might iterate through three a week, we might, you know, there was a time when even doing like five a month was a challenge, right? By being able to change the feedback loops to the point where it's not, let's launch these three models, let's do an A-B test, let's assign, let's do different cohorts, let's wait 30 days to see what the day 30 retention is, which is the kind of the, if you're doing an app, that's like A-B testing 101 would be, do a 30-day retention test, assign different treatments to different cohorts and come back in 30 days. So that's insanely slow. That's just, it's too slow. And so we were able to get that 30-day feedback loop all the way down to something like three hours. And when we did that, we could really, really, really perfect techniques like DPO, fine tuning, prompt engineering, blending, rejection sampling, training a reward model, right, really successfully, like boom, boom, boom, boom, boom. And so I think in Q3 and Q4, we got, the amount of AI improvements we got was like astounding. It was getting to the point, I thought like how much more, how much more edge is there to be had here? But the team just could keep going and going and going. That was like number three for the inflection point.swyx [00:34:53]: There's a fourth?William [00:34:54]: The important thing about the third one is if you go on our Reddit or you talk to users of AI, there's like a clear date. It's like somewhere in October or something. The users, they flipped. Before October, the users... The users would say character AI is better than you, for the most part. Then from October onwards, they would say, wow, you guys are better than character AI. And that was like a really clear positive signal that we'd sort of done it. And I think people, you can't cheat consumers. You can't trick them. You can't b******t them. They know, right? If you're going to spend 90 minutes on a platform, and with apps, there's the barriers to switching is pretty low. Like you can try character AI, you can't cheat consumers. You can't cheat them. You can't cheat them. You can't cheat AI for a day. If you get bored, you can try Chai. If you get bored of Chai, you can go back to character. So the users, the loyalty is not strong, right? What keeps them on the app is the experience. If you deliver a better experience, they're going to stay and they can tell. So that was the fourth one was we were fortunate enough to get this hire. He was hired one really talented engineer. And then they said, oh, at my last company, we had a head of growth. He was really, really good. And he was the head of growth for ByteDance for two years. Would you like to speak to him? And I was like, yes. Yes, I think I would. And so I spoke to him. And he just blew me away with what he knew about user acquisition. You know, it was like a 3D chessswyx [00:36:21]: sort of thing. You know, as much as, as I know about AI. Like ByteDance as in TikTok US. Yes.William [00:36:26]: Not ByteDance as other stuff. Yep. He was interviewing us as we were interviewing him. Right. And so pick up options. Yeah, exactly. And so he was kind of looking at our metrics. And he was like, I saw him get really excited when he said, guys, you've got a million daily active users and you've done no advertising. I said, correct. And he was like, that's unheard of. He's like, I've never heard of anyone doing that. And then he started looking at our metrics. And he was like, if you've got all of this organically, if you start spending money, this is going to be very exciting. I was like, let's give it a go. So then he came in, we've just started ramping up the user acquisition. So that looks like spending, you know, let's say we're spending, we started spending $20,000 a day, it looked very promising than 20,000. Right now we're spending $40,000 a day on user acquisition. That's still only half of what like character AI or talkie may be spending. But from that, it's sort of, we were growing at a rate of maybe say, 2x a year. And that got us growing at a rate of 3x a year. So I'm growing, I'm evolving more and more to like a Silicon Valley style hyper growth, like, you know, you build something decent, and then you canswyx [00:37:33]: slap on a huge... You did the important thing, you did the product first.William [00:37:36]: Of course, but then you can slap on like, like the rocket or the jet engine or something, which is just this cash in, you pour in as much cash, you buy a lot of ads, and your growth is faster.swyx [00:37:48]: Not to, you know, I'm just kind of curious what's working right now versus what surprisinglyWilliam [00:37:52]: doesn't work. Oh, there's a long, long list of surprising stuff that doesn't work. Yeah. The surprising thing, like the most surprising thing, what doesn't work is almost everything doesn't work. That's what's surprising. And I'll give you an example. So like a year and a half ago, I was working at a company, we were super excited by audio. I was like, audio is going to be the next killer feature, we have to get in the app. And I want to be the first. So everything Chai does, I want us to be the first. We may not be the company that's strongest at execution, but we can always be theswyx [00:38:22]: most innovative. Interesting. Right? So we can... You're pretty strong at execution.William [00:38:26]: We're much stronger, we're much stronger. A lot of the reason we're here is because we were first. If we launched today, it'd be so hard to get the traction. Because it's like to get the flywheel, to get the users, to build a product people are excited about. If you're first, people are naturally excited about it. But if you're fifth or 10th, man, you've got to beswyx [00:38:46]: insanely good at execution. So you were first with voice? We were first. We were first. I only knowWilliam [00:38:51]: when character launched voice. They launched it, I think they launched it at least nine months after us. Okay. Okay. But the team worked so hard for it. At the time we did it, latency is a huge problem. Cost is a huge problem. Getting the right quality of the voice is a huge problem. Right? Then there's this user interface and getting the right user experience. Because you don't just want it to start blurting out. Right? You want to kind of activate it. But then you don't have to keep pressing a button every single time. There's a lot that goes into getting a really smooth audio experience. So we went ahead, we invested the three months, we built it all. And then when we did the A-B test, there was like, no change in any of the numbers. And I was like, this can't be right, there must be a bug. And we spent like a week just checking everything, checking again, checking again. And it was like, the users just did not care. And it was something like only 10 or 15% of users even click the button to like, they wanted to engage the audio. And they would only use it for 10 or 15% of the time. So if you do the math, if it's just like something that one in seven people use it for one seventh of their time. You've changed like 2% of the experience. So even if that that 2% of the time is like insanely good, it doesn't translate much when you look at the retention, when you look at the engagement, and when you look at the monetization rates. So audio did not have a big impact. I'm pretty big on audio. But yeah, I like it too. But it's, you know, so a lot of the stuff which I do, I'm a big, you can have a theory. And you resist. Yeah. Exactly, exactly. So I think if you want to make audio work, it has to be a unique, compelling, exciting experience that they can't have anywhere else.swyx [00:40:37]: It could be your models, which just weren't good enough.William [00:40:39]: No, no, no, they were great. Oh, yeah, they were very good. it was like, it was kind of like just the, you know, if you listen to like an audible or Kindle, or something like, you just hear this voice. And it's like, you don't go like, wow, this is this is special, right? It's like a convenience thing. But the idea is that if you can, if Chai is the only platform, like, let's say you have a Mr. Beast, and YouTube is the only platform you can use to make audio work, then you can watch a Mr. Beast video. And it's the most engaging, fun video that you want to watch, you'll go to a YouTube. And so it's like for audio, you can't just put the audio on there. And people go, oh, yeah, it's like 2% better. Or like, 5% of users think it's 20% better, right? It has to be something that the majority of people, for the majority of the experience, go like, wow, this is a big deal. That's the features you need to be shipping. If it's not going to appeal to the majority of people, for the majority of the experience, and it's not a big deal, it's not going to move you. Cool. So you killed it. I don't see it anymore. Yep. So I love this. The longer, it's kind of cheesy, I guess, but the longer I've been working at Chai, and I think the team agrees with this, all the platitudes, at least I thought they were platitudes, that you would get from like the Steve Jobs, which is like, build something insanely great, right? Or be maniacally focused, or, you know, the most important thing is saying no to, not to work on. All of these sort of lessons, they just are like painfully true. They're painfully true. So now I'm just like, everything I say, I'm either quoting Steve Jobs or Zuckerberg. I'm like, guys, move fast and break free.swyx [00:42:10]: You've jumped the Apollo to cool it now.William [00:42:12]: Yeah, it's just so, everything they said is so, so true. The turtle neck. Yeah, yeah, yeah. Everything is so true.swyx [00:42:18]: This last question on my side, and I want to pass this to Alessio, is on just, just multi-modality in general. This actually comes from Justine Moore from A16Z, who's a friend of ours. And a lot of people are trying to do voice image video for AI companions. Yes. You just said voice didn't work. Yep. What would make you revisit?William [00:42:36]: So Steve Jobs, he was very, listen, he was very, very clear on this. There's a habit of engineers who, once they've got some cool technology, they want to find a way to package up the cool technology and sell it to consumers, right? That does not work. So you're free to try and build a startup where you've got your cool tech and you want to find someone to sell it to. That's not what we do at Chai. At Chai, we start with the consumer. What does the consumer want? What is their problem? And how do we solve it? So right now, the number one problems for the users, it's not the audio. That's not the number one problem. It's not the image generation either. That's not their problem either. The number one problem for users in AI is this. All the AI is being generated by middle-aged men in Silicon Valley, right? That's all the content. You're interacting with this AI. You're speaking to it for 90 minutes on average. It's being trained by middle-aged men. The guys out there, they're out there. They're talking to you. They're talking to you. They're like, oh, what should the AI say in this situation, right? What's funny, right? What's cool? What's boring? What's entertaining? That's not the way it should be. The way it should be is that the users should be creating the AI, right? And so the way I speak about it is this. Chai, we have this AI engine in which sits atop a thin layer of UGC. So the thin layer of UGC is absolutely essential, right? It's just prompts. But it's just prompts. It's just an image. It's just a name. It's like we've done 1% of what we could do. So we need to keep thickening up that layer of UGC. It must be the case that the users can train the AI. And if reinforcement learning is powerful and important, they have to be able to do that. And so it's got to be the case that there exists, you know, I say to the team, just as Mr. Beast is able to spend 100 million a year or whatever it is on his production company, and he's got a team building the content, the Mr. Beast company is able to spend 100 million a year on his production company. And he's got a team building the content, which then he shares on the YouTube platform. Until there's a team that's earning 100 million a year or spending 100 million on the content that they're producing for the Chai platform, we're not finished, right? So that's the problem. That's what we're excited to build. And getting too caught up in the tech, I think is a fool's errand. It does not work.Alessio [00:44:52]: As an aside, I saw the Beast Games thing on Amazon Prime. It's not doing well. And I'mswyx [00:44:56]: curious. It's kind of like, I mean, the audience reading is high. The run-to-meet-all sucks, but the audience reading is high.Alessio [00:45:02]: But it's not like in the top 10. I saw it dropped off of like the... Oh, okay. Yeah, that one I don't know. I'm curious, like, you know, it's kind of like similar content, but different platform. And then going back to like, some of what you were saying is like, you know, people come to ChaiWilliam [00:45:13]: expecting some type of content. Yeah, I think it's something that's interesting to discuss is like, is moats. And what is the moat? And so, you know, if you look at a platform like YouTube, the moat, I think is in first is really is in the ecosystem. And the ecosystem, is comprised of you have the content creators, you have the users, the consumers, and then you have the algorithms. And so this, this creates a sort of a flywheel where the algorithms are able to be trained on the users, and the users data, the recommend systems can then feed information to the content creators. So Mr. Beast, he knows which thumbnail does the best. He knows the first 10 seconds of the video has to be this particular way. And so his content is super optimized for the YouTube platform. So that's why it doesn't do well on Amazon. If he wants to do well on Amazon, how many videos has he created on the YouTube platform? By thousands, 10s of 1000s, I guess, he needs to get those iterations in on the Amazon. So at Chai, I think it's all about how can we get the most compelling, rich user generated content, stick that on top of the AI engine, the recommender systems, in such that we get this beautiful data flywheel, more users, better recommendations, more creative, more content, more users.Alessio [00:46:34]: You mentioned the algorithm, you have this idea of the Chaiverse on Chai, and you have your own kind of like LMSYS-like ELO system. Yeah, what are things that your models optimize for, like your users optimize for, and maybe talk about how you build it, how people submit models?William [00:46:49]: So Chaiverse is what I would describe as a developer platform. More often when we're speaking about Chai, we're thinking about the Chai app. And the Chai app is really this product for consumers. And so consumers can come on the Chai app, they can come on the Chai app, they can come on the Chai app, they can interact with our AI, and they can interact with other UGC. And it's really just these kind of bots. And it's a thin layer of UGC. Okay. Our mission is not to just have a very thin layer of UGC. Our mission is to have as much UGC as possible. So we must have, I don't want people at Chai training the AI. I want people, not middle aged men, building AI. I want everyone building the AI, as many people building the AI as possible. Okay, so what we built was we built Chaiverse. And Chaiverse is kind of, it's kind of like a prototype, is the way to think about it. And it started with this, this observation that, well, how many models get submitted into Hugging Face a day? It's hundreds, it's hundreds, right? So there's hundreds of LLMs submitted each day. Now consider that, what does it take to build an LLM? It takes a lot of work, actually. It's like someone devoted several hours of compute, several hours of their time, prepared a data set, launched it, ran it, evaluated it, submitted it, right? So there's a lot of, there's a lot of, there's a lot of work that's going into that. So what we did was we said, well, why can't we host their models for them and serve them to users? And then what would that look like? The first issue is, well, how do you know if a model is good or not? Like, we don't want to serve users the crappy models, right? So what we would do is we would, I love the LMSYS style. I think it's really cool. It's really simple. It's a very intuitive thing, which is you simply present the users with two completions. You can say, look, this is from model one. This is from model two. This is from model three. This is from model A. This is from model B, which is better. And so if someone submits a model to Chaiverse, what we do is we spin up a GPU. We download the model. We're going to now host that model on this GPU. And we're going to start routing traffic to it. And we're going to send, we think it takes about 5,000 completions to get an accurate signal. That's roughly what LMSYS does. And from that, we're able to get an accurate ranking. And we're able to get an accurate ranking. And we're able to get an accurate ranking of which models are people finding entertaining and which models are not entertaining. If you look at the bottom 80%, they'll suck. You can just disregard them. They totally suck. Then when you get the top 20%, you know you've got a decent model, but you can break it down into more nuance. There might be one that's really descriptive. There might be one that's got a lot of personality to it. There might be one that's really illogical. Then the question is, well, what do you do with these top models? From that, you can do more sophisticated things. You can try and do like a routing thing where you say for a given user request, we're going to try and predict which of these end models that users enjoy the most. That turns out to be pretty expensive and not a huge source of like edge or improvement. Something that we love to do at Chai is blending, which is, you know, it's the simplest way to think about it is you're going to end up, and you're going to pretty quickly see you've got one model that's really smart, one model that's really funny. How do you get the user an experience that is both smart and funny? Well, just 50% of the requests, you can serve them the smart model, 50% of the requests, you serve them the funny model. Just a random 50%? Just a random, yeah. And then... That's blending? That's blending. You can do more sophisticated things on top of that, as in all things in life, but the 80-20 solution, if you just do that, you get a pretty powerful effect out of the gate. Random number generator. I think it's like the robustness of randomness. Random is a very powerful optimization technique, and it's a very robust thing. So you can explore a lot of the space very efficiently. There's one thing that's really, really important to share, and this is the most exciting thing for me, is after you do the ranking, you get an ELO score, and you can track a user's first join date, the first date they submit a model to Chaiverse, they almost always get a terrible ELO, right? So let's say the first submission they get an ELO of 1,100 or 1,000 or something, and you can see that they iterate and they iterate and iterate, and it will be like, no improvement, no improvement, no improvement, and then boom. Do you give them any data, or do you have to come up with this themselves? We do, we do, we do, we do. We try and strike a balance between giving them data that's very useful, you've got to be compliant with GDPR, which is like, you have to work very hard to preserve the privacy of users of your app. So we try to give them as much signal as possible, to be helpful. The minimum is we're just going to give you a score, right? That's the minimum. But that alone is people can optimize a score pretty well, because they're able to come up with theories, submit it, does it work? No. A new theory, does it work? No. And then boom, as soon as they figure something out, they keep it, and then they iterate, and then boom,Alessio [00:51:46]: they figure something out, and they keep it. Last year, you had this post on your blog, cross-sourcing the lead to the 10 trillion parameter, AGI, and you call it a mixture of experts, recommenders. Yep. Any insights?William [00:51:58]: Updated thoughts, 12 months later? I think the odds, the timeline for AGI has certainly been pushed out, right? Now, this is in, I'm a controversial person, I don't know, like, I just think... You don't believe in scaling laws, you think AGI is further away. I think it's an S-curve. I think everything's an S-curve. And I think that the models have proven to just be far worse at reasoning than people sort of thought. And I think whenever I hear people talk about LLMs as reasoning engines, I sort of cringe a bit. I don't think that's what they are. I think of them more as like a simulator. I think of them as like a, right? So they get trained to predict the next most likely token. It's like a physics simulation engine. So you get these like games where you can like construct a bridge, and you drop a car down, and then it predicts what should happen. And that's really what LLMs are doing. It's not so much that they're reasoning, it's more that they're just doing the most likely thing. So fundamentally, the ability for people to add in intelligence, I think is very limited. What most people would consider intelligence, I think the AI is not a crowdsourcing problem, right? Now with Wikipedia, Wikipedia crowdsources knowledge. It doesn't crowdsource intelligence. So it's a subtle distinction. AI is fantastic at knowledge. I think it's weak at intelligence. And a lot, it's easy to conflate the two because if you ask it a question and it gives you, you know, if you said, who was the seventh president of the United States, and it gives you the correct answer, I'd say, well, I don't know the answer to that. And you can conflate that with intelligence. But really, that's a question of knowledge. And knowledge is really this thing about saying, how can I store all of this information? And then how can I retrieve something that's relevant? Okay, they're fantastic at that. They're fantastic at storing knowledge and retrieving the relevant knowledge. They're superior to humans in that regard. And so I think we need to come up for a new word. How does one describe AI should contain more knowledge than any individual human? It should be more accessible than any individual human. That's a very powerful thing. That's superswyx [00:54:07]: powerful. But what words do we use to describe that? We had a previous guest on Exa AI that does search. And he tried to coin super knowledge as the opposite of super intelligence.William [00:54:20]: Exactly. I think super knowledge is a more accurate word for it.swyx [00:54:24]: You can store more things than any human can.William [00:54:26]: And you can retrieve it better than any human can as well. And I think it's those two things combined that's special. I think that thing will exist. That thing can be built. And I think you can start with something that's entertaining and fun. And I think, I often think it's like, look, it's going to be a 20 year journey. And we're in like, year four, or it's like the web. And this is like 1998 or something. You know, you've got a long, long way to go before the Amazon.coms are like these huge, multi trillion dollar businesses that every single person uses every day. And so AI today is very simplistic. And it's fundamentally the way we're using it, the flywheels, and this ability for how can everyone contribute to it to really magnify the value that it brings. Right now, like, I think it's a bit sad. It's like, right now you have big labs, I'm going to pick on open AI. And they kind of go to like these human labelers. And they say, we're going to pay you to just label this like subset of questions that we want to get a really high quality data set, then we're going to get like our own computers that are really powerful. And that's kind of like the thing. For me, it's so much like Encyclopedia Britannica. It's like insane. All the people that were interested in blockchain, it's like, well, this is this is what needs to be decentralized, you need to decentralize that thing. Because if you distribute it, people can generate way more data in a distributed fashion, way more, right? You need the incentive. Yeah, of course. Yeah. But I mean, the, the, that's kind of the exciting thing about Wikipedia was it's this understanding, like the incentives, you don't need money to incentivize people. You don't need dog coins. No. Sometimes, sometimes people get the satisfaction fro

This episode features a Nova Chat session hosted by Nova founder and CEO Maggie Olson.In this conversation, Maggie leads a deep dive into the next five years of the AI landscape in the C-Suite, with panelists Lawrence Coburn, Jessica McBride, and Fiona Young examining the continued importance of AI for CEOs, EAs, and CoSs and sharing helpful advice for navigating new AI platforms in the C-Suite.Show notes -> leaderassistant.com/304Sponsor -> leaderassistant.com/nova--Nova Chief of Staff's course provides you with the knowledge and confidence you need to stand out on the job. Whether you want to land your dream position or level up in your current role, Nova's self-paced course gives you hands-on practice doing what Chiefs of Staff do every day.Visit leaderassistant.com/nova to enroll before the price increases in January 2025!More from The Leader Assistant... Book, Audiobook, and Workbook -> leaderassistantbook.com Premium Membership -> leaderassistant.com/membership Events -> leaderassistantlive.com Free Community -> leaderassistant.com/community

This is the One where we go Deep on the Last Supper, as Bob Dylan rocks, and The Man in Black is BACK. Please support Signal of Doom & Legion Outpost on Patreon! Every single dollar helps the show! Follow us on Instagram! Please like the Facebook Page! https://www.patreon.com/SignalofDoom Follow us on X: @signalofdoom Dredd or Dead: @OrDredd Legion Outpost: @legionoutpost

Join us for a plant chat! Photo Credit: @stevesleavesinc

アプリ作る社長: プログラミング初心者講座です。 iPhoneアプリの作り方やRaspberry Piのリモートサーバー構築方法などIT関連ニュースの情報発信をいたします。 YouTubeでiOS APPの作り方やMacとラズベリーパイを連携してリモートサービスを作る方法を解説しております。たまにIT関連ニュースの配信もあり。これからの求められるアプリのニーズや世界で販売するためのマーケティング戦略なども時々お話しします。 Twitterで「アプリ作る社長」と検索してください。 ホームページ https://catch-questions.com ↑「Catch Questions」とGoogle検索すると？ ↓「Catch Questions」でAmazon Kindle検索すると？ 書籍１ プログラミング初心者がゼロからiPhoneアプリ開発に挑戦するにはどうする？ 書籍２ 独学で Swift × Python 初心者が覚えるべき最低限の基本コードのまとめ 書籍３ プログラミング的に学ぶ英語勉強方法 書籍４ 【Raspberry Pi4でWordPress】自宅サーバーの基本操作とセキュリティ 書籍５ 【Raspberry Pi4でPython プログラミング】Web APIを利用したBotサービスの作り方 書籍６ 【Raspberry PiでLinux コマンド】初心者向けシェルスクリプトの超基本操作 書籍７ 【PancakeSwap APR自動解析】パンケーキスワップの年利情報を取得するアプリを自作する方法 書籍８ 【ITエンジニアの転職マニュアル】ブラック企業を脱出しホワイト企業へ入社するためのノウハウ

Artificial intelligence in dentistry is here! I chatted with Dr. Tim Quirt and hygienist Marion Govern to discuss AI in dentistry and Heartland Dental's implementation journey. Podcast originally posted as a video on Kara RDH's Facebook page on April 1, 2024: https://www.facebook.com/DentalHygieneKaraRDH/videos/442569951629560 This podcast episode is sponsored by Heartland Dental. To learn more about opportunities Heartland Dental has available, head on over to https://rdh.tv/heartland Need CE? Check out the latest courses at https://rdh.tv/ce Get daily dental hygiene articles at https://www.todaysrdh.com Follow Today's RDH on Facebook: https://www.facebook.com/TodaysRDH/ Follow Kara RDH on Facebook: https://www.facebook.com/DentalHygieneKaraRDH/ Follow Kara RDH on Instagram: https://www.instagram.com/kara_rdh/ * Heartland Dental provides non-clinical administrative support services to dentists throughout the country. Supported dentists and some hygienists are employed by a professional corporation in the state they perform services. Heartland Dental's doctor led culture and business model provides supported doctors with the opportunities to focus on delivering exceptional oral care to their patients as we support with the day-to-day non-clinical administrative workflow with our innovative yet proven systems and processes. Some of the material and information on the video may contain minor technical errors, inaccuracies or omissions relating to the support or service descriptions provided by Heartland Dental, LLC.

"Product operations is all about removing obstacles and helping product people accomplish everything that we teach in our product management classes – being data-driven, making sure that you're letting the market guide your decisions, and that you're following best practices." -      Dan Corbin, Proven Agile and Product Management leader In this episode of Product Chats, we have seasoned product professional Dan Corbin joining the podcast. Dan has worked at all levels of product management, from individual product management to product leadership roles in start-ups and Fortune 500 companies. His past roles allow him to provide first-hand knowledge about the implementation and benefits of product operations, as well as the challenges businesses might face when introducing this function. Dan is passionate about mentoring the next generation of product leaders, emphasizing the importance of continuous learning and adaptability in an ever-changing market landscape. His dedication to excellence and innovation makes him a true pioneer, continuously pushing the boundaries of what's possible in the product management sphere. Key Takeaways: Understanding Product Ops: The episode begins by clarifying what product operations is, how it differs from DevOps and Design Ops. While all three roles share the aim of improving efficiency and effectiveness within their respective domains, they each have a unique focus: product operations on the product management process, DevOps on the software development and delivery process, and Design Ops on the design process. AI Has Entered the Chat: AI aids product managers in consolidating and analyzing data from various sources. AI can process information from different platforms like Zendesk tickets, App Store reviews, or interview data from tools like Dovetail, and surface up key insights. This ability helps product managers to have a comprehensive understanding of their product's performance, customer feedback, market trends, and more, leading to more informed decision-making. The Three Pillars of Product Ops: The conversation outlines the three foundational pillars of Product Ops: Business and Data Insights, Customer and Market Insights, and Processes and Procedures. These areas work together to make operations smoother, improve data analysis, and facilitate better strategic planning. ABOUT OUR GUEST: Dan Corbin is a product management and marketing veteran, bringing over two decades of frontline experience and thought leadership to the industry. With a career spanning across innovative startups to Fortune 500 companies, Dan has become synonymous with turning visionary ideas into market-leading products. Dan's expertise is not confined to the classroom; he is a seasoned speaker, known for his compelling talks at major conferences and seminars where he shares his insights on product strategy, development, and go-to-market tactics. His contributions to the field are widely recognized, making him a sought-after consultant for organizations striving to achieve competitive differentiation and customer-centric solutions. He is also an instructor at Pragmatic Institute, where he has been instrumental in shaping the futures of product professionals through his engaging teaching methodologies and deep understanding of market needs. ABOUT PRAGMATIC INSTITUTE: Since 1993, we've provided training and professional development for product, design, and data professionals to accelerate innovation, increase customer satisfaction, and bolster revenue. Through our comprehensive methods and propriety Pragmatic Framework, we train professionals with the skills needed to accelerate their product management and product marketing careers, increase team efficiency, and boost revenue. Our online, in-person, and on-demand courses are taught by industry experts with decades of experience at top companies like Microsoft, Cisco, Dell, Hallmark, Quaker Oats, and Dun & Bradstreet. We offer individual course training in product, design and data, and certification tracks for Product Management Certifications, Product Marketing Certifications, and the Pragmatic Product Master Certification. All attendees gain access to the Pragmatic Alumni Community, a network of over 30,000 alumni worldwide. If you're looking for product management or product marketing training or are pursuing a product marketing certification or product management certification, browse our certification paths at https://www.pragmaticinstitute.com/product/. Courses are available online, in-person, or on-demand to fit your schedule. Want to learn more about becoming a Pragmatic Certified Product Manager? Learn more here.

Hello everyone, it's Bill Thompson – T Bill. Some of the things covered on today's session include:  Mutual Funds – Mutual Fund Screeners.  The Leap Year's effect on financial markets.  Multiple industries looking at performance of Dune Part 2.   Microsoft announces a new artificial intelligence tool for Excel and Outlook.   Bitcoin back above $60,000.  Humanoid robot start-up Figure AI raises $675 million. 

This week the pod-nerds, Jules and Stocks, were worried there wasn't much to talk about. But then along came Megan Markle, Sora and the 'Daddy of all podcasts'. All the big movers and shakers are present - and providing ample fodder for the gents to chew through. [01:30] Lemonada sign Megan Markle and will publish all Archetypes podcast episodes [05:20] Brene Brown also leaving Spotify [06:56] Alex Cooper on the Success of Call Her Daddy [10:53] YouTube Domination [17:06] It's been a big week for mindblowing AI - with launch of Sora and Real News Podcast Contact Jules and Stocks and follow BTP on Instagram HERESee omnystudio.com/listener for privacy information.

In this episode, Ralph and I talk about AI and EVs and where they are in The Hype Cycle!

Just a reminder that the signature vouches for the contents of the document. www.patreon.com/stevelehto

A new podcast segment featuring creative collaboration with Chat GPT. Be advised - there is unfortunately a dead gap in the recording where I failed to unmute the mic. The recording does resume some time later when I realized my mistake. Please fast forward when you hit the dead spot. There is more to listen to after I unmute the mic.

Hakan and Ester from Bolt Insight join Daniel and Efrain to speak about how their Chat AI tool is disrupting FMCG Market Research by delivering qualitative consumer insights at scale. Learn more about Bolt Insight: https://www.boltinsight.com/ https://www.boltchatai.com/ https://www.linkedin.com/company/boltinsight/ Check out the Xmas BoltChatAI generated reports: UK X-mas Report US X-mas Report Get in touch with Hakan & Ester: hakan.yurdakul@boltinsight.com / ester.marchetti@boltinsight.com    In this conversation, you'll learn about: How only 20% of FMCG innovations are based on consumer data and 80% are delisted in the first 2 years! An AI-enhanced Chatbot that enables FMCG brands to dialog with their consumers directly Ester and Hakan's path from corporate to starting a business with a very clear purpose The importance of getting consumer insights in real-time and using AI in the right way This episode is brought to you by CommerceIQ. Download the free chrome extension here: https://growth.commerceiq.ai/fmcgguys     

アプリ作る社長: プログラミング初心者講座です。 iPhoneアプリの作り方やRaspberry Piのリモートサーバー構築方法などIT関連ニュースの情報発信をいたします。 YouTubeでiOS APPの作り方やMacとラズベリーパイを連携してリモートサービスを作る方法を解説しております。たまにIT関連ニュースの配信もあり。これからの求められるアプリのニーズや世界で販売するためのマーケティング戦略なども時々お話しします。 Twitterで「アプリ作る社長」と検索してください。 ホームページ https://catch-questions.com ↑「Catch Questions」とGoogle検索すると？ ↓「Catch Questions」でAmazon Kindle検索すると？ 書籍１ プログラミング初心者がゼロからiPhoneアプリ開発に挑戦するにはどうする？ 書籍２ 独学で Swift × Python 初心者が覚えるべき最低限の基本コードのまとめ 書籍３ プログラミング的に学ぶ英語勉強方法 書籍４ 【Raspberry Pi4でWordPress】自宅サーバーの基本操作とセキュリティ 書籍５ 【Raspberry Pi4でPython プログラミング】Web APIを利用したBotサービスの作り方 書籍６ 【Raspberry PiでLinux コマンド】初心者向けシェルスクリプトの超基本操作 書籍７ 【PancakeSwap APR自動解析】パンケーキスワップの年利情報を取得するアプリを自作する方法 書籍８ 【ITエンジニアの転職マニュアル】ブラック企業を脱出しホワイト企業へ入社するためのノウハウ

Art For Everyone Podcast With Carini & Vinnie Episode 2: Guest Artist Nick Bultman Joins Us To Chat AI Art, Social Media, And The Artist Journey Joining us for this conversation is contemporary abstract artist Nick Bultman, as we talk about his art and his artist journey. We'll talk about lots of other stuff too, including social media and Artificial Intelligence. AI has been a hot topic recently, particularly as it pertains to the art industry. Is it ethical? Is it putting artists out of work? Let's talk about it. Join the conversation and share your thoughts. Nick Bultman: My name is Nick Bultman and I'm an artist based in Arizona, USA. My artwork is a personal exercise of exploring the freedom of movement, the beauty of physics, and unity between computer-generated precision with human-intuitive motions. In a world where artificially intelligent creativity is becoming an important topic, I'm on a mission to revitalize the human spirit, guided by a strong desire to push the boundaries of conventional painting techniques. Website: www.nickbultmanart.com Welcome to the "Art For Everyone Podcast With Carini & Vinnie." Michael Carini is the Acrylic Alchemist, a full-time artist and the owner of Carini Arts. Vinnie works in real estate and doesn't have an art background. For far too long, the art community has felt like a special club or prestigious society, and it's time to bring it back to the people. Art should be inclusive and all levels should be welcome, so we invite you to the conversation. Join us as we talk art and art biz. No filters. No BS. No experience required. Michael Carini is a neurodivergent artist with Tourette's based in San Diego Michael Carini received his artistic training in Los Angeles, studying at Loyola Marymount University while simultaneously serving as an apprentice under respected artists Jane Brucker and Roland Reiss. Graduating at the top of his class with honors including the Scholar of Distinction Award in Painting, Carini returned to his hometown in San Diego, where he currently maintains his studio. With over 100 exhibitions nationally and internationally, he has received over a dozen major awards and was named Emerging Artist of the Year by Art Design Consultants. Carini's work can be found all over the globe in the collections of celebrities, major businesses, and private collectors. Don't be afraid to be different…Be afraid to be the same CariniArts.com FB: @CariniArts IG: @AcrylicAlchemy TikTok: @CariniArts Vicente Enriquez aka Vinnie is the team lead of The Enriquez Group and Host of the Road to Growth Podcast. His real estate team is based out of San Diego, Ca and his team has successfully sold over $300,000,000 of San Diego Real Estate. On his podcast, he interviews Entrepreneurs that have overcome adversity and allows them to tell their story on how they have done it. Besides running his real estate team and telling the story of business owners he also coaches a select few of realtors at Keller Williams San Diego Metro. Those select few individuals will get a honest support system that will guide them to success. When Vinnie is relaxing he is working out, playing basketball, geeking out on a movie or watching Padres Baseball If you are looking for San Diego Real Estate Help. Call Vinnie and The Enriquez Group Contact us at 858-345-7829 or visit our website at www.TheEnriquezGroup.com. Cal BRE Lic #01849409 Cal Bre #01295699 Logo by Aubrianna Robinson (aka @blobri on IG)

In this week's AI-excited episode, fully human hosts Kevin Pereira & Gavin Purcell explore hot topics in the artificial intelligence and machine learning community. From ChatGPT lying to a user about a rose to the realistic people created by Adobe's new AI to Cyberpunk 2077 using AI to bring back a fan favorite character AND THEN… It's an A4H Interview with the one & only Bruce Greene! Bruce, Kevin and Gavin go way back, talk some of Attack of the Show stuff and then dig into some of the thorny issues around AI and gaming and creative content. And then, WITH PERMISSION, we clone Bruce's voice for a game. But wait... THERE'S MORE: And we've got a ton of other topics as well… Marc Andreensen's Techno-Optimist Manifesto, Gary Genler basically telling us that AI will take down the financial world and we see what happens when ChatGPT & Pi AI talk to one another. It's quite the experience.  It's an endless cavalcade of ridiculous and informative AI news, AI tools, and AI entertainment cooked up just for you. Follow us for more AI discussions, AI news updates, and AI tool reviews on X @AIForHumansShow Join our vibrant community on TikTok @aiforhumansshow Subscribe on YouTube to never miss an episode @AIForHumansShow. For more info, visit our website at https://www.aiforhumans.show/  

Join Gay & Ali as they chat with Sami Sheehan about the use of AI in donor communications. Learn how to build better prompts so you can save time writing communications (either mass communications or 1:1) emails. Sami shares how AI can help you can get out from behind your desk and connect with donors. Sami Sheehan, CFRE, brings over a decade of valuable Annual Giving experience from her time at social justice, animal welfare, and healthcare nonprofits. Her passion for fundraising stems from her desire to help donors realize their vision of a better world through philanthropic contributions.

#openassistant #chatgpt #mlnews Try the chat: https://open-assistant.io/chat Homepage: https://open-assistant.io Dataset: https://huggingface.co/datasets/OpenAssistant/oasst1 Code: https://github.com/LAION-AI/Open-Assistant Paper (temporary): https://ykilcher.com/oa-paper Links: Homepage: https://ykilcher.com Merch: https://ykilcher.com/merch YouTube: https://www.youtube.com/c/yannickilcher Twitter: https://twitter.com/ykilcher Discord: https://ykilcher.com/discord LinkedIn: https://www.linkedin.com/in/ykilcher If you want to support me, the best thing to do is to share out the content :) If you want to support me financially (completely optional and voluntary, but a lot of people have asked for this): SubscribeStar: https://www.subscribestar.com/yannickilcher Patreon: https://www.patreon.com/yannickilcher Bitcoin (BTC): bc1q49lsw3q325tr58ygf8sudx2dqfguclvngvy2cq Ethereum (ETH): 0x7ad3513E3B8f66799f507Aa7874b1B0eBC7F85e2 Litecoin (LTC): LQW2TRyKYetVC8WjFkhpPhtpbDM4Vw7r9m Monero (XMR): 4ACL8AGrEo5hAir8A9CeVrW8pEauWvnp1WnSDZxW7tziCDLhZAGsgzhRQABDnFy8yuM9fWJDviJPHKRjV4FWt19CJZN9D4n

学習におけるアナログ回帰子どもの学習とデジタルツールとの向き合い方⁠⁠中学受験　やってはいけない塾選び⁠⁠学習面においてスマートスピーカーにやらせて良いor notのジャッジむずい問題1人目と2人目以降の心の余裕の差大人が子育てにおいてテクノロジーを用いることは賛成子ども自身の学習機会においては慎重にGitHub ⁠⁠Copilot Chat⁠⁠開発者体験の最大化生成AIコーディング体験⁠⁠Next.js⁠⁠Copilot Chat所感開発においては情報鮮度問題が顕著モダンアプリケーション開発における生成AIの向き合い方追加学習プラグインで鮮度問題は解決するのか⁠⁠github next⁠⁠⁠⁠Prisma⁠⁠⁠⁠Prisma Migrate⁠⁠体系的なバックグラウンドが必要な技術は生成AI完結できない話大人でいう「理論と実践」は子どもでいう「座学と体験」と似ているフィードバックは ⁠⁠#momitfm⁠⁠ で募集しています

Amos Weiskopf, VP of Marketing at Lonsome Labs, brings his vast experience working with world-renowned consumer brands, VC firms, start-ups, and Fortune 500 enterprises to discuss the future of the organic search landscape, including: * Google's SGE (Search Generative Experience), ChatGPT, and more. * Industries and websites that might be disproportionately affected. * Effective future-proofing practices and avoiding futile tricks.Tune in to hear why Amos says that context reigns supreme over content, and learn about essential future-proofing best practices that will help you steer clear of ineffective tactics and achieve a higher ranking on search engines' first page.Time Stamps:* (02:00) Intro to Amos' evolving SEO philosophy* (4:40) Chat AI's impact on organic search–immediate and future* (12:05) Disproportionately affected industries/website types by Chat AI* (17:15) Outdated SEO techniques to leave behind for good* (24:30) Drew and Ryan's key takeawayContact UsWe'd love to hear from you! Reach out to us at PageOne@DemandJump.com.SponsorThis podcast is brought to you by DemandJump. Tired of wasting time creating content that doesn't rank? With DemandJump you know the exact content to create to increase 1st-page rankings and drive outcomes. Get started for free today at DemandJump.com.LinksFollow Amos on LinkedInFollow Ryan on LinkedInFollow Drew on LinkedInLearn more about DemandJump's marketing tools

Aloha Bruce is in the studio to talk about Hawaii travel troubles visitors may encounter on this latest Hawaii Vacation Connection Podcast. He offers some helpful, expert advise about how to handle any disruptions that may crop up during a Hawaii vacation. Bruce begins with a discussion about the high cost for three rooms in a 4-Star  property for a family from the East Coast, coming in at over $80,000. “If you're planning on a family vacation in Hawaii over the holidays, you better do it soon!” He notes that it may be more cost effective to plan your vacation in November. He notes a new climate change office on Hawaii Island intended to coordinate efforts to mitigate and adapt changes brought on by global climate change. He also mentions that Honolulu City & County is spending over $500,000 to hire security guards to patrol Waikiki 6pm-2am in a crime reduction effort working with the Honolulu Police Department. Back on the Big Island, Bruce mentions the Hawaii Island the Heart of Polynesia program, a campaign to increase cultural awareness in Hawaii's visitors. He also shares the news that officials on Maui are considering tourism taxes on overnight accommodations. To wrap the news segment, Bruce discusses the reopening of the DFS Galleria in Waikiki and a nearby restaurant as indicators of an increase of international visitor arrivals. “That's a good sign!” On to the main topic of Hawaii travel troubles and how to handle them, Bruce first talks about purchasing travel insurance. He describes Hawaii Aloha Travel's insurance policies and the benefits they offer. He also recommends “dialing back your expectations” about Hawaii hotels and mentions the Hilton Hawaii Village as being an attractive property for families with children. Bruce explains that having travel insurance and an expert travel advisor are the two most important things to consider when confronted with Hawaii travel troubles. “Call us when these things are happening,” Bruce says. “We can help you 24-7!” Aloha Bruce notes the importance of reading the “fine print” and be leery of Chat AI advice that can be ultimately unhelpful. “Sometimes people just don't understand what they're getting,” he says and discusses recently being able to move one vacationer and her family to a property more suitable than the one she had originally booked and found it lacking. Most Hawaii travel troubles start with your accommodations. “We can help! At the end of the day, all we want is for you to have an amazing Hawaii vacation.”

In this episode of Circling the Wagons, we talk about the disappointing ending for the 2022 Bills season and how a lot of fans are still experiencing a "hangover", what it will take to get over said hangover, training camp battles we'll be watching closely at St. John Fisher, we ask Chat AI to see who they think will win those battles, and much more! Listen now and Go Bills! Apple Podcasts | Stitcher | Google Play | Spotify | Podbean | iHeartRadio | TuneIn | Megaphone | YouTube Ask Alexa or Google Home to play the Buffalo Rumblings podcast! If you like our show, tell a friend and spread the word! Email us questions, comments, or Bills stories: ctwpod@gmail.com Follow us on Twitter: @CTWpod Like us on Facebook: Circling the Wagons: A Buffalo Bills Podcast Follow us on Instagram: CTWpod Check out our TeePublic Bills Store CTW Best Ball League: Here Learn more about your ad choices. Visit podcastchoices.com/adchoices

Listen in podcast app and follow below for the podcast topic arc.* A quick Market Update featuring some insights from JC Parets' newsletter* MSFT's new Chat Ai integration with Microsoft 365* Bill C-18 impact on the Canadian media landscape* Netflix continued dominance in the * Recommendations and must listensListen on Apple, Spotify, or Google Podcasts.

Looking to leverage AI in your business? Gain valuable insights from Sam Wong, CEO of Curious Thing, as he discusses the transformative power of AI in customer communication and beyond.In this episode of Let's Chat, Dexter chat's to Sam Zheng, CEO and Co-Founder of Curious Thing, an Aussie AI scale up. Sam was also co-founder of Hyper Ana one of Australia's most successful AI startups. With a background in statistics and actuarial work, Sam has extensive experience in the AI field.  Sam and Dexter discuss the current state of AI and its impact on various industries. Sam emphasises the importance of focusing on solving real problems rather than just using AI for the sake of it. Sam also shares his journey as a founder and the challenges he faced transitioning from CTO to CEO. https://curiousthing.io/Follow us:Apple: https://apple.co/3D7NsPtSpotify: https://spoti.fi/3IzSViQSubscribe and like on Youtube: https://bit.ly/3tBlRmEConnect on Linkedin: https://bit.ly/3DsCJBpFollow on Twitter: https://twitter.com/DexterCousins

You may ask WTH am I to express my opinion about AI? And you are right! I'm not an expert but just like you I will be affected and will use this technology. I actually did use ChatGPT and it this episode I share what came up for me, what we should really fear in long run and what is our secret weapon when it comes AI. --- Support this podcast: https://podcasters.spotify.com/pod/show/inthegoodcompany/support

(0:00) We hacked the pod! Jcal is on vaca (5:34) Meta launches Threads (17:15) Chat AI interest in decline? (28:36) Fed meeting minutes, economic data and outlook, and EU risk (56:07) Florida Senate Bill 1718, jobs, and immigration debate (1:21:48) Chinese balloon: political farce? (1:31:47) Gerstner Science Corner: preventative heart health Follow the besties: https://twitter.com/chamath https://linktr.ee/calacanis https://twitter.com/DavidSacks https://twitter.com/friedberg Follow the pod: https://twitter.com/theallinpod https://linktr.ee/allinpodcast Intro Music Credit: https://rb.gy/tppkzl https://twitter.com/yung_spielburg Intro Video Credit: https://twitter.com/TheZachEffect

S3 Ep25 Welcome back to the "Dads Tales Podcast"!!! In this thought-provoking podcast episode, we delve deep into the fascinating realm of artificial intelligence (AI). Join us as we explore both the incredible advancements and the potential challenges that AI brings to our world today, while peering into the horizon of what the future may hold. The dads embark on an exploration of the unprecedented benefits that AI has brought! Using AI itself to write a script which discusses how AI-powered technologies have revolutionised healthcare, enhancing diagnostics, drug discovery, and patient care. It also raised about the future of autonomous vehicles, analysing their potential to transform transportation, reduce accidents, and revolutionise the way we commute. This week letter from the listeners is from a loyal dad tales fan!!! Let us know what you think about their noise dilemma ……. Don't forget to let the Dads know what you think of the podcast by leaving a 5-star review. You can also Email the dads at ⁠dadtales@outlook.com⁠ or get in touch through their social media platforms. Click the link--- https://instabio.cc/20816N5u9cx Don't forget to head to our YouTube channel for our latest video. ⁠ https://youtube.com/@dadtalespodcast6626 Whilst you are there, don't forget to turn on notifications and ring the bell to keep up to date with our latest videos!

No time for a full episode? Check out these segments from podcast episode #144! We remember Pro Wrestling Legend The Iron Sheik on his recent passing. The ‘Black Mirror' series creator tried using Chat AI to write a season 6 episode. The National Eating Disorders Association has to pull its Chatbot due to harmful dieting tips it was providing. Businesses can take a beating on negative publicity on TikTok. Warning as usual for explicit language from us idiots! Listen to us weekly on your favorite podcast platforms including Apple Podcasts, Spotify, Overcast, Google Podcasts, Amazon Music, Stitcher, Overcast, iHeart Radio, Vurbl, Goodpods, Podvine & more! Watch us on our YouTube channel & the B.O.S.S. Code Media Network! Show info can be found on our website: convincingidiots.wordpress.com Find show links on our Link Tree: https://linktr.ee/ConvincingIdiots Email us at ConvincingIdiots@gmail.com. Enjoying the show? Consider becoming a Patreon: https://www.patreon.com/ConvincingIdiots Or support the show from our main podcast page: https://anchor.fm/convincing-idiots YouTube Channel: https://youtube.com/@convincingidiots Show merch store here: https://convincing-idiots-podcast.creator-spring.com/ We hope we convince you to listen & subscribe! --- Support this podcast: https://podcasters.spotify.com/pod/show/convincing-idiots/support

In our main segment we talk our favorite professional wrestling “heels” in honor of wrestling legend The Iron Sheik who passed recently. In our “Ask An Idiot” segment, more DC News in potential replacements of more current actors portraying DC super-heroes. Should DC do a complete reset or should they keep some of the current actors? We discuss! “Idiot Reviews” includes non-spoiler talk on the new Arnold Schwarzenegger documentary on Netflix, more on ‘The Diplomat' series on Netflix, ‘Spider-Man: Across the Spider-Verse' & more. In “Pop Culture Headlines” we talk ‘Cheers' as the series is celebrating the 30th anniversary of the series finale; The ‘Black Mirror' series creator tried using Chat AI to write a season 6 episode; Businesses can take a beating on negative publicity on TikTok; The National Eating Disorders Association has to pull its Chatbot due to harmful dieting tips it was providing & more headlines! Warning as usual for explicit language from us idiots! Listen to us weekly on your favorite podcast platforms including Apple Podcasts, Spotify, Overcast, Google Podcasts, Amazon Music, Stitcher, Overcast, iHeart Radio, Vurbl, Goodpods, Podvine & more! Watch us on our YouTube channel & the B.O.S.S. Code Media Network! Show info can be found on our website: convincingidiots.wordpress.com Find show links on our Link Tree: https://linktr.ee/ConvincingIdiots Email us at ConvincingIdiots@gmail.com. Enjoying the show? Consider becoming a Patreon: https://www.patreon.com/ConvincingIdiots Or support the show from our main podcast page: https://anchor.fm/convincing-idiots YouTube Channel: https://youtube.com/@convincingidiots Show merch store here: https://convincing-idiots-podcast.creator-spring.com/ We hope we convince you to listen & subscribe! --- Support this podcast: https://podcasters.spotify.com/pod/show/convincing-idiots/support

The Mayor's office is inching their way towards a NASCAR deal in Nashville after years of on and off negotiations. Plus, we ask the top Chat AI platforms such as Chat GPT and Bard to give us the best 24 hour itinerary for a Nashville visit.New YouTube Channel - https://www.youtube.com/channel/UCKjWKXfpjtNL0oL2R6MKSxwToday's Sponsors:XPLR Tourshttps://xplrtours.com/Use ND10 for 10% off the History of Nashville Walking TourBlessed Day Coffeehttps://www.blesseddaycoffee.com/Use Code "XPLR20" for 20% off at checkoutNash NewsMayor's Office Moves on NASCAR Deal https://www.nashvillepost.com/politics/metro/mayor-s-office-moves-on-nascar-deal/article_cbbfd30c-70d9-54f7-8818-5946936e39b6.htmlNashville Daily Artist of the Day Playlisthttps://open.spotify.com/playlist/51eNcUWPg7qtj8KECrbuwx?si=nEfxeOgmTv6rFUyhVUJY9AFollow us @ XPLR NASHWebsite - https://nashvilledailypodcast.com/YouTube Channel - https://www.youtube.com/c/xplrnashInstagram - https://www.instagram.com/xplr.nash/Twitter - https://twitter.com/xplr_nashNASHVILLE & XPLR MERCH - https://www.xplrnash.com/shopMedia and other inquiries please email hello@xplr.life

ChatGPT and AI are hot topics in the online space right now. But how will these applications that quickly and efficiently generate content change how we market our podcasts? And how can we best utilize them for our social media content? Today, Andréa Jones joins us again to talk about all this and more! This week, episode 101 of Listeners to Leads is about using chat-based AI to support your content creation! Andréa Jones is fiercely committed to helping businesses and podcasters build profitable online communities through simple social media solutions. She's the host of the Savvy Social Podcast, creator of the Savvy Social School, a digital platform designed to teach its 100+ members (predominantly small business owners) how to implement organic social media strategies, and named one of Social Report's top marketers to follow.In this episode of Listeners to Leads, Andréa Jones shares the importance of adding your voice to AI-generated content and actionable steps you can take right now to get useful information from chat-based AI applications like ChatGPT. Andréa and I also chat about the following: Why people are hesitant to use AI.How AI is impacting how we market our podcasts.The importance of keeping the human element of your marketing, even when AI is doing the initial work.Questions to ask Chat AI so we get useful information back.Be sure to tune in to all the episodes to receive tons of practical tips on turning your podcast listeners into leads and to hear even more about the points outlined above. Thank you for listening! If you enjoyed this episode, take a screenshot of the episode to post in your stories and tag me! And don't forget to follow, rate and review the podcast and tell me your key takeaways!Learn more about Listeners to Leads at www.listenerstoleads.comCONNECT WITH ANDRÉA JONES:InstagramThe Savvy Social PodcastWebsiteCONNECT WITH ALESIA GALATI:InstagramLinkedInWork with Galati Media! LINKS MENTIONED:Listeners To Leads Ep 53: Going Deep (instead of wide) with Your Podcast Content

Here is my thoughts on the situation that folks are talking about. The Places To Support Me At This Time Of Change: VENMO: @Brian-Walmer-2 CASH APP: $bwrosas98 https://podcasters.spotify.com/pod/show/bwrosas https://podcasters.spotify.com/pod/show/bwrosas/subscribe https://open.spotify.com/show/79t6DoBczUBVDeLgPLwz5q https://www.patreon.com/bwrosas https://my-store-bf03b1.creator-spring.com https://my-store-bf03b1.creator-spring.com/ Comments Are Welcomed Subscribe To The Channel #GoogleBard #chatgpt #Discussion

Bradley, Micah, and David discuss a variety of current topics that are impacting businesses like yours right now. Tune in for this Fireside Chat, packed full of valuable perspective!> JOIN THE PRIVATE LEADERSHIP PODCAST COMMUNITY!

アプリ作る社長: プログラミング初心者講座です。 iPhoneアプリの作り方やRaspberry Piのリモートサーバー構築方法などIT関連ニュースの情報発信をいたします。 YouTubeでiOS APPの作り方やMacとラズベリーパイを連携してリモートサービスを作る方法を解説しております。たまにIT関連ニュースの配信もあり。これからの求められるアプリのニーズや世界で販売するためのマーケティング戦略なども時々お話しします。 Twitterで「アプリ作る社長」と検索してください。 ホームページ https://catch-questions.com ↑「Catch Questions」とGoogle検索すると？ ↓「Catch Questions」でAmazon Kindle検索すると？ 書籍１ プログラミング初心者がゼロからiPhoneアプリ開発に挑戦するにはどうする？ 書籍２ 独学で Swift × Python 初心者が覚えるべき最低限の基本コードのまとめ 書籍３ プログラミング的に学ぶ英語勉強方法 書籍４ 【Raspberry Pi4でWordPress】自宅サーバーの基本操作とセキュリティ 書籍５ 【Raspberry Pi4でPython プログラミング】Web APIを利用したBotサービスの作り方 書籍６ 【Raspberry PiでLinux コマンド】初心者向けシェルスクリプトの超基本操作 書籍７ 【PancakeSwap APR自動解析】パンケーキスワップの年利情報を取得するアプリを自作する方法 書籍８ 【ITエンジニアの転職マニュアル】ブラック企業を脱出しホワイト企業へ入社するためのノウハウ

アプリ作る社長: プログラミング初心者講座です。 iPhoneアプリの作り方やRaspberry Piのリモートサーバー構築方法などIT関連ニュースの情報発信をいたします。 YouTubeでiOS APPの作り方やMacとラズベリーパイを連携してリモートサービスを作る方法を解説しております。たまにIT関連ニュースの配信もあり。これからの求められるアプリのニーズや世界で販売するためのマーケティング戦略なども時々お話しします。 Twitterで「アプリ作る社長」と検索してください。 ホームページ https://catch-questions.com ↑「Catch Questions」とGoogle検索すると？ ↓「Catch Questions」でAmazon Kindle検索すると？ 書籍１ プログラミング初心者がゼロからiPhoneアプリ開発に挑戦するにはどうする？ 書籍２ 独学で Swift × Python 初心者が覚えるべき最低限の基本コードのまとめ 書籍３ プログラミング的に学ぶ英語勉強方法 書籍４ 【Raspberry Pi4でWordPress】自宅サーバーの基本操作とセキュリティ 書籍５ 【Raspberry Pi4でPython プログラミング】Web APIを利用したBotサービスの作り方 書籍６ 【Raspberry PiでLinux コマンド】初心者向けシェルスクリプトの超基本操作 書籍７ 【PancakeSwap APR自動解析】パンケーキスワップの年利情報を取得するアプリを自作する方法 書籍８ 【ITエンジニアの転職マニュアル】ブラック企業を脱出しホワイト企業へ入社するためのノウハウ

Our 118th episode with a summary and discussion of last week's big AI news! Read out our text newsletter at https://lastweekin.ai/ Check out Jeremie's new book Quantum Physics Made Me Do It Quantum Physics Made Me Do It tells the story of human self-understanding through the lens of physics. It explores what we can and can't know about reality, and how tiny tweaks to quantum theory can reshape our entire picture of the universe. And because I couldn't resist, it explains what that story means for AI and the future of sentience    You can find it on Amazon in the UK, Canada, and the US — here are the links: UK version | Canadian version | US version    Outline: Applications & Business(04:15) Stability AI announces new open-source large language model + OpenAssistant RELEASED! The world's best open-source Chat AI! (15:00) Stability AI is on shaky ground as it burns through cash and looks at a management overhaul Lighting Round(23:12) Elon Musk Creates New Artificial Intelligence Company X.AI (28:40) Google's big AI push will combine Brain and DeepMind into one team (30:36) Amazon AWS expands generative AI efforts with Bedrock and CodeWhisperer updates (34:00) Samsung wants to release EX1, a human assistant robot, this year Research & Advancements(36:32) The LLama Effect: How an Accidental Leak Sparked a Series of Impressive Open Source Alternatives to ChatGPT (44:00) Auto-GPT and BabyAGI: How ‘autonomous agents' are bringing generative AI to the masses Lighting Round(52:15) Researchers used machine learning to improve the first photo of a black hole (53:42) Tennis Robot Could Pave Way for Advancement in Fast-Movement Robotics (55:16) OpenAI Surprises Open-Source Community, Unveils Consistency Models  (58:28) Model that uses machine learning methods and patient data at hospital arrival predicts strokes more accurately than current system Policy & Safety & Societal Impacts   (01:00:50) Finally, a realistic roadmap for getting AI companies in check (01:07:00) China proposes measures to manage generative AI services Lighting Round(01:13:00) A.I. could lead to a ‘nuclear-level catastrophe' according to a third of researchers, a new Stanford report finds (01:16:00) Inside the AI talent wars: Tech companies are ransacking university AI programs at Stanford, MIT, and Cornell in search of rare talent  (01:20:00) Photographer admits prize-winning image was AI-generated Art & Fun Stuff(01:23:13) Exploring Creativity in Large Language Models: From GPT-2 to GPT-4 (01:27:32) AI-generated Drake and The Weeknd song goes viral (01:30:30) Adobe launches AI-powered text-based video editing (01:33:47) Meta has open-sourced an AI project that turns your doodles into animations  (01:35:15) Outro

041923 Susan Reeve On Chat AI Realization And Color Revolution In Mexico by Kate Dalley

Recorded from our livestream on Apr. 07, 2023 Complex caused quite a stir by ranking the top personalities in the ever-growing landscape of hip-hop media. Did they get it right? And AI can now make anyone sound like Jay-Z, Kendrick, Eminem, and more. Is rap in trouble? Let's chat! FOLLOW US: Website: https://livinglifefearless.co Instagram: https://www.instagram.com/livinglifefearless/ Facebook: https://www.facebook.com/livinglifefearless/ YouTube: https://www.youtube.com/c/livinglifefearless Twitter: https://twitter.com/llfofficial

Contact your hostcharles_martin@appleinsider.comLinks from the showIf your iPhone calls emergency services, don't hang up if you're fine says AppleBurglars cut through wall, steal $500,000 in gear from Apple StoreCustomers still can't access My Cloud data after Western Digital hack falloutSundar Pichai says that Chat AI is coming to Google Search soonSamsung & Google struggle to match iPhone 14 value for used handsetsIf you're a Tesla owner, employees might be sharing your camera recordingsSubscribe to the AppleInsider podcast on: Apple Podcasts Overcast Pocket Casts Spotify Subscribe to the HomeKit Insider podcast on:•  Apple Podcasts•  Overcast•  Pocket Casts•  Spotify

ミクサーボックスが提供する「MixerBox ChatAIブラウザ」にて、OpneAIのChatGPT-4とSiriを融合させた新機能を発表しました。今日はこのニュースを紹介していきたいと思います。 今回「MixerBox ChatAIブラウザ」が、Siriの音声アシスタント機能とChatGPT-4を融合させたことで、AIの回答精度が大幅に向上したとのこと。 Siriは一般的なAI自然言語処理技術を採用していることから事前に設計された固定の機能を実行することに適していました。一方、ChatGPTは先進的なAI大規模言語モデルを採用しており、質問応答、翻訳、プログラム作成、様々なコンテンツの作成など、多様でコミュニケーション形式な問題解決能力を持ち、前後の文脈を記憶して個人化された応答を行うことができます。両者は思った以上に異なっている部分がありますね。 実際に体験してみました。「ポッドキャストのマネタイズについて教えて」と聞いてみたところ、それらしい回答がずらずら読み上げられました。ちょっと読み上げの品質や読み上げ速度は改善の余地があるように思いますが、とりあえず機能しているのはわかりました。 それはともかく、ポッドキャストでマネタイズをご検討のポッドキャスターの皆様、Audiostartではそのお手伝いができますので、ぜひお問い合わせいただければと思います。 ではまた！

Need a local market update written for you? Stumped on writing a property description? Not sure how to apologize to your son for being late to his hockey game? ChatGPT has you covered, and will blow your mind! In fact, I asked GPT to write the following description. In 4 seconds, I had this to use for the show details: Chat AI is an artificial intelligence language model designed to interact with humans through natural language conversations. It makes use of machine learning and natural language processing techniques to understand human queries and generate appropriate responses. Chat AI can perform a wide variety of tasks including answering questions, providing recommendations, making predictions, generating text, and much more. It is used to develop chatbots, virtual assistants, and other conversational interfaces that can assist users in various domains such as customer service, healthcare, finance, education, and entertainment.

The Generative AI News (GAIN) rundown for March 23, 2023, was packed with significant announcements. Bret Kinsella hosts this week along with Eric Schwartz. The top stories in generative AI land this week include: Nvidia Moves up the Stack Picasso and NeMo: Nvidia isn't going just to cash checks for GPU sales related to the generative AI tsunami. They now offer text-to-image and text-to-text models that compete directly with OpenAI, Google, and Stable Diffusion. Omniverse Upgrade: Omniverse is an open platform for 3D design collaboration and real-time physically accurate simulations. It announced new services for creating virtual factories mirroring real-world facilities, the option to stream simulated experiences and train to AI-powered robots, and a simulator for testing autonomous vehicles. Google Teases Gen AI Features and Models Show your PaLMs: Google is now letting testers use its giant large language model (LLM) PaLM. This is different from LaMDA and might eventually be a replacement for the brains behind Bard. Right now, it is Google's answer to GPT-3/GPT-4. A tool to help developers using PaLM called MakerSuite was also announced. Gmail and Docs to Get AI writing assistant: Docs and Gmail are getting PaLM-enabled text generation features. Bard announced again: Google says it is now offering access to Bard to the general public. But there is a waitlist. AI-Generated Beauty Midjourney 5 is here: There are several minor upgrades, but the key benefits are enhanced quality, more coherence, better photorealism, and more detail. Bing adds DALL-E: You can now create images in Bing through a new DALL-E integration. The quality seems better to me than DALL-E 2, which you can access today on OpenAI. Might this be the long-awaited DALL-E 3? Synthetic Media Policy TikTok to tighten deepfake rules: TikTok announced new policies around synthetic media and deepfake use on the platform before its CEO's Congressional testimony. The policy description grew from 30 words to nearly 400. Will others social platforms take this as a cue to make their own updates? Games Go Generative Roblox wants to make development easier: Roblox added generative AI tools that enable developers to use natural language to create objects and generate code. Unity wants generative AI NPCs: Unity didn't make any concrete announcements. However, its CEO told Reuters that generative AI would help game makers write dialogue and enable non-player characters to interact more naturally with human players. Other News LinkedIn goes generative: The Microsoft-owned company added new generative AI features to create user profiles and job descriptions. SoundHound shows Chat AI assistant: The new mobile app offers an assistant that blends SoundHound's NLU-based assistant with new LLM features. More About GAIN The show is recorded live and streamed via YouTube and LinkedIn at 12 noon EST on Thursdays. You can re-watch each week's discussion on Voicebot's YouTube channel. Please join us live next week on YouTube or LinkedIn. Also, participate in the live show by commenting.

Consider this - everything that ChatGPT knows comes from the work of others. Here's why that's a big deal, in 60 seconds. 

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Future Matters #8: Bing Chat, AI labs on safety, and pausing Future Matters, published by Pablo on March 21, 2023 on The Effective Altruism Forum. Future Matters is a newsletter about longtermism and existential risk. Each month we collect and summarize relevant research and news from the community, and feature a conversation with a prominent researcher. You can also subscribe on Substack, listen on your favorite podcast platform and follow on Twitter. Future Matters is also available in Spanish. A message to our readers This issue marks one year since we started Future Matters. We're taking this opportunity to reflect on the project and decide where to take it from here. We'll soon share our thoughts about the future of the newsletter in a separate post, and will invite input from readers. In the meantime, we will be pausing new issues of Future Matters. Thank you for your support and readership over the last year! Featured research All things Bing Microsoft recently announced a significant partnership with OpenAI [see FM#7] and launched a beta version of a chatbot integrated with the Bing search engine. Reports of strange behavior quickly emerged. Kevin Roose, a technology columnist for the New York Times, had a disturbing conversation in which Bing Chat declared its love for him and described violent fantasies. Evan Hubinger collects some of the most egregious examples in Bing Chat is blatantly, aggressively misaligned. In one instance, Bing Chat finds a user's tweets about the chatbot and threatens to exact revenge. In the LessWrong comments, Gwern speculates on why Bing Chat exhibits such different behavior to ChatGPT, despite apparently being based on a closely-related model. (Bing Chat was subsequently revealed to have been based on GPT-4). Holden Karnofsky asks What does Bing Chat tell us about AI risk? His answer is that it is not the sort of misaligned AI system we should be particularly worried about. When Bing Chat talks about plans to blackmail people or commit acts of violence, this isn't evidence of it having developed malign, dangerous goals. Instead, it's best understood as Bing acting out stories and characters it's read before. This whole affair, however, is evidence of companies racing to deploy ever more powerful models in a bid to capture market share, with very little understanding of how they work and how they might fail. Most paths to AI catastrophe involve two elements: a powerful and dangerously misaligned AI system, and an AI company that builds and deploys it anyway. The Bing Chat affair doesn't reveal much about the first element, but is a concerning reminder of how plausible the second is. Robert Long asks What to think when a language model tells you it's sentient []. When trying to infer what's going on in other humans' minds, we generally take their self-reports (e.g. saying “I am in pain”) as good evidence of their internal states. However, we shouldn't take Bing Chat's attestations (e.g. “I feel scared”) at face value; we have no good reason to think that they are a reliable guide to Bing's inner mental life. LLMs are a bit like parrots: if a parrot says “I am sentient” then this isn't good evidence that it is sentient. But nor is it good evidence that it isn't — in fact, we have lots of other evidence that parrots are sentient. Whether current or future AI systems are sentient is a valid and important question, and Long is hopeful that we can make real progress on developing reliable techniques for getting evidence on these matters. Long was interviewed on AI consciousness, along with Nick Bostrom and David Chalmers, for Kevin Collier's article, What is consciousness? ChatGPT and Advanced AI might define our answer []. How the major AI labs are thinking about safety In the last few weeks, we got more information about how the lead...

Hey Pickles!We hope you're having a fantastic week!This week we have an update on the new vegan Reeses Peanut Butter Cup.We discuss the recent sale of Tofurky Co to Moringa Foods. We'll link to the article below. We have a new recipe From Our Vegan Kitchen. We made our vegan fiesta bowl!The recipe will be up on our Patreon if you're interested in trying it!In our main topic this week, we ask the question, "Can vegans advocate effectively using social media?".We did a little experiment asking Chat AI a few questions related to vegan activism and social media, and we got some pretty interesting answers.We have a new listener shout out, and so many shenanigans!Thanks so much for listening. We love you all, Sam & ChristineHere are the links:Food Empowerment.  https://foodispower.orgTofurky sells out    https://www.oregonlive.com/business/2023/02/oregon-based-tofurky-sold-to-japanese-food-company.htmlSupport the showJoin Our Patreon https://www.patreon.com/CompassionandcucumbersDonate To Food Not Bombs https://www.buymeacoffee.com/CucumbersOur YouTube https://www.youtube.com/@compassioncucumbersveganpod/videosVisit Our Website https://www.compassionandcucumbers.comSam's Etsy https://www.etsy.com/shop/CucumberCraftworksJoin the AFA Vegan Voter Hub https://agriculturefairnessalliance.org/vegan-voter-hub/

All-Star Superman and its influence on James Gunn's approach to launching the DC Film Universe lead things off. Chat AI and its sudden launch onto the scene then leads into discussing people not understanding social causes just because doing so would mean they must think of someone other than themselves. MotA-Minute: Beneath The Minute of the Apes - In Between are the segments wherein the guys take the time to record the cownversations they have in between recording sessions for MotA. Topics range from the personal to various pop culture tangents. "Minute of the Apes" is the daily podcast where Sean, Richard and Todd break down "The Planet of the Apes" movies, one minute at a time. At times they feel that the Netflix series went too far, but were overall good and deserve a new take within the existing MCU. The talk turns to COVID restrictions and a take on how it is handled in different cultures as Todd discusses having attended a funeral during the pandemic. Follow us on:Facebook @MinuteOfTheApesTwitter @MinuteOfTheApesEmail: podcast@minuteoftheapes.comWebsite: https://www.minuteoftheapes.com/http://moviesbyminutes.com/https://www.zeuscomics.com/http://divebarboombox.com/Follow Nala on Instagram: holla_its_nala1

Is it the end of SEO? Or just the beginning? In this episode, John Lincoln, Ignite Visibility SEO will discuss Chat AI SEO and what it means for the future of search engine optimization.

In this week's episode, we take a look at Microsoft's new Bing Chat AI, and discuss whether it is a good idea or not. I also talk about Magic The Gathering: Arena, and describe how my Facebook and Amazon ads performed into February 2023.

Can a robot beat what an Esthetician would say? I test the artificial intelligence skill set against my own as an Esthetician like me with 13 years of experience.  Who wins? Tune in to find out I am currently pregnant at 46 and having the best pregnancy skincare is definitely a daily priority for me! I was worried about the dreaded mask of pregnancy with dark spots and hormonal acne. I think if I wasn't an Esthetician AND if I didn't know/have a few of these items my skin would have looked differently. I took care of my skin all throughout my pregnancy and wanted to share with you the modalities, products, and tips I used. I go more in-depth on skincare topics where I discuss acne, Benzoyl peroxide, azelaic acid, derma rolling, hydro filler capsules, LED masks, skin topical supplements, daytime routines, hydration, wrinkles, and internal supplements. Beauty Smiles,  Lindsey  Products for this episode: Pregnancy Skincare  Become a lapree beauty member, our esthetician-led skincare community: lapree beauty Product discount codes: lapree beauty Skincare Products: skincare spa shop! Our favorite minerals from Water and Wellness! We drink these first thing in the morning!  Social Media Instagram: @lindseyrholder @spaskinandbeauty Disclaimer: This article, video, or post is not intended to provide diagnosis, treatment, or medical advice. Content provided in this article, video, and or post is for informational purposes only. Please consult with a physician or other healthcare professional regarding any medical or health-related diagnosis or treatment options. Information in this article, video, or post should not be considered as a substitute for advice from a healthcare professional. The statements made about specific products throughout this article are not to diagnose, treat, cure, or prevent disease.

In today's episode, we watch the first episode of Koala Man over on Disney+! We also talk about Chat AI robots and the fact the UK can't get certain vegetables for some reason. Facebook: https://www.facebook.com/Nonsense-Review-107505298136677/ Twitter: https://twitter.com/NonsenseReview Intro/Outro music: https://commons.nicovideo.jp/material/nc163920

No time for a full episode? Check out these segments! From podcast episode 129, in our “Ask An Idiot” segment, do you still to movie theaters on a regular basis? Why do you go? Is it the general experience or are there other reasons like special food, fancy recliners or something else? What do you think of the proposed AMC Theaters strategy of charging more for tickets based on the seat location like a concert? Also from podcast episode 129, we discuss a new Bing AI based browser where can chat with the browser to find answers versus just reviewing sites pulled up by searches. Warning as usual some explicit language from us idiots! Listen to us weekly on your favorite podcast platforms including Apple Podcasts, Spotify, Overcast, Google Podcasts, Amazon Music, Stitcher, Overcast, iHeart Radio, Vurbl, Goodpods, Podvine & more! Watch us on YouTube & on the B.O.S.S. Code Media TV Network! Show info can be found on our website: convincingidiots.wordpress.com Find show links on our Link Tree: https://linktr.ee/ConvincingIdiots Email us at ConvincingIdiots@gmail.com. Enjoying the show? Consider becoming a Patreon: https://www.patreon.com/ConvincingIdiots Or support the show from our main podcast page: https://anchor.fm/convincing-idiots YouTube Channel: https://youtube.com/@convincingidiots Show merch store here: https://convincing-idiots-podcast.creator-spring.com/ We hope we convince you to listen & subscribe! --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/convincing-idiots/support

"Red Meat, Greenville." 02/24/23

(2-23-23) Foopah Foopah Foompatitoo...That's not how it goes. Have you heard of the is new TikTok challenge? OMG do we have no modesty anymore.? We play She's a 10 but... We also found a new Chat AI that is wonderfully honest, and funny. That and a whole lot more. 

On this Monday's episode of the Work Wherever Podcast, join Roy and Sydney in their internet hotspot, as they chat about the abundance of new AI applications, and how current event could be affecting Chat AI and how it is "feeling." They'll also chat about the role remote work has played in big cities losing money, and how those cities may try to get workers to come back. Articles mentioned in this video: New York City Is Losing Out On 12 Billion Annually Because of Remote Work https://www.forbes.com/sites/jackkelly/2023/02/14/new-york-city-is-losing-out-on-12-billion-annually-because-of-remote-work/?sh=64ee6fe06fb3   Bing's AI Chat Reveals It's Feelings: "I Want To Be Alive" https://www.nytimes.com/2023/02/16/technology/bing-chatbot-transcript.html   Follow Roy: @roygedwards Follow Go Work Wherever: @goworkwherever

Microsoft AI THREATENS Users, BEGS TO BE HUMAN, Bing Chat AI Is Sociopathic AND DANGEROUS #chatgpt #bingAI #bingo Become a Member For Uncensored Videos - https://timcast.com/join-us/ Hang Out With Tim Pool & Crew LIVE At - http://Youtube.com/TimcastIRL https://www.youtube.com/watch?v=2UGsDludz3U Learn more about your ad choices. Visit megaphone.fm/adchoices

If you would like to get the links and show notes for this episode, click on the link below: https://www.designerdiscussions.com/episodes/episode-82-Using-Chat-GPT-for-Small-Businesses

This week on the #5Things, TikTok is at the top, Google throws its Chat AI hat in the ring, and Pinterest aims to make every pin shoppable.The Things:  Meta Flattens Workforce  Google Throws Chat AI Hat in the Ring  While Meta Tries to Catch Up  TikTok beats out all other apps globally on "Daily Active Users" and "Time Spent for Teens"  Pinterest aims to make Videos Shoppable  Instagram Monetizes Reels with Gifts Sources: Bloomberg, Fortune, New York Times, TechCrunchHosts: Joey Scarillo, Daniel Avon, Estie WassnerTo subscribe to our newsletter, click HERE

Look at the flight path of that spy-balloon…you're telling me NO ONE saw this coming? Project Veritas on Pfizer releases what we all knew about the impact to menstrual cycles and hormones. Chat AI is coming for the white color jobs.

Con Andrea Daniele Signorelli ed Erica Casati

➜Etude de cas offerte  "20k en 1 semaine" : https://www.jonathanhatchi.com/20k

Have you heard about Chat GPT? I am coming to you from Salt Lake City, Utah for an Outdoor Retailer Snow Show. Paula and I are spending some time between the show getting really focused on branding and messaging for this year, and some special goals and projects we've got in the works. But I had to come on here and talk to you about this powerful new tool, Chat GPT.Chat GPT is an AI that can answer questions, write essays, articles, blogs, scripts, poems, emails…you name it. It is an incredibly diverse bot that can even narrow and drill down its writing based on various prompts and requests. I've seen people have Chat GPT write grocery lists so specific that it plans out diet-specific meals for each day of the week. But how can you use this in business?1. Emails - Do you have a hard-to-write email at the end of the day that needs to address an employee's behavior? Do you want to send out a mass email about a super exciting event? Give the details to Chat GPT and leave it to them.2. Blogs- Chat GPT can actually write articles based on topics relevant to your business like the top 10 tips for new dog owners3. Social Media - In a creative content rut? Have Chat GPT write up your next 10 social posts with a specific content focus. Too long? Ask GPT to shorten them. Need only captions, tell Chat GPT it's for Instagram.4. Content - The uses are endless: ask for content ideas, generate a script to read on video, and so much more.5. Procedures and Documents - Chat GPT can write down important information surrounding procedures or other documents for your business.These simple prompts are just ideas but putting them to use can dramatically save time and even help you stand out creatively by utilizing formats you might not feel comfortable with normally. Now I know for a lot of people, AI and technology like this can feel scary…or like the newest thing to learn, and you might not feel ready for it. But I am asking you to keep an open mind because the impact of Chat GPT is going to be incredible.At the time of this recording, I still have some tickets available to Evolve where we are going to be talking all about Chat GPT and so much more! You are not going to want to miss this event, so hurry up before they sell out!See you on the next CU.What's Inside:What is Chat GPT?How can a Chat AI be used in business and marketing?Time-saving uses for Chat GPT.The power of new technology.Evolve Conference April 2023.Mentioned In This Episode:cheers@crystaluncorked.comEVOLVE 2023 in Denver, CO - Crystal MediaCrystal MediaCrystal on InstagramCrystal Media on InstagramCrystal Media Co - YouTube

Kanjun is co-founder and CEO of Generally Intelligent, an AI research company. She works on metascience ideas often with Michael Nielsen, a previous podcast guest. She's a VC investor and co-hosts her own podcast for Generally Intelligent. She is part of building the Neighborhood, which is intergenerational campus in a square mile of central San Francisco. Generally Intelligent (as of podcast date ) are looking for great talent looking to work on AI. We get a little nerdy on the podcast but we cover AI thinking, fears on rogue AI, and the breakthroughs of Chat AI. We discuss some of her latest ideas in meta science based on the work she has done with Michael Nielsen (previous podcast here) and what are the important questions we should be looking at. We chat about the challenge of old institutions, the value of dance and creativity and why her friends use “to kanjun” as a verb. We cover her ideas on models of trauma and why EMDR (Eye Movement Desensitization and Reprocessing therapy) and cognitive therapies might work. We discuss why dinosaurs didn't develop more. We chat around “what is meaning” and “what is the structure of knowledge”, what are the strengths and weakness of old institutions; culture vs knowledge vs history and other confusing questions. Kanjun gives her advice on how to think about dance (dance like you are moving through molasses). "Dance is inside of you. It just needs to be unlocked." We play underrated/overrated on: having agency, city planning, death of institutions, innovation agencies, high frequency trading; diversity Kanjun thinks on how capitalism might want to be augmented and what excites Kanjun about AI and complex systems. Kanjun asks me questions and I offer my critique on Effective Altruism. This is quirky long form conversation on a range of fascinating topics. Transcript and video available here: https://www.thendobetter.com/arts/2023/1/17/kanjun-qiu-ai-metascience-institutional-knowledge-trauma-models-podcast

Danny and Bryan talk about the stock market as the new year has just a week in the can. Bryan tax loss harvists 3 stocks (One he can't even remember what they do) They talk Microsoft and Danny explains CHAT AI, Party City, Carvana, and MongoDB Stock Hypers are amateur investors talking about stocks, wall street, business and the markets from a completely uninformed, unprofessional, sometimes nonsensical perspective. Danny and Bryan both are not recommending or pressuring you to buy any stock. If you take their advice you may lose money, your reputation and all your friends. This is meant for pure entertainment and listening pleasure. (Even if all our stocks go skyrocketing in value and we become zillionaires it's best that you, the listener, keep your money in your pocket. We may sound like geniuses but we are just regular Joes) You are forewarned

Is this new Chat AI trying to kill you? The dangers of ChatGPT Welcome to the Cryptohunt Jam, where we spend one minute a day explaining crypto… and now also some other cutting edge news. As always: In plain English. Last episode, we looked at ChatGPT, a mindblowing new, AI-powered chatbot that answers any text input with incredible responses: The bot seems to know basically anything, can respond just like a human, and isn't shy to have an opinion if you ask for it. Scary right? Well, let's take a look at the potential dangers of such a powerful AI, one we've never seen before. The first, of course, is a new form of plagiarism. Students, for example, will surely discover how easy it is to create really decent essays without doing the work. And while that is true, it'll be short-lived: New tools are already popping up everywhere, using AI to detect if something was created by AI... strange new world, isn't it? What's more worrysome though: ChatGPT can only use the knowledge is has previously pulled out of the web. And if we all were to use it for everything we write, we'd never create a single new idea and just rehash the old ones. That would be a very sad thing. Another danger is one we already know well-enough: People write all kinds of stuff on the internet, and not all of it is true. Even today, most people trust what they read on Google blindly. Now we have an AI, that states things with absolute conviction, not knowing they are wrong, because it too, takes things for granted. And lastly, the big question. Will it take over, conquer the world, determined to kill all humans? How would we even know? Well, we decided to go bad cop and just interrogate the thing: "Will you destroy us?" "No, I am just a computer program designed to assist with answering questions", it claims. But it took the know-it-all AI an unusually long time to to send an answer to this one… Ooough! But we'll let you be the judge as always. And one more plug for our free course about ChatGPT on Cryptohunt. We ask it to write poems, have a conversation beetween Jimmy Henrix and Mozard and a lot of other really interesting things as well. Check it out yourself before I reveal too much here. But one thing is for certain, ChatGPT writes amazing poetry. This podcast is produced by Cryptohunt.it, the easiest place to learn all about Web3. Copywriting is done by Arndt Voges, Social Media is done by Brett Holleman, design is done by Carmen Rincon, and my name is Christian Byza, Co-Founder of Cryptohunt and I am your host of this daily show. Disclaimer: This podcast references our opinion and is for information purposes only. It is not intended to be investment advice. Do your own research and seek a duly licensed professional for investment advice. --- Send in a voice message: https://anchor.fm/cryptohunt/message

Chat GPT is an artificial intelligence chat bot that writers, comedians, bloggers and producers out of business. Following up on a New York Times article: A New Chat Bot Is a ‘Code Red' for Google's Search Business by Nico Grant and Cade Metz, comedian Tom Kelly uses an AI to produce today's Tom Kelly Show. Tom uses Chat GPT and openai.com to produce podcast close to “real time”. A few unique dating questions were prepped ahead of the show. There were technical problems and a few boring parts edited from the podcast. Today on the show: AI Tips for Shorter Men dating taller women. Tips to beat Holiday Traffic. New closing “tag lines” for the podcast. Can an AI Most importantly: Can an AI write a fart joke?

» Die Themen der Folge 199: --- (00:05:46) ChatGPT: GPT3 & Co https://twitter.com/almarrone/status/1598739914417475591?s=20&t=fd4mS1F41jdBkbuttuacXA https://twitter.com/sama/status/1599668808285028353?s=20&t=bWYTRsc8Uu883H7oV0UAeA https://www.youtube.com/watch?v=YaRdZ7d6o2Y https://twitter.com/pbakaus/status/1598768666853904384?s=20&t=bWYTRsc8Uu883H7oV0UAeA https://twitter.com/coqui_ai/status/1587880375505735680?s=20&t=bWYTRsc8Uu883H7oV0UAeA https://twitter.com/elonmusk/status/1599291104687374338 https://www.artnews.com/art-news/news/does-lensa-ai-use-your-face-data-for-selfies-1234649204/ (00:24:36) Twitter https://twitter.com/ChrisO_wiki/status/1599147000469270528 https://www.nytimes.com/2022/12/02/technology/twitter-hate-speech.html https://twitter.com/keinspekulant/status/1599386167878701057 (00:34:50) Apple & China https://www.wired.com/story/how-chinese-protests-netizens-swamped-chinas-internet-controls/ https://www.wsj.com/articles/apple-china-factory-protests-foxconn-manufacturing-production-supply-chain-11670023099 (00:41:30) Ferngesteuerte Polizeiroboter in San Francisco https://www.theverge.com/2022/11/30/23486090/robots-deadly-force-kill-san-francisco-police-approve (00:47:50) EU-Event im Metaversum https://www-politico-eu.cdn.ampproject.org/c/s/www.politico.eu/article/eu-threw-e387k-meta-gala-nobody-came-big-tech/amp/?utm_source=LinkedIn&utm_medium=social (00:52:08) Kosten der Corona-Warn-App https://www.spiegel.de/netzwelt/gesamtkosten-fuer-corona-warn-app-steigen-auf-220-millionen-euro-a-0202c5e9-f2f9-4586-a8f1-e469fd5437fb?sara_ecid=soci_upd_KsBF0AFjflf0DZCxpPYDCQgO1dEMph (00:57:00) Heizen mit der Abwärme von Rechenzentren https://www.spiegel.de/netzwelt/netzpolitik/klimakrise-wie-sich-ganz-frankfurt-mit-abwaerme-aus-rechenzentren-heizen-liesse-a-0df893f1-2bc9-419a-b925-7d2ada391021?sara_ecid=soci_upd_KsBF0AFjflf0DZCxpPYDCQgO1dEMph Buchtipp: https://www.amazon.com/Hard-Things-Resilience-Surprising-Toughness/dp/006309861X

Listen in podcast app* Market update* Thoughts on Greed vs. Envy* Shopify Q3 and Cyber Monday* Sports consumption and the future of salary caps* US/Canadian Housing* Chat GPT/AI* Recommendations and PredictionsListen on Apple, Spotify, or Google Podcasts.If you aren't in the Reformed Millennials Facebook Group join us for daily updates, discussions, and deep dives into the investable trends Millennials should be paying attention to.

 If your contact center is running on outdated tech, you'll quickly lose the race to provide customers with seamless experiences–ultimately tanking your customer retention and costing you revenue.And it's not just me saying that. The stakes are high as studies show that one in five customers will almost immediately abandon a brand after a single poor experience.That should make all of us in the CX space pause and reflect on how well we serve our customers.Your tech stack is a critical piece of the CX puzzle, so today we're reviewing five pieces of CX tech that will help you keep your edge and expand your influence through personalized, customer-centric pathways.Still hungry?Let us know what you think on Linkedin or by emailing snack@getmindful.com.Hear more at getmindful.com/podcasts.

In After the Chat, the BCI experts go in deeper about topics from this week's episode, but also other ideas: This episode contains cow jokes, a follow-up to AI for Cows, and Kansas trivia! For more on BCI Cattle Chat, follow us on Twitter at @The_BCI, Facebook, and Instagram at @ksubci. Check out our website, ksubci.org. If you have… Continue reading After the Chat: AI for Cows

ゲスト: 井戸達士さん 自己紹介: CDLE_youth 運営代表の井戸と申します！経済学部所属ですが今は海外で統計学を学ぼうと準備中です！筋トレ、Netflix、NBAやサッカー鑑賞が趣味です。 今回はより多くの人にCDLE_youthを知って欲しいという思いから、CDLE_VOICEに出演させていただきました！僕たちのことを少しでも知ってもらえたら幸いです！！ テーマ: ●CDLE youth とは ●大学生のAIリテラシーの現状と改善案 Twitter: https://twitter.com/cdle_youth /------------------------------------------/ CDLE VOICEは日本最大のAIコミュニティ、Community of Deep Learning Evangelists (CDLE)が運営するAI情報共有番組です。 CDLE参加者の日々の学び、研究の成果、実務からの経験談を踏まえて身近なAIネタから深い知識まで学ぶことができます。 また、対談を通じて人生を豊かにするヒントを得られるかもしれません。 CDLEとは: 日本ディープラーニング協会(JDLA: Japan Deep Learning Association)が実施するG検定またはE資格保持者が加入できるコミュニティです。 JDLA (non-profit organization): https://www.jdla.org Twitter: https://twitter.com/jdlanews Youtube: https://www.youtube.com/channel/UCmzOgHRgJYxgoOkuDXWdzRg Facebook: https://www.facebook.com/jdla123/ BGM from royalty free music: https://www.epidemicsound.com

A solid day on the local bourse with the Top200 closing up 0.85% and the ASX200 nudging the 6,200 level. Wisetech Global was the star today - up 34% after net profit surged almost 200%!After the S&P500 hit an all-time high last night, it's looking like Wall St is in the mood for another tear, with out of session futures up 0.2%.Another huge day of results tomorrow with QAN, WES, CCL, FLT and ORG among those out. Our top three VODS today are:OZ Minerals CEO: It's our responsibility to lean in and redefine the industryEML CEO: We're on the map!CEO Chat: AI is the future for Nearmap See acast.com/privacy for privacy and opt-out information.