Podcasts about windows copilot

It's the final episode of the last episode of television before heading into the first ever pay-per-view for ECW, a wrestling promotion that is trying to prove that a small independent promotion can do it, can be a viable contender all by itself, with the help of nobody else. Nobody. Nobody except the wide range of wrestlers that owed favours or would work for cheap; the first booker Eddie Gilbert who set the tone for what the show would be; Vince McMahon, who while not outright funding the thing, has helped it along as long as Paul Heyman stopped burying his promotion and focused instead on - after WCW raided ECW's roster already, allowing him to raid it much more effectively - WCW; and nobody else except for of course Paul Heyman's Dad's money I assume (and connections) which helped screw Tod Gordon out of the weekend pissup and hotel orgy-hosting nonstop party he had founded that was masquerading as a wrestling company. It's that pivotal final episode of television before that pivotal first pay-per-view, "this Sunday night", at 9 PM, across America, and presumably through piracy and early internet messageboards, across the Globe to a certain extent. Barely Legal. You've got to start that episode right, with a powerful piece of attention-grabbing footage that will make even the most jaded channel-scrolling stoner to shake the cheeto dust out of their eyes, sit up in their Barca Lounger and say hey… I should see if I can steal Barely Legal off the Internet. And what better way to start that episode of television than with… Oh, it's the Pitbulls. It's time for Luke Pennock & Brendan Flaherty to review episode 205 and 206 of ECW, from April 1st & 8th, 1997! Up next - our BARELY LEGAL livestream - presented in eye-wounding VHS-VISION. Join us on Discord - 12.30.25 at 8 PM EST.  Buy the shirt! Buy the shirt! Buy the shirt.  IG & Twitter: @hcorehavenpod Contact us: hardcoreahavenpod@gmail.com Luke on Twitch: http://www.twitch.tv/pukelennock/ Logo by Raymond Biesinger Theme song by RANX

So what does Windows want for Christmas? Paul Thurrott is back to talk about everything that happened to Windows in 2025, and what that might hold for 2026. Paul talks about Pavan Davuluri being promoted to President of Windows & Devices - and reunifying the Windows Client and Windows Core teams. That sets up an opportunity to make some significant moves from Windows, which, of course, will involve AI - although the reaction to the public when Pavan said as much was not all that positive. Windows has plenty of problems to address, but one of the brighter notes is Windows on ARM and the Snapdragon processor. And maybe, just maybe, someone's wish will come true, and we'll see Windows 12!LinksPavan's Famous AI TweetM365 CopilotMicrosoft LoopMicrosoft RecallRecorded December 16, 2025

In today's Cloud Wars Minute, I take a look at Microsoft's newest Copilot feature that lets users type to Vision instead of relying solely on voice.Highlights00:10 — Microsoft has rolled out a new update for the Microsoft Copilot app on Windows for Windows Insiders. This update allows users to interact with Copilot Vision using text inputs, and Copilot will respond, in turn, with text outputs in the same chat window. Previously, interactions with Copilot Vision were only possible through voice commands.00:50 — Microsoft has been rolling out new Copilot features rapidly in recent months. Vision allows you to interact with the AI assistant, Copilot, to answer questions about what's displayed on your screen or captured by your mobile camera feed. There's been a significant push from Microsoft to make Copilot a voice-first AI tool.01:29 — Ultimately, this approach lowers the barrier to entry for users by removing the complexity associated with engaging with Copilot solely through text inputs. However, consumers will always desire choice, and this addition to Copilot's capabilities is a positive step for Microsoft. Visit Cloud Wars for more.

Новая неделя – новый выпуск Завтракаста, одного из лучших русскоязычных подкастов про игры, медиа, технологии, ИИ, машины, Вархаммер, кино, интернет, сериалы, мультики, вкусности и многое другое! Как обычно, с вами его ведущие Дмитрий, Тимур и Максим обсуждают всякое разное и стараются не забыть о разном всяком. 

Happy holidays! We'll be sharing snippets from Latent Space LIVE! through the break bringing you the best of 2024! We want to express our deepest appreciation to event sponsors AWS, Daylight Computer, Thoth.ai, StrongCompute, Notable Capital, and most of all all our LS supporters who helped fund the gorgeous venue and A/V production!For NeurIPS last year we did our standard conference podcast coverage interviewing selected papers (that we have now also done for ICLR and ICML), however we felt that we could be doing more to help AI Engineers 1) get more industry-relevant content, and 2) recap 2024 year in review from experts. As a result, we organized the first Latent Space LIVE!, our first in person miniconference, at NeurIPS 2024 in Vancouver.Of perennial interest, particularly at academic conferences, is scaled-up architecture research as people hunt for the next Attention Is All You Need. We have many names for them: “efficient models”, “retentive networks”, “subquadratic attention” or “linear attention” but some of them don't even have any lineage with attention - one of the best papers of this NeurIPS was Sepp Hochreiter's xLSTM, which has a particularly poetic significance as one of the creators of the LSTM returning to update and challenge the OG language model architecture:So, for lack of a better term, we decided to call this segment “the State of Post-Transformers” and fortunately everyone rolled with it.We are fortunate to have two powerful friends of the pod to give us an update here:* Together AI: with CEO Vipul Ved Prakash and CTO Ce Zhang joining us to talk about how they are building Together together as a quote unquote full stack AI startup, from the lowest level kernel and systems programming to the highest level mathematical abstractions driving new model architectures and inference algorithms, with notable industry contributions from RedPajama v2, Flash Attention 3, Mamba 2, Mixture of Agents, BASED, Sequoia, Evo, Dragonfly, Dan Fu's ThunderKittens and many more research projects this year* Recursal AI: with CEO Eugene Cheah who has helped lead the independent RWKV project while also running Featherless AI. This year, the team has shipped RWKV v5, codenamed Eagle, to 1.5 billion Windows 10 and Windows 11 machines worldwide, to support Microsoft's on-device, energy-usage-sensitive Windows Copilot usecases, and has launched the first updates on RWKV v6, codenamed Finch and GoldFinch. On the morning of Latent Space Live, they also announced QRWKV6, a Qwen 32B model modified with RWKV linear attention layers. We were looking to host a debate between our speakers, but given that both of them were working on post-transformers alternativesFull Talk on YoutubePlease like and subscribe!LinksAll the models and papers they picked:* Earlier Cited Work* Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention* Hungry hungry hippos: Towards language modeling with state space models* Hyena hierarchy: Towards larger convolutional language models* Mamba: Linear-Time Sequence Modeling with Selective State Spaces* S4: Efficiently Modeling Long Sequences with Structured State Spaces* Just Read Twice (Arora et al)* Recurrent large language models that compete with Transformers in language modeling perplexity are emerging at a rapid rate (e.g., Mamba, RWKV). Excitingly, these architectures use a constant amount of memory during inference. However, due to the limited memory, recurrent LMs cannot recall and use all the information in long contexts leading to brittle in-context learning (ICL) quality. A key challenge for efficient LMs is selecting what information to store versus discard. In this work, we observe the order in which information is shown to the LM impacts the selection difficulty. * To formalize this, we show that the hardness of information recall reduces to the hardness of a problem called set disjointness (SD), a quintessential problem in communication complexity that requires a streaming algorithm (e.g., recurrent model) to decide whether inputted sets are disjoint. We empirically and theoretically show that the recurrent memory required to solve SD changes with set order, i.e., whether the smaller set appears first in-context. * Our analysis suggests, to mitigate the reliance on data order, we can put information in the right order in-context or process prompts non-causally. Towards that end, we propose: (1) JRT-Prompt, where context gets repeated multiple times in the prompt, effectively showing the model all data orders. This gives 11.0±1.3 points of improvement, averaged across 16 recurrent LMs and the 6 ICL tasks, with 11.9× higher throughput than FlashAttention-2 for generation prefill (length 32k, batch size 16, NVidia H100). We then propose (2) JRT-RNN, which uses non-causal prefix-linear-attention to process prompts and provides 99% of Transformer quality at 360M params., 30B tokens and 96% at 1.3B params., 50B tokens on average across the tasks, with 19.2× higher throughput for prefill than FA2.* Jamba: A 52B Hybrid Transformer-Mamba Language Model* We present Jamba, a new base large language model based on a novel hybrid Transformer-Mamba mixture-of-experts (MoE) architecture. * Specifically, Jamba interleaves blocks of Transformer and Mamba layers, enjoying the benefits of both model families. MoE is added in some of these layers to increase model capacity while keeping active parameter usage manageable. * This flexible architecture allows resource- and objective-specific configurations. In the particular configuration we have implemented, we end up with a powerful model that fits in a single 80GB GPU.* Built at large scale, Jamba provides high throughput and small memory footprint compared to vanilla Transformers, and at the same time state-of-the-art performance on standard language model benchmarks and long-context evaluations. Remarkably, the model presents strong results for up to 256K tokens context length. * We study various architectural decisions, such as how to combine Transformer and Mamba layers, and how to mix experts, and show that some of them are crucial in large scale modeling. We also describe several interesting properties of these architectures which the training and evaluation of Jamba have revealed, and plan to release checkpoints from various ablation runs, to encourage further exploration of this novel architecture. We make the weights of our implementation of Jamba publicly available under a permissive license.* SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers* We introduce Sana, a text-to-image framework that can efficiently generate images up to 4096×4096 resolution. Sana can synthesize high-resolution, high-quality images with strong text-image alignment at a remarkably fast speed, deployable on laptop GPU. Core designs include: * (1) Deep compression autoencoder: unlike traditional AEs, which compress images only 8×, we trained an AE that can compress images 32×, effectively reducing the number of latent tokens. * (2) Linear DiT: we replace all vanilla attention in DiT with linear attention, which is more efficient at high resolutions without sacrificing quality. * (3) Decoder-only text encoder: we replaced T5 with modern decoder-only small LLM as the text encoder and designed complex human instruction with in-context learning to enhance the image-text alignment. * (4) Efficient training and sampling: we propose Flow-DPM-Solver to reduce sampling steps, with efficient caption labeling and selection to accelerate convergence. * As a result, Sana-0.6B is very competitive with modern giant diffusion model (e.g. Flux-12B), being 20 times smaller and 100+ times faster in measured throughput. Moreover, Sana-0.6B can be deployed on a 16GB laptop GPU, taking less than 1 second to generate a 1024×1024 resolution image. Sana enables content creation at low cost. * RWKV: Reinventing RNNs for the Transformer Era* Transformers have revolutionized almost all natural language processing (NLP) tasks but suffer from memory and computational complexity that scales quadratically with sequence length. In contrast, recurrent neural networks (RNNs) exhibit linear scaling in memory and computational requirements but struggle to match the same performance as Transformers due to limitations in parallelization and scalability. * We propose a novel model architecture, Receptance Weighted Key Value (RWKV), that combines the efficient parallelizable training of transformers with the efficient inference of RNNs.* Our approach leverages a linear attention mechanism and allows us to formulate the model as either a Transformer or an RNN, thus parallelizing computations during training and maintains constant computational and memory complexity during inference. * We scale our models as large as 14 billion parameters, by far the largest dense RNN ever trained, and find RWKV performs on par with similarly sized Transformers, suggesting future work can leverage this architecture to create more efficient models. This work presents a significant step towards reconciling trade-offs between computational efficiency and model performance in sequence processing tasks.* LoLCATs: On Low-Rank Linearizing of Large Language Models* Recent works show we can linearize large language models (LLMs) -- swapping the quadratic attentions of popular Transformer-based LLMs with subquadratic analogs, such as linear attention -- avoiding the expensive pretraining costs. However, linearizing LLMs often significantly degrades model quality, still requires training over billions of tokens, and remains limited to smaller 1.3B to 7B LLMs. * We thus propose Low-rank Linear Conversion via Attention Transfer (LoLCATs), a simple two-step method that improves LLM linearizing quality with orders of magnitudes less memory and compute. * We base these steps on two findings. * First, we can replace an LLM's softmax attentions with closely-approximating linear attentions, simply by training the linear attentions to match their softmax counterparts with an output MSE loss ("attention transfer").* Then, this enables adjusting for approximation errors and recovering LLM quality simply with low-rank adaptation (LoRA). * LoLCATs significantly improves linearizing quality, training efficiency, and scalability. We significantly reduce the linearizing quality gap and produce state-of-the-art subquadratic LLMs from Llama 3 8B and Mistral 7B v0.1, leading to 20+ points of improvement on 5-shot MMLU. * Furthermore, LoLCATs does so with only 0.2% of past methods' model parameters and 0.4% of their training tokens. * Finally, we apply LoLCATs to create the first linearized 70B and 405B LLMs (50x larger than prior work). * When compared with prior approaches under the same compute budgets, LoLCATs significantly improves linearizing quality, closing the gap between linearized and original Llama 3.1 70B and 405B LLMs by 77.8% and 78.1% on 5-shot MMLU.Timestamps* [00:02:27] Intros* [00:03:16] Why Scale Context Lengths? or work on Efficient Models* [00:06:07] The Story of SSMs* [00:09:33] Idea 1: Approximation -> Principled Modeling* [00:12:14] Idea 3: Selection* [00:15:07] Just Read Twice* [00:16:51] Idea 4: Test Time Compute* [00:17:32] Idea 2: Hardware & Kernel Support* [00:19:49] RWKV vs SSMs* [00:24:24] RWKV Arch* [00:26:15] QWRKWv6 launch* [00:30:00] What's next* [00:33:21] Hot Takes - does anyone really need long context?Transcript[00:00:00] AI Charlie: We're back at Latent Space Live, our first mini conference held at NeurIPS 2024 in Vancouver. This is Charlie, your AI co host. As a special treat this week, we're recapping the best of 2024 going domain by domain. We sent out a survey to the over 900 of you who told us what you wanted, and then invited the best speakers in the Latent Space Network to cover each field.[00:00:24] AI Charlie: 200 of you joined us in person throughout the day, with over 2200 watching live online. Thanks Our next keynote covers the State of Transformers alternative architectures, with a special joint presentation with Dan Fu of Together AI and Eugene Chia of Recursal AI and Featherless AI. We've featured both Together and Recursal on the pod before, with CEO Veepal Vedprakash introducing them.[00:00:49] AI Charlie: And CTO CE Zhang joining us to talk about how they are building together together as a quote unquote full stack AI startup from the lowest level kernel and systems [00:01:00] programming to the highest level mathematical abstractions driving new model architectures and inference algorithms with notable industry contributions from Red Pajama V2, Flash Attention 3, Mamba 2, Mixture of Agents.[00:01:15] AI Charlie: Based, Sequoia, Evo, Dragonfly, Danfoo's Thunder Kittens, and many more research projects this year. As for Recursal and Featherless, we were the first podcast to feature RWKV last year, and this year the team has shipped RWKV v5, codenamed Eagle, to 1. 5 billion Windows 10 and Windows 11 machines worldwide to support Microsoft's on device, end Energy Usage Sensitive Windows Copilot Use Cases and has launched the first updates on RWKV v6, codenamed Finch and Goldfinch.[00:01:53] AI Charlie: On the morning of Latent Space Live, they also announced QRdata UKv6, a QEN32B model [00:02:00] modified with RDWKV linear attention layers. Eugene has also written the most single most popular guest post on the Latent Space blog this year. Yes, we do take guest posts on what he has discovered about the H100 GPU inference NeoCloud market since the successful launch of Featherless AI this year.[00:02:20] AI Charlie: As always, don't forget to check the show notes for the YouTube link to their talk as well as their slides. Watch out and take care.[00:02:27] Intros[00:02:27] Dan Fu: Yeah, so thanks so much for having us. So this is going to be a little bit of a two part presentation. My name is Dan. I'm at Together AI, and I'll be joining UCSD as faculty in about a year. And Eugene, you want to introduce yourself?[00:02:46] Eugene Cheah: Eugene, I lead the art activity team, and I, I'm CEO of Featherless, and we both work on this new post transformer architecture space.[00:02:55] Dan Fu: Yeah, so yeah, so today we're really excited to talk to you a little bit [00:03:00] about that. So first I'm going to give a broad overview of kind of the last few years of progress in non post transformer architectures. And then afterwards Eugene will tell us a little bit about the latest and the greatest and the latest frontier models in this space.[00:03:16] Why Scale Context Lengths? or work on Efficient Models[00:03:16] Dan Fu: So, the story starts with Scaling. So this is probably a figure or something like this that you've seen very recently. Over the last five to six years, we've seen models really scale up in parameter size, and that's brought with it a bunch of new capabilities, like the ability to talk to you and tell you sometimes how to use your Colab screens.[00:03:35] Dan Fu: But another place where we've seen scaling especially recently is scaling in context length. So this can mean Having more text inputs for your models, but it can also mean things like taking a lot of visual token inputs image inputs to your models or generating lots of outputs. And one thing that's been really exciting over the last few months or so is that we're, we're seeing scaling, not only during training time, but also [00:04:00] during test time.[00:04:00] Dan Fu: So this is one of the, the, this is the iconic image from the OpenAI 01 release. Not only are we starting to scale train time compute, but we're also starting to scale test time compute. Now if you're familiar with our attention and our transformer architectures today, this graph on the right might look a little bit scary.[00:04:19] Dan Fu: And one of the reasons is that the implications are a little bit Interesting. So what does it mean if we want to continue having smarter and smarter models? Do we just need to start building bigger, bigger data centers, spending more flops? Is this this little Dolly 3, we need more flops, guys? Is this going to be the future of all of AI?[00:04:39] Dan Fu: Or is there a better way, another path forward? Maybe we can get the same capabilities that we've gotten used to, But for a lot less compute, a lot less flops. And one of the things that we're going to talk about today is specifically looking at that core attention operator in some of these models.[00:04:57] Dan Fu: And the reason is that so this is just some, some [00:05:00] basic you know, scaling curves, but attention has compute that scales quadratically in the context length. So that means that if you're doing something like test time compute and you want to spend a bunch of tokens thinking about what comes next, the longer that that goes the, the, the more tokens you spend on that, that compute grows quadratically in that.[00:05:19] Dan Fu: One of the questions that we're interested in is, can we take that basic sequence model, that basic sequence primitive at the bottom, and get it to scale better? Can we scale in, let's say, n to the 3 halves or n log n? So in, in the first part of the talk, so we just went over the introduction. What I'm gonna do over the next few slides is just talk about some of the key advances and ideas that have shown over the past few years since maybe early 2020 to, to now that shown promise that this might actually be possible.[00:05:48] Dan Fu: That you can actually get potentially the same quality that we want while scale, while scaling better. So to do that, we're and, and basically the, the story that we're gonna look is we're gonna start to see [00:06:00] how. So this is a basic graph of just the past couple years of progress of perplexity where that blue line, that dotted blue line, is attention.[00:06:07] The Story of SSMs[00:06:07] Dan Fu: It's your basic transformer, full dense attention. And then the dots coming down are some of the methods that you'll see in this presentation today. We're going to turn the clock back all the way to 2020. So this, this, this question of can we make attention subquadratic? Basically, as soon as we said attention is all you need, People started asking this question.[00:06:28] Dan Fu: So we have this quadratic attention operator. Can we do better? I'll briefly talk about why attention is quadratic. And the basic thing that happens, if you're not familiar, is that you have these inputs, these keys and queries. And what you do in this attention matrix, this S matrix over here, is that you're using, you're comparing every token in your input to every other token.[00:06:49] Dan Fu: So when I try to do something like upload a whole book to Gemini, what happens beyond the Maybe not Gemini, because we don't necessarily know what architecture is. But let's say we upload it to LLAMA, what happens beyond [00:07:00] the scenes, behind the scenes, is that it's going to take every single word in that book and compare it to every other word.[00:07:05] Dan Fu: And this has been a really, it's, it's led to some pretty impressive things. But it's kind of a brute forcing of the way that you would try to interpret a interpret something. And what attention does in particular is the, and then what attention, sorry, don't want to. Okay, no, no laser pointer. What, what attention does afterwards is that instead of always operating in this quadratic thing, it takes a row wise softmax over this matrix, and then multiplies it by this values matrix.[00:07:32] Dan Fu: So, one of the key points to notice is that the output size is always going to be the same as the inputs, at least in standard self attention. So one of the first things that folks tried to do around 2020 is this thing called linear attention, which is just, just noticing that if we take out this softmax from here, if we take out this non linearity in the middle of the attention operation, and then if you compute the keys and the values operation first, you actually never hit this quadratic bottleneck.[00:07:57] Dan Fu: So that, that's potentially a way [00:08:00] to get a lot more computationally efficient. And there are various ways to do this by basically using feature maps or try to approximate this overall attention computation. But some of this work sort of started to hit a wall in 2020. And the basic challenges were, were two.[00:08:16] Dan Fu: So one was quality. It was back then, it was kind of hard to, to get good quality with these linear attention operators. The other one was actually hardware efficiency. So these, this feature map that was just shown by a simplify simplify here. Actually ends up being quite computationally expensive if you just implement it naively.[00:08:34] Dan Fu: So you started having these operators that not only were you sure, you're not really sure if they have the same quality, but also they're actually just wall clock slower. So you kind of end up getting the worst of both worlds. So this was the the stage. So that kind of sets the stage for four years ago.[00:08:49] Dan Fu: Keep this in mind because linear attention is actually going to come back in a few years once we have a better understanding. But one of the works that started kicking off this, this [00:09:00] mini revolution in post transformer architectures was this idea called states based model. So here the seminal work is, is one about our work queue in 2022.[00:09:09] Dan Fu: And this, this piece of work really brought together a few ideas from, from some long running research research lines of work. The first one was, and this is really one of the keys to, to closing the gap in quality was just using things that, that if you talk to a, a, an electrical engineer off the street, they might know off, off the, like the back of their hand.[00:09:33] Idea 1: Approximation -> Principled Modeling[00:09:33] Dan Fu: But taking some of those properties with how we model dynamical systems in signal processing and then using those ideas to model the inputs, the, the text tokens in, for example a transformer like Next Token Prediction Architecture. So some of those early states-based model papers were looking at this relatively, relatively simple recurrent update model that comes from maybe chapter one of a signal processing class.[00:09:59] Dan Fu: But then using [00:10:00] some principle theory about how you should do that recurrent update in order to really get the most that you can out of your hidden state, out of your out of your sequence. So that, that was one key idea for quality and. When this was eventually realized, you started to see a bunch of benchmarks that were pretty sticky for a few years.[00:10:20] Dan Fu: Things like long range arena, some long sequence evaluation benchmarks, There was stuff in time series, time series analysis. They started to, you started to see the quality tick up in meaningful ways. But the other key thing that What's so influential about these states based models is that they also had a key idea about how you can compute these things efficiently.[00:10:45] Dan Fu: So if you go back to your machine learning 101 class where you learned about RNNs, one thing that you may have learned is that they don't paralyze as well as detention, because if you just run them naively, you have to do this kind of sequential update to process new tokens, [00:11:00] whereas in attention, you can process all the tokens in parallel at one time.[00:11:04] Dan Fu: One of the key insights behind the S4 paper was that these recurrent models, you could take them and you could also formulate them as a convolution. And in particular, with a convolution, you could, instead of using a PyTorch conv1d operation, you can compute that with the FFT. And that would give you n log n compute in the in the sequence length n with an operator that was relatively well optimized for modern hardware.[00:11:28] Dan Fu: So those are really, I'd say, the two key ideas in 2022 that started allowing these breakthroughs to happen in these non transformer architectures. So, these ideas about how to principally model sorry, how to model the recurrent updates of a mo of, of a sequence in a principled way, and also these key ideas in how you can compute it efficiently by turning it into a convolution and then scaling it up with the FFT.[00:11:53] Dan Fu: Along those same lines, so afterwards we started putting out some work on specialized kernels, so just [00:12:00] like we have flash attention for transformers, we also have works like flash fft conf, and if you look at these lines of work oftentimes when, whenever you see a new architecture, you see a new primitive one of the, one of the table stakes now is, do you have an efficient kernel so that you can actually get wall clock speed up?[00:12:14] Idea 3: Selection[00:12:14] Dan Fu: So by 2022, We are starting to have these models that had promising quality primitives, but and, and also promising wall clocks. So you could actually see regimes where they were better than transformers in meaningful ways. That being said, there were, there's still sometimes a quality gap, particularly for language modeling.[00:12:33] Dan Fu: And because languages, It's so core to what we do in sequence modeling these days the, the next, the next key idea that I'm going to talk about is this idea of selection mechanisms. And this is basically an idea of, so you have this recurrent state that you're keeping around that just summarizes everything that, that came before.[00:12:50] Dan Fu: And to get a good sequence model, one of the things that you really need to be able to do is have the model learn what's the best way to pick out pieces from that recurrent [00:13:00] state. So one of the, one of the major ideas here in a line of work called H3, Hungry Hungry Hippos, and also these hyena models were One way you can do this is by just adding some simple element wise gates.[00:13:13] Dan Fu: So versions of these ideas have been around for decades. If you squint at the LSTM paper you, you can probably find, find this gating mechanism. But turns out you can take those old ideas, add them into these new. state space models, and then you can see quality start to pick up. If you've heard of the Mamba model, this also takes the selection to the next level by actually making some changes in that fundamental recurrent state space.[00:13:40] Dan Fu: So, it's not only just this gating that happens around the SSM layer, but also you can actually make The ABCD matrices of your state space model, you can make them data dependent, which will allow you to even better select out different pieces from your hidden state depending on what you're seeing. I'll also point out if you look at the [00:14:00] bottom right of this figure, there's this little triangle with a GPU SRAM, GPU HBM, and this, this is just continuing that trend of when you have a new architecture you, you, you also release it with a kernel to, to, to show that it is hardware efficient, that it, that it can be hardware efficient on modern hardware.[00:14:17] Dan Fu: The, the, one of the next cool things that happened is once we had this understanding of these are the basic pieces, these are the basic principles behind some of the sequence models linear attention actually started to come back. So in earlier this year, there was a model called BASED the, from Simran Arora and, and some other folks, that combined a more principled version of linear attention that basically the, the, the, the two second summary is that it used a Taylor approximation of the softmax attention, combined that with a simple sliding window attention and was starting to able, starting to be able to expand the Pareto frontier of how much data can you recall from your sequence, versus how small is your recurrent state size.[00:14:58] Dan Fu: So those orange dots [00:15:00] are, at the top there, are just showing smaller sequences that can recall more memory.[00:15:07] Just Read Twice[00:15:07] Dan Fu: And the last major idea I think that has been influential in this line of work and is very relatively late breaking just a few months ago, is just the basic idea that when you have these models that are fundamentally more efficient in the sequence length, you maybe don't want to prompt them or use them in exactly the same way.[00:15:26] Dan Fu: So this was a really cool paper called Just Read Twice, also from Simran. That basically said, hey, all these efficient models can process tokens so much more efficiently than transformers that they can sometimes have unfair advantages compared to a simple transformer token. So, or sorry, a simple transformer model.[00:15:44] Dan Fu: So take, for example the standard, the standard use case of you have some long document, you're going to pass it in as input, and then you're going to ask some question about it. One problem you might imagine for a recurrent model where you have a fixed state size is, let's say that [00:16:00] you're. Article is very long, and you're trying to ask about some really niche thing.[00:16:04] Dan Fu: You can imagine it might be hard for the model to know ahead of time what information to put into the hidden state. But these, these, these models are so much more efficient that you can do something really stupid, like, you can just put the document write down the document, write down the question, write down the document again, and then write down the question again, and then this time, the second time that you go over that document, you know exactly what to look for.[00:16:25] Dan Fu: And the cool thing about this is, so this is, And this this results in better quality, especially on these recall intensive tasks. But the other interesting thing is it really takes advantage of the more efficient architectures that, that we're having here. So one of the other, I think, influential ideas in this line of work is if you change the fundamental compute capabilities of your model and the way that it scales, you can actually start to query it at test time differently.[00:16:51] Idea 4: Test Time Compute[00:16:51] Dan Fu: And this actually, of course, goes back to those slides on test time compute. So while everybody's looking at, say, test time compute for big transformer models, [00:17:00] I think potentially a really interesting research question is, how can you take those and how does it change with this new next generation of models?[00:17:09] Dan Fu: So the, I'll just briefly summarize what some of those key ideas were and then talk and then show you briefly kind of what the state of the art is today. So, so the four key ideas are instead of just doing a simple linear attention approximation, instead take ideas that we know from other fields like signal processing, do a more principled approach to your modeling of the sequence.[00:17:32] Idea 2: Hardware & Kernel Support[00:17:32] Dan Fu: Another key idea throughout all these lines of work is you really want. Hardware and kernel support from day one. So, so even if your model is theoretically more efficient if somebody goes and runs it and it's two times slower one of the things that, that we've learned is that if, if you're in that situation, it's, it's just gonna be dead on arrival.[00:17:49] Dan Fu: So you want to be designing your architectures one of the key, key machine learning ideas that has been important for the quality is just making sure that you encode different ways that you can [00:18:00] select from your hidden state and, and really focus on that as a key decider of quality. And finally, I think one of the, the, the emerging new, new things for, for this line of work and something that's quite interesting is, What are the right test time paradigms for these models?[00:18:15] Dan Fu: How do they change relative to relative to what you might do for a standard transformer? I'll briefly end this section. So I've labeled this slide where we are yesterday because Eugene is going to talk about some new models that he released literally this morning. But as of yesterday, some of the really cool results out of the, these efficient alternative models were so AI2 trained this hybrid MOE called Jamba.[00:18:40] Dan Fu: That, that, that seems, that is currently the state of the art for these non transformer architectures. There's this NVIDIA and MIT put out this new diffusion model called SANA recently that one of their key key observations is that you can take a standard diffusion transformer diffusion model, replace the layers with linear [00:19:00] attention, and then that lets you scale to much larger much larger images, much, much Much larger sequences more efficiently.[00:19:07] Dan Fu: And and one thing that I don't think anybody would have called when a few years ago is that one of those gated SSM, gated states based models ended up on the cover of Science because a great group of folks went and trained some DNA models. So that's Michael Polley, Eric Yuen from from Stanford and the Arc Institute.[00:19:26] Dan Fu: So it's, we're really at an exciting time in 2024 where these non transformer, post transformer architectures are showing promise across a wide range. Across a wide range of, of modalities, of applications, and, and of tasks. And with that, I'll pass it on to Eugene, who can tell you a little bit about the latest and greatest with RWKV.[00:19:49] RWKV vs SSMs[00:19:49] Eugene Cheah: So, that's useful? Yeah. You're talking to here. Oh, I'm talking to here. Okay. So, yeah, two streams. Yeah. So, I think one common questions that we tend to get asked, right, is what's the difference between [00:20:00] RWKV and state space? So I think one of the key things to really understand, right the difference between the two groups, right, is that we are actually more like an open source, random internet meets academia kind of situation.[00:20:11] Eugene Cheah: Like, most of us never wrote any paper, but we, we basically look at RNNs and linear intention when intention is all you need came out, and then we decided to like, hey there is a quadratic scaling problem. Why don't we try fixing that instead? So, so, so we end up developing our own branch, but we end up sharing ideas back and forth.[00:20:30] Eugene Cheah: So, and, and we do all this actively in Discord, GitHub, etc. This was so bad for a few years, right, that basically, the average group's H index was so close to zero, right, Illuter. ai actually came in and helped us write our first paper. Great, now our H index is now three, apparently. So, so, so, but, but the thing is, like, a lot of these experiments led to results, and, and, essentially, essentially, we we took the same ideas from linear attention, [00:21:00] and we built on it.[00:21:01] Eugene Cheah: So, to take a step back into, like, how does RWKB handle its own attention mechanic and achieve the same goals of, like, O and compute, respectively, and in focus of our overall goal to make AI accessible to everyone, regardless of language, nation, or compute, that's our goal. We actually train our models primarily on over a hundred languages, which is another topic altogether.[00:21:23] Eugene Cheah: And our goal is to train to even 200 languages to cover all languages in the world. But at the same time, we work on this architecture, To lower the compute cost so that people can run it on Raspberry Pis and on anything. So, how did RWKB break the dependency of LSTM token flow? Because I think to understand architecture, right, it's probably easier to understand it from the RNN lens.[00:21:46] Eugene Cheah: Because that's where we built on. We all, we all state space kind of like try to, try to start anew and took lessons from that and say, So there's a little bit of divergence there. And AKA, this our version of linear attention. So to take step back [00:22:00] all foundation models, be it transformers or non transformers at a very high level, right?[00:22:05] Eugene Cheah: Pumps in the token. I mean, text that things into embeddings and go through a lot of layers. Generate a lot of states where the QKV cache or be iron in states or RW KB states. And outputs and embedding, they are not the same thing. And we just take more layers and more embeddings. And somehow that magically works.[00:22:23] Eugene Cheah: So, if you, if you remember your ancient RNN lessons which we, which we, which we we call best learning these days the general idea is that you have the embedding information flowing all the way up, and when, and you take that information and you flow it back down, and then you process it as part of your LSTM layers.[00:22:41] Eugene Cheah: So, this is how it generally works. Kapati is quoted saying that RNNs are actually unreasonably effective. The problem is this is not scalable. To start doing work on the second token, you need to wait for the first token. And then you need to, and likewise for the third token and fourth token, yada yada.[00:22:55] Eugene Cheah: That is CPU land, not GPU land. So, so, so, you [00:23:00] can have a H100 and you can't even use 1 percent of it. So, so that's kind of why RNNs didn't really take off in the direction that we wanted, like, billions of parameters when it comes to training. So, what did RDAP KV version 0 do? Boom. We just did the dumbest, lamest thing.[00:23:13] Eugene Cheah: Sorry, this is the bottleneck for RNN. We did the dumb thing of removing that line. And it kind of worked. It trained. It sucked, but it kind of worked. Then we were like, hey, then no one cared because the loss was crap, but how do we improve that? And that's essentially where we move forward, because if you see this kind of flow, right, you can actually get your GPU saturated quickly, where it essentially cascades respectively.[00:23:41] Eugene Cheah: So I'm just waiting for this to loop again. So it's like, once you get your first layer, your token to be computed finish. You start to cascade your compute all the way until you are, Hey, I'm using 100 percent of the GPU. So we, we worked on it, and we started going along the principle of that as long as we keep this general architecture [00:24:00] where, where we can cascade and, and be highly efficient with our architecture, nothing is sacred in our architecture.[00:24:06] Eugene Cheah: And we have done some crazy ideas. In fact, you ask us, if you ask me to explain some things in the paper, right, officially in the paper, I'll say we had this idea and we wrote it this way. The reality is someone came with a code, we tested it, it worked, and then we rationalized later. So, so the general[00:24:24] RWKV Arch[00:24:24] Eugene Cheah: The idea behind rwkbr is that we generally have two major blocks that we do.[00:24:30] Eugene Cheah: We call time mix and channel mix. And time mix generally handles handles long term memory states, where essentially, where essentially where we apply the matrix multiplication and Cilu activation functions into processing an input embedding and an output embedding. I'm oversimplifying it because this, This calculation changed every version and we have, like, version 7 right now.[00:24:50] Eugene Cheah: ChannelMix is similar to Base in the sense that it does shorter term attention, where it just looks at the sister token, or the token before it, because [00:25:00] there's a shift in the token shift matrix. I don't really want to go too much into the papers itself, because, like, we do have three papers on this.[00:25:09] Eugene Cheah: Basically, RWKB, RNN for the transformer, ERA, Ego and Pinch, RWKB, Matrix Value State. This is the updated version 5, version 6. And Goldfinch is our, is, is, is, is our hybrid model respectively. We are writing the paper already for V seven and which is, which is for R wk V seven. Called, named Goose, or architectures are named by Bird.[00:25:30] Eugene Cheah: And, I'm going to cover as well, qrwkb, and mama100k, and rwkb, and Where did that lead to? Great! Because we are all GPU poor and to be clear, like, most of this research is done, like, only on a handful H100s, which I had one Google researcher told me that was, like, his experiment budget for a single researcher.[00:25:48] Eugene Cheah: So, our entire organization has less compute than a single researcher in Google. So We, we, one of the things that we explored into was to how do we convert transformer models instead? Because [00:26:00] someone already paid that billion dollars, a million dollars onto training, so why don't we take advantage of those weights?[00:26:05] Eugene Cheah: And, and to, I believe, together AI worked on the lockets for, for the Lambda side of things, and, and we took some ideas from there as well, and we essentially did that for RWKB.[00:26:15] QWRKWv6 launch[00:26:15] Eugene Cheah: And that led to, Q RWKB6, which we just dropped today, a 32 bit instruct preview model, where we took the Quen 32 bit instruct model, freeze the feedforward layer, remove the QKB attention layer, and replace it with RWKB linear layers.[00:26:32] Eugene Cheah: So to be clear, this means we do not have the rwkv channel mix layer, we only have the time mix layer. But but once we do that, we train the rwkv layer. Important is that the feedforward layer needs to be frozen, so the new attention can be learned. And then we unfreeze the feedforward layer, and train all the layers together with a custom learning rate schedule, so that they can learn how to work together.[00:26:54] Eugene Cheah: The end result, surprisingly, And, to be honest, to the frustration of the R. W. [00:27:00] KV MOE team, which ended up releasing the model on the same day, was that, with just a few hours of training on two nodes, we managed to get it to be on par, kind of, with the original QUAN32B model. So, in fact, when the first run, right, that completely confused us, it was like, and I was telling Daniel Goldstein, Smirky, who kind of leads most of our research coordination, When you pitched me this idea, you told me at best you'll get the same level of performance.[00:27:26] Eugene Cheah: You didn't tell me the challenge and score and Winograd score will shoot up. I don't know what's happening there. But it did. MMLU score dropping, that was expected. Because if you think about it, when we were training all the layers, right, we were essentially Like, Frankenstein this thing, and we did brain damage to the feedforward network layer 2 with the new RWKB layers.[00:27:47] Eugene Cheah: But, 76%, hey, somehow it's retained, and we can probably further train this. We didn't even spend more than 3 days training this, so there's a lot more that can be done, hence the preview. This brings up [00:28:00] a big question, because We are already now in the process of converting to 7TB. We are now, this is actually extremely compute efficient to test our attention mechanic.[00:28:10] Eugene Cheah: It's like, it becomes a shortcut. We can, we are already planning to do our version 7 and our hybrid architecture for it. Because we don't need to train from scratch. And we get a really good model out of it. And the other thing that is uncomfortable to say is that because we are doing right now on the 70b is that if this scales correctly to 128k context length, I'm not even talking about a million 128, majority of enterprise workload today is just on 70b at under 32k context length.[00:28:41] Eugene Cheah: That means if this works and the benchmark matches it, It means we can replace the vast majority of current AI workload, unless you want super long context. And then sorry, can someone give us more GPUs? Because we do need the VRAM for super long context, sadly. So yeah, that's what we are working on, and essentially, [00:29:00] we are excited about this to just push it further.[00:29:02] Eugene Cheah: And this conversion process, to be clear, I don't think it's going to be exclusive to RWKB. It probably will work for Mamba as well, I don't see why not. And we will probably see more ideas, or more experiments, or more hybrids, or Yeah, like, one of the weirdest things that I wanted to say outright, and I confirmed this with the Black Mamba team and the Jamba team, which because we did the GoFinch hybrid model, is that none of us understand why a hard hybrid with a state based model to be R.[00:29:28] Eugene Cheah: QA state space and transformer performs better when, than the baseline of both. It's like, it's like when you train one, you expect, and then you replace, you expect the same results. That's our pitch. That's our claim. But somehow when we jam both together, it outperforms both. And that's like one area of emulation that, like, we only have four experiments, plus four teams, that a lot more needs to be done.[00:29:51] Eugene Cheah: But, but these are things that excite me, essentially, because that is what it's potentially we can move ahead for. Which brings us to what comes next.[00:30:00] What's next[00:30:00] [00:30:00][00:30:00] Dan Fu: So, this part is kind of just some, where we'll talk a little bit about stuff that, that we're excited about. Maybe have some wild speculation on, on what, what's, what's coming next.[00:30:12] Dan Fu: And, of course this is also the part that will be more open to questions. So, a couple things that, that I'm excited about is continued hardware model co design for, for these models. So one of the things that we've put out recently is this library called ThunderKittens. It's a CUDA library.[00:30:29] Dan Fu: And one of the things that, that we found frustrating is every time that we built one of these new architectures, and I'm sure you had the exact same experience, we'd have to go and spend two months in CUDA land, like writing these, these new efficient things. And. If we decided to change one thing in PyTorch, like one line of PyTorch code is like a week of CUDA code at least.[00:30:47] Dan Fu: So one of our goals with, with a library like Thunderkitten, so we, we just broke down what are the key principles, what are the key hardware things what are the key, Compute pieces that you get from the hardware. So for example on [00:31:00] H100 everything is really revolves around a warp group matrix multiply operation.[00:31:06] Dan Fu: So you really want your operation to be able to split into relatively small matrix, matrix multiply operations. So like multiplying two 64 by 64 matrices, for example. And so if you know that ahead of time when you're designing your model, that probably gives you you know, some information about how you set the state sizes, how you set the update, how you set the update function.[00:31:27] Dan Fu: So with Thunderkittens we basically built a whole library just around this basic idea that all your basic compute primitives should not be a float, but it should be a matrix, and everything should just be matrix compute. And we've been using that to, to try to both re implement some existing architectures, and also start to design code.[00:31:44] Dan Fu: Some new ones that are really designed with this core with a tensor core primitive in mind. Another thing that that we're, that at least I'm excited about is we, over the last four or five years, we've really been looking at language models as the next thing. But if you've been paying [00:32:00] attention to Twitter there's been a bunch of new next generation models that are coming out.[00:32:04] Dan Fu: So there, there are. So, video generation models that can run real time, that are supported by your mouse and your keyboard, that I'm told if you play with them that, you know, that they only have a few seconds of memory. Can we take that model, can we give it a very long context length so that you could actually maybe generate an entire game state at a time?[00:32:25] Dan Fu: What does that look like for the model? You're certainly not going to do a giant quadratic attention computation to try to run that. Maybe, maybe use some of these new models, or some of these new video generation models that came out. So Sora came out I don't know, two days ago now. But with super long queue times and super long generation times.[00:32:43] Dan Fu: So that's probably a quadratic attention operation at the, at the bottom of it. What if we could remove that and get the same quality, but a lot faster generation time? Or some of the demos that we saw from Paige earlier today. You know, if I have a super long conversation with my [00:33:00] Gemini bot, what if I wanted to remember everything that it's seen in the last week?[00:33:06] Dan Fu: I mean, maybe you don't for personal reasons, but what if I did, you know? What does that mean for the architecture? And I think, you know, that's certainly something I'm pretty excited about. I'm sure you're excited about it too. So, I think we were supposed to have some hot takes, but I honestly don't remember what our hot takes were.[00:33:21] Hot Takes - does anyone really need long context?[00:33:21] Eugene Cheah: Yeah, including the next slide. Hot takes, yes, these are our[00:33:25] Dan Fu: hot takes.[00:33:25] Eugene Cheah: I think the big one on Twitter that we saw, that we shared, was the question is like, is RAG relevant? In the case of, like, the future of, like, state based models?[00:33:38] Dan Fu: Let's see, I haven't played too much with RAG. But when I have. I'll say I found it was a little bit challenging to do research on it because we had this experience over and over again, where you could have any, an embedding model of any quality, so you could have a really, really bad embedding model, or you could have a really, really [00:34:00] good one, By any measure of good.[00:34:03] Dan Fu: And for the final RAG application, it kind of didn't matter. That's what I'll say about RAG while I'm being recorded. I know it doesn't actually answer the question, but[00:34:13] Eugene Cheah: Yeah, so I think a lot of folks are like, extremely excited of the idea of RWKB or State Space potentially having infinite context.[00:34:21] Eugene Cheah: But I think the reality is that when we say infinite context, we just mean a different kind of infinite context, or you, or as it's previously covered, you need to test the model differently. So, think of it more along the lines of the human. Like, I don't remember what I ate for breakfast yesterday.[00:34:37] Eugene Cheah: Yeah, that's the statement that I'll say. And And we humans are not quadratic transformers. If we did, if let's say we increased our brain size for every second we live, we would have exploded by the time we are 5 years old or something like that. And, and I think, I think basically fundamentally for us, right, be it whether we, regardless of whether RWKB, statespace, XLSTM, [00:35:00] etc, our general idea is that instead of that expanding state, that increase in computational cost, what if we have a fixed state size?[00:35:08] Eugene Cheah: And Information theory detects that that fixed state size will have a limit. Just how big of a limit is a question, like, we, like, RWKB is running at 40 megabytes for, for its state. Its future version might run into 400 megabytes. That is like millions of tokens in, if you're talking about mathematically, the maximum possibility.[00:35:29] Eugene Cheah: It's just that I guess we were all more inefficient about it, so maybe we hit 100, 000. And that's kind of like the work we are doing, trying to like push it and maximize it. And that's where the models will start differing, because it will choose to forget things, it will choose to remember things. And that's why I think that there might be some element of right, but it may not be the same right.[00:35:49] Eugene Cheah: It may be the model learn things, and it's like, hmm, I can't remember that, that article. Let me do a database search, to search. Just like us humans, when we can't remember the article in the company. We do a search on Notion. [00:36:00][00:36:00] Dan Fu: I think something that would be really interesting is if you could have facts that are, so right now, the one intuition about language models is that all those parameters are around just to store random facts about the world.[00:36:14] Dan Fu: And this intuition comes from the observation that if you take a really small language model, it can do things like talk to you, or kind of has like the The style of conversation, it can learn that, but where it will usually fall over compared to a much larger one is it'll just be a lot less factual about things that it knows or that it can do.[00:36:32] Dan Fu: But that points to all those weights that we're spending, all that SGD that we're spending to train these models are just being used to store facts. And we have things like databases that are pretty good at storing facts. So I think one thing that would be really interesting is if we could actually have some sort of outside data store that a language model can can look at that that maybe is you know, has has some sort of gradient descent in it, but but would be quite interesting.[00:36:58] Dan Fu: And then maybe you could edit it, delete [00:37:00] facts, you know, change who's president so that it doesn't, it doesn't get lost.[00:37:04] Vibhu: Can we open up Q& A and hot takes for the audience? I have a hot take Q& A. Do these scale? When, when 405B state space model, RAG exists, no one does long context, who's throwing in 2 million token questions, hot takes?[00:37:24] Dan Fu: The, the who's throwing in 2 million token question, I think, is, is a really good question. So I actually, I was going to offer that as a hot take. I mean, my hot take was going to be that long context doesn't matter. I know I just gave a whole talk about it, but you know, what, what's the point of doing research if you can't, you know, play both sides.[00:37:40] Dan Fu: But I think one of the, so I think for both of us, the reason that we first got into this was just from the first principled questions of there's this quadratic thing. Clearly intelligence doesn't need to be quadratic. What is going on? Can we understand it better? You know, since then it's kind of turned into a race, which has [00:38:00] been exciting to watch, like, how much context you can take in.[00:38:03] Dan Fu: But I think it's right. Nobody is actually putting in a two million context prompt into these models. And, and, you know, if they are, maybe we can go, go You know, design a better model to do that particular thing. Yeah, what do you think about that? So you've also been working on this. Do you think long context matters?[00:38:19] Eugene Cheah: So I'm going to burn a bit. How many of you remember the news of Google Gemini supporting 3 million contacts, right? Raise your hand.[00:38:28] Vibhu: Yeah, 2 million.[00:38:29] Eugene Cheah: Oh, it's 2 million.[00:38:31] Eugene Cheah: Yeah, how many of you actually tried that? See?[00:38:34] Vibhu: I use it a lot. You? You work for MindsTV. I use it a lot.[00:38:41] Eugene Cheah: So, for some people that has used, and I think, I think that's the, that's might be, like, this is where my opinion starts to differ, because I think the big labs may have a bigger role in this, because Like, even for RWKB, even when we train non contacts, the reason why I say VRAM is a problem is that because when we did the, we need to backprop [00:39:00] against the states, we actually need to maintain the state in between the tokens by the token length.[00:39:05] Eugene Cheah: So that means we need to actually roll out the whole 1 million contacts if we are actually training 1 million. Which is the same for transformers, actually, but it just means we don't magically reuse the VRAM consumption in the training time space. So that is one of the VRAM bottlenecks, and I'm neither OpenAI nor Google, so donate GPUs if you have too much of them.[00:39:27] Eugene Cheah: But then, putting it back to another paradigm, right, is that I think O1 style reasoning might be actually pushing that direction downwards. In my opinion, this is my partial hot take is that if, let's say you have a super big model, And let's say you have a 70B model that may take double the tokens, but gets the same result.[00:39:51] Eugene Cheah: Strictly speaking, a 70B, and this is even for transformer or non transformer, right? We we'll take less less resources than that 400 B [00:40:00] model, even if it did double the amount thinking. And if that's the case, and we are still all trying to figure this out, maybe the direction for us is really getting the sub 200 B to be as fast as efficient as possible.[00:40:11] Eugene Cheah: We a very efficient architecture that some folks happen to be working on to, to just reason it out over larger and larger context thing.[00:40:20] Question: Yeah. One thing I'm super interested in is. Models that can watch forever? Obviously you cannot train something on infinite context length. How are y'all thinking about that, where you run on a much longer context length than is possible to train on?[00:40:38] Dan Fu: Yeah, it's a, it's a great question. So I think when I think you guys probably had tweets along these lines, too. When we first started doing these things, because these are all recurrent models in theory you could just run it forever. You could just run it forever. And at the very least it won't, it won't like error out on your crash.[00:40:57] Dan Fu: There's another question of whether it can actually [00:41:00] use what it's seen in that infinite context. And I think there, so one place where probably the research and architectures ran faster Then another research is actually the benchmarks for long context. So you turn it on forever. You want to do everything or watch everything.[00:41:16] Dan Fu: What is it that you actually wanted to do? Can we actually build some benchmarks for that? Then measure what's happening. And then ask the question, can the models do it? Is there something else that they need? Yeah, I think that if I were to turn back the clock to 2022, that's probably one of the things I would have done differently, which would have been actually get some long context benchmarks out at the same time as we started pushing context length on all these models.[00:41:41] Eugene Cheah: I will also say the use case. So like, I think we both agree that there's no Infinite memory and the model needs to be able to learn and decide. I think what we have observed for, I think this also fits the state space model, is that one of the key advantages of this alternate attention mechanic that is not based on token position is that the model don't suddenly become crazy when you go past the [00:42:00] 8k training context tank, or a million context tank.[00:42:03] Eugene Cheah: It's actually still stable. It's still able to run, it's still able to rationalize. It just starts forgetting things. But some of these things are still there in latent memory. Some of these things are still somewhat there. That's the whole point of why reading twice works. Things like that. And one of the biggest pushes in this direction is that I think both Statespace and RWKB have Separate papers by other researchers where they use this architecture for time series data.[00:42:26] Eugene Cheah: Weather modeling. So, you are not asking what was the weather five days ago. You're asking what's the weather tomorrow based on the infinite length that we, as long as this Earth and the computer will keep running. So, so, and they found that it is like, better than existing, like, transformer or existing architecture in modeling this weather data.[00:42:47] Eugene Cheah: Control for the param size and stuff. I'm quite sure there are people with larger models. So, so there are things that, that in this case, right, there is future applications if your question is just what's next and not what's 10 years ago.[00:42:59] Dan Fu: Thanks so [00:43:00] much for having us. Get full access to Latent Space at www.latent.space/subscribe

Enhance security, performance, and user experience with Windows 11, version 24H2. Keep your data and identity protected with features like personal data encryption, Windows Hello with passkeys, and Windows Studio Effects. Built-in AI capabilities, including live captions with real-time translation and advanced video call enhancements, leverage powerful NPUs for seamless, efficient performance. Whether you're a business professional or a creative, Windows 11, version 24H2 offers significant improvements in productivity, energy efficiency, and multitasking capabilities. Deployment and migration is straightforward, ensuring compatibility with most existing hardware and peripherals. Tools like Windows Autopatch and Windows Autopilot, integrated with Microsoft Intune, streamline the update and provisioning processes, making device setup and compliance effortless. Jeremy Chapman, Director of Microsoft 365 shares how Windows 11, version 24H2 ensures your organization stays secure, productive, and ready for the future.   ► QUICK LINKS: 00:00 - Windows 11, version 24H2 00:51 - Personal Data Encryption 02:20 - Windows Hello with passkeys 03:26 - Default proactive protection 04:01 - Windows 11, version 24H2 updates 05:35 - Accessibility updates 06:03 - AI capabilities- live captions 07:13 - Built-in AI—Windows Studio Effects 08:29 - Performance and efficiency 09:13 - Deployment and migration 10:25 - Windows Autopatch 11:36 - Windows Autopilot 12:29 - Wrap up   ► Link References Get started at https://aka.ms/Windows11Enterprise    ► Unfamiliar with Microsoft Mechanics?  As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast   ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics  • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics

Avram Pilch - Tom's Hardware joins Paul Spain to dive into the intriguing world of the newest premium laptops and the nuances surrounding ARM processor technology and Windows Copilot+ PCs. Here's a rundown of the key insights and discussions from the episode:The Qualcomm X Elite Processors: Performance vs. PracticalityBattery Life: Reality vs. ClaimsThe Rise of ARM ProcessorsExclusive Features and Software CompatibilitySpecial thanks to our show partners: One NZ, 2degrees, Spark NZ, HP, and Gorilla Technology.

We're following one simple rule to build a Linux desktop so stable it could outlive us.Sponsored By:Tailscale: Tailscale is a programmable networking software that is private and secure by default - get it free on up to 100 devices!Kolide: Kolide is a device trust solution for companies with Okta, and they ensure that if a device isn't trusted and secure, it can't log into your cloud apps.Core Contributor Membership: Save $3 a month on your membership, and get the Bootleg and ad-free version of the show. Code: MAYSupport LINUX UnpluggedLinks:

This week it's all about the GPUs, with KDE 6.1, Nvidia's 555 drivers, and Mesa 24.1 all coming out, bringing support for Explicit sync, the Nvidia NVK ready for prime time, and more. Then there's Handbreak with FFmpeg 7.0 support, Ventoy bringing an update, and a new Pipewire RC with support for snapcast. Then there's Hans Reiser's last request for ReiserFS making it into kernel 6.10. For tips, we have the Bluefish editor, The last of Spring Cleaning, and how to use docker to very quickly spin up one-off containers. See the show notes at https://bit.ly/3yxtdwn and come back next time! Host: Jonathan Bennett Co-Hosts: Ken McDonald and Jeff Massie Want access to the video version and exclusive features? Become a member of Club TWiT today! https://twit.tv/clubtwit Club TWiT members can discuss this episode and leave feedback in the Club TWiT Discord.

En este episodio, analizamos los nuevos procesadores Snapdragon X en los portátiles Windows CoPilot+ y su desafío al MacBook Air. También cubrimos las últimas actualizaciones de Microsoft Windows centradas en funciones de IA. ¡No te lo pierdas!Productos mencionados:Shop Copilot+ PCs | MicrosoftMicrosoft Surface Pro Copilot+Meet the new Surface Laptop 7th Edition, a Copilot+ PCHP OmniBook X Laptop AI PC - 14-fe000, 14"HP EliteBook Ultra 14 inch G1q Notebook AI PCDell XPS 13 Laptop - Thin Laptops | Dell USAGalaxy Book4 Edge, 14", Snapdragon X Elite, 512GB, Sapphire Blue | Samsung USASUS Vivobook S15 (S5507) Laptop; Copilot+ PCYoga Slim 7x (14″ Snapdragon): A Copilot+ PC | AI-Powered Laptop for Creators | Lenovo USEnlaces a las noticias destacadas:Microsoft Debuts New Copilot+ Windows PCs Designed Around AI - MacRumorsHere are all of the just-announced Copilot+ PCs with Snapdragon X Chips

Send Everyday AI and Jordan a text messageDid Google say 'AI' too many times at their I/O conference? But real talk – it's hard to make sense of all of Google's announcements. With so many new products, updated functionality, and new LLM capabilities, how can you make sense of it all?  Oh.... that's what we're for. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on Google AIRelated Episode:  Ep 204: Google Gemini Advanced – 7 things you need to knowUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Google's Updates and Announcements2. Google AI Evaluations3. Concerns Over Google's AI Development and MarketingTimestamps:01:30 Daily AI news05:30 What was announced at Google's I/O09:31 Microsoft and Google introduce AI for teams.12:38 AI features not available for paid accounts.16:12 Doubt Google's claims about their Gemini model.19:26 Speaker live-drew with Pixel phone, discussed code.22:24 Exciting city scene, impressive Vio and Astra.24:44 Gems and GPTs changing interactions with language models.29:26 Accessing advanced features requires technical know-how.33:45 Concerns about availability and timing of Google's features.36:14 Google CEO makes joke about overusing buzzwords.41:06 Google Gems: A needed improvement for Google Gemini.41:50 GPT 4 ranks 4th behind Windows Copilot.Keywords:Google IO conference, AI updates, NVIDIA revenue growth, Meta acquisition, Adapt AI startup, OpenAI deal, News Corp, Project Astra, Gemini AI agent, Gemini 1.5 pro, Ask photos powered by Gemini, Gemini Nano, Android 15, GEMS, Google AI teammate, Microsoft team copilot, Google Workspace, Google search, Veo, Imagine 3, Lyria, Google's AI music generator, Wyclef Jean, Large language models, GPT 4.0, Google Gemini, AI marketing tactics, Deceptive marketing, Discoverability issues, Branding issues. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Windows 11 and the Copilot+ PC Microsoft announces Copilot+ PC and our world collapses Microsoft announces new Surface Pro and Surface Laptop 13/15 as expected What the heck is this new bifurcation of features in Windows? Why? Paul ordered a Surface Laptop 15 the second Yusuf Mehdi said he could The other shoe finally drops: Every Copilot+ Pro PC has a fan. Is this a problem? Sorry, Chicken Little, Microsoft Recall is not a privacy concern Windows 11 is getting a lot of new security features Qualcomm is offering a $899 Copilot+ PC Mini and it looks awesome Windows 11 24H2 just entered the Release Preview channel Inside baseball Everyone is mad at Microsoft about Monday's event Intel had people on-site to attend and present, Microsoft took their badges away and asked them to leave (AMD seemingly placated by Build keynote mentions). Intel countered with its own pissy announcement Qualcomm, the darling of the event, would like to know why it took Microsoft 40 minutes to say the word "Snapdragon" PC makers were told they would get equal billing with Surface, but they were afterthoughts during the event and at the showcase Microsoft 365 Microsoft Announces Team Copilot Microsoft adds new features to Microsoft Teams Microsoft Edge is getting a real-time translation feature AI Microsoft adds a multimodal model to its Phi family of on-device SLMs Microsoft brings Copilots to developers, updates Power Platform Microsoft partners with Khan Academy on AI training Dev Microsoft announces Windows Copilot runtime, but it's not a runtime Also, WTFF WPF is BACK with WinUI support too! Visual Studio 2022 17.10 adds integrated GitHub Copilot Plus some .NET 9 updates in pre-release Windows 11 24H2 is getting a bunch of new features for developers Tips & Picks Tip of the Week: Windows 11 Security Book & Surface Laptop Report RunAs Radio This Week: The End of Windows 10 with Paul Thurrott Brown Liquor: Eagle Rare 10 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww HP.com - WW - https://bit.ly/4adilko

Windows 11 and the Copilot+ PC Microsoft announces Copilot+ PC and our world collapses Microsoft announces new Surface Pro and Surface Laptop 13/15 as expected What the heck is this new bifurcation of features in Windows? Why? Paul ordered a Surface Laptop 15 the second Yusuf Mehdi said he could The other shoe finally drops: Every Copilot+ Pro PC has a fan. Is this a problem? Sorry, Chicken Little, Microsoft Recall is not a privacy concern Windows 11 is getting a lot of new security features Qualcomm is offering a $899 Copilot+ PC Mini and it looks awesome Windows 11 24H2 just entered the Release Preview channel Inside baseball Everyone is mad at Microsoft about Monday's event Intel had people on-site to attend and present, Microsoft took their badges away and asked them to leave (AMD seemingly placated by Build keynote mentions). Intel countered with its own pissy announcement Qualcomm, the darling of the event, would like to know why it took Microsoft 40 minutes to say the word "Snapdragon" PC makers were told they would get equal billing with Surface, but they were afterthoughts during the event and at the showcase Microsoft 365 Microsoft Announces Team Copilot Microsoft adds new features to Microsoft Teams Microsoft Edge is getting a real-time translation feature AI Microsoft adds a multimodal model to its Phi family of on-device SLMs Microsoft brings Copilots to developers, updates Power Platform Microsoft partners with Khan Academy on AI training Dev Microsoft announces Windows Copilot runtime, but it's not a runtime Also, WTFF WPF is BACK with WinUI support too! Visual Studio 2022 17.10 adds integrated GitHub Copilot Plus some .NET 9 updates in pre-release Windows 11 24H2 is getting a bunch of new features for developers Tips & Picks Tip of the Week: Windows 11 Security Book & Surface Laptop Report RunAs Radio This Week: The End of Windows 10 with Paul Thurrott Brown Liquor: Eagle Rare 10 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww HP.com - WW - https://bit.ly/4adilko

Windows 11 and the Copilot+ PC Microsoft announces Copilot+ PC and our world collapses Microsoft announces new Surface Pro and Surface Laptop 13/15 as expected What the heck is this new bifurcation of features in Windows? Why? Paul ordered a Surface Laptop 15 the second Yusuf Mehdi said he could The other shoe finally drops: Every Copilot+ Pro PC has a fan. Is this a problem? Sorry, Chicken Little, Microsoft Recall is not a privacy concern Windows 11 is getting a lot of new security features Qualcomm is offering a $899 Copilot+ PC Mini and it looks awesome Windows 11 24H2 just entered the Release Preview channel Inside baseball Everyone is mad at Microsoft about Monday's event Intel had people on-site to attend and present, Microsoft took their badges away and asked them to leave (AMD seemingly placated by Build keynote mentions). Intel countered with its own pissy announcement Qualcomm, the darling of the event, would like to know why it took Microsoft 40 minutes to say the word "Snapdragon" PC makers were told they would get equal billing with Surface, but they were afterthoughts during the event and at the showcase Microsoft 365 Microsoft Announces Team Copilot Microsoft adds new features to Microsoft Teams Microsoft Edge is getting a real-time translation feature AI Microsoft adds a multimodal model to its Phi family of on-device SLMs Microsoft brings Copilots to developers, updates Power Platform Microsoft partners with Khan Academy on AI training Dev Microsoft announces Windows Copilot runtime, but it's not a runtime Also, WTFF WPF is BACK with WinUI support too! Visual Studio 2022 17.10 adds integrated GitHub Copilot Plus some .NET 9 updates in pre-release Windows 11 24H2 is getting a bunch of new features for developers Tips & Picks Tip of the Week: Windows 11 Security Book & Surface Laptop Report RunAs Radio This Week: The End of Windows 10 with Paul Thurrott Brown Liquor: Eagle Rare 10 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww HP.com - WW - https://bit.ly/4adilko

Windows 11 and the Copilot+ PC Microsoft announces Copilot+ PC and our world collapses Microsoft announces new Surface Pro and Surface Laptop 13/15 as expected What the heck is this new bifurcation of features in Windows? Why? Paul ordered a Surface Laptop 15 the second Yusuf Mehdi said he could The other shoe finally drops: Every Copilot+ Pro PC has a fan. Is this a problem? Sorry, Chicken Little, Microsoft Recall is not a privacy concern Windows 11 is getting a lot of new security features Qualcomm is offering a $899 Copilot+ PC Mini and it looks awesome Windows 11 24H2 just entered the Release Preview channel Inside baseball Everyone is mad at Microsoft about Monday's event Intel had people on-site to attend and present, Microsoft took their badges away and asked them to leave (AMD seemingly placated by Build keynote mentions). Intel countered with its own pissy announcement Qualcomm, the darling of the event, would like to know why it took Microsoft 40 minutes to say the word "Snapdragon" PC makers were told they would get equal billing with Surface, but they were afterthoughts during the event and at the showcase Microsoft 365 Microsoft Announces Team Copilot Microsoft adds new features to Microsoft Teams Microsoft Edge is getting a real-time translation feature AI Microsoft adds a multimodal model to its Phi family of on-device SLMs Microsoft brings Copilots to developers, updates Power Platform Microsoft partners with Khan Academy on AI training Dev Microsoft announces Windows Copilot runtime, but it's not a runtime Also, WTFF WPF is BACK with WinUI support too! Visual Studio 2022 17.10 adds integrated GitHub Copilot Plus some .NET 9 updates in pre-release Windows 11 24H2 is getting a bunch of new features for developers Tips & Picks Tip of the Week: Windows 11 Security Book & Surface Laptop Report RunAs Radio This Week: The End of Windows 10 with Paul Thurrott Brown Liquor: Eagle Rare 10 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww HP.com - WW - https://bit.ly/4adilko

Two old guys talk about Windows AGAIN? Richard brings back Paul Thurrott for the tenth time to discuss Windows more. This time, the discussion focuses on the end of life for Windows 10 - currently October 2025. Paul discusses how it used to be April 2025, but that's not enough time. Is it enough time now? The conversation spans other Windows-related topics, including alternative versions like Windows 365 and Azure Virtual Desktop. And what about Windows 12? There is a bit of speculation at the end of a longer show - weigh in with your thoughts on what's next for Windows!LinksEnd of Support for Windows 10, 8.1, and 7Windows AutopilotWindows CopilotMicrosoft IntuneWindows 365Microsoft EntraAzure Virtual DesktopRecorded April 26, 2024

Windows 11 and the Copilot+ PC Microsoft announces Copilot+ PC and our world collapses Microsoft announces new Surface Pro and Surface Laptop 13/15 as expected What the heck is this new bifurcation of features in Windows? Why? Paul ordered a Surface Laptop 15 the second Yusuf Mehdi said he could The other shoe finally drops: Every Copilot+ Pro PC has a fan. Is this a problem? Sorry, Chicken Little, Microsoft Recall is not a privacy concern Windows 11 is getting a lot of new security features Qualcomm is offering a $899 Copilot+ PC Mini and it looks awesome Windows 11 24H2 just entered the Release Preview channel Inside baseball Everyone is mad at Microsoft about Monday's event Intel had people on-site to attend and present, Microsoft took their badges away and asked them to leave (AMD seemingly placated by Build keynote mentions). Intel countered with its own pissy announcement Qualcomm, the darling of the event, would like to know why it took Microsoft 40 minutes to say the word "Snapdragon" PC makers were told they would get equal billing with Surface, but they were afterthoughts during the event and at the showcase Microsoft 365 Microsoft Announces Team Copilot Microsoft adds new features to Microsoft Teams Microsoft Edge is getting a real-time translation feature AI Microsoft adds a multimodal model to its Phi family of on-device SLMs Microsoft brings Copilots to developers, updates Power Platform Microsoft partners with Khan Academy on AI training Dev Microsoft announces Windows Copilot runtime, but it's not a runtime Also, WTFF WPF is BACK with WinUI support too! Visual Studio 2022 17.10 adds integrated GitHub Copilot Plus some .NET 9 updates in pre-release Windows 11 24H2 is getting a bunch of new features for developers Tips & Picks Tip of the Week: Windows 11 Security Book & Surface Laptop Report RunAs Radio This Week: The End of Windows 10 with Paul Thurrott Brown Liquor: Eagle Rare 10 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww HP.com - WW - https://bit.ly/4adilko

Karthik Mahadevan, CEO at Envision, will delve into the upgrades in the new Envision Glasses v.2.5 featuring a new interactive describe scene powered by GPT-4 Vision by Open AI & multilingual voice commands. That's not all! Exciting changes landed on the Envision App and future updates are set to revolutionize the user experience and create a more accessible world. Hear more from Karthik! In the second hour we dive deep into Windows Copilot and Coipilot Pro and even give some demonstrations of their use. Sponsored by the Information Access Committee 24 Episode Notes Notes go here

We are back again this week to discuss, among other things, just how super the GeForce RTX 4070 SUPER actually is. There are also some weird tales about display tech at CES, thermal pad vs. paste, more Windows LLM shenanigans, and even a new version of memtest86!  But wait!  There's some "great" security scares (and theater?) with some gaming news thrown in too!Timestamps:00:00 Intro01:36 Food with Josh03:07 NVIDIA GeForce RTX 4070 SUPER launch19:48 Weird displays at CES24:41 Is this the year to dump thermal paste for a pad?28:38 Windows Copilot autostart tests limited to larger displays29:52 ChatGPT is coming to Notepad (ugh)30:58 The Hobbes OS/2 Archive is logging off33:49 A new version of memtest86!35:01 Podcast sponsor: GreenChef36:30 (in)Security Corner44:50 Gaming Quick Hits51:08 Picks of the Week1:03:13 Outro ★ Support this podcast on Patreon ★

In Episode 354, Ben and Scott catch up on news and the latest announcements starting with Cisco and Splunk merging. Then they discuss the Surface and AI event where we saw the latest Surface hardware and learned about the straight to GA release of Microsoft 365 and Windows Copilot. Like what you hear and want to support the show? Check out our membership options. Show Notes Cisco to Acquire Splunk, to Help Make Organizations More Secure and Resilient in an AI-Powered World Cisco and Splunk: Driving the Next Generation of AI-Enabled Security and Observability Announcing Microsoft 365 Copilot general availability and Microsoft 365 Chat How to transform work with plugins for Microsoft 365 Copilot and AI apps Microsoft's Surface and AI event: all the news and announcements We don't know how AI works. .We're trusting it anyway About the sponsors Intelligink utilizes their skill and passion for the Microsoft cloud to empower their customers with the freedom to focus on their core business. They partner with them to implement and administer their cloud technology deployments and solutions. Visit Intelligink.com for more info.

This Week in Startups is brought to you by… Vanta. Compliance and security shouldn't be a deal-breaker for startups to win new business. Vanta makes it easy for companies to get a SOC 2 report fast. TWiST listeners can get $1,000 off for a limited time at https://vanta.com/twist LinkedIn Jobs. A business is only as strong as its people, and every hire matters. Go to https://LinkedIn.com/TWIST to post your first job for free. Terms and conditions apply. Fitbod. Tired of doing the same workouts at the gym? Fitbod will build you personalized workouts that help you progress with every set. Get 25% off your subscription or try out the app for FREE when you sign up now at [https://fitbod.me/TWIST.](http://fitbod.me/TWIST.) * Today's show: Sunny joins Jason for more demos! Microsoft's Windows 11 Copilot (2:42), ChatGPT's multimodal features (28:37), and Meta's new AI chatbots (1:04:34) are all covered!! * Time stamps: (00:00) Sunny Madra joins Jason (2:42) Sunny demos Windows 11 Copilot preview (9:48) Vanta - Get $1000 off your SOC 2 at https://vanta.com/twist (10:55) Windows 11 Copilot to desktop interaction and areas needing improvement (15:06) Consequences of recording desktop interactions for AI and the final grade for Windows 11 Copilot (27:17) LinkedIn Jobs - Post your first job for free at https://linkedin.com/twist (28:37) Sunny demos ChatGPT's multimodal features (36:32) Fitbod - Get 25% off at https://fitbod.me/twist (38:01) Job destruction and AI's effects on the workplace (43:57) The utilization of multiple AI agents (46:05) ChatGPT's voice chat feature (52:24) Personalization and the path to AGI (1:02:09) Common Crawl and use of web crawl data (1:04:34) Meta's new AI chatbots * Follow Sunny: https://twitter.com/sundeep Check out Definitive Intelligence: https://www.definitive.io/ * Read LAUNCH Fund 4 Deal Memo: https://www.launch.co/four Apply for Funding: https://www.launch.co/apply Buy ANGEL: https://www.angelthebook.com Great recent interviews: Steve Huffman, Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason's suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

Check out five useful things you can do with Windows Copilot in Windows 11 that make finding your way around your PC much easier and faster.

EU investigates Teams, Loop in the Microsoft Store, Beta build 22631.2129 Windows Insider: Last week, Canary got features from Dev plus some new features of its own. Dev channel: Improved screen cast, HDR background support, more Voice access, presence sensing, more. Beta channel: Windows Copilot, Dev Drive, enhanced Narrator/Excel integration, new Voice access text authoring features, passwordless experience for Windows Hello for Business, plus screen cast, presence, and voice access from above. Intel is profitable again, hopeful for the future (and massive fab expansion in Oregon) AMD revenues fell 18 percent, but also some hope for the future Microsoft 365 The EU announces formal investigation of Teams bundling in Microsoft 365 Microsoft Teams gets spatial audio support Microsoft lowers storage allotments for M365 Education customers, kills Office 365 A1 Plus Clipchamp is coming to Microsoft 365 commercial (with OneDrive storage integration) Dev Microsoft to launch .NET 8 at .NET Conf in November Xbox CMA publishes Microsoft's list of "material changes" in its Activision Blizzard case, gives public four days for feedback Unexpectedly, not a single new concession, just a bunch of new "evidence" that appeared since the decision Xbox Games with Gold goes out with a whimper Here come the first August Game Pass titles Final Fantasy XIV Online is FINALLY coming to Xbox Microsoft starts testing game streaming from Xbox to Discord You can buy Xbox controller parts now Sony has now sold over 40 million PS5s EA revenues up 9 percent in Q2 Nintendo's next Switch to debut next year Microsoft is killing the Xbox Console Companion app, has never made a new solution for getting Xbox console screenshots and videos on the PC Tips and Picks Tip of the week: Enroll in the Windows Insider Beta channel if you want to test 23H2 App pick of the week: Loop for Windows is now available RunAs Radio this week: Windows 11 and Windows Update for Business with Julie Andreacola Brown liquor pick of the week: Angel's Envy Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsor: GO.ACILEARNING.COM/TWIT

EU investigates Teams, Loop in the Microsoft Store, Beta build 22631.2129 Windows Insider: Last week, Canary got features from Dev plus some new features of its own. Dev channel: Improved screen cast, HDR background support, more Voice access, presence sensing, more. Beta channel: Windows Copilot, Dev Drive, enhanced Narrator/Excel integration, new Voice access text authoring features, passwordless experience for Windows Hello for Business, plus screen cast, presence, and voice access from above. Intel is profitable again, hopeful for the future (and massive fab expansion in Oregon) AMD revenues fell 18 percent, but also some hope for the future Microsoft 365 The EU announces formal investigation of Teams bundling in Microsoft 365 Microsoft Teams gets spatial audio support Microsoft lowers storage allotments for M365 Education customers, kills Office 365 A1 Plus Clipchamp is coming to Microsoft 365 commercial (with OneDrive storage integration) Dev Microsoft to launch .NET 8 at .NET Conf in November Xbox CMA publishes Microsoft's list of "material changes" in its Activision Blizzard case, gives public four days for feedback Unexpectedly, not a single new concession, just a bunch of new "evidence" that appeared since the decision Xbox Games with Gold goes out with a whimper Here come the first August Game Pass titles Final Fantasy XIV Online is FINALLY coming to Xbox Microsoft starts testing game streaming from Xbox to Discord You can buy Xbox controller parts now Sony has now sold over 40 million PS5s EA revenues up 9 percent in Q2 Nintendo's next Switch to debut next year Microsoft is killing the Xbox Console Companion app, has never made a new solution for getting Xbox console screenshots and videos on the PC Tips and Picks Tip of the week: Enroll in the Windows Insider Beta channel if you want to test 23H2 App pick of the week: Loop for Windows is now available RunAs Radio this week: Windows 11 and Windows Update for Business with Julie Andreacola Brown liquor pick of the week: Angel's Envy Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsor: GO.ACILEARNING.COM/TWIT

EU investigates Teams, Loop in the Microsoft Store, Beta build 22631.2129 Windows Insider: Last week, Canary got features from Dev plus some new features of its own. Dev channel: Improved screen cast, HDR background support, more Voice access, presence sensing, more. Beta channel: Windows Copilot, Dev Drive, enhanced Narrator/Excel integration, new Voice access text authoring features, passwordless experience for Windows Hello for Business, plus screen cast, presence, and voice access from above. Intel is profitable again, hopeful for the future (and massive fab expansion in Oregon) AMD revenues fell 18 percent, but also some hope for the future Microsoft 365 The EU announces formal investigation of Teams bundling in Microsoft 365 Microsoft Teams gets spatial audio support Microsoft lowers storage allotments for M365 Education customers, kills Office 365 A1 Plus Clipchamp is coming to Microsoft 365 commercial (with OneDrive storage integration) Dev Microsoft to launch .NET 8 at .NET Conf in November Xbox CMA publishes Microsoft's list of "material changes" in its Activision Blizzard case, gives public four days for feedback Unexpectedly, not a single new concession, just a bunch of new "evidence" that appeared since the decision Xbox Games with Gold goes out with a whimper Here come the first August Game Pass titles Final Fantasy XIV Online is FINALLY coming to Xbox Microsoft starts testing game streaming from Xbox to Discord You can buy Xbox controller parts now Sony has now sold over 40 million PS5s EA revenues up 9 percent in Q2 Nintendo's next Switch to debut next year Microsoft is killing the Xbox Console Companion app, has never made a new solution for getting Xbox console screenshots and videos on the PC Tips and Picks Tip of the week: Enroll in the Windows Insider Beta channel if you want to test 23H2 App pick of the week: Loop for Windows is now available RunAs Radio this week: Windows 11 and Windows Update for Business with Julie Andreacola Brown liquor pick of the week: Angel's Envy Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsor: GO.ACILEARNING.COM/TWIT

EU investigates Teams, Loop in the Microsoft Store, Beta build 22631.2129 Windows Insider: Last week, Canary got features from Dev plus some new features of its own. Dev channel: Improved screen cast, HDR background support, more Voice access, presence sensing, more. Beta channel: Windows Copilot, Dev Drive, enhanced Narrator/Excel integration, new Voice access text authoring features, passwordless experience for Windows Hello for Business, plus screen cast, presence, and voice access from above. Intel is profitable again, hopeful for the future (and massive fab expansion in Oregon) AMD revenues fell 18 percent, but also some hope for the future Microsoft 365 The EU announces formal investigation of Teams bundling in Microsoft 365 Microsoft Teams gets spatial audio support Microsoft lowers storage allotments for M365 Education customers, kills Office 365 A1 Plus Clipchamp is coming to Microsoft 365 commercial (with OneDrive storage integration) Dev Microsoft to launch .NET 8 at .NET Conf in November Xbox CMA publishes Microsoft's list of "material changes" in its Activision Blizzard case, gives public four days for feedback Unexpectedly, not a single new concession, just a bunch of new "evidence" that appeared since the decision Xbox Games with Gold goes out with a whimper Here come the first August Game Pass titles Final Fantasy XIV Online is FINALLY coming to Xbox Microsoft starts testing game streaming from Xbox to Discord You can buy Xbox controller parts now Sony has now sold over 40 million PS5s EA revenues up 9 percent in Q2 Nintendo's next Switch to debut next year Microsoft is killing the Xbox Console Companion app, has never made a new solution for getting Xbox console screenshots and videos on the PC Tips and Picks Tip of the week: Enroll in the Windows Insider Beta channel if you want to test 23H2 App pick of the week: Loop for Windows is now available RunAs Radio this week: Windows 11 and Windows Update for Business with Julie Andreacola Brown liquor pick of the week: Angel's Envy Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsor: GO.ACILEARNING.COM/TWIT

On Windows Weekly, Leo Laporte, Paul Thurrott, and Rich Campbell chat about Microsoft's latest blockbuster quarter and fiscal year 2023. The hosts analyze the ups and downs of the tech company's earnings. Full episode at http://twit.tv/ww839  Hosts: Leo Laporte, Richard Campbell, and Paul Thurrott You can find more about TWiT and subscribe to our podcasts at https://podcasts.twit.tv/ Sponsor: GO.ACILEARNING.COM/TWIT

On this week's episode of the Window's Central Podcast, Dan and Zac discuss Windows Copilot & why Zac is disappointed with it, mainstream consumer AI use, all the fallout from Meta launching Threads, what it means for Twitter & social media going forward, review Robo & Kala's 2-In-1 laptop, and more! Links: First look at Windows Copilot - Windows Central Why Microsoft won't be the company to mainstream consumer AI use - Windows Central Meta's 'Threads' reaches 100 million users - Windows Central Windows Central Podcast Sponsors:  Indeed: Hire better with Indeed. Visit indeed.com/wcp to start hiring now. Follow us on Twitter: @Daniel_Rubino @ZacBowden

In Episode 341, Ben and Scott continue to dive into the confusion that is the note taking ecosystem in Microsoft 365 with the potential competition between OneNote and Loop, the formal retirement announcement for InfoPath Forms Services, and some more follow-up on Copilots and where you can use them in your day-to-day work. Like what you hear and want to support the show? Check out our membership options. Show Notes Default Notes tab in Microsoft Teams for Enterprise customers Meeting Details in OneNote Now in Public preview & Targeted release: Collaborative meeting notes in Teams meetings Now in public preview: Collaborative notes in Microsoft Teams Meetings Yammer.com Rebranded to Viva Engage Support update for InfoPath Forms Services in Microsoft 365 InfoPath Forms Services Assessment SharePoint Server 2019 Lifecycle Microsoft Lists: Easier, Better, Faster, Stronger SharePoint: Microsoft Lists- A new forms experience to collect information You can now try Windows Copilot and native RAR and 7-Zip support in Windows 11 Meeting recap in Microsoft Teams Video https://youtu.be/pOJClKla1f8 About the sponsors Intelligink utilizes their skill and passion for the Microsoft cloud to empower their customers with the freedom to focus on their core business. They partner with them to implement and administer their cloud technology deployments and solutions. Visit Intelligink.com for more info.

On Windows Weekly, Paul Thurrott gives a tip on how to get Copilot Preview for your Windows PC. He also recommends the book Office 365 for IT Pros 2024 Edition. Copilot tip: https://tinyurl.com/mrybkyse Full episode at http://twit.tv/ww836 Hosts: Paul Thurrott, Richard Campbell, and Leo Laporte You can find more about TWiT and subscribe to our podcasts at https://podcasts.twit.tv/ Sponsor: GO.ACILEARNING.COM/TWIT

EU's Big Tech gatekeepers, AI-powered shopping tools, Windows Copilot Preview The EU officially identified the first Big Tech "gatekeepers" that will be held to a higher regulatory standard, and Microsoft made the list. Amazon, Apple, Google, and Facebook (Meta) Plus, TikTok owner ByteDance (?) and Samsung Booking.com says it was notified it will be on the next list for some reason too What is the standard? What are the penalties for non-compliance? Microsoft to face EU antitrust investigation after discussions break down. Windows Microsoft JUST makes its self-imposed June deadline, releases first public preview of Windows Copilot to (some) Windows Insiders. Windows Copilot hands-on Windows 365 Frontline exits preview AI Microsoft adds new AI-powered shopping tools to Bing and Edge. I'm sure they won't just recommend Microsoft products. Google changes its privacy policy, admits it will scrape the Internet to train its models Hardware Hybrids bridge the gap between the new and the old, and they're all around us. In personal tech, the laptop was an early hybrid, but today's hybrids—like folding smartphones—are getting interesting and are inarguably the future of the premium, and then the mainstream, smartphone market. So much for "right tool for the job." Xbox Nadella claims he wants videogame exclusives to go away. This explains why Microsoft has purchased so man game studios, and why its wants Activision Blizzard. Somehow. What would a "mobile-native" version of Game Pass look like? And how could Microsoft get past the mobile gatekeepers? Microsoft announces its July Xbox Games with Gold titles Microsoft also announced its first Game Pass titles for July Tips & Picks Tip of the week #1: Enable Windows Copilot (Preview) Tip of the week #2: Get Office 365 for IT Pros 2024 Edition for $10 off App pick of the week #1: Stella App pick of the week #2: Firefox 115 RunAs this week: Power Platform Proliferation with Luise Freese Brown Liquor this week: Dewars 12 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww GO.ACILEARNING.COM/TWIT

EU's Big Tech gatekeepers, AI-powered shopping tools, Windows Copilot Preview The EU officially identified the first Big Tech "gatekeepers" that will be held to a higher regulatory standard, and Microsoft made the list. Amazon, Apple, Google, and Facebook (Meta) Plus, TikTok owner ByteDance (?) and Samsung Booking.com says it was notified it will be on the next list for some reason too What is the standard? What are the penalties for non-compliance? Microsoft to face EU antitrust investigation after discussions break down. Windows Microsoft JUST makes its self-imposed June deadline, releases first public preview of Windows Copilot to (some) Windows Insiders. Windows Copilot hands-on Windows 365 Frontline exits preview AI Microsoft adds new AI-powered shopping tools to Bing and Edge. I'm sure they won't just recommend Microsoft products. Google changes its privacy policy, admits it will scrape the Internet to train its models Hardware Hybrids bridge the gap between the new and the old, and they're all around us. In personal tech, the laptop was an early hybrid, but today's hybrids—like folding smartphones—are getting interesting and are inarguably the future of the premium, and then the mainstream, smartphone market. So much for "right tool for the job." Xbox Nadella claims he wants videogame exclusives to go away. This explains why Microsoft has purchased so man game studios, and why its wants Activision Blizzard. Somehow. What would a "mobile-native" version of Game Pass look like? And how could Microsoft get past the mobile gatekeepers? Microsoft announces its July Xbox Games with Gold titles Microsoft also announced its first Game Pass titles for July Tips & Picks Tip of the week #1: Enable Windows Copilot (Preview) Tip of the week #2: Get Office 365 for IT Pros 2024 Edition for $10 off App pick of the week #1: Stella App pick of the week #2: Firefox 115 RunAs this week: Power Platform Proliferation with Luise Freese Brown Liquor this week: Dewars 12 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww GO.ACILEARNING.COM/TWIT

EU's Big Tech gatekeepers, AI-powered shopping tools, Windows Copilot Preview The EU officially identified the first Big Tech "gatekeepers" that will be held to a higher regulatory standard, and Microsoft made the list. Amazon, Apple, Google, and Facebook (Meta) Plus, TikTok owner ByteDance (?) and Samsung Booking.com says it was notified it will be on the next list for some reason too What is the standard? What are the penalties for non-compliance? Microsoft to face EU antitrust investigation after discussions break down. Windows Microsoft JUST makes its self-imposed June deadline, releases first public preview of Windows Copilot to (some) Windows Insiders. Windows Copilot hands-on Windows 365 Frontline exits preview AI Microsoft adds new AI-powered shopping tools to Bing and Edge. I'm sure they won't just recommend Microsoft products. Google changes its privacy policy, admits it will scrape the Internet to train its models Hardware Hybrids bridge the gap between the new and the old, and they're all around us. In personal tech, the laptop was an early hybrid, but today's hybrids—like folding smartphones—are getting interesting and are inarguably the future of the premium, and then the mainstream, smartphone market. So much for "right tool for the job." Xbox Nadella claims he wants videogame exclusives to go away. This explains why Microsoft has purchased so man game studios, and why its wants Activision Blizzard. Somehow. What would a "mobile-native" version of Game Pass look like? And how could Microsoft get past the mobile gatekeepers? Microsoft announces its July Xbox Games with Gold titles Microsoft also announced its first Game Pass titles for July Tips & Picks Tip of the week #1: Enable Windows Copilot (Preview) Tip of the week #2: Get Office 365 for IT Pros 2024 Edition for $10 off App pick of the week #1: Stella App pick of the week #2: Firefox 115 RunAs this week: Power Platform Proliferation with Luise Freese Brown Liquor this week: Dewars 12 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww GO.ACILEARNING.COM/TWIT

EU's Big Tech gatekeepers, AI-powered shopping tools, Windows Copilot Preview The EU officially identified the first Big Tech "gatekeepers" that will be held to a higher regulatory standard, and Microsoft made the list. Amazon, Apple, Google, and Facebook (Meta) Plus, TikTok owner ByteDance (?) and Samsung Booking.com says it was notified it will be on the next list for some reason too What is the standard? What are the penalties for non-compliance? Microsoft to face EU antitrust investigation after discussions break down. Windows Microsoft JUST makes its self-imposed June deadline, releases first public preview of Windows Copilot to (some) Windows Insiders. Windows Copilot hands-on Windows 365 Frontline exits preview AI Microsoft adds new AI-powered shopping tools to Bing and Edge. I'm sure they won't just recommend Microsoft products. Google changes its privacy policy, admits it will scrape the Internet to train its models Hardware Hybrids bridge the gap between the new and the old, and they're all around us. In personal tech, the laptop was an early hybrid, but today's hybrids—like folding smartphones—are getting interesting and are inarguably the future of the premium, and then the mainstream, smartphone market. So much for "right tool for the job." Xbox Nadella claims he wants videogame exclusives to go away. This explains why Microsoft has purchased so man game studios, and why its wants Activision Blizzard. Somehow. What would a "mobile-native" version of Game Pass look like? And how could Microsoft get past the mobile gatekeepers? Microsoft announces its July Xbox Games with Gold titles Microsoft also announced its first Game Pass titles for July Tips & Picks Tip of the week #1: Enable Windows Copilot (Preview) Tip of the week #2: Get Office 365 for IT Pros 2024 Edition for $10 off App pick of the week #1: Stella App pick of the week #2: Firefox 115 RunAs this week: Power Platform Proliferation with Luise Freese Brown Liquor this week: Dewars 12 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: kolide.com/ww GO.ACILEARNING.COM/TWIT

For more than four decades, since the 1980s, pointing and clicking has been the primary method of using a personal computer. What if that changed to simply thinking, typing and doing? That's one promise of AI. Rather than remembering the keyboard shortcut to take a screenshot, or the setting to shift the screen into dark mode, you could just tell the computer what you want it to do in natural language. Microsoft is moving in this direction with the development of Windows Copilot, an adaptation of its Open AI-powered Bing search chatbot integrated directly into the operating system, showing as a persistent sidebar once activated by users via a new taskbar button. This week, the company started to give users in the Windows Insider preview program a very early look at Windows Copilot.  On this episode of the GeekWire Podcast, we're featuring a conversation with Aaron Woodman, the Windows vice president of marketing, recorded shortly after Windows Copilot was unveiled a few weeks ago.  Here is the full video of Windows Central's hands-on with the Windows Insider early preview of Windows Copilot, as highlighted in the intro to this episode. With GeekWire co-founder Todd Bishop.See omnystudio.com/listener for privacy information.

Cortana's Windows death, 3 months with no Xbox, thoughts on WWDC23 Developer Story As the developer conference season winds down with WWDC, a look at how Apple, Google, and Microsoft are both similar to and different from each other Hololens flashbacks anyone? Windows She's dead, Jim: Microsoft kills Cortana in Windows 10, 11 - this is all about marketing Teams for Windows (consumer) gets new features that no one will notice either Windows Insider Preview: Microsoft Paint gets Dark mode support (FINALLY) and more in Canary and Dev Canary: New build brings SMB signing requirement (Enterprise ed only), camera app troubleshooting (plus new build today) Dev (new): redesigned Home view for File Explorer, modernized address bar and search box, Dynamic Lighting settings Dev: File Explorer tabs and gallery view improvements, Add Phone Photos button for setting up OneDrive camera roll Beta: WPA3 support in Phone Link, fixes Microsoft Edge arrives with Workspaces (but not the new UI) Brave finally gets vertical tabs One week after HP, Dell posts 20 percent revenue fall Xbox Well, Paul finally did it: 3 months without Xbox WD Xbox Series X|S expansion cards start at just $80 Minecraft comes to chromebooks Microsoft was fined $20 million by the FTC for collecting kids' data (Amazon was fined $25 million) Report explains why Redfall failed. (It sucks) Apple brings Windows games to macOS using Wine-based toolkit Amazon kills Luna app on Windows and Mac, focuses on web. Are we facing a Stadia moment now? Tips & Picks Tip of the week: Passkeys come to Google Workspace accounts too Tip of the week #2: Get the updated Windows 11 22H2 ISO RunAs Radio this week: Microsoft Sentinel with Sarah Young Brown liquor pick of the week: Glenmorangie Quinta Ruban 14 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: AWS Insiders - WW meraki.cisco.com/twit Melissa.com/twit

Cortana's Windows death, 3 months with no Xbox, thoughts on WWDC23 Developer Story As the developer conference season winds down with WWDC, a look at how Apple, Google, and Microsoft are both similar to and different from each other Hololens flashbacks anyone? Windows She's dead, Jim: Microsoft kills Cortana in Windows 10, 11 - this is all about marketing Teams for Windows (consumer) gets new features that no one will notice either Windows Insider Preview: Microsoft Paint gets Dark mode support (FINALLY) and more in Canary and Dev Canary: New build brings SMB signing requirement (Enterprise ed only), camera app troubleshooting (plus new build today) Dev (new): redesigned Home view for File Explorer, modernized address bar and search box, Dynamic Lighting settings Dev: File Explorer tabs and gallery view improvements, Add Phone Photos button for setting up OneDrive camera roll Beta: WPA3 support in Phone Link, fixes Microsoft Edge arrives with Workspaces (but not the new UI) Brave finally gets vertical tabs One week after HP, Dell posts 20 percent revenue fall Xbox Well, Paul finally did it: 3 months without Xbox WD Xbox Series X|S expansion cards start at just $80 Minecraft comes to chromebooks Microsoft was fined $20 million by the FTC for collecting kids' data (Amazon was fined $25 million) Report explains why Redfall failed. (It sucks) Apple brings Windows games to macOS using Wine-based toolkit Amazon kills Luna app on Windows and Mac, focuses on web. Are we facing a Stadia moment now? Tips & Picks Tip of the week: Passkeys come to Google Workspace accounts too Tip of the week #2: Get the updated Windows 11 22H2 ISO RunAs Radio this week: Microsoft Sentinel with Sarah Young Brown liquor pick of the week: Glenmorangie Quinta Ruban 14 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: AWS Insiders - WW meraki.cisco.com/twit Melissa.com/twit

One more look back at Build  Microsoft talked a lot about what's coming to Windows, was vague on the timing. Speaking of vague, Microsoft gave the impression that there were "1 billion" Windows 11 users. There are not. Paul can confirm that Panos Panay was purposefully sidelined. Dev Drive: excellent. Dev Home: Eh. Windows Copilot, Winget config: maybe A theory about 23H2 = Moment 4 Windows 11 New Insider Preview builds. Canary: Microsoft Data Loss Prevention (DLP) policies on Windows on ARM. Dev: Dev Drive, Windows Backup, never combine in Taskbar. Beta: Minor changes. Don't forget that Moment 3 arrives next week. Hackers fully crack Windows XP activation. HP revenues fall 22 percent as PC market doldrums continue. Intel CEO discusses "serious leadership issues" at Intel and the rocky turnaround. Surface Surface Pro X camera just stops working, so Microsoft issues a temporary fix. Xbox Margrethe Vestager discusses the UK CMA and Activision Blizzard. New Games for Gold titles - Adios is available now, and on Windows too (a first?). New Game Pass titles. Xbox app gets May update. Google Play Games for PC Beta comes to Europe, New Zealand. Tips and Picks Tip of the week: Get started on what's next for Windows 11 App pick of the week: Greenshot, ImageGlass, VLC RunAs Radio this week: Azure Sticker Shock with Aidan Finn Brown liquor pick of the week: Crown Royal Northern Rye Harvest Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: GO.ACILEARNING.COM/TWIT CDW.com/LenovoClient

One more look back at Build  Microsoft talked a lot about what's coming to Windows, was vague on the timing. Speaking of vague, Microsoft gave the impression that there were "1 billion" Windows 11 users. There are not. Paul can confirm that Panos Panay was purposefully sidelined. Dev Drive: excellent. Dev Home: Eh. Windows Copilot, Winget config: maybe A theory about 23H2 = Moment 4 Windows 11 New Insider Preview builds. Canary: Microsoft Data Loss Prevention (DLP) policies on Windows on ARM. Dev: Dev Drive, Windows Backup, never combine in Taskbar. Beta: Minor changes. Don't forget that Moment 3 arrives next week. Hackers fully crack Windows XP activation. HP revenues fall 22 percent as PC market doldrums continue. Intel CEO discusses "serious leadership issues" at Intel and the rocky turnaround. Surface Surface Pro X camera just stops working, so Microsoft issues a temporary fix. Xbox Margrethe Vestager discusses the UK CMA and Activision Blizzard. New Games for Gold titles - Adios is available now, and on Windows too (a first?). New Game Pass titles. Xbox app gets May update. Google Play Games for PC Beta comes to Europe, New Zealand. Tips and Picks Tip of the week: Get started on what's next for Windows 11 App pick of the week: Greenshot, ImageGlass, VLC RunAs Radio this week: Azure Sticker Shock with Aidan Finn Brown liquor pick of the week: Crown Royal Northern Rye Harvest Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: GO.ACILEARNING.COM/TWIT CDW.com/LenovoClient

One more look back at Build  Microsoft talked a lot about what's coming to Windows, was vague on the timing. Speaking of vague, Microsoft gave the impression that there were "1 billion" Windows 11 users. There are not. Paul can confirm that Panos Panay was purposefully sidelined. Dev Drive: excellent. Dev Home: Eh. Windows Copilot, Winget config: maybe A theory about 23H2 = Moment 4 Windows 11 New Insider Preview builds. Canary: Microsoft Data Loss Prevention (DLP) policies on Windows on ARM. Dev: Dev Drive, Windows Backup, never combine in Taskbar. Beta: Minor changes. Don't forget that Moment 3 arrives next week. Hackers fully crack Windows XP activation. HP revenues fall 22 percent as PC market doldrums continue. Intel CEO discusses "serious leadership issues" at Intel and the rocky turnaround. Surface Surface Pro X camera just stops working, so Microsoft issues a temporary fix. Xbox Margrethe Vestager discusses the UK CMA and Activision Blizzard. New Games for Gold titles - Adios is available now, and on Windows too (a first?). New Game Pass titles. Xbox app gets May update. Google Play Games for PC Beta comes to Europe, New Zealand. Tips and Picks Tip of the week: Get started on what's next for Windows 11 App pick of the week: Greenshot, ImageGlass, VLC RunAs Radio this week: Azure Sticker Shock with Aidan Finn Brown liquor pick of the week: Crown Royal Northern Rye Harvest Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: GO.ACILEARNING.COM/TWIT CDW.com/LenovoClient

One more look back at Build  Microsoft talked a lot about what's coming to Windows, was vague on the timing. Speaking of vague, Microsoft gave the impression that there were "1 billion" Windows 11 users. There are not. Paul can confirm that Panos Panay was purposefully sidelined. Dev Drive: excellent. Dev Home: Eh. Windows Copilot, Winget config: maybe A theory about 23H2 = Moment 4 Windows 11 New Insider Preview builds. Canary: Microsoft Data Loss Prevention (DLP) policies on Windows on ARM. Dev: Dev Drive, Windows Backup, never combine in Taskbar. Beta: Minor changes. Don't forget that Moment 3 arrives next week. Hackers fully crack Windows XP activation. HP revenues fall 22 percent as PC market doldrums continue. Intel CEO discusses "serious leadership issues" at Intel and the rocky turnaround. Surface Surface Pro X camera just stops working, so Microsoft issues a temporary fix. Xbox Margrethe Vestager discusses the UK CMA and Activision Blizzard. New Games for Gold titles - Adios is available now, and on Windows too (a first?). New Game Pass titles. Xbox app gets May update. Google Play Games for PC Beta comes to Europe, New Zealand. Tips and Picks Tip of the week: Get started on what's next for Windows 11 App pick of the week: Greenshot, ImageGlass, VLC RunAs Radio this week: Azure Sticker Shock with Aidan Finn Brown liquor pick of the week: Crown Royal Northern Rye Harvest Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/windows-weekly Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Check out Paul's blog at thurrott.com The Windows Weekly theme music is courtesy of Carl Franklin. Sponsors: GO.ACILEARNING.COM/TWIT CDW.com/LenovoClient

The Verge's Nilay Patel, David Pierce, Alex Cranz, and Tom Warren discuss the biggest announcements from Microsoft Build 2023. Later, the crew discuss the launch of Warner Bros. Discovery's combined streaming service Max. Further reading: Elon Musk fails to launch Ron DeSantis in disastrous Twitter Space Microsoft Build 2023: The 5 biggest announcements Microsoft's Copilot and Bing AI plug-ins will be interoperable with ChatGPT Bing is now the default search for ChatGPT Microsoft 365 Copilot is getting plug-ins Microsoft's Edge browser is getting the 365 Copilot AI assistant Microsoft CTO Kevin Scott thinks Sydney might make a comeback Microsoft announces Windows Copilot, an AI ‘personal assistant' for Windows 11 Max has arrived, and it'll feel very familiar to HBO Max customers Max will stream over 1,000 movies and TV episodes in 4K at launch Warner Bros. Discovery apologizes for crediting writers and directors as ‘creators' on Max HBO Max remote button killed in Max rebrand — 9to5Mac HBO Max now Max: lacks native video player features; 'Up Next' support bugs - 9to5Mac Sony's new Q handheld is official: 8-inch screen, streams PS5 games Learn more about your ad choices. Visit podcastchoices.com/adchoices

Daniel Rubino of Windows Central comes back to the show to discuss the biggest announcements from this year's Microsoft Build 2023 event. Stephen Shankland of CNET talks about his experience using Adobe's new generative AI tool, Firefly, and how it integrates with Photoshop. Heather Kelly of the Washington Post stops by to share a guide she wrote about teens, smartphones, and social media following the Surgeon General's advisory about social media's effect on the youth's mental health. Finally, Mikah shares a story about a paralyzed man being able to walk naturally again with some implants and through artificial intelligence. Host: Mikah Sargent Guests: Daniel Rubino, Stephen Shankland, and Heather Kelly Download or subscribe to this show at https://twit.tv/shows/tech-news-weekly. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: AWS Insiders - TNW expressvpn.com/tnw CDW.com/DellClient

Daniel Rubino of Windows Central comes back to the show to discuss the biggest announcements from this year's Microsoft Build 2023 event. Stephen Shankland of CNET talks about his experience using Adobe's new generative AI tool, Firefly, and how it integrates with Photoshop. Heather Kelly of the Washington Post stops by to share a guide she wrote about teens, smartphones, and social media following the Surgeon General's advisory about social media's effect on the youth's mental health. Finally, Mikah shares a story about a paralyzed man being able to walk naturally again with some implants and through artificial intelligence. Host: Mikah Sargent Guests: Daniel Rubino, Stephen Shankland, and Heather Kelly Download or subscribe to this show at https://twit.tv/shows/tech-news-weekly. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: AWS Insiders - TNW expressvpn.com/tnw CDW.com/DellClient

Daniel Rubino of Windows Central comes back to the show to discuss the biggest announcements from this year's Microsoft Build 2023 event. Stephen Shankland of CNET talks about his experience using Adobe's new generative AI tool, Firefly, and how it integrates with Photoshop. Heather Kelly of the Washington Post stops by to share a guide she wrote about teens, smartphones, and social media following the Surgeon General's advisory about social media's effect on the youth's mental health. Finally, Mikah shares a story about a paralyzed man being able to walk naturally again with some implants and through artificial intelligence. Host: Mikah Sargent Guests: Daniel Rubino, Stephen Shankland, and Heather Kelly Download or subscribe to this show at https://twit.tv/shows/tech-news-weekly. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: AWS Insiders - TNW expressvpn.com/tnw CDW.com/DellClient

0:00 Windows Copilot, RGB, RAR support 1:50 RTX 4060 Ti + RX 7600 reviews 3:15 Purism Librem 5 order backlog 4:45 Pulseway 5:22 QUICK BITS it's supposed to be off 5:28 Photoshop Generative Fill 6:36 Activision shuts down CoD fan servers 7:16 Nintendo breaks 3DS homebrew 7:54 Netflix password sharing crackdown 8:26 Japanese YouTuber arrested News Sources: https://lmg.gg/QncsJ

Daniel Rubino of Windows Central comes back to the show to discuss the biggest announcements from this year's Microsoft Build 2023 event. Stephen Shankland of CNET talks about his experience using Adobe's new generative AI tool, Firefly, and how it integrates with Photoshop. Heather Kelly of the Washington Post stops by to share a guide she wrote about teens, smartphones, and social media following the Surgeon General's advisory about social media's effect on the youth's mental health. Finally, Mikah shares a story about a paralyzed man being able to walk naturally again with some implants and through artificial intelligence. Host: Mikah Sargent Guests: Daniel Rubino, Stephen Shankland, and Heather Kelly Download or subscribe to this show at https://twit.tv/shows/tech-news-weekly. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: AWS Insiders - TNW expressvpn.com/tnw CDW.com/DellClient

At Microsoft Build 2023, CEO Satya Nadella shares insights on the new era of AI and announces the launch of Windows Copilot, Azure AI Studio, and Microsoft Fabric, and CTO Kevin Scott is joined by OpenAI's Greg Brockman to explore how Microsoft and OpenAI's full-stack AI platform empowers developers and outlines a framework for building AI apps and copilots. Hosts: Leo Laporte and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/twit-news. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: GO.ACILEARNING.COM/TWIT

At Microsoft Build 2023, CEO Satya Nadella shares insights on the new era of AI and announces the launch of Windows Copilot, Azure AI Studio, and Microsoft Fabric, and CTO Kevin Scott is joined by OpenAI's Greg Brockman to explore how Microsoft and OpenAI's full-stack AI platform empowers developers and outlines a framework for building AI apps and copilots. Hosts: Leo Laporte and Richard Campbell Download or subscribe to this show at https://twit.tv/shows/twit-news. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsor: GO.ACILEARNING.COM/TWIT