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Apparently “premium AI dictation” requires a subscription and the cloud. Bullshit. We are literally building tiny models that run ENTIRELY on your devices, do a cloud-like dictation polish, and cost you $0. 1 model shipped. 3 more coming at speeds that shouldn’t be possible. Follow us, and be a... show more

FluidVoice

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54,521 次观看 • 19 天前 •via X (Twitter)

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PERPLEXITY 🔥: A new Hybrid mode is coming soon on Mac, letting local models handle some subtasks. > Gemma 4 (for 16 GB machines), Qwen3.6, and Perplexity's own model (For 32 GB machines) are currently supported. > "In Hybrid mode, Computer orchestrates in the cloud and delegates suitable subtasks to a model on your Mac." > "Local models run on your Mac's own memory and processor — the more capable your machine, the larger the models it can run." > "Privacy Gate is a small model that runs entirely on your Mac. It inspects anything headed to the cloud for personal or sensitive information — and if it finds any, you decide how to handle it before anything is sent." That would be huge 👀

PERPLEXITY 🔥: A new Hybrid mode is coming soon on Mac, letting local models handle some subtasks. > Gemma 4 (for 16 GB machines), Qwen3.6, and Perplexity's own model (For 32 GB machines) are currently supported. > "In Hybrid mode, Computer orchestrates in the cloud and delegates suitable subtasks to a model on your Mac." > "Local models run on your Mac's own memory and processor — the more capable your machine, the larger the models it can run." > "Privacy Gate is a small model that runs entirely on your Mac. It inspects anything headed to the cloud for personal or sensitive information — and if it finds any, you decide how to handle it before anything is sent." That would be huge 👀

🚨 AI News | TestingCatalog

41,281 次观看 • 15 天前

Actual Computer CEO Tom Lynch predicts the next wave of AI inference will increasingly move from the cloud to local computers: "How many tokens does the world go through a day right now? That number is probably like 500 trillion or so. Google themselves claims 100 trillion per day. The publicly accountable numbers are like 350 trillion or so." "I like to look at it as where are the next tokens coming from. The next 100 trillion, what percentage of those are going to be local versus cloud? You're going to see a larger degree of growth in new tokens coming from local versus how it has been almost entirely coming from cloud up until now." "Especially in a business sense, 95% of the tokens that people run a business on are coming from the cloud. I know very few people running businesses on local models entirely right now." "Hugging Face acquisition shows that NVIDIA cares about making sure people use these more and more. How fast it changes is going to be entirely dependent on the hardware accessible to people." Actual Computer

Actual Computer CEO Tom Lynch predicts the next wave of AI inference will increasingly move from the cloud to local computers: "How many tokens does the world go through a day right now? That number is probably like 500 trillion or so. Google themselves claims 100 trillion per day. The publicly accountable numbers are like 350 trillion or so." "I like to look at it as where are the next tokens coming from. The next 100 trillion, what percentage of those are going to be local versus cloud? You're going to see a larger degree of growth in new tokens coming from local versus how it has been almost entirely coming from cloud up until now." "Especially in a business sense, 95% of the tokens that people run a business on are coming from the cloud. I know very few people running businesses on local models entirely right now." "Hugging Face acquisition shows that NVIDIA cares about making sure people use these more and more. How fast it changes is going to be entirely dependent on the hardware accessible to people." Actual Computer

MTS

17,711 次观看 • 12 天前

We asked (Co-Founder & CEO, webAI) about the advantages of running AI on devices. "There's no free lunch, but there are things cloud players can't do. It's RAM intensive, yes, but by distributing across devices, we can unlock more accuracy and context. But if you're hosting for a million users on Nvidia, you can't do that." "With our stack, everything's downstream only. Think about health data, like you want that to be private. The dream is personalized models for millions that never leave their device."

We asked (Co-Founder & CEO, webAI) about the advantages of running AI on devices. "There's no free lunch, but there are things cloud players can't do. It's RAM intensive, yes, but by distributing across devices, we can unlock more accuracy and context. But if you're hosting for a million users on Nvidia, you can't do that." "With our stack, everything's downstream only. Think about health data, like you want that to be private. The dream is personalized models for millions that never leave their device."

TBPN

10,109 次观看 • 1 年前

SITUATION EXPLAINED: 70% of frontier model queries could run locally for free. clem 🤗, co-founder and CEO of Hugging Face: "There was an interesting study from Stanford published last year showing that 70% of the queries that people ask to ChatGPT could be accurately answered locally on your laptop. For free." "Most of the AI workloads that people do today with frontier models could be done by models that are cheaper, faster, more customizable, more controllable. And they don't do it because frankly it's a pain to pick the right model." "You're subsidized so you don't have to care because you have your subscription, so you route everything to Einstein. 'Hey Einstein, what's the weather today?'" "In normal life, he would be like, 'I'm not answering your silly question.' But because it's AI and subsidized by the AI labs, all the questions are getting routed to Einstein versus in an ideal world you have different models that are more specialized and better at answering your questions in different domains." "It's possible that routing is gonna redistribute a lot of the value capture from frontier models to a more long tail of models. It's like AI maturing... we are in the first phase where it's very simple, everyone using just one giant model. Now we're moving to the second phase."

SITUATION EXPLAINED: 70% of frontier model queries could run locally for free. clem 🤗, co-founder and CEO of Hugging Face: "There was an interesting study from Stanford published last year showing that 70% of the queries that people ask to ChatGPT could be accurately answered locally on your laptop. For free." "Most of the AI workloads that people do today with frontier models could be done by models that are cheaper, faster, more customizable, more controllable. And they don't do it because frankly it's a pain to pick the right model." "You're subsidized so you don't have to care because you have your subscription, so you route everything to Einstein. 'Hey Einstein, what's the weather today?'" "In normal life, he would be like, 'I'm not answering your silly question.' But because it's AI and subsidized by the AI labs, all the questions are getting routed to Einstein versus in an ideal world you have different models that are more specialized and better at answering your questions in different domains." "It's possible that routing is gonna redistribute a lot of the value capture from frontier models to a more long tail of models. It's like AI maturing... we are in the first phase where it's very simple, everyone using just one giant model. Now we're moving to the second phase."

MTS

50,185 次观看 • 2 个月前

Google just shipped a free dictation app for Mac and iPhone called AI Edge Eloquent, and the model running it is Gemma 4 12B, entirely on your device. What it actually does: you speak, it transcribes, removes filler words, and polishes the result before dropping clean text into whatever app you are using. You can also give it voice commands to reformat, like "translate to Hindi" or "make this a bullet list." Audio and video file transcription is built in too. The interesting part is the privacy angle. Most AI writing tools send your audio to a server. This one never leaves your machine, which matters if you are dictating anything sensitive. The tradeoff is hardware: you need a Mac with at least 16GB of RAM to run a 12B parameter model comfortably.

Google just shipped a free dictation app for Mac and iPhone called AI Edge Eloquent, and the model running it is Gemma 4 12B, entirely on your device. What it actually does: you speak, it transcribes, removes filler words, and polishes the result before dropping clean text into whatever app you are using. You can also give it voice commands to reformat, like "translate to Hindi" or "make this a bullet list." Audio and video file transcription is built in too. The interesting part is the privacy angle. Most AI writing tools send your audio to a server. This one never leaves your machine, which matters if you are dictating anything sensitive. The tradeoff is hardware: you need a Mac with at least 16GB of RAM to run a 12B parameter model comfortably.

Aditya ⚡Rao

85,093 次观看 • 3 个月前

We are excited to share a demo of our platform. Check out our core features of creating agents, creating plugins, and interacting with them through chat. This is a work-in-progress update to give you all a sneak peek at what we’re building. There’s so much more the platform can do. We’ve laid a strong foundation, and now it’s time to refine and polish it. Stay tuned for more updates and demos over the next week. $COFFEE

We are excited to share a demo of our platform. Check out our core features of creating agents, creating plugins, and interacting with them through chat. This is a work-in-progress update to give you all a sneak peek at what we’re building. There’s so much more the platform can do. We’ve laid a strong foundation, and now it’s time to refine and polish it. Stay tuned for more updates and demos over the next week. $COFFEE

Coffee - ai/acc ☕️

10,611 次观看 • 1 年前

🗣️ Celebrating Our Community Legends: Building a Legacy Together We're bursting with excitement as we forge ahead, hand-in-hand with our incredible community. Your unwavering belief in our mission and vision is not just inspiring, it's the fuel that drives us forward. To each and every one of you who stands with us, day in and day out – you are more than supporters; you are the pulsating heart of our vibrant community. As we continue on this journey, let's craft a brand that echoes your voices, reflects your values, and resonates with your experiences. You're not just part of our story – you're the authors of a legendary saga we're writing together. Here's to building a future that we can all be proud of, filled with shared successes and milestones. You are the heroes in this narrative, the legends that will be remembered. The G-Media Team!

Gokhshtein Network

20,411 次观看 • 2 年前

Osmantic founder Ahmad warns companies relying on cloud AI are building on models that can be changed, slowed down, or taken away without them even knowing: "If you're using any quantity of tokens, you should start hosting your own LLMs. You don't know when a model is gonna change on you. APIs are always having this latest endpoint, so you always end up, it gets rug pulled from underneath you" "How could you tell if a certain country is getting 5, 10 IQ points drop in their inference from the cloud? You can't tell from the cloud. What I'm seeing from OpenAI is that they are making their models slower so that they can serve with the limited compute they have" "It has to be in the back of your mind, is your data safe? Is there a more efficient way to get quality tokens, cheaper alternatives, and something that is yours and you can own the infrastructure end to end?" Osmantic

Osmantic founder Ahmad warns companies relying on cloud AI are building on models that can be changed, slowed down, or taken away without them even knowing: "If you're using any quantity of tokens, you should start hosting your own LLMs. You don't know when a model is gonna change on you. APIs are always having this latest endpoint, so you always end up, it gets rug pulled from underneath you" "How could you tell if a certain country is getting 5, 10 IQ points drop in their inference from the cloud? You can't tell from the cloud. What I'm seeing from OpenAI is that they are making their models slower so that they can serve with the limited compute they have" "It has to be in the back of your mind, is your data safe? Is there a more efficient way to get quality tokens, cheaper alternatives, and something that is yours and you can own the infrastructure end to end?" Osmantic

MTS

14,952 次观看 • 5 天前

We’re redefining what’s possible with AI. With the release of our latest model, Command A, optimized for real-world agentic and multilingual tasks, we’re demonstrating our commitment to bringing enterprises AI that goes beyond the ordinary, and offers security & efficiency. Our team has developed highly capable and efficient models that can be run on just 2 GPUs. Check out our tech report to learn more:

We’re redefining what’s possible with AI. With the release of our latest model, Command A, optimized for real-world agentic and multilingual tasks, we’re demonstrating our commitment to bringing enterprises AI that goes beyond the ordinary, and offers security & efficiency. Our team has developed highly capable and efficient models that can be run on just 2 GPUs. Check out our tech report to learn more:

Cohere

16,426 次观看 • 1 年前

Austen Allred on Gauntlet AI: "We're very up front that we're 80 to 100 hours a week. If you think that that's a terrible idea, please don't come." "We're in Austin, all right? That's a sacrifice for a lot of people. If you don't think like coming to Austin for 100 hours a week and jamming on AI unpaid and just building stuff to figure out how much you can learn and hopefully getting a job on the other side... if you don't think that's awesome, that's totally fine. Please don't come." "There are some psychos out there that think that that's a good time. We wanna collect all those psychos. So come all, come all ye crazy people. And if that's not for you, that's okay." "There are companies that come to us and say, "Hey, we want, you know, 100 engineers that are going to sit in our division of printer drivers and sit there." And I'm like, "They would kill themselves." The people that are coming to Gauntlet would not do that. And so we turn companies down too." So we know who we are, we know what we stand for. You know, it helps that I'm one of those people that would've loved that. So is Ash Tilawat, and so is everybody else that works at Gauntlet. "So it's not hard for us to find other crazy people like ourselves. And that doesn't have to be you. That's okay." "We're not trying to empire build or solve all of humanity's greatest problems. We know that there's a limit to who we're addressing and what we're addressing at any given time." "So our goal is to be the best thing we can possibly be for that weird island of misfits. And for the companies that need a weird island of misfits, we'll be that all day long."

Austen Allred on Gauntlet AI: "We're very up front that we're 80 to 100 hours a week. If you think that that's a terrible idea, please don't come." "We're in Austin, all right? That's a sacrifice for a lot of people. If you don't think like coming to Austin for 100 hours a week and jamming on AI unpaid and just building stuff to figure out how much you can learn and hopefully getting a job on the other side... if you don't think that's awesome, that's totally fine. Please don't come." "There are some psychos out there that think that that's a good time. We wanna collect all those psychos. So come all, come all ye crazy people. And if that's not for you, that's okay." "There are companies that come to us and say, "Hey, we want, you know, 100 engineers that are going to sit in our division of printer drivers and sit there." And I'm like, "They would kill themselves." The people that are coming to Gauntlet would not do that. And so we turn companies down too." So we know who we are, we know what we stand for. You know, it helps that I'm one of those people that would've loved that. So is Ash Tilawat, and so is everybody else that works at Gauntlet. "So it's not hard for us to find other crazy people like ourselves. And that doesn't have to be you. That's okay." "We're not trying to empire build or solve all of humanity's greatest problems. We know that there's a limit to who we're addressing and what we're addressing at any given time." "So our goal is to be the best thing we can possibly be for that weird island of misfits. And for the companies that need a weird island of misfits, we'll be that all day long."

Ben Averbook

12,153 次观看 • 10 个月前

Everyone wrote Apple off as the AI loser, but one hardware spec might flip that story upside down (Save this). @jason called Apple a screaming buy on the back of a single chip detail. The rumored M7 Ultra, expected around 2028, is designed to support up to 1.5TB of unified memory, enough to run frontier class trillion parameter AI models locally, with no cloud required. The Street's bear case on Apple is straightforward. Apple has no frontier model of its own, Siri has stumbled for years and the company effectively rents OpenAI's models for its hardest queries. That narrative treats Apple as the one Magnificent Seven name that missed the AI wave entirely but the bull case flips that framing on its head. If frontier AI models keep shrinking and getting cheaper to run, Apple doesn't need the smartest model in the world, it just needs to own the device that model runs on. And unified memory is the mechanism that makes this possible. Unlike traditional systems where the CPU and GPU each need separate memory, Apple's architecture lets the CPU, GPU and Neural Engine draw from one shared pool. A fully specced M7 Ultra could theoretically run something on the scale of a 1.2 trillion parameter model locally and that capability plugs directly into the one advantage Apple has spent over a decade building: privacy. Apple has already shipped Private Cloud Compute, a system designed so even Apple can't access user data processed off device. Apple doubled down on this at WWDC 2026, framing on device privacy as non-negotiable while rivals default to the cloud. If the best AI models get small enough to run on Apple silicon, the moat stops being the model and becomes the hardware it has to sit on. Milk Road Pro remains bullish on Apple and it remains as one of our core positions, if you want the full thesis + our full AI trades, come join us using the link below for just a $1.

Everyone wrote Apple off as the AI loser, but one hardware spec might flip that story upside down (Save this). @jason called Apple a screaming buy on the back of a single chip detail. The rumored M7 Ultra, expected around 2028, is designed to support up to 1.5TB of unified memory, enough to run frontier class trillion parameter AI models locally, with no cloud required. The Street's bear case on Apple is straightforward. Apple has no frontier model of its own, Siri has stumbled for years and the company effectively rents OpenAI's models for its hardest queries. That narrative treats Apple as the one Magnificent Seven name that missed the AI wave entirely but the bull case flips that framing on its head. If frontier AI models keep shrinking and getting cheaper to run, Apple doesn't need the smartest model in the world, it just needs to own the device that model runs on. And unified memory is the mechanism that makes this possible. Unlike traditional systems where the CPU and GPU each need separate memory, Apple's architecture lets the CPU, GPU and Neural Engine draw from one shared pool. A fully specced M7 Ultra could theoretically run something on the scale of a 1.2 trillion parameter model locally and that capability plugs directly into the one advantage Apple has spent over a decade building: privacy. Apple has already shipped Private Cloud Compute, a system designed so even Apple can't access user data processed off device. Apple doubled down on this at WWDC 2026, framing on device privacy as non-negotiable while rivals default to the cloud. If the best AI models get small enough to run on Apple silicon, the moat stops being the model and becomes the hardware it has to sit on. Milk Road Pro remains bullish on Apple and it remains as one of our core positions, if you want the full thesis + our full AI trades, come join us using the link below for just a $1.

Milk Road AI

37,459 次观看 • 1 个月前

Here's a sneak peek at the new enemy that will be added in our next update 👀 You can also see the new parry effects and indicator that are coming soon! 🎮 Play The Spirit of the Samurai Now: #SotS 🦊 #screenshotsaturday #update #action #gamedev

Here's a sneak peek at the new enemy that will be added in our next update 👀 You can also see the new parry effects and indicator that are coming soon! 🎮 Play The Spirit of the Samurai Now: #SotS 🦊 #screenshotsaturday #update #action #gamedev

The Spirit of the Samurai - OUT NOW

19,494 次观看 • 1 年前

turns out my habits were only half of it 9 steps to cut your Grok Bot usage by over 50% (if you're on a Cursor plan): 1. open cursor desktop app settings 2. go to the models option in the side menu 3. flip off any models you don't want to be using 4. next, set task models in the top of the page to a model you prefer that's cost efficient (do not leave it on default, this is IMPORTANT) 5. otherwise... your task models could auto set to high and/or fast... that's a more expensive model, and you get billed 2x 6. after, you'll click on the cloud agents option in your side menu, and it'll take you to the cursor web dashboard for your account 7. you will need to scroll down to the preferences section on that page and click on the default model option (again IMPORTANT) 8. set that to a cost efficient model you prefer and don't leave it on default... otherwise your cloud agents may use high and/or fast yet again 9. bonus tip (won't apply to most): lastly click on the spending option in your web dashboard's side menu and also make sure your on-demand usage is not on unlimited and is set to a cap you're comfortable with my token usage has reduced 60% after doing this and I'm sure it'll be different for everyone... but make sure to check this process can be a tad bit confusing too let me know if you need any help!

turns out my habits were only half of it 9 steps to cut your Grok Bot usage by over 50% (if you're on a Cursor plan): 1. open cursor desktop app settings 2. go to the models option in the side menu 3. flip off any models you don't want to be using 4. next, set task models in the top of the page to a model you prefer that's cost efficient (do not leave it on default, this is IMPORTANT) 5. otherwise... your task models could auto set to high and/or fast... that's a more expensive model, and you get billed 2x 6. after, you'll click on the cloud agents option in your side menu, and it'll take you to the cursor web dashboard for your account 7. you will need to scroll down to the preferences section on that page and click on the default model option (again IMPORTANT) 8. set that to a cost efficient model you prefer and don't leave it on default... otherwise your cloud agents may use high and/or fast yet again 9. bonus tip (won't apply to most): lastly click on the spending option in your web dashboard's side menu and also make sure your on-demand usage is not on unlimited and is set to a cap you're comfortable with my token usage has reduced 60% after doing this and I'm sure it'll be different for everyone... but make sure to check this process can be a tad bit confusing too let me know if you need any help!

klöss

35,455 次观看 • 11 天前

⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

OptimAI Network

43,645 次观看 • 1 年前

$THIS IS WHERE "THE CLOUD" ACTUALLY LIVES - A ROOM OF DELL STORAGE ARRAYS YOU RENT A SLIVER OF EVERY MONTH. that clip is a real datacenter aisle, rack after rack of dell powerstore arrays, every hexagon panel packed with drives. this is "the cloud." not a metaphor, this room, plus the power, cooling and staff keeping it alive. when you pay for cloud storage, you rent a few gigabytes of these arrays. forever. the bill grows with every photo. here's the part they'd rather you not connect. these enterprise drives run on a schedule. data centers swap them out long before they fail, by the pallet. those decommissioned drives get tested and resold as recertified, the same 20tb enterprise disk for a fraction of new. so the exact hardware humming in this room ends up in a nas on your desk, minus the monthly rent. no cloud subscription, no data on someone else's array, no bill that grows with your library. the uncomfortable part isn't that the cloud is huge. it's that "the cloud" was always just this room, and you can buy a piece of it once instead of renting it forever. follow RetroChainer for what the cloud doesn't want you to picture, and bookmark this before your next storage renewal.$

THIS IS WHERE "THE CLOUD" ACTUALLY LIVES - A ROOM OF DELL STORAGE ARRAYS YOU RENT A SLIVER OF EVERY MONTH. that clip is a real datacenter aisle, rack after rack of dell powerstore arrays, every hexagon panel packed with drives. this is "the cloud." not a metaphor, this room, plus the power, cooling and staff keeping it alive. when you pay for cloud storage, you rent a few gigabytes of these arrays. forever. the bill grows with every photo. here's the part they'd rather you not connect. these enterprise drives run on a schedule. data centers swap them out long before they fail, by the pallet. those decommissioned drives get tested and resold as recertified, the same 20tb enterprise disk for a fraction of new. so the exact hardware humming in this room ends up in a nas on your desk, minus the monthly rent. no cloud subscription, no data on someone else's array, no bill that grows with your library. the uncomfortable part isn't that the cloud is huge. it's that "the cloud" was always just this room, and you can buy a piece of it once instead of renting it forever. follow RetroChainer for what the cloud doesn't want you to picture, and bookmark this before your next storage renewal.

RetroChainer

33,825 次观看 • 1 个月前

Today we're launching Accomplish FREE - powered by our new hybrid model router. Since we launched Accomplish a few weeks ago, we've been blown away by what users are building with it. Hundreds of thousands of you downloaded the app and took it for a spin, but one thing kept coming up: not everyone wants to bring their own API key just to get started. So today we're fixing that with free, built-in models - made possible by a massive shift that's happened in just the past few weeks: the rise of fully hosted open-weight models - locally on your Windows machine with NVIDIA NVIDIA GeForce, on your Mac with Apple MLX, or on Accomplish cloud, for FREE. Our new hybrid routing algorithm dynamically routes between cloud models and models running locally on your machine - optimizing for local execution by automatically detecting your hardware capabilities and each sub-task's complexity: coding, visuals, simple classifications - every LLM call is routed to the best model. We also brought some of our favorite enterprise features to the free tier: scheduled task dispatch, Google Workspace integration (Google Drive Docs, Sheets, Slides) via the new Google Workspace CLI, native Slack MCP connectivity, and more. Accomplish FREE is available for macOS, Windows, and Linux. Download, send a task - and boom, it just works with ZERO configuration! Download link in bio / first comment >>

Today we're launching Accomplish FREE - powered by our new hybrid model router. Since we launched Accomplish a few weeks ago, we've been blown away by what users are building with it. Hundreds of thousands of you downloaded the app and took it for a spin, but one thing kept coming up: not everyone wants to bring their own API key just to get started. So today we're fixing that with free, built-in models - made possible by a massive shift that's happened in just the past few weeks: the rise of fully hosted open-weight models - locally on your Windows machine with NVIDIA NVIDIA GeForce, on your Mac with Apple MLX, or on Accomplish cloud, for FREE. Our new hybrid routing algorithm dynamically routes between cloud models and models running locally on your machine - optimizing for local execution by automatically detecting your hardware capabilities and each sub-task's complexity: coding, visuals, simple classifications - every LLM call is routed to the best model. We also brought some of our favorite enterprise features to the free tier: scheduled task dispatch, Google Workspace integration (Google Drive Docs, Sheets, Slides) via the new Google Workspace CLI, native Slack MCP connectivity, and more. Accomplish FREE is available for macOS, Windows, and Linux. Download, send a task - and boom, it just works with ZERO configuration! Download link in bio / first comment >>

Or Hiltch

103,729 次观看 • 5 个月前

context switching is the mind killer 💀 ai can be used to supercharge distraction and addiction. we at daylight are trying to figure out how to superpower your focus and stay in flow. here’s a sneak peek of ai reading on the daylight, no more context switching —

context switching is the mind killer 💀 ai can be used to supercharge distraction and addiction. we at daylight are trying to figure out how to superpower your focus and stay in flow. here’s a sneak peek of ai reading on the daylight, no more context switching —

daylight

319,252 次观看 • 1 年前

AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

RetroChainer

16,995 次观看 • 1 个月前

We just crossed 100k downloads of OpenWhispr! 🤯 This feels like a good time for a reminder of why we’re building it. Your ideas and conversations are becoming more valuable, while software is becoming easier to build than ever. But that creates some worrying incentives for existing software companies: use your proprietary data to train better AI models to stay competitive, and lock that data behind walled gardens to keep you from leaving. We think that’s pretty shitty. You should stay because a product is useful, not because your data is stuck there. If billions of people are going to feel comfortable sharing their most private information when talking to AI, and organizations are going to trust it with their work, we have to earn that trust. For us, that starts with being fully transparent about how your data is handled, and giving you full control over it. That’s what we’re building with OpenWhispr. You can run models on your own device, use your own cloud provider, or use our cloud service. We’re not anti-cloud. We just think it should be your choice. We’re still super early, but I’m genuinely excited to bring you along for more of this. This is the first in a series of videos sharing the new features we’re building, what we’re figuring out, and the team behind it. And if you’re still here reading, we’re officially hiring for two really important roles: - Founding Engineering Lead - Social / Brand / Growth Creator You can find more info about both on our website!

Gabe Stein

12,282 次观看 • 5 天前