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Sam Altman makes a strong point here. Human computer interaction hasn’t fundamentally changed in decades. Windows, pointers, apps, even mobile are variations of the same model. AI breaks that pattern. AI can understand language, hold long context, and operate continuously instead of being a simple on/off tool. That enables... show more

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11,602 views • 7 months ago •via X (Twitter)

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Sam Altman says today's models are still dumb because they barely understand your life The next shift is a model that knows your context, your work, your goals, your people, and the way you use your computer "that is gonna be a complete change to what it feels like to use AI"

Sam Altman says today's models are still dumb because they barely understand your life The next shift is a model that knows your context, your work, your goals, your people, and the way you use your computer "that is gonna be a complete change to what it feels like to use AI"

Haider.

117,890 views • 5 months ago

Sam Altman: AI models need their own device so they can stay with you and understand the context of your life. “The iPhone is currently the greatest piece of consumer hardware ever made.” “But it was not meant for a world where you needed hardware that could absorb all the context of your life.” “My phone is in my pocket, and it’s not gonna understand us.” “I would like a device that can participate, understand, and know about this conversation.” “And OpenAI is committed to building something along those lines.”

Sam Altman: AI models need their own device so they can stay with you and understand the context of your life. “The iPhone is currently the greatest piece of consumer hardware ever made.” “But it was not meant for a world where you needed hardware that could absorb all the context of your life.” “My phone is in my pocket, and it’s not gonna understand us.” “I would like a device that can participate, understand, and know about this conversation.” “And OpenAI is committed to building something along those lines.”

Veee

112,491 views • 14 days ago

Proactive AI Agents Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These are useful, but I’m excited about products that take this further and shift the paradigm from “ask → answer” to “observe → act." These agents will continuously monitor context in the background across all of your connected tools and data, predict what matters, and take action before being asked to do so – much like a human does. So instead of you prompting the model, the model will start prompting you. Examples here could include agents that remind you about tasks you forgot to complete, resolve customer issues before support tickets are filed, or debug and ship code fixes automatically. This shift represents a new paradigm where AI products behave more like humans and less like tools. We’re already starting to see this dynamic with products like OpenClaw, Poke, and more - and we’ve only scratched the surface of capabilities here. We’re accepting applications for the next cohort of a16z speedrun – If you’re building the next generation of AI products, apply online.

Proactive AI Agents Today’s AI products are reactive. You give the model a prompt, it responds with an answer. These are useful, but I’m excited about products that take this further and shift the paradigm from “ask → answer” to “observe → act." These agents will continuously monitor context in the background across all of your connected tools and data, predict what matters, and take action before being asked to do so – much like a human does. So instead of you prompting the model, the model will start prompting you. Examples here could include agents that remind you about tasks you forgot to complete, resolve customer issues before support tickets are filed, or debug and ship code fixes automatically. This shift represents a new paradigm where AI products behave more like humans and less like tools. We’re already starting to see this dynamic with products like OpenClaw, Poke, and more - and we’ve only scratched the surface of capabilities here. We’re accepting applications for the next cohort of a16z speedrun – If you’re building the next generation of AI products, apply online.

Kenan Saleh

130,119 views • 4 months ago

Sam Altman, CEO of OpenAI, on why the iPhone, the greatest consumer device ever made, is the wrong hardware for the AI era: Sam argues the iPhone's basic design wasn't made for a world where AI needs to live alongside your entire life. "I think the iPhone is currently the greatest piece of consumer hardware ever made by a lot. Like, incredible what that has done." The iPhone was designed for a pre-AI world. Sam Altman explains: "It was not meant for a world where you needed a piece of hardware that could absorb all of the context of your life. You know, you can use the phone, you can stop using the phone, you can put it in your pocket, but it's kind of like on or off." That binary, on or off, in use or in your pocket, is the core mismatch. A device that flips between active and dormant can't continuously absorb the context that a personal AGI would need to actually be useful to you. Sam uses the conversation he's having in that moment as the example: "This has been a very interesting conversation. I would love this to be referenced by my personal AGI later, but my phone is in my pocket and it's not going to understand." The vision he's pointing toward is a device that participates differently: "I would like a device that, if I wanted to, can participate and understand and know about this conversation." The shift Sam is describing is from a device you pick up and put down, to one that quietly captures the context of your life. Without that continuous context, a personal AGI can't actually be personal.

Sam Altman, CEO of OpenAI, on why the iPhone, the greatest consumer device ever made, is the wrong hardware for the AI era: Sam argues the iPhone's basic design wasn't made for a world where AI needs to live alongside your entire life. "I think the iPhone is currently the greatest piece of consumer hardware ever made by a lot. Like, incredible what that has done." The iPhone was designed for a pre-AI world. Sam Altman explains: "It was not meant for a world where you needed a piece of hardware that could absorb all of the context of your life. You know, you can use the phone, you can stop using the phone, you can put it in your pocket, but it's kind of like on or off." That binary, on or off, in use or in your pocket, is the core mismatch. A device that flips between active and dormant can't continuously absorb the context that a personal AGI would need to actually be useful to you. Sam uses the conversation he's having in that moment as the example: "This has been a very interesting conversation. I would love this to be referenced by my personal AGI later, but my phone is in my pocket and it's not going to understand." The vision he's pointing toward is a device that participates differently: "I would like a device that, if I wanted to, can participate and understand and know about this conversation." The shift Sam is describing is from a device you pick up and put down, to one that quietly captures the context of your life. Without that continuous context, a personal AGI can't actually be personal.

Big Brain AI

25,447 views • 4 months ago

Ash Sarkar, "Sam Altman CEO of OpenAI said AI will cure cancer. Now says you can have sex with a robot" "And I think that tells you something about the direction that this is going in" "Which is, rather than AI enhancing human innovation, critical thinking, the progress of science" "It's being used to exploit our insecurities" #BBCQT

Ash Sarkar, "Sam Altman CEO of OpenAI said AI will cure cancer. Now says you can have sex with a robot" "And I think that tells you something about the direction that this is going in" "Which is, rather than AI enhancing human innovation, critical thinking, the progress of science" "It's being used to exploit our insecurities" #BBCQT

Farrukh

280,660 views • 11 months ago

Sam Altman thinks the next major shift in consumer tech could be AI-first hardware. His vision goes beyond a smarter phone, a device that can understand conversations, remember context and actually participate in your life. “The iPhone is probably the greatest piece of consumer hardware ever created.” But Altman says it wasn’t designed for an AI-first world.

Sam Altman thinks the next major shift in consumer tech could be AI-first hardware. His vision goes beyond a smarter phone, a device that can understand conversations, remember context and actually participate in your life. “The iPhone is probably the greatest piece of consumer hardware ever created.” But Altman says it wasn’t designed for an AI-first world.

Joe Rogan Podcast News

37,519 views • 5 days ago

Sam Altman says the four hour work week isn't coming, even with AI: "Technology for a long time has been promising people that they’re going to work less and have all this leisure. And it has gone in that direction." "But somehow we never get the promise of the four hour workweek at mass scale in society. And I don’t expect AI to change that." "Clearly, society is not working for a lot of people, and more productivity gains that actually accrue to people would be a great thing. And I suspect they will. I suspect that will happen."

Sam Altman says the four hour work week isn't coming, even with AI: "Technology for a long time has been promising people that they’re going to work less and have all this leisure. And it has gone in that direction." "But somehow we never get the promise of the four hour workweek at mass scale in society. And I don’t expect AI to change that." "Clearly, society is not working for a lot of people, and more productivity gains that actually accrue to people would be a great thing. And I suspect they will. I suspect that will happen."

dnap

196,074 views • 2 months ago

Sam Altman: the ideal AI is a tiny model with superhuman reasoning, a trillion-token context window, and access to every tool. “The platonic ideal is a very tiny model that has superhuman reasoning capabilities.” “It can run ridiculously fast.” “One trillion tokens of context and access to every tool you can possibly imagine.” “Using these models as databases is sort of ridiculous.” “The amazing thing is they can reason.” “Directionally, we’re headed there.”

Sam Altman: the ideal AI is a tiny model with superhuman reasoning, a trillion-token context window, and access to every tool. “The platonic ideal is a very tiny model that has superhuman reasoning capabilities.” “It can run ridiculously fast.” “One trillion tokens of context and access to every tool you can possibly imagine.” “Using these models as databases is sort of ridiculous.” “The amazing thing is they can reason.” “Directionally, we’re headed there.”

Veee

68,477 views • 15 days ago

Generative UI will be the next big shift in AI. Where your product UI is dynamically generated, based on user intent and context. If you are a developer building AI apps, you need to hear this out:

Generative UI will be the next big shift in AI. Where your product UI is dynamically generated, based on user intent and context. If you are a developer building AI apps, you need to hear this out:

Pratham

119,252 views • 10 months ago

Qwen3.8-Flash-Next is still going strong at 364.7K tokens of context on an M5 Max. And this isn’t just a static long-context test. The model was reasoning about how to speed up its own workflow while using tools, and the tool calls kept working without misses. Setup: • Qwen3.8-Flash-Next • M5 Max • 128GB unified memory • MLX-Serve PR #363 • OpenCode 2 • 364.7K context The interesting part isn’t simply getting hundreds of thousands of tokens into memory. It’s what happens once the context gets this large. Long-context inference usually comes with a painful tradeoff. As the KV cache grows, memory pressure increases and generation can slow down. But this setup is still pushing through 364K tokens while maintaining a usable agent workflow. The model can reason, call tools, inspect results, continue working, and keep the session moving. And the tool calls reportedly haven’t missed so far. That’s important for agentic coding. A huge context window is only useful if the model can actually operate reliably inside it. A 400K-token context that constantly breaks tool calls isn’t very useful. A 364K session that can keep reasoning and executing tools is a different story. And the test isn’t finished yet. The current run is approaching 400K tokens, with the expectation that it can keep going. This is also another interesting example of why Apple Silicon keeps showing up in local LLM experiments. The M5 Max’s unified memory gives a large model and its growing KV cache access to one shared memory pool. With MLX-Serve continuing to improve, these machines are becoming surprisingly capable long-context inference boxes. The bigger takeaway: Context length is becoming a workload, not just a model specification. Running a model at 256K is one thing. Keeping an agent alive at 300K+ while it reasons and uses tools is much more interesting. And Qwen3.8-Flash-Next is showing that this can be pushed surprisingly far on a single 128GB Mac. 364.7K and counting. Next stop: 400K.

Qwen3.8-Flash-Next is still going strong at 364.7K tokens of context on an M5 Max. And this isn’t just a static long-context test. The model was reasoning about how to speed up its own workflow while using tools, and the tool calls kept working without misses. Setup: • Qwen3.8-Flash-Next • M5 Max • 128GB unified memory • MLX-Serve PR #363 • OpenCode 2 • 364.7K context The interesting part isn’t simply getting hundreds of thousands of tokens into memory. It’s what happens once the context gets this large. Long-context inference usually comes with a painful tradeoff. As the KV cache grows, memory pressure increases and generation can slow down. But this setup is still pushing through 364K tokens while maintaining a usable agent workflow. The model can reason, call tools, inspect results, continue working, and keep the session moving. And the tool calls reportedly haven’t missed so far. That’s important for agentic coding. A huge context window is only useful if the model can actually operate reliably inside it. A 400K-token context that constantly breaks tool calls isn’t very useful. A 364K session that can keep reasoning and executing tools is a different story. And the test isn’t finished yet. The current run is approaching 400K tokens, with the expectation that it can keep going. This is also another interesting example of why Apple Silicon keeps showing up in local LLM experiments. The M5 Max’s unified memory gives a large model and its growing KV cache access to one shared memory pool. With MLX-Serve continuing to improve, these machines are becoming surprisingly capable long-context inference boxes. The bigger takeaway: Context length is becoming a workload, not just a model specification. Running a model at 256K is one thing. Keeping an agent alive at 300K+ while it reasons and uses tools is much more interesting. And Qwen3.8-Flash-Next is showing that this can be pushed surprisingly far on a single 128GB Mac. 364.7K and counting. Next stop: 400K.

FHILY👑

39,982 views • 1 month ago

The coming merger of AI agents with the physical world. @iddris, founder/CEO of Open Matter and I have a wide-ranging conversation about how the next platform shift may not be just AI chat, robotics, smart glasses, or autonomous cars separately. It may be the connective tissue between all of them. This video teaches viewers that the next wave of AI agents will not just operate inside apps, browsers, calendars, and spreadsheets. The real frontier is agents that can understand, coordinate, and act in the physical world. Iddris explains a vision for “agentic infrastructure for atoms”: systems that let AI agents manage physical objects, deliveries, storage, location, identity, logistics, robots, vehicles, and real-world context.

The coming merger of AI agents with the physical world. @iddris, founder/CEO of Open Matter and I have a wide-ranging conversation about how the next platform shift may not be just AI chat, robotics, smart glasses, or autonomous cars separately. It may be the connective tissue between all of them. This video teaches viewers that the next wave of AI agents will not just operate inside apps, browsers, calendars, and spreadsheets. The real frontier is agents that can understand, coordinate, and act in the physical world. Iddris explains a vision for “agentic infrastructure for atoms”: systems that let AI agents manage physical objects, deliveries, storage, location, identity, logistics, robots, vehicles, and real-world context.

Robert Scoble

17,484 views • 4 months ago

sam altman: - someday everyone should have a personal robot. - we will definitely build humanoid robots, while also exploring other form factors. - the form factor is less important than figuring out the AI brain that makes the robot work. - he also agreed on building a kind of “super-app” that combines ChatGPT and Codex for AI. - he wants one AI interface that can do whatever you need. - it could use your computer and access your context when needed. - you shouldn't have to choose tabs, tools, or modes. AI should figure it out. - AI should be smart enough to understand what you want and act on it.

sam altman: - someday everyone should have a personal robot. - we will definitely build humanoid robots, while also exploring other form factors. - the form factor is less important than figuring out the AI brain that makes the robot work. - he also agreed on building a kind of “super-app” that combines ChatGPT and Codex for AI. - he wants one AI interface that can do whatever you need. - it could use your computer and access your context when needed. - you shouldn't have to choose tabs, tools, or modes. AI should figure it out. - AI should be smart enough to understand what you want and act on it.

SciTech Era

31,585 views • 1 month ago

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.

Brian Roemmele

72,312 views • 10 months ago

Sam Altman says AI may need a new hardware form factor OpenAI and Jony Ive are exploring a family of devices to make AI easier to use — this will take time (not this year, maybe not next) The Goal is a new kind of computer built around AI, a companion through your life

Sam Altman says AI may need a new hardware form factor OpenAI and Jony Ive are exploring a family of devices to make AI easier to use — this will take time (not this year, maybe not next) The Goal is a new kind of computer built around AI, a companion through your life

Haider.

193,273 views • 11 months ago