Podcasts about cpx

Join Kyle, Nader, Vibhu, and swyx live at NVIDIA GTC next week!Now that AIE Europe tix are ~sold out, our attention turns to Miami and World's Fair!The definitive AI Accelerator chip company has more than 10xed this AI Summer:And is now a $4.4 trillion megacorp… that is somehow still moving like a startup. We are blessed to have a unique relationship with our first ever NVIDIA guests: Kyle Kranen who gave a great inference keynote at the first World's Fair and is one of the leading architects of NVIDIA Dynamo (a Datacenter scale inference framework supporting SGLang, TRT-LLM, vLLM), and Nader Khalil, a friend of swyx from our days in Celo in The Arena, who has been drawing developers at GTC since before they were even a glimmer in the eye of NVIDIA:Nader discusses how NVIDIA Brev has drastically reduced the barriers to entry for developers to get a top of the line GPU up and running, and Kyle explains NVIDIA Dynamo as a data center scale inference engine that optimizes serving by scaling out, leveraging techniques like prefill/decode disaggregation, scheduling, and Kubernetes-based orchestration, framed around cost, latency, and quality tradeoffs. We also dive into Jensen's “SOL” (Speed of Light) first-principles urgency concept, long-context limits and model/hardware co-design, internal model APIs (https://build.nvidia.com), and upcoming Dynamo and agent sessions at GTC.Full Video pod on YouTubeTimestamps00:00 Agent Security Basics00:39 Podcast Welcome and Guests07:19 Acquisition and DevEx Shift13:48 SOL Culture and Dynamo Setup27:38 Why Scale Out Wins29:02 Scale Up Limits Explained30:24 From Laptop to Multi Node33:07 Cost Quality Latency Tradeoffs38:42 Disaggregation Prefill vs Decode41:05 Kubernetes Scaling with Grove43:20 Context Length and Co Design57:34 Security Meets Agents58:01 Agent Permissions Model59:10 Build Nvidia Inference Gateway01:01:52 Hackathons And Autonomy Dreams01:10:26 Local GPUs And Scaling Inference01:15:31 Long Running Agents And SF ReflectionsTranscriptAgent Security BasicsNader: Agents can do three things. They can access your files, they can access the internet, and then now they can write custom code and execute it. You literally only let an agent do two of those three things. If you can access your files and you can write custom code, you don't want internet access because that's one to see full vulnerability, right?If you have access to internet and your file system, you should know the full scope of what that agent's capable of doing. Otherwise, now we can get injected or something that can happen. And so that's a lot of what we've been thinking about is like, you know, how do we both enable this because it's clearly the future.But then also, you know, what, what are these enforcement points that we can start to like protect?swyx: All right.Podcast Welcome and Guestsswyx: Welcome to the Lean Space podcast in the Chromo studio. Welcome to all the guests here. Uh, we are back with our guest host Viu. Welcome. Good to have you back. And our friends, uh, Netter and Kyle from Nvidia. Welcome.Kyle: Yeah, thanks for having us.swyx: Yeah, thank you. Actually, I don't even know your titles.Uh, I know you're like architect something of Dynamo.Kyle: Yeah. I, I'm one of the engineering leaders [00:01:00] and a architects of Dynamo.swyx: And you're director of something and developers, developer tech.Nader: Yeah.swyx: You're the developers, developers, developers guy at nvidia,Nader: open source agent marketing, brev,swyx: and likeNader: Devrel tools and stuff.swyx: Yeah. BeenNader: the focus.swyx: And we're, we're kind of recording this ahead of Nvidia, GTC, which is coming to town, uh, again, uh, or taking over town, uh, which, uh, which we'll all be at. Um, and we'll talk a little bit about your sessions and stuff. Yeah.Nader: We're super excited for it.GTC Booth Stunt Storiesswyx: One of my favorite memories for Nader, like you always do like marketing stunts and like while you were at Rev, you like had this surfboard that you like, went down to GTC with and like, NA Nvidia apparently, like did so much that they bought you.Like what, what was that like? What was that?Nader: Yeah. Yeah, we, we, um. Our logo was a chaka. We, we, uh, we were always just kind of like trying to keep true to who we were. I think, you know, some stuff, startups, you're like trying to pretend that you're a bigger, more mature company than you are. And it was actually Evan Conrad from SF Compute who was just like, you guys are like previousswyx: guest.Yeah.Nader: Amazing. Oh, really? Amazing. Yeah. He was just like, guys, you're two dudes in the room. Why are you [00:02:00] pretending that you're not? Uh, and so then we were like, okay, let's make the logo a shaka. We brought surfboards to our booth to GTC and the energy was great. Yeah. Some palm trees too. They,Kyle: they actually poked out over like the, the walls so you could, you could see the bread booth.Oh, that's so funny. AndNader: no one else,Kyle: just from very far away.Nader: Oh, so you remember it backKyle: then? Yeah I remember it pre-acquisition. I was like, oh, those guys look cool,Nader: dude. That makes sense. ‘cause uh, we, so we signed up really last minute, and so we had the last booth. It was all the way in the corner. And so I was, I was worried that no one was gonna come.So that's why we had like the palm trees. We really came in with the surfboards. We even had one of our investors bring her dog and then she was just like walking the dog around to try to like, bring energy towards our booth. Yeah.swyx: Steph.Kyle: Yeah. Yeah, she's the best,swyx: you know, as a conference organizer, I love that.Right? Like, it's like everyone who sponsors a conference comes, does their booth. They're like, we are changing the future of ai or something, some generic b******t and like, no, like actually try to stand out, make it fun, right? And people still remember it after three years.Nader: Yeah. Yeah. You know what's so funny?I'll, I'll send, I'll give you this clip if you wanna, if you wanna add it [00:03:00] in, but, uh, my wife was at the time fiance, she was in medical school and she came to help us. ‘cause it was like a big moment for us. And so we, we bought this cricket, it's like a vinyl, like a vinyl, uh, printer. ‘cause like, how else are we gonna label the surfboard?So, we got a surfboard, luckily was able to purchase that on the company card. We got a cricket and it was just like fine tuning for enterprises or something like that, that we put on the. On the surfboard and it's 1:00 AM the day before we go to GTC. She's helping me put these like vinyl stickers on.And she goes, you son of, she's like, if you pull this off, you son of a b***h. And so, uh, right. Pretty much after the acquisition, I stitched that with the mag music acquisition. I sent it to our family group chat. Ohswyx: Yeah. No, well, she, she made a good choice there. Was that like basically the origin story for Launchable is that we, it was, and maybe we should explain what Brev is andNader: Yeah.Yeah. Uh, I mean, brev is just, it's a developer tool that makes it really easy to get a GPU. So we connect a bunch of different GPU sources. So the basics of it is like, how quickly can we SSH you into a G, into a GPU and whenever we would talk to users, they wanted A GPU. They wanted an A 100. And if you go to like any cloud [00:04:00] provisioning page, usually it's like three pages of forms or in the forms somewhere there's a dropdown.And in the dropdown there's some weird code that you know to translate to an A 100. And I remember just thinking like. Every time someone says they want an A 100, like the piece of text that they're telling me that they want is like, stuffed away in the corner. Yeah. And so we were like, what if the biggest piece of text was what the user's asking for?And so when you go to Brev, it's just big GPU chips with the type that you want withswyx: beautiful animations that you worked on pre, like pre you can, like, now you can just prompt it. But back in the day. Yeah. Yeah. Those were handcraft, handcrafted artisanal code.Nader: Yeah. I was actually really proud of that because, uh, it was an, i I made it in Figma.Yeah. And then I found, I was like really struggling to figure out how to turn it from like Figma to react. So what it actually is, is just an SVG and I, I have all the styles and so when you change the chip, whether it's like active or not it changes the SVG code and that somehow like renders like, looks like it's animating, but it, we just had the transition slow, but it's just like the, a JavaScript function to change the like underlying SVG.Yeah. And that was how I ended up like figuring out how to move it from from Figma. But yeah, that's Art Artisan. [00:05:00]Kyle: Speaking of marketing stunts though, he actually used those SVGs. Or kind of use those SVGs to make these cards.Nader: Oh yeah. LikeKyle: a GPU gift card Yes. That he handed out everywhere. That was actually my first impression of thatNader: one.Yeah,swyx: yeah, yeah.Nader: Yeah.swyx: I think I still have one of them.Nader: They look great.Kyle: Yeah.Nader: I have a ton of them still actually in our garage, which just, they don't have labels. We should honestly like bring, bring them back. But, um, I found this old printing press here, actually just around the corner on Ven ness. And it's a third generation San Francisco shop.And so I come in an excited startup founder trying to like, and they just have this crazy old machinery and I'm in awe. ‘cause the the whole building is so physical. Like you're seeing these machines, they have like pedals to like move these saws and whatever. I don't know what this machinery is, but I saw all three generations.Like there's like the grandpa, the father and the son, and the son was like, around my age. Well,swyx: it's like a holy, holy trinity.Nader: It's funny because we, so I just took the same SVG and we just like printed it and it's foil printing, so they make a a, a mold. That's like an inverse of like the A 100 and then they put the foil on it [00:06:00] and then they press it into the paper.And I remember once we got them, he was like, Hey, don't forget about us. You know, I guess like early Apple and Cisco's first business cards were all made there. And so he was like, yeah, we, we get like the startup businesses but then as they mature, they kind of go somewhere else. And so I actually, I think we were talking with marketing about like using them for some, we should go back and make some cards.swyx: Yeah, yeah, yeah. You know, I remember, you know, as a very, very small breadth investor, I was like, why are we spending time like, doing these like stunts for GPUs? Like, you know, I think like as a, you know, typical like cloud hard hardware person, you go into an AWS you pick like T five X xl, whatever, and it's just like from a list and you look at the specs like, why animate this GP?And, and I, I do think like it just shows the level of care that goes throughout birth and Yeah. And now, and also the, and,Nader: and Nvidia. I think that's what the, the thing that struck me most when we first came in was like the amount of passion that everyone has. Like, I think, um, you know, you talk to, you talk to Kyle, you talk to, like, every VP that I've met at Nvidia goes so close to the metal.Like, I remember it was almost a year ago, and like my VP asked me, he's like, Hey, [00:07:00] what's cursor? And like, are you using it? And if so, why? Surprised at this, and he downloaded Cursor and he was asking me to help him like, use it. And I thought that was, uh, or like, just show him what he, you know, why we were using it.And so, the amount of care that I think everyone has and the passion, appreciate, passion and appreciation for the moment. Right. This is a very unique time. So it's really cool to see everyone really like, uh, appreciate that.swyx: Yeah.Acquisition and DevEx Shiftswyx: One thing I wanted to do before we move over to sort of like research topics and, uh, the, the stuff that Kyle's working on is just tell the story of the acquisition, right?Like, not many people have been, been through an acquisition with Nvidia. What's it like? Uh, what, yeah, just anything you'd like to say.Nader: It's a crazy experience. I think, uh, you know, we were the thing that was the most exciting for us was. Our goal was just to make it easier for developers.We wanted to find access to GPUs, make it easier to do that. And then all, oh, actually your question about launchable. So launchable was just make one click exper, like one click deploys for any software on top of the GPU. Mm-hmm. And so what we really liked about Nvidia was that it felt like we just got a lot more resources to do all of that.I think, uh, you [00:08:00] know, NVIDIA's goal is to make things as easy for developers as possible. So there was a really nice like synergy there. I think that, you know, when it comes to like an acquisition, I think the amount that the soul of the products align, I think is gonna be. Is going speak to the success of the acquisition.Yeah. And so it in many ways feels like we're home. This is a really great outcome for us. Like we you know, I love brev.nvidia.com. Like you should, you should use it's, it's theKyle: front page for GPUs.Nader: Yeah. Yeah. If you want GP views,Kyle: you go there, getswyx: it there, and it's like internally is growing very quickly.I, I don't remember You said some stats there.Nader: Yeah, yeah, yeah. It's, uh, I, I wish I had the exact numbers, but like internally, externally, it's been growing really quickly. We've been working with a bunch of partners with a bunch of different customers and ISVs, if you have a solution that you want someone that runs on the GPU and you want people to use it quickly, we can bundle it up, uh, in a launchable and make it a one click run.If you're doing things and you want just like a sandbox or something to run on, right. Like open claw. Huge moment. Super exciting. Our, uh, and we'll talk into it more, but. You know, internally, people wanna run this, and you, we know we have to be really careful from the security implications. Do we let this run on the corporate network?Security's guidance was, Hey, [00:09:00] run this on breath, it's in, you know, it's, it's, it's a vm, it's sitting in the cloud, it's off the corporate network. It's isolated. And so that's been our stance internally and externally about how to even run something like open call while we figure out how to run these things securely.But yeah,swyx: I think there's also like, you almost like we're the right team at the right time when Nvidia is starting to invest a lot more in developer experience or whatever you call it. Yeah. Uh, UX or I don't know what you call it, like software. Like obviously NVIDIA is always invested in software, but like, there's like, this is like a different audience.Yeah. It's aNader: widerKyle: developer base.swyx: Yeah. Right.Nader: Yeah. Yeah. You know, it's funny, it's like, it's not, uh,swyx: so like, what, what is it called internally? What, what is this that people should be aware that is going on there?Nader: Uh, what, like developer experienceswyx: or, yeah, yeah. Is it's called just developer experience or is there like a broader strategy hereNader: in Nvidia?Um, Nvidia always wants to make a good developer experience. The thing is and a lot of the technology is just really complicated. Like, it's not, it's uh, you know, I think, um. The thing that's been really growing or the AI's growing is having a huge moment, not [00:10:00] because like, let's say data scientists in 2018, were quiet then and are much louder now.The pie is com, right? There's a whole bunch of new audiences. My mom's wondering what she's doing. My sister's learned, like taught herself how to code. Like the, um, you know, I, I actually think just generally AI's a big equalizer and you're seeing a more like technologically literate society, I guess.Like everyone's, everyone's learning how to code. Uh, there isn't really an excuse for that. And so building a good UX means that you really understand who your end user is. And when your end user becomes such a wide, uh, variety of people, then you have to almost like reinvent the practice, right? Yeah. You haveKyle: to, and actually build more developer ux, right?Because the, there are tiers of developer base that were added. You know, the, the hackers that are building on top of open claw, right? For example, have never used gpu. They don't know what kuda is. They, they, they just want to run something.Nader: Yeah.Kyle: You need new UX that is not just. Hey, you know, how do you program something in Cuda and run it?And then, and then we built, you know, like when Deep Learning was getting big, we built, we built Torch and, and, but so recently the amount of like [00:11:00] layers that are added to that developer stack has just exploded because AI has become ubiquitous. Everyone's using it in different ways. Yeah. It'sNader: moving fast in every direction.Vertical, horizontal.Vibhu: Yeah. You guys, you even take it down to hardware, like the DGX Spark, you know, it's, it's basically the same system as just throwing it up on big GPU cluster.Nader: Yeah, yeah, yeah. It's amazing. Blackwell.swyx: Yeah. Uh, we saw the preview at the last year's GTC and that was one of the better performing, uh, videos so far, and video coverage so far.Awesome. This will beat it. Um,Nader: that wasswyx: actually, we have fingersNader: crossed. Yeah.DGX Spark and Remote AccessNader: Even when Grace Blackwell or when, um, uh, DGX Spark was first coming out getting to be involved in that from the beginning of the developer experience. And it just comes back to what youswyx: were involved.Nader: Yeah. St. St.swyx: Mars.Nader: Yeah. Yeah. I mean from, it was just like, I, I got an email, we just got thrown into the loop and suddenly yeah, I, it was actually really funny ‘cause I'm still pretty fresh from the acquisition and I'm, I'm getting an email from a bunch of the engineering VPs about like, the new hardware, GPU chip, like we're, or not chip, but just GPU system that we're putting out.And I'm like, okay, cool. Matters. Now involved with this for the ux, I'm like. What am I gonna do [00:12:00] here? So, I remember the first meeting, I was just like kind of quiet as I was hearing engineering VPs talk about what this box could be, what it could do, how we should use it. And I remember, uh, one of the first ideas that people were idea was like, oh, the first thing that it was like, I think a quote was like, the first thing someone's gonna wanna do with this is get two of them and run a Kubernetes cluster on top of them.And I was like, oh, I think I know why I'm here. I was like, the first thing we're doing is easy. SSH into the machine. And then, and you know, just kind of like scoping it down of like, once you can do that every, you, like the person who wants to run a Kubernetes cluster onto Sparks has a higher propensity for pain, then, then you know someone who buys it and wants to run open Claw right now, right?If you can make sure that that's as effortless as possible, then the rest becomes easy. So there's a tool called Nvidia Sync. It just makes the SSH connection really simple. So, you know, if you think about it like. If you have a Mac, uh, or a PC or whatever, if you have a laptop and you buy this GPU and you want to use it, you should be able to use it like it's A-A-G-P-U in the cloud, right?Um, but there's all this friction of like, how do you actually get into that? That's part of [00:13:00] Revs value proposition is just, you know, there's a CLI that wraps SSH and makes it simple. And so our goal is just get you into that machine really easily. And one thing we just launched at CES, it's in, it's still in like early access.We're ironing out some kinks, but it should be ready by GTC. You can register your spark on Brev. And so now if youswyx: like remote managed yeah, local hardware. Single pane of glass. Yeah. Yeah. Because Brev can already manage other clouds anyway, right?Vibhu: Yeah, yeah. And you use the spark on Brev as well, right?Nader: Yeah. But yeah, exactly. So, so you, you, so you, you set it up at home you can run the command on it, and then it gets it's essentially it'll appear in your Brev account, and then you can take your laptop to a Starbucks or to a cafe, and you'll continue to use your, you can continue use your spark just like any other cloud node on Brev.Yeah. Yeah. And it's just like a pre-provisioned centerswyx: in yourNader: home. Yeah, exactly.swyx: Yeah. Yeah.Vibhu: Tiny little data center.Nader: Tiny little, the size ofVibhu: your phone.SOL Culture and Dynamo Setupswyx: One more thing before we move on to Kyle. Just have so many Jensen stories and I just love, love mining Jensen stories. Uh, my favorite so far is SOL. Uh, what is, yeah, what is S-O-L-S-O-LNader: is actually, i, I think [00:14:00] of all the lessons I've learned, that one's definitely my favorite.Kyle: It'll always stick with you.Nader: Yeah. Yeah. I, you know, in your startup, everything's existential, right? Like we've, we've run out of money. We were like, on the risk of, of losing payroll, we've had to contract our team because we l ran outta money. And so like, um, because of that you're really always forcing yourself to I to like understand the root cause of everything.If you get a date, if you get a timeline, you know exactly why that date or timeline is there. You're, you're pushing every boundary and like, you're not just say, you're not just accepting like a, a no. Just because. And so as you start to introduce more layers, as you start to become a much larger organization, SOL is is essentially like what is the physics, right?The speed of light moves at a certain speed. So if flight's moving some slower, then you know something's in the way. So before trying to like layer reality back in of like, why can't this be delivered at some date? Let's just understand the physics. What is the theoretical limit to like, uh, how fast this can go?And then start to tell me why. ‘cause otherwise people will start telling you why something can't be done. But actually I think any great leader's goal is just to create urgency. Yeah. [00:15:00] There's an infiniteKyle: create compelling events, right?Nader: Yeah.Kyle: Yeah. So l is a term video is used to instigate a compelling event.You say this is done. How do we get there? What is the minimum? As much as necessary, as little as possible thing that it takes for us to get exactly here and. It helps you just break through a bunch of noise.swyx: Yeah.Kyle: Instantly.swyx: One thing I'm unclear about is, can only Jensen use the SOL card? Like, oh, no, no, no.Not everyone get the b******t out because obviously it's Jensen, but like, can someone else be like, no, likeKyle: frontline engineers use it.Nader: Yeah. Every, I think it's not so much about like, get the b******t out. It's like, it's like, give me the root understanding, right? Like, if you tell me something takes three weeks, it like, well, what's the first principles?Yeah, the first principles. It's like, what's the, what? Like why is it three weeks? What is the actual yeah. What's the actual limit of why this is gonna take three weeks? If you're gonna, if you, if let's say you wanted to buy a new computer and someone told you it's gonna be here in five days, what's the SOL?Well, like the SOL is like, I could walk into a Best Buy and pick it up for you. Right? So then anything that's like beyond that is, and is that practical? Is that how we're gonna, you know, let's say give everyone in the [00:16:00] company a laptop, like obviously not. So then like that's the SOL and then it's like, okay, well if we have to get more than 10, suddenly there might be some, right?And so now we can kind of piece the reality back.swyx: So, so this is the. Paul Graham do things that don't scale. Yeah. And this is also the, what people would now call behi agency. Yeah.Kyle: It's actually really interesting because there's a, there's a second hardware angle to SOL that like doesn't come up for all the org sol is used like culturally at aswyx: media for everything.I'm also mining for like, I think that can be annoying sometimes. And like someone keeps going IOO you and you're like, guys, like we have to be stable. We have to, we to f*****g plan. Yeah.Kyle: It's an interesting balance.Nader: Yeah. I encounter that with like, actually just with, with Alec, right? ‘cause we, we have a new conference so we need to launch, we have, we have goals of what we wanna launch by, uh, by the conference and like, yeah.At the end of the day, where isswyx: this GTC?Nader: Um, well this is like, so we, I mean we did it for CES, we did for GT CDC before that we're doing it for GTC San Jose. So I mean, like every, you know, we have a new moment. Um, and we want to launch something. Yeah. And we want to do so at SOL and that does mean that some, there's some level of prioritization that needs [00:17:00] to happen.And so it, it is difficult, right? I think, um, you have to be careful with what you're pushing. You know, stability is important and that should be factored into S-O-L-S-O-L isn't just like, build everything and let it break, you know, that, that's part of the conversation. So as you're laying, layering in all the details, one of them might be, Hey, we could build this, but then it's not gonna be stable for X, y, z reasons.And so that was like, one of our conversations for CES was, you know, hey, like we, we can get this into early access registering your spark with brev. But there are a lot of things that we need to do in order to feel really comfortable from a security perspective, right? There's a lot of networking involved before we deliver that to users.So it's like, okay. Let's get this to a point where we can at least let people experiment with it. We had it in a booth, we had it in Jensen's keynote, and then let's go iron out all the networking kinks. And that's not easy. And so, uh, that can come later. And so that was the way that we layered that back in.Yeah. ButKyle: It's not really about saying like, you don't have to do the, the maintenance or operational work. It's more about saying, you know, it's kind of like [00:18:00] highlights how progress is incremental, right? Like, what is the minimum thing that we can get to. And then there's SOL for like every component after that.But there's the SOL to get you, get you to the, the starting line. And that, that's usually how it's asked. Yeah. On the other side, you know, like SOL came out of like hardware at Nvidia. Right. So SOL is like literally if we ran the accelerator or the GPU with like at basically full speed with like no other constraints, like how FAST would be able to make a program go.swyx: Yeah. Yeah. Right.Kyle: Soswyx: in, in training that like, you know, then you work back to like some percentage of like MFU for example.Kyle: Yeah, that's a, that's a great example. So like, there's an, there's an S-O-L-M-F-U, and then there's like, you know, what's practically achievable.swyx: Cool. Should we move on to sort of, uh, Kyle's side?Uh, Kyle, you're coming more from the data science world. And, uh, I, I mean I always, whenever, whenever I meet someone who's done working in tabular stuff, graph neural networks, time series, these are basically when I go to new reps, I go to ICML, I walk the back halls. There's always like a small group of graph people.Yes. Absolute small group of tabular people. [00:19:00] And like, there's no one there. And like, it's very like, you know what I mean? Like, yeah, no, like it's, it's important interesting work if you care about solving the problems that they solve.Kyle: Yeah.swyx: But everyone else is just LMS all the time.Kyle: Yeah. I mean it's like, it's like the black hole, right?Has the event horizon reached this yet in nerves? Um,swyx: but like, you know, those are, those are transformers too. Yeah. And, and those are also like interesting things. Anyway, uh, I just wanted to spend a little bit of time on, on those, that background before we go into Dynamo, uh, proper.Kyle: Yeah, sure. I took a different path to Nvidia than that, or I joined six years ago, seven, if you count, when I was an intern.So I joined Nvidia, like right outta college. And the first thing I jumped into was not what I'd done in, during internship, which was like, you know, like some stuff for autonomous vehicles, like heavyweight object detection. I jumped into like, you know, something, I'm like, recommenders, this is popular. Andswyx: yeah, he did RexiKyle: as well.Yeah, Rexi. Yeah. I mean that, that was the taboo data at the time, right? You have tables of like, audience qualities and item qualities, and you're trying to figure out like which member of [00:20:00] the audience matches which item or, or more practically which item matches which member of the audience. And at the time, really it was like we were trying to enable.Uh, recommender, which had historically been like a little bit of a CP based workflow into something that like, ran really well in GPUs. And it's since been done. Like there are a bunch of libraries for Axis that run on GPUs. Uh, the common models like Deeplearning recommendation model, which came outta meta and the wide and deep model, which was used or was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips, especially to do, you know, vector lookups.But it was very interesting at the time and super, super relevant because like we were starting to get like. This explosion of feeds and things that required rec recommenders to just actively be on all the time. And sort of transitioned that a little bit towards graph neural networks when I discovered them because I was like, okay, you can actually use graphical neural networks to represent like, relationships between people, items, concepts, and that, that interested me.So I jumped into that at [00:21:00] Nvidia and, and got really involved for like two-ish years.swyx: Yeah. Uh, and something I learned from Brian Zaro Yeah. Is that you can just kind of choose your own path in Nvidia.Kyle: Oh my God. Yeah.swyx: Which is not a normal big Corp thing. Yeah. Like you, you have a lane, you stay in your lane.Nader: I think probably the reason why I enjoy being in a, a big company, the mission is the boss probably from a startup guy. Yeah. The missionswyx: is the boss.Nader: Yeah. Uh, it feels like a big game of pickup basketball. Like, you know, if you play one, if you wanna play basketball, you just go up to the court and you're like, Hey look, we're gonna play this game and we need three.Yeah. And you just like find your three. That's honestly for every new initiative that's what it feels like. Yeah.Vibhu: It also like shows, right? Like Nvidia. Just releasing state-of-the-art stuff in every domain. Yeah. Like, okay, you expect foundation models with Nemo tron voice just randomly parakeet.Call parakeet just comes out another one, uh, voice. TheKyle: video voice team has always been producing.Vibhu: Yeah. There's always just every other domain of paper that comes out, dataset that comes out. It's like, I mean, it also stems back to what Nvidia has to do, right? You have to make chips years before they're actually produced.Right? So you need to know, you need to really [00:22:00] focus. TheKyle: design process starts likeVibhu: exactlyKyle: three to five years before the chip gets to the market.Vibhu: Yeah. I, I'm curious more about what that's like, right? So like, you have specialist teams. Is it just like, you know, people find an interest, you go in, you go deep on whatever, and that kind of feeds back into, you know, okay, we, we expect predictions.Like the internals at Nvidia must be crazy. Right? You know? Yeah. Yeah. You know, you, you must. Not even without selling to people, you have your own predictions of where things are going. Yeah. And they're very based, very grounded. Right?Kyle: Yeah. It, it, it's really interesting. So there's like two things that I think that Amed does, which are quite interesting.Uh, one is like, we really index into passion. There's a big. Sort of organizational top sound push to like ensure that people are working on the things that they're passionate about. So if someone proposes something that's interesting, many times they can just email someone like way up the chain that they would find this relevant and say like, Hey, can I go work on this?Nader: It's actually like I worked at a, a big company for a couple years before, uh, starting on my startup journey and like, it felt very weird if you were to like email out of chain, if that makes [00:23:00] sense. Yeah. The emails at Nvidia are like mosh pitsswyx: shoot,Nader: and it's just like 60 people, just whatever. And like they're, there's this,swyx: they got messy like, reply all you,Nader: oh, it's in, it's insane.It's insane. They justKyle: help. You know, Maxim,Nader: the context. But, but that's actually like, I've actually, so this is a weird thing where I used to be like, why would we send emails? We have Slack. I am the entire, I'm the exact opposite. I feel so bad for anyone who's like messaging me on Slack ‘cause I'm so unresponsive.swyx: Your emailNader: Maxi, email Maxim. I'm email maxing Now email is a different, email is perfect because man, we can't work together. I'm email is great, right? Because important threads get bumped back up, right? Yeah, yeah. Um, and so Slack doesn't do that. So I just have like this casino going off on the right or on the left and like, I don't know which thread was from where or what, but like the threads get And then also just like the subject, so you can have like working threads.I think what's difficult is like when you're small, if you're just not 40,000 people I think Slack will work fine, but there's, I don't know what the inflection point is. There is gonna be a point where that becomes really messy and you'll actually prefer having email. ‘cause you can have working threads.You can cc more than nine people in a thread.Kyle: You can fork stuff.Nader: You can [00:24:00] fork stuff, which is super nice and just like y Yeah. And so, but that is part of where you can propose a plan. You can also just. Start, honestly, momentum's the only authority, right? So like, if you can just start, start to make a little bit of progress and show someone something, and then they can try it.That's, I think what's been, you know, I think the most effective way to push anything for forward. And that's both at Nvidia and I think just generally.Kyle: Yeah, there's, there's the other concept that like is explored a lot at Nvidia, which is this idea of a zero billion dollar business. Like market creation is a big thing at Nvidia.Like,swyx: oh, you want to go and start a zero billion dollar business?Kyle: Jensen says, we are completely happy investing in zero billion dollar markets. We don't care if this creates revenue. It's important for us to know about this market. We think it will be important in the future. It can be zero billion dollars for a while.I'm probably minging as words here for, but like, you know, like, I'll give an example. NVIDIA's been working on autonomous driving for a a long time,swyx: like an Nvidia car.Kyle: No, they, they'veVibhu: used the Mercedes, right? They're around the HQ and I think it finally just got licensed out. Now they're starting to be used quite a [00:25:00] bit.For 10 years you've been seeing Mercedes with Nvidia logos driving.Kyle: If you're in like the South San Santa Clara, it's, it's actually from South. Yeah. So, um. Zero billion dollar markets are, are a thing like, you know, Jensen,swyx: I mean, okay, look, cars are not a zero billion dollar market. But yeah, that's a bad example.Nader: I think, I think he's, he's messaging, uh, zero today, but, or even like internally, right? Like, like it's like, uh, an org doesn't have to ruthlessly find revenue very quickly to justify their existence. Right. Like a lot of the important research, a lot of the important technology being developed that, that's kind ofKyle: where research, research is very ide ideologically free at Nvidia.Yeah. Like they can pursue things that they wereswyx: Were you research officially?Kyle: I was never in research. Officially. I was always in engineering. Yeah. We in, I'm in an org called Deep Warning Algorithms, which is basically just how do we make things that are relevant to deep warning go fast.swyx: That sounds freaking cool.Vibhu: And I think a lot of that is underappreciated, right? Like time series. This week Google put out time. FF paper. Yeah. A new time series, paper res. Uh, Symantec, ID [00:26:00] started applying Transformers LMS to Yes. Rec system. Yes. And when you think the scale of companies deploying these right. Amazon recommendations, Google web search, it's like, it's huge scale andKyle: Yeah.Vibhu: You want fast?Kyle: Yeah. Yeah. Yeah. Actually it's, it, I, there's a fun moment that brought me like full circle. Like, uh, Amazon Ads recently gave a talk where they talked about using Dynamo for generative recommendation, which was like super, like weirdly cathartic for me. I'm like, oh my God. I've, I've supplanted what I was working on.Like, I, you're using LMS now to do what I was doing five years ago.swyx: Yeah. Amazing. And let's go right into Dynamo. Uh, maybe introduce Yeah, sure. To the top down and Yeah.Kyle: I think at this point a lot of people are familiar with the term of inference. Like funnily enough, like I went from, you know, inference being like a really niche topic to being something that's like discussed on like normal people's Twitter feeds.It's,Nader: it's on billboardsKyle: here now. Yeah. Very, very strange. Driving, driving, seeing just an inference ad on 1 0 1 inference at scale is becoming a lot more important. Uh, we have these moments like, you know, open claw where you have these [00:27:00] agents that take lots and lots of tokens, but produce, incredible results.There are many different aspects of test time scaling so that, you know, you can use more inference to generate a better result than if you were to use like a short amount of inference. There's reasoning, there's quiring, there's, adding agency to the model, allowing it to call tools and use skills.Dyno sort came about at Nvidia. Because myself and a couple others were, were sort of talking about the, these concepts that like, you know, you have inference engines like VLMS, shelan, tenor, TLM and they have like one single copy. They, they, they sort of think about like things as like one single copy, like one replica, right?Why Scale Out WinsKyle: Like one version of the model. But when you're actually serving things at scale, you can't just scale up that replica because you end up with like performance problems. There's a scaling limit to scaling up replicas. So you actually have to scale out to use a, maybe some Kubernetes type terminology.We kind of realized that there was like. A lot of potential optimization that we could do in scaling out and building systems for data [00:28:00] center scale inference. So Dynamo is this data center scale inference engine that sits on top of the frameworks like VLM Shilling and 10 T lm and just makes things go faster because you can leverage the economy of scale.The fact that you have KV cash, which we can define a little bit later, uh, in all these machines that is like unique and you wanna figure out like the ways to maximize your cash hits or you want to employ new techniques in inference like disaggregation, which Dynamo had introduced to the world in, in, in March, not introduced, it was a academic talk, but beforehand.But we are, you know, one of the first frameworks to start, supporting it. And we wanna like, sort of combine all these techniques into sort of a modular framework that allows you to. Accelerate your inference at scale.Nader: By the way, Kyle and I became friends on my first date, Nvidia, and I always loved, ‘cause like he always teaches meswyx: new things.Yeah. By the way, this is why I wanted to put two of you together. I was like, yeah, this is, this is gonna beKyle: good. It's very, it's very different, you know, like we've, we, we've, we've talked to each other a bunch [00:29:00] actually, you asked like, why, why can't we scale up?Nader: Yeah.Scale Up Limits ExplainedNader: model, you said model replicas.Kyle: Yeah. So you, so scale up means assigning moreswyx: heavier?Kyle: Yeah, heavier. Like making things heavier. Yeah, adding more GPUs. Adding more CPUs. Scale out is just like having a barrier saying, I'm gonna duplicate my representation of the model or a representation of this microservice or something, and I'm gonna like, replicate it Many times.Handle, load. And the reason that you can't scale, scale up, uh, past some points is like, you know, there, there, there are sort of hardware bounds and algorithmic bounds on, on that type of scaling. So I'll give you a good example that's like very trivial. Let's say you're on an H 100. The Maxim ENV link domain for H 100, for most Ds H one hundreds is heus, right?So if you scaled up past that, you're gonna have to figure out ways to handle the fact that now for the GPUs to communicate, you have to do it over Infin band, which is still very fast, but is not as fast as ENV link.swyx: Is it like one order of magnitude, like hundreds or,Kyle: it's about an order of magnitude?Yeah. Okay. Um, soswyx: not terrible.Kyle: [00:30:00] Yeah. I, I need to, I need to remember the, the data sheet here, like, I think it's like about 500 gigabytes. Uh, a second unidirectional for ENV link, and about 50 gigabytes a second unidirectional for Infin Band. I, it, it depends on the, the generation.swyx: I just wanna set this up for people who are not familiar with these kinds of like layers and the trash speedVibhu: and all that.Of course.From Laptop to Multi NodeVibhu: Also, maybe even just going like a few steps back before that, like most people are very familiar with. You see a, you know, you can use on your laptop, whatever these steel viol, lm you can just run inference there. All, there's all, you can, youcan run it on thatVibhu: laptop. You can run on laptop.Then you get to, okay, uh, models got pretty big, right? JLM five, they doubled the size, so mm-hmm. Uh, what do you do when you have to go from, okay, I can get 128 gigs of memory. I can run it on a spark. Then you have to go multi GPU. Yeah. Okay. Multi GPU, there's some support there. Now, if I'm a company and I don't have like.I'm not hiring the best researchers for this. Right. But I need to go [00:31:00] multi-node, right? I have a lot of servers. Okay, now there's efficiency problems, right? You can have multiple eight H 100 nodes, but, you know, is that as a, like, how do you do that efficiently?Kyle: Yeah. How do you like represent them? How do you choose how to represent the model?Yeah, exactly right. That's a, that's like a hard question. Everyone asks, how do you size oh, I wanna run GLM five, which just came out new model. There have been like four of them in the past week, by the way, like a bunch of new models.swyx: You know why? Right? Deep seek.Kyle: No comment. Oh. Yeah, but Ggl, LM five, right?We, we have this, new model. It's, it's like a large size, and you have to figure out how to both scale up and scale out, right? Because you have to find the right representation that you care about. Everyone does this differently. Let's be very clear. Everyone figures this out in their own path.Nader: I feel like a lot of AI or ML even is like, is like this. I think people think, you know, I, I was, there was some tweet a few months ago that was like, why hasn't fine tuning as a service taken off? You know, that might be me. It might have been you. Yeah. But people want it to be such an easy recipe to follow.But even like if you look at an ML model and specificKyle: to you Yeah,Nader: yeah.Kyle: And the [00:32:00] model,Nader: the situation, and there's just so much tinkering, right? Like when you see a model that has however many experts in the ME model, it's like, why that many experts? I don't, they, you know, they tried a bunch of things and that one seemed to do better.I think when it comes to how you're serving inference, you know, you have a bunch of decisions to make and there you can always argue that you can take something and make it more optimal. But I think it's this internal calibration and appetite for continued calibration.Vibhu: Yeah. And that doesn't mean like, you know, people aren't taking a shot at this, like tinker from thinking machines, you know?Yeah. RL as a service. Yeah, totally. It's, it also gets even harder when you try to do big model training, right? We're not the best at training Moes, uh, when they're pre-trained. Like we saw this with LAMA three, right? They're trained in such a sparse way that meta knows there's gonna be a bunch of inference done on these, right?They'll open source it, but it's very trained for what meta infrastructure wants, right? They wanna, they wanna inference it a lot. Now the question to basically think about is, okay, say you wanna serve a chat application, a coding copilot, right? You're doing a layer of rl, you're serving a model for X amount of people.Is it a chat model, a coding model? Dynamo, you know, back to that,Kyle: it's [00:33:00] like, yeah, sorry. So you we, we sort of like jumped off of, you know, jumped, uh, on that topic. Everyone has like, their own, own journey.Cost Quality Latency TradeoffsKyle: And I, I like to think of it as defined by like, what is the model you need? What is the accuracy you need?Actually I talked to NA about this earlier. There's three axes you care about. What is the quality that you're able to produce? So like, are you accurate enough or can you complete the task with enough, performance, high enough performance. Yeah, yeah. Uh, there's cost. Can you serve the model or serve your workflow?Because it's not just the model anymore, it's the workflow. It's the multi turn with an agent cheaply enough. And then can you serve it fast enough? And we're seeing all three of these, like, play out, like we saw, we saw new models from OpenAI that you know, are faster. You have like these new fast versions of models.You can change the amount of thinking to change the amount of quality, right? Produce more tokens, but at a higher cost in a, in a higher latency. And really like when you start this journey of like trying to figure out how you wanna host a model, you, you, you think about three things. What is the model I need to serve?How many times do I need to call it? What is the input sequence link was [00:34:00] the, what does the workflow look like on top of it? What is the SLA, what is the latency SLA that I need to achieve? Because there's usually some, this is usually like a constant, you, you know, the SLA that you need to hit and then like you try and find the lowest cost version that hits all of these constraints.Usually, you know, you, you start with those things and you say you, you kind of do like a bit of experimentation across some common configurations. You change the tensor parallel size, which is a form of parallelismVibhu: I take, it goes even deeper first. Gotta think what model.Kyle: Yes, course,ofKyle: course. It's like, it's like a multi-step design process because as you said, you can, you can choose a smaller model and then do more test time scaling and it'll equate the quality of a larger model because you're doing the test time scaling or you're adding a harness or something.So yes, it, it goes way deeper than that. But from the performance perspective, like once you get to the model you need, you need to host, you look at that and you say, Hey. I have this model, I need to serve it at the speed. What is the right configuration for that?Nader: You guys see the recent, uh, there was a paper I just saw like a few days ago that, uh, if you run [00:35:00] the same prompt twice, you're getting like double Just try itagain.Nader: Yeah, exactly.Vibhu: And you get a lot. Yeah. But the, the key thing there is you give the context of the failed try, right? Yeah. So it takes a shot. And this has been like, you know, basic guidance for quite a while. Just try again. ‘cause you know, trying, just try again. Did you try again? All adviceNader: in life.Vibhu: Just, it's a paper from Google, if I'm not mistaken, right?Yeah,Vibhu: yeah. I think it, it's like a seven bas little short paper. Yeah. Yeah. The title's very cute. And it's just like, yeah, just try again. Give it ask context,Kyle: multi-shot. You just like, say like, hey, like, you know, like take, take a little bit more, take a little bit more information, try and fail. Fail.Vibhu: And that basic concept has gone pretty deep.There's like, um, self distillation, rl where you, you do self distillation, you do rl and you have past failure and you know, that gives some signal so people take, try it again. Not strong enough.swyx: Uh, for, for listeners, uh, who listen to here, uh, vivo actually, and I, and we run a second YouTube channel for our paper club where, oh, that's awesome.Vivo just covered this. Yeah. Awesome. Self desolation and all that's, that's why he, to speed [00:36:00] on it.Nader: I'll to check it out.swyx: Yeah. It, it's just a good practice, like everyone needs, like a paper club where like you just read papers together and the social pressure just kind of forces you to just,Nader: we, we,there'sNader: like a big inference.Kyle: ReadingNader: group at a video. I feel so bad every time. I I, he put it on like, on our, he shared it.swyx: One, one ofNader: your guys,swyx: uh, is, is big in that, I forget es han Yeah, yeah,Kyle: es Han's on my team. Actually. Funny. There's a, there's a, there's a employee transfer between us. Han worked for Nater at Brev, and now he, he's on my team.He wasNader: our head of ai. And then, yeah, once we got in, andswyx: because I'm always looking for like, okay, can, can I start at another podcast that only does that thing? Yeah. And, uh, Esan was like, I was trying to like nudge Esan into like, is there something here? I mean, I don't think there's, there's new infant techniques every day.So it's like, it's likeKyle: you would, you would actually be surprised, um, the amount of blog posts you see. And ifswyx: there's a period where it was like, Medusa hydra, what Eagle, like, youKyle: know, now we have new forms of decode, uh, we have new forms of specula, of decoding or new,swyx: what,Kyle: what are youVibhu: excited? And it's exciting when you guys put out something like Tron.‘cause I remember the paper on this Tron three, [00:37:00] uh, the amount of like post train, the on tokens that the GPU rich can just train on. And it, it was a hybrid state space model, right? Yeah.Kyle: It's co-designed for the hardware.Vibhu: Yeah, go design for the hardware. And one of the things was always, you know, the state space models don't scale as well when you do a conversion or whatever the performance.And you guys are like, no, just keep draining. And Nitron shows a lot of that. Yeah.Nader: Also, something cool about Nitron it was released in layers, if you will, very similar to Dynamo. It's, it's, it's essentially it was released as you can, the pre-training, post-training data sets are released. Yeah. The recipes on how to do it are released.The model itself is released. It's full model. You just benefit from us turning on the GPUs. But there are companies like, uh, ServiceNow took the dataset and they trained their own model and we were super excited and like, you know, celebrated that work.ZoomVibhu: different. Zoom is, zoom is CGI, I think, uh, you know, also just to add like a lot of models don't put out based models and if there's that, why is fine tuning not taken off?You know, you can do your own training. Yeah,Kyle: sure.Vibhu: You guys put out based model, I think you put out everything.Nader: I believe I know [00:38:00]swyx: about base. BasicallyVibhu: without baseswyx: basic can be cancelable.Vibhu: Yeah. Base can be cancelable.swyx: Yeah.Vibhu: Safety training.swyx: Did we get a full picture of dymo? I, I don't know if we, what,Nader: what I'd love is you, you mentioned the three axes like break it down of like, you know, what's prefilled decode and like what are the optimizations that we can get with Dynamo?Kyle: Yeah. That, that's, that's, that's a great point. So to summarize on that three axis problem, right, there are three things that determine whether or not something can be done with inference, cost, quality, latency, right? Dynamo is supposed to be there to provide you like the runtime that allows you to pull levers to, you know, mix it up and move around the parade of frontier or the preto surface that determines is this actually possible with inference And AI todayNader: gives you the knobs.Kyle: Yeah, exactly. It gives you the knobs.Disaggregation Prefill vs DecodeKyle: Uh, and one thing that like we, we use a lot in contemporary inference and is, you know, starting to like pick up from, you know, in, in general knowledge is this co concept of disaggregation. So historically. Models would be hosted with a single inference engine. And that inference engine [00:39:00] would ping pong between two phases.There's prefill where you're reading the sequence generating KV cache, which is basically just a set of vectors that represent the sequence. And then using that KV cache to generate new tokens, which is called Decode. And some brilliant researchers across multiple different papers essentially made the realization that if you separate these two phases, you actually gain some benefits.Those benefits are basically a you don't have to worry about step synchronous scheduling. So the way that an inference engine works is you do one step and then you finish it, and then you schedule, you start scheduling the next step there. It's not like fully asynchronous. And the problem with that is you would have, uh, essentially pre-fill and decode are, are actually very different in terms of both their resource requirements and their sometimes their runtime.So you would have like prefill that would like block decode steps because you, you'd still be pre-filing and you couldn't schedule because you know the step has to end. So you remove that scheduling issue and then you also allow you, or you yourself, to like [00:40:00] split the work into two different ki types of pools.So pre-fill typically, and, and this changes as, as model architecture changes. Pre-fill is, right now, compute bound most of the time with the sequence is sufficiently long. It's compute bound. On the decode side because you're doing a full Passover, all the weights and the entire sequence, every time you do a decode step and you're, you don't have the quadratic computation of KV cache, it's usually memory bound because you're retrieving a linear amount of memory and you're doing a linear amount of compute as opposed to prefill where you retrieve a linear amount of memory and then use a quadratic.You know,Nader: it's funny, someone exo Labs did a really cool demo where for the DGX Spark, which has a lot more compute, you can do the pre the compute hungry prefill on a DG X spark and then do the decode on a, on a Mac. Yeah. And soVibhu: that's faster.Nader: Yeah. Yeah.Kyle: So you could, you can do that. You can do machine strat stratification.Nader: Yeah.Kyle: And like with our future generation generations of hardware, we actually announced, like with Reuben, this [00:41:00] new accelerator that is prefilled specific. It's called Reuben, CPX. SoKubernetes Scaling with GroveNader: I have a question when you do the scale out. Yeah. Is scaling out easier with Dynamo? Because when you need a new node, you can dedicate it to either the Prefill or, uh, decode.Kyle: Yeah. So Dynamo actually has like a, a Kubernetes component in it called Grove that allows you to, to do this like crazy scaling specialization. It has like this hot, it's a representation that, I don't wanna go too deep into Kubernetes here, but there was a previous way that you would like launch multi-node work.Uh, it's called Leader Worker Set. It's in the Kubernetes standard, and Leader worker set is great. It served a lot of people super well for a long period of time. But one of the things that it's struggles with is representing a set of cases where you have a multi-node replica that has a pair, right?You know, prefill and decode, or it's not paired, but it has like a second stage that has a ratio that changes over time. And prefill and decode are like two different things as your workload changes, right? The amount of prefill you'll need to do may change. [00:42:00] The amount of decode that you, you'll need to do might change, right?Like, let's say you start getting like insanely long queries, right? That probably means that your prefill scales like harder because you're hitting these, this quadratic scaling growth.swyx: Yeah.And then for listeners, like prefill will be long input. Decode would be long output, for example, right?Kyle: Yeah. So like decode, decode scale. I mean, decode is funny because the amount of tokens that you produce scales with the output length, but the amount of work that you do per step scales with the amount of tokens in the context.swyx: Yes.Kyle: So both scales with the input and the output.swyx: That's true.Kyle: But on the pre-fold view code side, like if.Suddenly, like the amount of work you're doing on the decode side stays about the same or like scales a little bit, and then the prefilled side like jumps up a lot. You actually don't want that ratio to be the same. You want it to change over time. So Dynamo has a set of components that A, tell you how to scale.It tells you how many prefilled workers and decoded workers you, it thinks you should have, and also provides a scheduling API for Kubernetes that allows you to actually represent and affect this scheduling on, on, on your actual [00:43:00] hardware, on your compute infrastructure.Nader: Not gonna lie. I feel a little embarrassed for being proud of my SVG function earlier.swyx: No, itNader: wasreallyKyle: cute. I, Iswyx: likeNader: it's all,swyx: it's all engineering. It's all engineering. Um, that's where I'mKyle: technical.swyx: One thing I'm, I'm kind of just curious about with all with you see at a systems level, everything going on here. Mm-hmm. And we, you know, we're scaling it up in, in multi, in distributed systems.Context Length and Co Designswyx: Um, I think one thing that's like kind of, of the moment right now is people are asking, is there any SOL sort of upper bounds. In terms of like, let's call, just call it context length for one for of a better word, but you can break it down however you like.Nader: Yeah.swyx: I just think like, well, yeah, I mean, like clearly you can engage in hybrid architectures and throw in some state space models in there.All, all you want, but it looks, still looks very attention heavy.Kyle: Yes. Uh, yeah. Long context is attention heavy. I mean, we have these hybrid models, um,swyx: to take and most, most models like cap out at a million contexts and that's it. Yeah. Like for the last two years has been it.Kyle: Yeah. The model hardware context co-design thing that we're seeing these days is actually super [00:44:00] interesting.It's like my, my passion, like my secret side passion. We see models like Kimmy or G-P-T-O-S-S. I'm use these because I, I know specific things about these models. So Kimmy two comes out, right? And it's an interesting model. It's like, like a deep seek style architecture is MLA. It's basically deep seek, scaled like a little bit differently, um, and obviously trained differently as well.But they, they talked about, why they made the design choices for context. Kimmy has more experts, but fewer attention heads, and I believe a slightly smaller attention, uh, like dimension. But I need to remember, I need to check that. Uh, it doesn't matter. But they discussed this actually at length in a blog post on ji, which is like our pu which is like credit puswyx: Yeah.Kyle: Um, in, in China. Chinese red.swyx: Yeah.Kyle: It's, yeah. So it, it's, it's actually an incredible blog post. Uh, like all the mls people in, in, in that, I've seen that on GPU are like very brilliant, but they, they talk about like the creators of Kimi K two [00:45:00] actually like, talked about it on, on, on there in the blog post.And they say, we, we actually did an experiment, right? Attention scales with the number of heads, obviously. Like if you have 64 heads versus 32 heads, you do half the work of attention. You still scale quadratic, but you do half the work. And they made a, a very specific like. Sort of barter in their system, in their architecture, they basically said, Hey, what if we gave it more experts, so we're gonna use more memory capacity.But we keep the amount of activated experts the same. We increase the expert sparsity, so we have fewer experts act. The ratio to of experts activated to number of experts is smaller, and we decrease the number of attention heads.Vibhu: And kind of for context, what the, what we had been seeing was you make models sparser instead.So no one was really touching heads. You're just having, uh,Kyle: well, they, they did, they implicitly made it sparser.Vibhu: Yeah, yeah. For, for Kimmy. They did,Kyle: yes.Vibhu: They also made it sparser. But basically what we were seeing was people were at the level of, okay, there's a sparsity ratio. You want more total parameters, less active, and that's sparsity.[00:46:00]But what you see from papers, like, the labs like moonshot deep seek, they go to the level of, okay, outside of just number of experts, you can also change how many attention heads and less attention layers. More attention. Layers. Layers, yeah. Yes, yes. So, and that's all basically coming back to, just tied together is like hardware model, co-design, which isKyle: hardware model, co model, context, co-design.Vibhu: Yeah.Kyle: Right. Like if you were training a, a model that was like. Really, really short context, uh, or like really is good at super short context tasks. You may like design it in a way such that like you don't care about attention scaling because it hasn't hit that, like the turning point where like the quadratic curve takes over.Nader: How do you consider attention or context as a separate part of the co-design? Like I would imagine hardware or just how I would've thought of it is like hardware model. Co-design would be hardware model context co-designKyle: because the harness and the context that is produced by the harness is a part of the model.Once it's trained in,Vibhu: like even though towards the end you'll do long context, you're not changing architecture through I see. Training. Yeah.Kyle: I mean you can try.swyx: You're saying [00:47:00] everyone's training the harness into the model.Kyle: I would say to some degree, orswyx: there's co-design for harness. I know there's a small amount, but I feel like not everyone has like gone full send on this.Kyle: I think, I think I think it's important to internalize the harness that you think the model will be running. Running into the model.swyx: Yeah. Interesting. Okay. Bash is like the universal harness,Kyle: right? Like I'll, I'll give. An example here, right? I mean, or just like a, like a, it's easy proof, right? If you can train against a harness and you're using that harness for everything, wouldn't you just train with the harness to ensure that you get the best possible quality out of,swyx: Well, the, uh, I, I can provide a counter argument.Yeah, sure. Which is what you wanna provide a generally useful model for other people to plug into their harnesses, right? So if youKyle: Yeah. Harnesses can be open, open source, right?swyx: Yeah. So I mean, that's, that's effectively what's happening with Codex.Kyle: Yeah.swyx: And, but like you may want like a different search tool and then you may have to name it differently or,Nader: I don't know how much people have pushed on this, but can you.Train a model, would it be, have you have people compared training a model for the for the harness versus [00:48:00] like post training forswyx: I think it's the same thing. It's the same thing. It's okay. Just extra post training. INader: see.swyx: And so, I mean, cognition does this course, it does this where you, you just have to like, if your tool is slightly different, um, either force your tool to be like the tool that they train for.Hmm. Or undo their training for their tool and then Oh, that's re retrain. Yeah. It's, it's really annoying and like,Kyle: I would hope that eventually we hit like a certain level of generality with respect to training newswyx: tools. This is not a GI like, it's, this is a really stupid like. Learn my tool b***h.Like, I don't know if, I don't know if I can say that, but like, you know, um, I think what my point kind of is, is that there's, like, I look at slopes of the scaling laws and like, this slope is not working, man. We, we are at a million token con

In this episode of the Oncology Brothers podcast, we discussed two challenging cases focused on Acute Myeloid Leukemia (AML). We welcomed Dr. Naval Daver, a leading expert from MD Anderson Cancer Center, to discuss: therapy-related AML and de novo AML where induction chemotherapy is not an option. Episode Highlights: • Overview of therapy-related AML and its increasing prevalence due to advancements in solid tumor treatments. • In-depth discussion on the prognosis and treatment options for patients with complex cytogenetics. • Comparison of induction treatments: CPX-351 vs. the traditional 7 + 3 regimen, including survival rates and side effects. • Insights into the use of hypomethylating agents combined with venetoclax for older patients with AML, particularly those with NPM1 mutations. • Practical considerations for administering these treatments in both inpatient and outpatient settings. Whether you're a healthcare professional or simply interested in the latest advancements in oncology, this episode provides valuable insights into the complexities of AML management. Follow us on social media: •⁠  ⁠X/Twitter: https://twitter.com/oncbrothers •⁠  ⁠Instagram: https://www.instagram.com/oncbrothers •⁠  Website: https://oncbrothers.com/ Don't forget to subscribe for more discussions on treatment algorithms, conference highlights, and the latest FDA approvals! #AcuteMyeloidLeukemia, #TherapyRelatedAML, #DeNovoAML, #TransplantIneligible, #OncologyBrothers

In this episode of Energy Talks, we take a more detailed look at power system testing device software. OMICRON product manager Lukas Klingenschmid talks about the critical role of software innovation in maximizing the potential of testing devices and enhancing user experience. More specifically, Lukas describes how new innovative software features in OMICRON's CPXpert software for its new CPX 200 testing device substantially optimize ease of use, data handling and decision-making.

True-Ecumenism vs. False Ecumenism from a Traditional Catholic Priest describing different views of the Eastern Orthodox. -CPX 33: https://youtu.be/600fkzBHdBc?si=q436jSgCTzFIce8Y -Filioque: https://padreperegrino.substack.com/p/the-filioque-in-the-eastern-fathers?r=nz485

The next-generation power system testing solutions, such as OMICRON's new CPX 200, are really ecosystems made up of interrelated parts the work together to highly optimize the testing experience for users. In this episode of Energy Talks, we take a more detailed look at one of these parts – testing device modularity. OMICRON product manager Jakob Hämmerle talks about the innovative modularity features of the new OMICRON CPX 200 power system testing device. He describes how device modularity greatly enhances flexibility and efficiency in power system testing and enables users to adapt to their evolving power system testing needs.

In today's episode, we had the pleasure of speaking with Eunice Wang, MD, about the secondary AML treatment paradigm. Dr Wang is a professor of oncology, leader of the Leukemia Clinical Disease Team, chief of leukemia in the Department of Medicine, and an assistant member of the Tumor Immunology Program in the Department of Immunology at Roswell Park Comprehensive Cancer Center in Buffalo, New York; as well as an associate professor in the Department of Medicine and an academic scholar at the Jacobs School of Medicine and Biomedical Sciences at the State University of New York at Buffalo. In our exclusive interview, Dr Wang discussed the prevalence of secondary AML, and explained that this population lacks standard therapies, often relying on allogeneic stem cell transplantation. She noted that CPX-351, a liposomal formulation of cytarabine and daunorubicin, has generated improved outcomes compared with 7+3 chemotherapy in this population. She also highlighted future research, which includes targeted therapies and less intensive regimens.

In this episode of Energy Talks, OMICRON product manager Michael Rädler introduces the new OMICRON CPX 200, which sets new standards in power system testing. Michael describes how this next-generation multifunctional testing technology was the result of intensive user interaction and an ecosystem approach to product development. Michael highlights the innovative CPX 200 features in the areas of hardware, modularity, performance, software, safety and data analysis and how these take power system testing to a higher level to meet user requirements today and beyond.

Podcast: Simply ICS CyberEpisode: S2 E5: Evolving Vendor and Integrator Cybersecurity in ICS/OTPub date: 2025-10-08Get Podcast Transcript →powered by Listen411 - fast audio-to-text and summarizationSelecting and managing ICS/OT cybersecurity vendors and integrators isn't just a procurement step - it's a strategic decision that shapes resilience, compliance, and long-term security outcomes. The best approach depends on organization size, resources, and security objectives.In this episode, Don and Tom are joined by Saltanat Mashirova, OT Cybersecurity Lead at CPX and OTCEP member with the Cyber Security Agency of Singapore. Salt brings deep global expertise across cybersecurity risk assessments (csHAZOP), ISA/IEC 62443 compliance, OT/ICS product development, governance, training, and the integration of both brownfield and greenfield assets.They'll also dive into how these challenges play out in industries like oil & gas, mining, energy, manufacturing, and more - where vendor and integrator choices can directly impact both safety and business outcomes.Salt shares her perspective as an industry-recognized leader, speaker, and award-winner (Top 40 Under 40 in Cybersecurity, SC Media “Women to Watch,” and more), with experience guiding global projects and engaging with everyone from engineers to CEOs.

Simon and Dan return with the second half of their deep dive into 50 Ways to Invest in the AI Revolution. While Part 1 covered the obvious giants—semiconductors, hyperscalers, pure-play AI software, enterprise apps, and data center REITs—this episode looks at some of the less obvious but equally important beneficiaries of AI. From utilities and grid infrastructure to commodities like uranium, copper, and natural gas, they explore the backbone powering AI’s massive energy demand. They also dig into healthcare, cybersecurity, IT consulting, and industrial automation—sectors where AI is already improving efficiency, margins, and innovation in ways most investors overlook. Once again, they highlight dozens of companies and ETFs across these subsectors, balancing both the opportunities and the risks. If you’re wondering how to get diversified AI exposure beyond the usual suspects like NVDA and MSFT, this episode is packed with fresh angles and ticker ideas. Tickers discussed: Utilities & infrastructure: NEE, CNP, D, CPX.TO, BEPC, BIP.UN.TO, PWR, MTZ, SU, ENB Commodities & energy: TECK.B.TO, TOU.TO, URA, U.UN.TO, UNG, ZEO.TO, BCIM Healthcare: GEHC, SMMNY, PFE, ISRG, WELL.TO, ZHQ.TO Cybersecurity: CRWD, PANW, HAK, CYBR.TOConsulting & IT services: ACN, IBM, INFY Industrial automation: ROK, ABB, PNG.V Check out our portfolio by going to Jointci.com Our Website Our New Youtube Channel! Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor Spotify - The Canadian Real Estate Investor Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense. See omnystudio.com/listener for privacy information.

欢迎收听雪球出品的财经有深度，雪球，国内领先的集投资交流交易一体的综合财富管理平台，聪明的投资者都在这里。今天分享的内容叫英伟达的护城河，来自古董鱼。看了一晚上英伟达的护城河，强行洗脑，最后的结论是英伟达不倒，我不撤退，一直AI下去。如果哪天英伟达被颠覆了，别问我还能不能拿，因为那时候我已经跑了。大家都以为英伟达的硬件强，其实它的隐形护城河是计算平台和编程模型加网络。我们来看看英伟达的先发优势与成熟度：他的计算平台和编程模型于 2007 年推出，经过近 20 年的发展，已成为 G P U 计算的行业标准。它积累了超过 400 万开发者，形成了庞大的社区和网络效应。从英伟达的全栈优化与工具链来看，计算平台和编程模型提供了从编译器、调试器到高度优化的核心库的全套工具。这些库经过英伟达的深度优化，能充分发挥其硬件性能，开发者无需编写底层代码即可获得顶尖性能。再从开发习惯与迁移成本来看，计算平台和编程模型广泛纳入大学课程和培训项目，工程师们从小白阶段就开始接触它。企业积累了大量的 CUDA 代码和专业知识，切换到其他平台需要重写代码、重新培训员工，并面临性能不确定的风险，这种切换成本高得难以想象。这种计算平台和编程模型的关键优势之一是，随着时间的推移，它通过新的软件更新不断改进硬件。刚刚对在H100和新的Blackwell GB200 NVL72这两种版本的芯片上运行AI训练进行了基准比较，结果表明了为什么计算平台和编程模型及其软件随着时间的推移的改进如此重要。最新，CoreWeave公司给出的数据，对 NVIDIA GB300 NVL72，进行了基准测试，其每 4x的 G P U 的单位时间内跑AI的速度比16x的H100高6倍，最初可不是这个比值，通过英伟达的计算平台和编程模型的不断优化，最后达到了这个高性能。其实一直有用CUDA转换器的，然而，用过转换器的，他们以大约80%的速度转换CUDA代码，而剩下的20%必须由内核工程师手动完成，这样成本并不便宜。同样有趣的是，虽然其他公司正在结成联盟，为Nv的全栈部分建立替代方案，但是目前没有一个与英伟达竞争的联盟出现。接着是英伟达网络的护城河。关于网络，通常说纵向扩展和横向扩展这两个部分，最近火的scale across先不提了。纵向扩展指的是机架里的 G P U 能够相互连接，形成单个 G P U 节点，并使其尽可能强大。然后，横向扩展网络使这些 G P U 节点能够连接到其他 G P U 节点，并共同形成一个大型 G P U 集群，使用其专有的 N V Link和 N V switches横向扩展时，他们使用从Mellanox收购中获得InfiniBand或以太网作为次要选项。英伟达的其他对手一起搞了个 U A link联盟，它的成员包含了能想到的其他公司。U A link有 A M D 、亚马逊、谷歌、英特尔、Meta、微软、思科、苹果、Astera Labs等公司组成。但它对 A M D 来说很重要，因为与英伟达相比，其最大的缺点之一是网络。网络不仅对培训人工智能工作负载很重要，而且对推理也很重要。随着推理模型的推论变得更加复杂，拥有良好的放大和缩小是关键。同时，为了解决这一挑战，他们希望支持所有可用的替代方案。这就是为什么他们有灵活的输入输出通道。这些灵活的输入输出通道使A M D能够支持不同的标准。虽然 U A Link还很年轻，但它已经遇到了很大的挫折。起初，博通是参与的关键公司之一，但后来退了。这是一个重大的挫折，因为 A M D 现在必须依靠AsteraLabs和Marvell来生产 U A Link联盟的交换机，而 U A Link交换机要到2027年才能准备就绪。这就是为什么我们可以看到，虽然 A M D 的MI400x显卡有 U A Link Serdes，但它并没有构成一个完整的扩展网络。不过，英伟达不仅仅是在关注这一发展，因为在UALink 1.0发布一个月后，他们宣布了NVLink Fusion，从纸面上看，它打开了NVLink生态系统。这对英伟达来说是一大步，因为一位前英伟达高级员工解释说，在内部实施这一步骤是多么具有挑战性，因为Meta想在他在那里工作时将 N V Links用于他们的MTIA，而英伟达的回答是坚定的“不”。NVLink 技术模块是用英伟达自家独有的方式和芯片传递数据的，其中一部分技术至今还是英伟达独有的。有了这套技术，英伟达只能让客户用他们的芯片间连接技术。现在客户也意识到了这一点，就像那位前英伟达员工提到的，他们担心这样一来，就算自己有定制的专用芯片ASIC，也会进一步被绑在英伟达的生态系统里 ，所以 U A Link到现在依旧是个替代选择。英伟达和 U A Link这边，有个关键角色是 Astera Labs公司 —— 毕竟现在博通已经自己单干、走自己的技术路线了。现在 U A Link联盟得靠 Astera Labs 来提供交换机。英伟达很清楚Astera Labs现在是 U A Link联盟里的核心部分，可能会想办法促使Astera Labs订购更多英伟达的 NVLink Fusion；而一旦Astera Labs用了NVLink Fusion，他们能为 U A Link服务的能力就会受限，至于这么做最终能不能帮到英伟达，还得靠时间来验证。在横向扩展方面，英伟达的InfiniBand网络技术，有个替代方案是支持远程直接内存访问的以太网。英伟达也支持这个替代方案，但只把它当作“次要选项”，英伟达甚至还有个 Spectrum X 以太网平台，因为他们通过收购，拿到了Spectrum系列交换机的技术和产能。很多大型科技公司也支持以太网，原因很实在：它成本更低，早就广泛用在数据中心里，而且有多家供应商可选。现在支持 RDMA 的以太网已经获得了不少采用度，因为大型科技公司和Meta这类企业，都愿意用它来减少对英伟达的依赖。不过，此前我们虽已探讨过纵向扩展和横向扩展软件与网络这两个核心层面，但还有一个新的关键层面才刚刚兴起，那就是HBM，高带宽内存。作为人工智能加速器的核心组件之一，HBM的重要性会随着AI模型向更大规模、更复杂结构发展，而愈发凸显。目前，海力士与美光是 HBM3 内存的主要供应商，不过三星预计也将完成相关认证流程，加入 HBM3 的供应体系。当向HBM4内存过渡时，将迎来一项关键变革：HBM4 的基础芯片晶圆需采用先进的逻辑芯片制造工艺。这意味着海力士与美光无法独立完成，必须将制造环节外包给台积电；同时，这些内存厂商还需与逻辑芯片设计公司或技术授权商展开合作，方能完成它的设计工作。这一变革为 “定制化 HBM 内存方案” 创造了空间，但反过来也意味着，HBM4的利润需与台积电共享一部分 —— 毕竟其制造环节高度依赖台积电。此外，HBM4 的复杂度远高于HBM3，需将内存厂商的芯片堆叠技术与代工厂的先进制造工艺相结合，这种局面实际上对英伟达更为有利，因为英伟达此前已计划自主设计HBM4的 3 纳米芯片裸片。事实上，我并不担心专用芯片ASIC会侵占过多市场份额。多数云服务提供商选择自主研发芯片，主要源于英伟达的市场垄断与显卡产能不足 —— 这实属无奈之举，他们为了更快获取可用算力，才不得不走上自主研发之路。此次英伟达发布的 Rubin 系列 CPX 产品，核心目标便是提升 AI 的上下文推理能力。在我看来，推理领域真正的领先者，并非 ASIC 这类专用推理芯片，仍属英伟达的产品。另有一项关键问题不容忽视：数据中心可使用的电力存在限制，尤其在北美地区，电力更是必须重视的硬性约束。为何 X AI 公司能在 122 天内建成全球规模最大的算力中心？一方面，马斯克拥有全球顶尖的工程团队与执行能力；更重要的是，X AI所能获得的供电支持，在全球范围内也处于顶尖水平。当你运营现有数据中心，或计划新建数据中心时，需与电力公司合作确定固定的电力使用额度，而这一额度具有明确上限 —— 你无法随意致电电力公司，提出 “需额外增加 10% 电力” 的需求。若我们对比英伟达当前一代与下一代服务器，那么在评估H100与GB300服务器时，核心衡量标准应是 “处理同等数量的令牌时，可节省多少电力”。而英伟达每次产品更新，实际上都在推进这项电力效率优化工作。所以，我想说的是英伟达的手里牌很多，老黄这个人能力强的可怕，就算现在出来ASIC和其他 G P U 竞争对手，都是更多跟随和模仿，对所有在供应链做硬件的公司都是利好，因为总的需求变多了，可以说遍地开花。

In this episode, Ben Bajarin and Jay Goldberg discuss the recent Apple iPhone launch event, highlighting the innovations in the iPhone Air and Apple's semiconductor strategy. They delve into Synopsys's disappointing earnings report and the subsequent market reactions, as well as Broadcom's position in the semiconductor landscape. The conversation also covers Nvidia's new CPX system and the implications for the market, concluding with a discussion on the funding of the AI boom and the financial strategies of major players like Oracle and OpenAI.

Send us a textToday we welcome Max Jeganathan as he discusses his book 'The Freedom Trap', exploring the concept of freedom in relation to everyday decision-making. He distinguishes between freedom and autonomy, emphasizing the importance of understanding their differences. The discussion delves into historical perspectives on freedom, the Christian viewpoint on autonomy, and the various traps associated with freedom, including being trapped by choice, consequences, success, and technology. The conversation highlights the need for responsibility in exercising freedom and the impact of societal expectations on individual choices.You can purchase The Freedom Trap at all major Christian book stores.You can find Max over on instagram https://www.instagram.com/primaxjeg/or at CPX https://publicchristianity.org/about/meet-our-speakers/Follow @hertheology on Instagram & YouTube. Head to hertheology.com to find out more.

The Moose on The Loose helps Canadians to invest with more conviction so they can enjoy their retirement. Today we are taking a look at how to build a portfolio with 4%+ yield: T. CTC.A. PEP CNQ, EPD, CVX, ENB or TRP CM, GWO, SLF, TD LIF CRT, VICI, O, GRT BEP, BIP, EMA (or CPX) more risky: MG, GIS, MO, TGT, ARE Get your Investment roadmap: https://dividendstocksrock.com/roadmap Download the Rockstar list here: https://moosemarkets.com/rockstars Join the Retirement Loop waitlist here: https://www.retirementloop.ca Why I prefer low yield vs high yield: https://moosemarkets.com/income

The Moose on The Loose helps Canadians to invest with more conviction so they can enjoy their retirement. 5 easy steps to clean your portfolio: https://moosemarkets.com/webinar Download the Rockstar list here: https://moosemarkets.com/rockstars Join the Retirement Loop waitlist here: https://www.retirementloop.ca Why I prefer low yield vs high yield: https://moosemarkets.com/income Companies mentioned in this episode: TFII.TO, HPS.A.TO, CPX.TO, CCO.TO, ADEN.TO, JWEL.TO, CNQ.TO, NA.TO

A talk given by Morten Sørensen on Network Segmentation at CPX 2025 in Vienna.

Episode 22: 2 April 2025Simon Smart talks to Max Jeganathan about his new book - the the latest in the Re:Considering series from CPX and Acorn Press.Check out the Re:Considering websiteOrder the book from Koorong or AmazonInstagram: Check out Max and Simon on Instagram at @primaxjeg and @simonsmartcpxProducer: Allan Dowthwaite

Newly diagnosed acute myeloid leukemia (AML) is traditionally treated with intensive chemotherapy for eligible patients, but ongoing research is exploring... The post Approaches to optimizing induction therapy in AML: FLT3 inhibitors, menin inhibitors, CPX-351, & more! appeared first on VJHemOnc.

An excerpt from a session with Danny Jung, Cyber Security Evangelist at SITS Group at CPX 2025 Vienna: Maestro for Everyone!

I talk about the highlights from CPX 2025 and include a mention to our upcoming Be Your Own TAC Part Deux session for EMEA and Americas on 27 March 2025!

What does the Christmas promise of “peace on earth” mean in the face of human suffering, natural disasters, and other heartbreaks that are part of all our lives?Twenty years ago, the Indian Ocean tsunami claimed the lives of some 225,000 people, after battering the coastlines of India, Indonesia, Malysia, the Maldives, Myanmar, Sri Lanka, Seychelles, Thailand, and Somalia.Tim Costello, then CEO of World Vision, was among the first to be on the ground in Sri Lanka, which was among the countries worst affected. He recounts being confronted with the mammoth scale of devastation on the ground and the tragedy of so many lives lost. Then we hear from former CPX-er Mark Stephens, now Lecturer in New Testament at Sydney Missionary Bible College, about what the Christmas promise of “peace on earth” could possibly mean in the face of untold human suffering – and what are the grounds of hope now and into the future.This is our last episode of Life & Faith for the year but we will be back in 2025. From the whole team at CPX, we wish you a Merry Christmas.

This week on the php podcast, Eric and John talk about Lazy Object in PHP 8.4, php[tek] 2025 first round of speaker selection is done, PHP Architect is now on Bluesky (@phparch.com), join the PHP Architect Squad on daily.dev. CPX, Security issues with RCS, and more… Links from the show: PHP: Lazy Objects – Manual […] The post php[podcast] 2024.12.5: Tek(nically) Speaking appeared first on php[architect].

Tim Winton talks to Life & Faith about his new novel Juice.Tim Winton is one of Australia's most loved writers. He is also well-known as an environmental activist and defender of landscapes and fragile ecosystems. And now, as a grandfather to 6 children, he is clearly deeply concerned about what we might be leaving behind to them and those who come after them.His lates novel, Juice, is set in the distant future, a time when climate catastrophe has wreaked havoc on the globe. Civilisation has crumbled. Huge parts of the earth, in a band emanating from the equator, are completely uninhabitable. It's all about the global unravelling that could accompany climate devastation. It's frightening and sobering. And yet somehow determinedly hopeful.Tim came into the CPX studio to talk about Juice and what inspired this challenging piece of art. Explore:Tim Winton's novel Juice Ningaloo NyingguluSimon Smart's review of Juice at ABC Religion & EthicsTell us what you think of Life & Faith in this 5-minute survey

Life & Faith producer, Allan Dowthwaite, takes over the studio to mark 500 episodes of amazing conversations.Allan Dowthwaite, CPX's media director, normally runs the recording studio for the team. But in this special episode, marking twelve-and-a-half years of the podcast, he's commandeered the mic as your personal guide to Life & Faith's greatest conversations, organised into the following categories for your listening pleasure.Links are included to any episode you want to listen to in full.The cultural waters in which we swim, featuring Sydney Morning Herald Economics Editor Ross Gittins, political scientist Dale Kuehne, New York Times film writer Alissa Wilkinson, cultural critic Andy Crouch, and author Tim Winton.How Christianity explains our world, featuring cold case detective Jim Warner Wallace, author Marilynne Robinson, author Francis Spufford, and historian Tom Holland.Surprising stories, featuring Oxford mathematician John Lennox, Alex Gaffikin, who wintered on Antarctica for two years, Johnnie Walker, beloved authority on the Camino de Santiago, and the late scholar of African-American religion, Albert J. Raboteau.Indigenous Australians, featuring Yorta Yorta man William Cooper, Torres Strait Islander leader and pastor Gabriel Bani, and Aunty Maureen Atkinson, member of the Stolen Generation.Changing one's mind about faith, featuring ABC Religion & Ethics editor Scott Stephens and author Susannah McFarlane.Ordinary people, extraordinary acts, featuring Australian nurse Valerie...

Summer rhymes with more time outside, pool parties or sunset walks, but it's actually a good time to benefit from the opportunities on the market while it's a little more quiet. Interested in CWB.TO, STN.TO, TIH.TO, CPX.TO, or DOL.TO? Dive in with us! Download the Dividend Income for Life Guide. Make sure to check out the complete show notes. Twitter: @TheDividendGuy FB: http://bit.ly/2Z7Q5gF YouTube: http://bit.ly/2Zs6r1r DividendStocksRock.com

Bill Bennett, director of the film The Way, My Way and Camino legend Johnnie Walker Santiago reflect on the spiritual riches of going on pilgrimage. “I see this walk as an 800km long cathedral”. So says Australian filmmaker Bill Bennett in the film The Way, My Way, which depicts Bill's experiences walking the Camino de Santiago.The Camino de Santiago, or the Way of St James, is a network of pilgrimage roads and paths running through Spain, France, and Portugal, leading to the cathedral at Santiago de Compostela in Galicia in north-western Spain, long believed to be the burial place of the Apostle James.The Camino has been an oft-travelled pilgrimage route since medieval times. These days, plenty of spiritual seekers like Bill, and others looking for connection and adventure, become modern-day pilgrims, driven to discover deeper truths about life along the way.This episode of Life & Faith interviews Bill Bennett, the director of The Way, My Way as well as Johnnie Walker Santiago, a beloved expert and authority on the Camino de Santiago. ---Explore:Trailer for The Way, My Way The book Bill Bennett wrote, upon which the film is based: The Way, My Way: A Camino memoir Johnnie Walker Santiago's guidebooks: Camino to Santiago: A spiritual companion and It's About Time: A call to the Camino de Santiago Check out CPX's new podcast, The Week @ CPX

This dreaded disease seems to strip away everything that makes us, well, us. A chaplain and a psychiatrist remind us of the human at the centre of the diagnosis.---The ‘d' word – dementia – is one that everyone fears. It seems to strip away everything that made that person with the disease the person we once knew. It's easy to lose sight of the person, the human at the centre of the diagnosis.Today, 420,000 Australians live with dementia, a number projected to double in the next 30 years, which makes it a significant and growing health challenge for Australia's ageing population.This episode of Life & Faith brings you two conversations that bring the human at the centre of the dementia diagnosis back into focus. We're featuring two interviews Natasha Moore did before going on maternity leave: with Neil Jeyasingam, Clinical Associate Professor of Psychiatry at the University of Sydney. Neil is also a CPX Associate. Natasha also spoke to Ben Boland, a chaplain with 15 years' experience in residential aged care – and whose father lives with dementia. Explore:Dementia Australia, the national peak body representing people with dementia, their families, and carers. Check out CPX's new podcast, The Week At CPX, to keep up-to-date with everything that's happening at CPX, plus a bit of commentary on the side.

Mercy Aiken tells Life & Faith of the joy-filled, yet painful life of Palestinian Christian, Bishara Awad.Bishara was a child in Jerusalem when his father was shot and killed during the Israeli-Arab war of 1948. The story of his life and that of his family provides a sobering portrait of life in Israel/Palestine during decades of war, violence, tension and dashed dreams for those seeking a peaceful resolution to conflict.Somehow, Bishara, a Palestinian Christian and community leader, remains unbowed, but also forgiving and empathetic towards his opponents. His story is told in the book, Yet in the Dark Streets Shining – a Palestinian Story of Hope and Resilience in Bethlehem. The coauthor of the book is Mercy Aiken – who came into the CPX studio. Mercy was in Australia with the Palestine Israel Ecumenical Network.The book: Yet in the Dark Streets Shining – a Palestinian Story of Hope and Resilience in BethlehemPalestine Israel Ecumenical Network

In this week's episode, we'll discuss gut microbiota exploitation by CPX-351 in acute myeloid leukemia. Then we'll learn about optimizing anti-myeloma immunity. New research shows that regulatory T cells suppress myeloma-specific immunity during autologous stem cell mobilization and transplantation. Finally we'll discuss among pediatric patients with ITP or other autoimmune cytopenias, which ones will go on to develop systemic lupus? Featured Articles: CPX-351 exploits the gut microbiota to promote mucosal barrier function, colonization resistance, and immune homeostasisRegulatory T cells suppress myeloma-specific immunity during autologous stem cell mobilization and transplantationAntinuclear antibody–associated autoimmune cytopenia in childhood is a risk factor for systemic lupus erythematosus

A brief overview of the product announcements made at CPX 2024. The materials are available on CheckMates: https://community.checkpoint.com/t5/General-Topics/CPX-2024/m-p/208174#M34494 

Asuntha Charles has lived in some toughest places in the world. And she's loved it.     Long    As a young woman, Asuntha Charles stubbornly defied her culture to advocate for vulnerable women and girls. That determination never left her as she dedicated her life to voiceless people in not only her native India, but places like Afghanistan, Bangladesh, Sudan and Iraq. Here she tells Life & Faith about her extraordinary life of service and care for people who needed that care most. And we also get an insight into the early influences that shaped her life and contributed to her holding a faith that sustains her even in the face of risk, and heartbreaking losses. Try listening to this and not be challenged and inspired! --- Sign up for the CPX newsletter here 

War correspondent Janine di Giovanni has covered the near-extinction of the ancient Christian communities of the Middle East.   ---  “They've survived plagues, they've survived pillages, they've survived raids, they've survived purges – and they most recently survived ISIS.”   The Christian communities of the Middle East – in places like Iraq and Syria, Egypt and Palestine – are ancient, and over recent decades have been facing various kinds of existential threat. Janine di Giovanni's book The Vanishing: The Twilight of Christianity in the Middle East is a work of “pre-archaeology”, recording the stories and courage of these communities even as they disappear.   Di Giovanni is a war correspondent and human rights investigator who has covered 18 wars and 3 genocides across her career, bearing witness to the terrible things that happen in our world. In this episode, she talks about visiting churches in war zones, why people stay, and whether faith – including her own belief in God – is strong enough to survive war. She also shares a bit about her current work with The Reckoning Project, a war crimes unit working within Ukraine.   “It's been an honour to work for 35 years in all these war zones with these extraordinary people. I feel very privileged and lucky every day of my life that I do this work, because … I have a purposeful life.”  ---  EXPLORE:  The Vanishing: The Twilight of Christianity in the Middle East, by Janine di Giovanni  The Reckoning Project  Sign up for the CPX newsletter here 

CPX writers talk about how they're hoping to breathe new life into a very old story.   ---  Get a glimpse into the CPX writers' room as Simon, Natasha, Justine and Max talk about what they're writing about Easter, or how they go about working out how to write about Easter.   Natasha talks about American novelist Marilynne Robinson's new book Reading Genesis and how Robinson's courteous and unapologetic way of doing “public Christianity” messes with how public conversations about God usually happen.   Max discusses how we may admire heroes for their greatness – like Homer's Achilles, for example – but we really long for goodness, expressed by saviours who willingly sacrifice themselves for others.  Simon discusses how a quirk of the calendar can put Anzac Day and Easter in proximity to each other, bringing those two events and their focus on sacrifice into conversation.   Justine talks about death denial among the tech titans of Silicon Valley who hope to solve the problem of death. She argues that they express what life feels like if Easter Saturday – the day Jesus lay dead in the grave – is never followed by Easter Sunday – the day that changed everything, according to the Christian faith, because it is the day that Jesus rose to new life.   --- Explore:  Natasha's piece on Marilynne Robinson's Reading Genesis  An article Simon wrote linking Anzac Day with Easter  Sign up for the CPX newsletter here 

We explore the spiritual needs of people in intensive care in hospital, or behind bars.  ---  “I went to see this lady and as soon as I walked in, she actually said, ‘f*** off, I don't want to have anything to do with you people'.”  Chaplaincy in Australia is contested. If people have had a bad experience with the church or concerned that someone might be trying to manipulate them, a chaplain walking up to say hi might get that response. Not least because people can be very vulnerable if they're dealing with a shocking medical episode in hospital or grappling with life in prison.  This Life & Faith episode takes you behind the scenes of two very different environments: the intensive care unit of a major Sydney hospital, and Kirkconnell Correctional Centre in regional NSW. Two chaplains from Jericho Road, a social service organisation linked with the Presbyterian Church in NSW, tell us about what it's like to care spiritually for people during very difficult times in their lives.   Content warning: there are some challenging stories told in these interviews. This episode is not suitable for children.  --- Explore:  Jericho Road's Love Your Neighbour course on chaplaincy Sign up for CPX's regular email newsletter to find out more about our work.

…of which CPX's Justine Toh is first and foremost.  --- In the lead up to Easter, Justine is giving up not only sugar, but her ignorance about all things Lent. She speaks to Catholic theologian Matt Tan, who goes by Awkward Asian Theologian on socials, about Lent and its three-fold focus: giving up, alms-giving, and prayer. They discuss the difficulty of self-sacrifice and the way that, strangely enough, it often proves the easier option over alms-giving, which needn't only include giving to charity, but also intentional, active investment in the lives of others.  Matt also alludes to the way church seasons induct the believer into an entirely different order of time. He cites the work of Neil Postman, who said the clock was originally invented to help monks keep to their daily prayer schedule. In time, however, the clock, went beyond the monastery and conquered the rest of the world. Time is now subdivided into increasingly minute moments that all need to be filled. So, what does it mean to live according to the rhythms of sacred time?  --- Explore  Simon Smart's Ash Wednesday article   Life & Faith episode with Matt Tan on the metaphysics of pornography  Follow Awkward Asian Theologian on Instagram 

20 years on from the founding of Facebook, what role do these platforms play in our lives?  ---  February 4 marked 20 years since Mark Zuckerburg launched the site that was initially known as The Facebook from his Harvard dorm room, so this seems like a good time to take stock of what social media now looks like, and what our lives look like as a result.  Whether you're an avid user of Facebook, Instagram, Twitter/X, TikTok, and more, or a social media sceptic, join Simon Smart, Justine Toh, and Natasha Moore for a frank chat about the better and worse of these platforms in 2024. With cameos from Andy Crouch, CPX brand manager (and socials pro) Clare Potts, and recent social media quitter Jess Forsyth, the discussion ranges from whether group chats count as social media to whether the internet is “made of demons” - as well as the advantages (and disciplines) of being an iceberg vs an ocean liner.   ---  EXPLORE:  New York Times article How Group Chats Rule the World   Philippa Moore's article about quitting social media   Paul Kingsnorth's Substack essays The Universal and The Neon God  Alan Jacobs' New Atlantis piece  Andy Crouch's Spiritual Practices for Public Leadership 

Reviewing some of the top cyber security stories for 2023.  Hope to see everyone at CPX 2024!

Our cultural narrative says there is no supernatural or transcendent realm. The CPX team wants to break that spell.  --- Seen & Heard is back – and this time, the team have disenchantment in their sights, or the belief that there is no more supernatural or transcendent realm to life, that science is the only verifiable path to truth, and that all things religious are debunked, once and for all.  But is this true? The books and films we've been reading and watching might disagree.   Natasha highlights beloved Australian author Helen Garner's encounter with an angel and our flirtation with the supernatural through occasions like Halloween, before taking us through the supernatural stylings of the latest Poirot film A Haunting in Venice, based (extremely loosely) on Agatha Christie's 1969 novel Hallowe'en Party.   Simon has been reading the biography of tennis icon and former World No. 1 Andre Agassi who, it turns out, hated tennis and wrestled with fame, but discovered that helping people is the “only perfection there is”.   A world that has cast off religion and the transcendent also leaves behind any account of the good life that goes along with those claims. Yet Agassi discovered that being the best tennis player in the world didn't fulfil him. Only serving others did, which resonates with the Christian claim that the good life is a life lived for others.   And Justine raves about Susannah Clarke's novel Piranesi and its vivid portrayal of what the disenchanted view of the world lacks: wonder, deep communion with the world, joy, and hope. Plus, Justine makes a bold claim:  Susannah Clarke is the 21st-century successor to C.S. Lewis.  --  Explore  Helen Garner describing her angelic encounter at the 2018 Sydney Writers' Festival (from 30 mins)  Sean Kelly's column mentioning Hilary Mantel's possibly demonic encounter  Trailer for A Haunting in Venice  Natasha's article on Halloween, published in the Sydney Morning Herald  Andre Agassi's Open: An Autobiography  The Guardian's interview with Susannah Clarke  Piranesi by Susannah Clarke  Wikipedia entry on the real-life Piranesi, the 18th-century architect and artist 

Featuring perspectives from Dr Naval Daver, including the following topics: Introduction: Biology, Classification, p53, Magrolimab (0:00) Case: A man in his early 70s with acute myeloid leukemia (AML) with a TP53 mutation, myelodysplastic syndromes (MDS)-related changes and complex cytogenetics who received CPX-351receives azacitidine/venetoclax and is now in palliative care — Anna Halpern, MD (9:06) Case: A woman in her late 50s with multiple comorbidities and FLT3-ITD-positive AML who experienced disease progression on azacitidine/venetoclax now receives gilteritinib — Bhavana (Tina) Bhatnagar, DO (17:01) Case: A woman in her early 70s with AML with FLT3-ITD and IDH1 mutations receives a hypomethylating agent with ivosidenib — Amany R Keruakous, MD, MS (29:10) Case: A man in his early 60s with newly diagnosed MDS with ring sideroblasts receives oral decitabine/cedazuridine — Khuda Dad Khan, MD, PhD (33:54) Case: A man in his mid 60s presents with copper deficiency and ring sideroblasts; genetic analysis reveals SF3B1 and DNMT3A mutations — Rachel J Cook, MD (42:25) Case: A woman in her early 70s with a history of extensively treated follicular lymphoma develops AML and receives CPX-351 — Ranju Gupta, MD (46:05) Case: A woman in her late 70s with newly diagnosed AML receives decitabine/venetoclax with concurrent voriconazole — Rebecca L Olin, MD, MSCE (51:05) Case: A woman in her late 90s is diagnosed with multiple myeloma and del(5q) MDS — Erik Rupard, MD (54:26) Journal Club with Dr Daver (57:28) CME information and select publications

#circuitpythonparsec Use the Circuit Playground library on the CPX and CPB boards to easily control on-board NeoPixels. Learn about CircuitPython: https://circuitpython.org Code examples here: https://github.com/jedgarpark/parsec/blob/main/2023-07-27/code.py Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Adafruit on Instagram: https://www.instagram.com/adafruit Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

#circuitpythonparsec Use the Circuit Playground library on the CPX and CPB boards to detect single and double taps with the on-board accelerometer. Learn about CircuitPython: https://circuitpython.org Code examples here: https://github.com/jedgarpark/parsec/blob/main/2023-07-13/code.py Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Adafruit on Instagram: https://www.instagram.com/adafruit Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

#circuitpythonparsec Use the Circuit Playground library on the CPX and CPB boards to light the LED and use the switch. Learn about CircuitPython: https://circuitpython.org Code examples here: https://github.com/jedgarpark/parsec/blob/main/2023-07-06/code.py Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Adafruit on Instagram: https://www.instagram.com/adafruit Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

We start this episode by talking about TD's Investor Sentiment Index and which stocks were the most bought and sold according to TD's data. We then look at data showing that the yield between equities, bonds and US treasuries is almost identical. We finish the episode by looking at the TSX return this year and the best performing TSX stocks over the last 5 years. Symbols of stocks discussed: TD.TO, ASE.TO, PMET.TO, FIL.TO, WELL.TO, BLU.TO, HWX.TO, KNT.TO, FOM.TO, CS.TO, TSU.TO, XENE.TO, SLI.TO, IVN.TO, LAC.TO, OLA.TO, RUP.TO, SHOP.TO, TFII.TO, NOA.TO, TRI.TO, GSY.TO, EQB.TO, CSU.TO, HCG.TO, ATS.TO SVI.TO, ATD.TO, ATZ.TO, L. TO, IFC.TO, CPX.TO, UNS.TO, ENB.TO, TSLA, SU.TO, NVDA, BNS.TO, CM.TO, BMO.TO, RY.TO, AC.TO, AMD, AAPL, AMZN Symbols of ETF discussed: XIC.TO, VFV.TO, VSP.TO, RSP, XFN.TO, XEG.TO, ZIN.TO, XMA.TO, XIT.TO Check out our portfolio by going to Jointci.com Our Website Canadian Investor Podcast Network Twitter: @cdn_investing Simon's twitter: @Fiat_Iceberg Braden's twitter: @BradoCapital Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor  Spotify - The Canadian Real Estate Investor  Sign up to Stratosphere for free

The CPX team freaks out about AI, explores stories of “efficiency” run amok, and probes our tech utopias.    --- The apocalypse will be ... boring.  Or so says Charlie Warzel, tech journalist for The Atlantic. He means that AI won't put you out of a job or take over the world, so much as overstuff your inbox and give you more mind-numbing tasks to complete.  Other people in the know about AI are less optimistic. Geoffrey Hinton, the “godfather” of AI who resigned from Google in May, Sam Altman, the CEO of the company behind ChatGPT, and others have sounded the alarm: AI is progressing too quickly, no one knows exactly how it works, and without careful regulation it will upend life as we know it.   There are a lot of unknowns where technology is concerned. One thing we do know, though, is it makes for great TV, and stories and books.  In this edition of Seen & Heard, the CPX team debriefs on what they've been watching and reading.   Natasha takes us through the twists and turns of Amazon Prime's Mrs Davis, a “bonkers” show about a nun facing off against Mrs Davis, the all-knowing algorithm against whom she has a grudge.   Simon looks at the way George Saunders' short story “Escape from Spiderhead” (and the Spiderhead film based on it) explores how “the greater good” is used to justify all kinds of evils.   Justine looks closer at the digital utopia on offer in Grace Chan's speculative novel Every Version of You, and finds that its promise of agelessness, no death, no suffering, and no body is basically heaven without God.     Explore:  ABC article on Replika  Every Version of You by Grace Chan  Escape From Spiderhead by George Saunders (via The New Yorker)  Mrs Davis trailer  Her and a Disembodied Future by Mark Stephens  Andy Crouch's Richard Johnson Lecture on why technology keeps disappointing us and Q&A  Charlie Warzel: Here's how AI will come for your job 

If you are an aspiring broker or even an investor who wants to see what it takes to be a top broker and how to separate yourself from the pack, this show is for you. We sit down and talk with fellow broker, David Gellner, of CPX who talks about his daily routine, what it takes to compete at a high level and how he prepares himself for this daily. We also talk about what the most important part of suceeding in brokerage is and ways you can elevate your brokerage game. You can reach David directly at dgellner@cpxone.com Enjoy the show!

Featuring perspectives from Drs Courtney DiNardo and Mark Levis, including the following topics: Introduction (0:00) Case: A man in his early 80s with newly diagnosed acute myeloid leukemia (AML) with significant comorbidities receives decitabine/venetoclax — Rebecca L Olin, MD, MSCE (7:36) Cases: A man in his mid 50s after 7 + 3 and allogeneic stem cell transplantation (SCT) presents with myeloid sarcoma; a man in his late 70s after 7 + 3 and allogeneic SCT presents with myeloid sarcoma — Spencer H Bachow, MD and Ranju Gupta, MD (12:16) Case: A man in his late 30s with core binding factor AML after induction CLAG-M with gemtuzumab ozogamicin followed by high-dose cytarabine x 4 — Anna Halpern, MD (18:10) Case: A woman in her mid 60s with newly diagnosed del(5q) AML with monocytic differentiation and multiple mutations (GATA2, BCOR, NF1 and RUNX1) receives azacitidine and venetoclax — Bhavana (Tina) Bhatnagar, DO (31:05) Selection of Therapy for Patients with AML (35:20) Cases: A man in his early 50s with therapy-related AML with an MLL mutation who receives CPX-351; a man in his early 70s with secondary AML with an IDH mutation — Amany R Keruakous, MD, MS and Priya Rudolph, MD, PhD (41:42) Case: A man in his early 70s with recurrent AML with an IDH2 mutation receives enasidenib and develops differentiation syndrome/disease progression — Dr Halpern (50:00) CME information and select publications

Study showing the time from diagnosis of AML to the start of intensive treatment indicate that a treatment delay has no negative prognostic impact. https://ashpublications.org/blood/article/136/7/823/460669/Does-time-from-diagnosis-to-treatment-affect-the RATIFY clinical trial showing the addition of midostaurin (FLT3 inhibitor) to 7+3 chemotherapy for AML https://www.nejm.org/doi/full/10.1056/nejmoa1614359 Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the European LeukemiaNet (ELN) https://ashpublications.org/blood/article/140/12/1345/485817/Diagnosis-and-management-of-AML-in-adults-2022 ASH 2022 abstract presenting Daunorubicin 60 Vs 90 mg/m2 https://ash.confex.com/ash/2022/webprogram/Paper157126.html ALFA-0701. The addition of gemtuzumab ozogamicin, an anti-CD33 antibody conjugate, to the standard treatment for patients with acute myeloid leukemiahttps://www.thelancet.com/article/S0140-6736(12)60485-1/fulltext Quizartinib data presented at EHA 2022 https://library.ehaweb.org/eha/2022/eha2022-congress/356965/harry.erba.quizartinib.prolonged.survival.vs.placebo.plus.intensive.induction.html?f=menu%3D6%2Abrowseby%3D8%2Asortby%3D2%2Amedia%3D3%2Ace_id%3D2233%2Amarker%3D1749%2Afeatured%3D17676 International Consensus Classification (ICC) of Myeloid Neoplasms and Acute Leukemiashttps://ashpublications.org/blood/article/140/11/1200/485730/International-Consensus-Classification-of-Myeloid The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasmshttps://www.nature.com/articles/s41375-022-01613-1  CPX-351 (cytarabine and daunorubicin) Liposome for Injection Versus Conventional Cytarabine Plus Daunorubicin in Older Patients With Newly Diagnosed Secondary Acute Myeloid Leukemiahttps://ascopubs.org/doi/10.1200/JCO.2017.77.6112?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed  Oral Azacitidine Maintenance Therapy for Acute Myeloid Leukemia in First Remissionhttps://www.nejm.org/doi/full/10.1056/NEJMoa2004444

Roman Catechism of Trent (RCT) p. 22-24 *** CPX 33 on the Eastern Rites of the Catholic Church: https://youtu.be/600fkzBHdBc Trinitarian Bible Apologetics from Dr. Taylor Marshall : The Trinity is one Substance and three divine Persons: Mt 28:19 – Baptism is Trinitarian “I baptize you in the name (singular) of the Father, and of Son, [...]

How to make a creepy animatronic crawling hand. It uses a glove from a halloween costume, outfitted with a servo motor and a Circuit Playground Express. This hand is designed to pull itself along the floor slowly, waiting until it finds a cold, dark spot, at which point it will stop and wait until temperature and light increase. (0:05) Learn guide here: https://learn.adafruit.com/crawling-hand-with-CPX-and-MakeCode Solder paste (0:43) So much testing! (0:59) Pick n place (1:36) #adafruit #manufacturing #nyc ----------------------------------------- Visit the Adafruit shop online - http://www.adafruit.com ----------------------------------------- LIVE CHAT IS HERE! http://adafru.it/discord Adafruit on Instagram: https://www.instagram.com/adafruit Subscribe to Adafruit on YouTube: http://adafru.it/subscribe New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ -----------------------------------------

Reviewing Golf Pride's newest grip, the CPX. The CPX is soft, yet with great traction. The EXO Diamond pattern helps golfers by providing a larger contact patch for better control. Also touching on some tinkering I have done, or plan to do, to a bunch of my clubs.

Catechism of Pope St. Pius X (CPX) p.131-135 Q/A 15-26. **** CPX 33 on the Eastern Rites: https://www.youtube.com/watch?v=600fkzBHdBc&t=1s Fr. Z on fasting expected of Roman Catholics in 1873 in Newark, NJ: https://wdtprs.com/2018/03/what-would-your-lent-have-been-like-in-1873/ Catechism of the Council of Trent: https://www.amazon.com/Catechism-Council-Trent/dp/089555884X/ref=sr_1_3?crid=3374R7MJFFT3C&keywords=catechism+of+trent&qid=1645990154&sprefix=catechism+of+tren%2Caps%2C115&sr=8-3