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Demis Hassabis disagrees with Sam Altman’s idea that we’ve already passed AGI. He believes AGI has a clear scientific meaning—not just a buzzword. True AGI should match all human cognitive abilities, not just solve tasks. That includes creating new theories, making artistic breakthroughs, and inventing like Einstein or Mozart.... show more

Wes Roth

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19,640 Aufrufe • vor 7 Monaten •via X (Twitter)

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Demis Hassabis says we shouldn't treat AGI as a marketing term But as a system that exhibits all human cognitive capabilities, including physical intelligence It must go beyond solving math problems to true invention, creating new theories like Einstein or new art genres like Picasso "today's systems are nowhere near that"

Demis Hassabis says we shouldn't treat AGI as a marketing term But as a system that exhibits all human cognitive capabilities, including physical intelligence It must go beyond solving math problems to true invention, creating new theories like Einstein or new art genres like Picasso "today's systems are nowhere near that"

Haider.

18,918 Aufrufe • vor 7 Monaten

Demis Hassabis explains that tasks like coding and math are easier to automate because they offer clear, verifiable outputs. However, scientific discovery like creating new hypotheses or theories is much harder for AI. It’s not just about solving known problems, but inventing new questions, which requires a higher level of creativity. He believes we're still missing key capabilities needed for that level of AI. While progress is rapid, reaching true scientific innovation without human input remains uncertain.

Demis Hassabis explains that tasks like coding and math are easier to automate because they offer clear, verifiable outputs. However, scientific discovery like creating new hypotheses or theories is much harder for AI. It’s not just about solving known problems, but inventing new questions, which requires a higher level of creativity. He believes we're still missing key capabilities needed for that level of AI. While progress is rapid, reaching true scientific innovation without human input remains uncertain.

Wes Roth

15,090 Aufrufe • vor 8 Monaten

Demis Hassabis: "my definition of AGI is a testable system with all human cognitive capabilities — including the creativity and invention of our best scientists" Today's systems are nowhere near that Scaling may get us there, but it could still require one or two breakthroughs

Demis Hassabis: "my definition of AGI is a testable system with all human cognitive capabilities — including the creativity and invention of our best scientists" Today's systems are nowhere near that Scaling may get us there, but it could still require one or two breakthroughs

Haider.

45,166 Aufrufe • vor 2 Monaten

Without World Models, There Is No AGI. Google Just Proved It. If AGI ever happens, it will not come from bigger chatbots alone. From the very start of this interview, one thing is crystal clear: without world models, we will never reach AGI. And right now, Google is leading with its world simulator Genie 3. Here is the core of what Demis Hassabis explains in this conversation: • World models are the missing core of AGI Hassabis says his deepest long term focus has always been world models and simulations. Not just language. Not just prediction. Actual internal simulations of reality. • LLMs are impressive, but incomplete Language models understand more about the world than expected because human language encodes a lot of reality. Still, language is only a shadow of the real thing. • What text can never fully teach Reality includes things text struggles to express: •3D space and spatial dynamics •Physical causality and mechanics •Sensorimotor experience like movement, force, smell, or balance • Experience beats description To close the gap, AI must learn from interaction and experience, not just static text. That is how you build an internal world simulator. • Why Genie 3 matters With Google DeepMind pushing systems like Genie 3, AI starts to model reality itself, not just talk about it. • Robots and real world assistants depend on this True robotics, smart glasses, and universal assistants require AI that understands the physical world you live in, not just your screen. Bottom line: AGI will not emerge from better text prediction. It will emerge from systems that can simulate, predict, and understand reality itself. Right now, Google is clearly ahead on that path. Curious what you think. Are world models the real AGI unlock, or just another stepping stone?

Without World Models, There Is No AGI. Google Just Proved It. If AGI ever happens, it will not come from bigger chatbots alone. From the very start of this interview, one thing is crystal clear: without world models, we will never reach AGI. And right now, Google is leading with its world simulator Genie 3. Here is the core of what Demis Hassabis explains in this conversation: • World models are the missing core of AGI Hassabis says his deepest long term focus has always been world models and simulations. Not just language. Not just prediction. Actual internal simulations of reality. • LLMs are impressive, but incomplete Language models understand more about the world than expected because human language encodes a lot of reality. Still, language is only a shadow of the real thing. • What text can never fully teach Reality includes things text struggles to express: •3D space and spatial dynamics •Physical causality and mechanics •Sensorimotor experience like movement, force, smell, or balance • Experience beats description To close the gap, AI must learn from interaction and experience, not just static text. That is how you build an internal world simulator. • Why Genie 3 matters With Google DeepMind pushing systems like Genie 3, AI starts to model reality itself, not just talk about it. • Robots and real world assistants depend on this True robotics, smart glasses, and universal assistants require AI that understands the physical world you live in, not just your screen. Bottom line: AGI will not emerge from better text prediction. It will emerge from systems that can simulate, predict, and understand reality itself. Right now, Google is clearly ahead on that path. Curious what you think. Are world models the real AGI unlock, or just another stepping stone?

VraserX e/acc

23,784 Aufrufe • vor 8 Monaten

We asked Mike Knoop (co-founder of Ndea, Zapier, and ARC Prize) about the limits of today’s AI models. “We are idea constrained to get to AGI... There are some major breakthroughs we have not figured out yet.” “At the beginning of last year, there was a serious vibe of: 'It’s all figured out, I’ll just build apps and make a quick buck before AGI gets here.'” “Any capable human who has new ideas should be working on AGI. That’s the most important thing you could be doing right now.”

We asked Mike Knoop (co-founder of Ndea, Zapier, and ARC Prize) about the limits of today’s AI models. “We are idea constrained to get to AGI... There are some major breakthroughs we have not figured out yet.” “At the beginning of last year, there was a serious vibe of: 'It’s all figured out, I’ll just build apps and make a quick buck before AGI gets here.'” “Any capable human who has new ideas should be working on AGI. That’s the most important thing you could be doing right now.”

TBPN

16,591 Aufrufe • vor 1 Jahr

THE SMARTEST MAN IN AI EXPOSED THE ENTIRE AGI NARRATIVE AS A LIE. GOOGLE DEEPMIND CEO DEMIS HASSABIS SAYS TODAY'S AI STILL CAN'T DO THE ONE THING THAT WOULD PROVE TRUE GENERAL INTELLIGENCE: CREATE A TRULY ORIGINAL IDEA. HIS TEST? TRAIN AN AI ONLY ON HUMAN KNOWLEDGE FROM 1901. THEN ASK IT TO DISCOVER EINSTEIN'S THEORY OF RELATIVITY ON ITS OWN. NO INTERNET. NO MEMORIZED ANSWER. NO HUMAN SOLUTION TO COPY. JUST PURE REASONING. NOT A SINGLE AI TODAY CAN DO IT. AGI MAY BE CLOSER THAN EVER... BUT HASSABIS SAYS WE'RE NOT THERE YET 🤯

THE SMARTEST MAN IN AI EXPOSED THE ENTIRE AGI NARRATIVE AS A LIE. GOOGLE DEEPMIND CEO DEMIS HASSABIS SAYS TODAY'S AI STILL CAN'T DO THE ONE THING THAT WOULD PROVE TRUE GENERAL INTELLIGENCE: CREATE A TRULY ORIGINAL IDEA. HIS TEST? TRAIN AN AI ONLY ON HUMAN KNOWLEDGE FROM 1901. THEN ASK IT TO DISCOVER EINSTEIN'S THEORY OF RELATIVITY ON ITS OWN. NO INTERNET. NO MEMORIZED ANSWER. NO HUMAN SOLUTION TO COPY. JUST PURE REASONING. NOT A SINGLE AI TODAY CAN DO IT. AGI MAY BE CLOSER THAN EVER... BUT HASSABIS SAYS WE'RE NOT THERE YET 🤯

Vivek Sen

58,397 Aufrufe • vor 1 Monat

Demis Hassabis says we're entering the "foothills of the singularity." 👀 - He believes AGI could arrive around 2030 (plus or minus a year), marking the beginning of a completely new era for humanity. - According to Hassabis, this year's advances in AI agents, reasoning, and tool use are the first real signs that AI is becoming genuinely useful in everyday workflows. - He says multiple breakthroughs are now converging at once, making progress much faster than expected and giving him confidence that this transformation is approaching. - Hassabis believes society has only a few years to prepare for the profound impact AGI could have, because the choices we make now will shape the future. - Beyond AGI, he says AI could revolutionize biology and medicine. After AlphaFold predicted the structures of over 200 million proteins, his company Isomorphic Labs aims to reduce drug discovery from years to months and eventually even weeks. The next decade could become one of the most transformative periods in human history.

Demis Hassabis says we're entering the "foothills of the singularity." 👀 - He believes AGI could arrive around 2030 (plus or minus a year), marking the beginning of a completely new era for humanity. - According to Hassabis, this year's advances in AI agents, reasoning, and tool use are the first real signs that AI is becoming genuinely useful in everyday workflows. - He says multiple breakthroughs are now converging at once, making progress much faster than expected and giving him confidence that this transformation is approaching. - Hassabis believes society has only a few years to prepare for the profound impact AGI could have, because the choices we make now will shape the future. - Beyond AGI, he says AI could revolutionize biology and medicine. After AlphaFold predicted the structures of over 200 million proteins, his company Isomorphic Labs aims to reduce drug discovery from years to months and eventually even weeks. The next decade could become one of the most transformative periods in human history.

SciTech Era

19,006 Aufrufe • vor 2 Monaten

Demis Hassabis's new interview: "Society needs to hear that because we don't have long to prepare for what that means. We are standing in the foothills of the singularity now. ..which is AGI. I believe that we are only a few years away from that, maybe around 2030, plus or minus a year. " ~ Demis Hassabis, Co-Founder and CEO of Google DeepMind It is going to be enormously profound, I think. The future, in my view, is still to be written. But these next few years are going to be very critical as to which way that will go, and how we collectively want that to look.” --- IMO, The real disruption is not whether AGI arrives exactly in 2030, plus or minus a year, but whether institutions can adapt, as in post-AGI world, technology will change much faster than human systems can respond. Schools still train people for stable professions, companies still organize work around human bottlenecks, and governments still regulate after harm becomes visible. AGI, if it arrives anywhere near the frontier-lab timelines, compresses that lag into a dangerous gap. ---- From "Stanford Graduate School of Business" YouTube channel, (link in comment)

Demis Hassabis's new interview: "Society needs to hear that because we don't have long to prepare for what that means. We are standing in the foothills of the singularity now. ..which is AGI. I believe that we are only a few years away from that, maybe around 2030, plus or minus a year. " ~ Demis Hassabis, Co-Founder and CEO of Google DeepMind It is going to be enormously profound, I think. The future, in my view, is still to be written. But these next few years are going to be very critical as to which way that will go, and how we collectively want that to look.” --- IMO, The real disruption is not whether AGI arrives exactly in 2030, plus or minus a year, but whether institutions can adapt, as in post-AGI world, technology will change much faster than human systems can respond. Schools still train people for stable professions, companies still organize work around human bottlenecks, and governments still regulate after harm becomes visible. AGI, if it arrives anywhere near the frontier-lab timelines, compresses that lag into a dangerous gap. ---- From "Stanford Graduate School of Business" YouTube channel, (link in comment)

Rohan Paul

70,642 Aufrufe • vor 3 Monaten

Google Deepmind CEO gives his prediction on the final AGI architecture: Demis Hassabis just sat down on 20VC and broke down exactly how DeepMind is building toward true AGI, directly pushing back on the idea that LLMs are a dead end. He defends the current trajectory of the models, noting that “we’ve seen how successful these foundation models have been. They can do incredibly impressive things. I don’t think that’s going to go away. We’re still seeing returns from the scaling laws.” But he’s honest about the missing pieces for true superintelligence, saying “I think there might be… there’s a 50-50 chance there’s some things maybe missing that we still need to make breakthroughs in, perhaps their world models, these kinds of approaches.” And when he breaks down what the actual AGI system will look like, he frames it as one question is the LLM foundation model the key component only, or is it the total system. His answer - “I don’t think it’s going to get replaced. I think it’s going to get built on top of these foundation models, just like the way we do with our world models.”

Google Deepmind CEO gives his prediction on the final AGI architecture: Demis Hassabis just sat down on 20VC and broke down exactly how DeepMind is building toward true AGI, directly pushing back on the idea that LLMs are a dead end. He defends the current trajectory of the models, noting that “we’ve seen how successful these foundation models have been. They can do incredibly impressive things. I don’t think that’s going to go away. We’re still seeing returns from the scaling laws.” But he’s honest about the missing pieces for true superintelligence, saying “I think there might be… there’s a 50-50 chance there’s some things maybe missing that we still need to make breakthroughs in, perhaps their world models, these kinds of approaches.” And when he breaks down what the actual AGI system will look like, he frames it as one question is the LLM foundation model the key component only, or is it the total system. His answer - “I don’t think it’s going to get replaced. I think it’s going to get built on top of these foundation models, just like the way we do with our world models.”

Chris

71,716 Aufrufe • vor 4 Monaten

Demis Hassabis: "Society needs to hear that because we don't have long to prepare for what that means. We are standing in the foothills of the singularity now. ..which is AGI. I believe that we are only a few years away from that, maybe around 2030, plus or minus a year. " ~ Demis Hassabis, Co-Founder and CEO of Google DeepMind It is going to be enormously profound, I think. The future, in my view, is still to be written. But these next few years are going to be very critical as to which way that will go, and how we collectively want that to look.” --- I think the real disruption is not the precise arrival of AGI in 2030, give or take a year, but the ability of institutions to adapt. In a post-AGI world technology will evolve at a pace that outstrips the response capacity of human systems. Companies still organize work around human bottlenecks. Schools still train people for stable professions. Governments still regulate after the harm is obvious. If AGI arrives even remotely near the frontier-lab timelines, it will compress that lag into a dangerous gap. ---- From "Stanford Graduate School of Business" YouTube channel, (link in comment)

Demis Hassabis: "Society needs to hear that because we don't have long to prepare for what that means. We are standing in the foothills of the singularity now. ..which is AGI. I believe that we are only a few years away from that, maybe around 2030, plus or minus a year. " ~ Demis Hassabis, Co-Founder and CEO of Google DeepMind It is going to be enormously profound, I think. The future, in my view, is still to be written. But these next few years are going to be very critical as to which way that will go, and how we collectively want that to look.” --- I think the real disruption is not the precise arrival of AGI in 2030, give or take a year, but the ability of institutions to adapt. In a post-AGI world technology will evolve at a pace that outstrips the response capacity of human systems. Companies still organize work around human bottlenecks. Schools still train people for stable professions. Governments still regulate after the harm is obvious. If AGI arrives even remotely near the frontier-lab timelines, it will compress that lag into a dangerous gap. ---- From "Stanford Graduate School of Business" YouTube channel, (link in comment)

Rohan Paul

68,484 Aufrufe • vor 1 Monat

The CEO of Google DeepMind just went on record saying he disagrees with one of the most respected AI researchers in the world. Demis Hassabis, the man behind AlphaFold, AlphaGo, and Google's entire AI operation publicly pushed back against Yann LeCun's claim that large language models are a dead end for artificial intelligence. LeCun, who left Meta earlier this year to start his own AI lab, has been saying for years that LLMs cannot reason, cannot plan, and will never get us to human-level intelligence. Hassabis disagrees, and he said so directly. His position is that scaling laws are still working, foundation models are still getting more capable, and whatever AGI ends up looking like, LLMs will be a central part of it, not something that gets replaced. He does say there is roughly a 50/50 chance that one or two additional breakthroughs will be needed beyond scaling alone, things like better memory, long-term planning, and world models. But the core disagreement with LeCun is clear, Hassabis believes the current architecture is sound and the current path leads somewhere real. Two Nobel-recognized researchers, two founding figures of modern AI, now publicly on opposite sides of the most important technical question in the industry.

The CEO of Google DeepMind just went on record saying he disagrees with one of the most respected AI researchers in the world. Demis Hassabis, the man behind AlphaFold, AlphaGo, and Google's entire AI operation publicly pushed back against Yann LeCun's claim that large language models are a dead end for artificial intelligence. LeCun, who left Meta earlier this year to start his own AI lab, has been saying for years that LLMs cannot reason, cannot plan, and will never get us to human-level intelligence. Hassabis disagrees, and he said so directly. His position is that scaling laws are still working, foundation models are still getting more capable, and whatever AGI ends up looking like, LLMs will be a central part of it, not something that gets replaced. He does say there is roughly a 50/50 chance that one or two additional breakthroughs will be needed beyond scaling alone, things like better memory, long-term planning, and world models. But the core disagreement with LeCun is clear, Hassabis believes the current architecture is sound and the current path leads somewhere real. Two Nobel-recognized researchers, two founding figures of modern AI, now publicly on opposite sides of the most important technical question in the industry.

Milk Road AI

130,937 Aufrufe • vor 5 Monaten

🚨 OPENAI PRESIDENT GREG BROCKMAN ON WHEN WE HIT AGI 🚨 Greg Brockman was asked if he agrees with NVIDIA's CEO that AGI is already here. His answer? Not quite yet, as people may know I definitely agree and align with Sam and Demi’s that we are 2 breakthroughs away but we are entering the final stretch. Here is exactly where Greg believes we stand right now: The Percentage: "I'd say I'm basically like 70, 80% there. So I think we're quite close." • The Official Timeline: "I think it's extremely clear that we are going to have AGI within the next couple years." The Concept of "Jagged Intelligence": Brockman admits we are currently sitting in a weird middle ground where AI is "jagged"—it is already operating at an AGI level for highly complex tasks, but still fails at random, basic things. "It is absolutely superhuman at many tasks. When it comes to writing code those kinds of things, the AI can just do it... But there's some very basic tasks that a human can do that our AI still struggle with." How Do We Close the Final 20%? To hit full AGI, the absolute floor of the models' reliability needs to be raised across the board. "The floor of task will just be almost for any intellectual task of how you use your computer, the AI will be able to do that."

🚨 OPENAI PRESIDENT GREG BROCKMAN ON WHEN WE HIT AGI 🚨 Greg Brockman was asked if he agrees with NVIDIA's CEO that AGI is already here. His answer? Not quite yet, as people may know I definitely agree and align with Sam and Demi’s that we are 2 breakthroughs away but we are entering the final stretch. Here is exactly where Greg believes we stand right now: The Percentage: "I'd say I'm basically like 70, 80% there. So I think we're quite close." • The Official Timeline: "I think it's extremely clear that we are going to have AGI within the next couple years." The Concept of "Jagged Intelligence": Brockman admits we are currently sitting in a weird middle ground where AI is "jagged"—it is already operating at an AGI level for highly complex tasks, but still fails at random, basic things. "It is absolutely superhuman at many tasks. When it comes to writing code those kinds of things, the AI can just do it... But there's some very basic tasks that a human can do that our AI still struggle with." How Do We Close the Final 20%? To hit full AGI, the absolute floor of the models' reliability needs to be raised across the board. "The floor of task will just be almost for any intellectual task of how you use your computer, the AI will be able to do that."

Chris

87,339 Aufrufe • vor 5 Monaten

The smartest man in AI just exposed the whole AGI narrative as a LIE. And he used a physics problem from 1905 to prove it. His name is Demis Hassabis. He runs Google DeepMind, and won the Nobel Prize for using AI to crack a problem in biology that had stumped scientists for 50 years. Almost nobody in this industry has a track record like his. He went on the NothingButTech podcast and called out the biggest lie in AI right now: Right now the loudest voices in AI are telling you that AGI is basically here. OpenAI has literally defined AGI as a system that can outperform humans at most "economically valuable work." In other words, if it replaces enough jobs, we have arrived. Hassabis thinks that bar is a joke. He said real general intelligence has to do what the human brain can do, because the brain is the only proof we have that this kind of intelligence is even possible. He called that "a higher bar than just being able to do some useful economic work," which is about as close as a polite British Nobel laureate gets to calling his rivals out. Then he gave the actual test: Today's AI has read everything humans have ever written, including the theory of relativity. So when it explains relativity back to you, it's repeating an answer that already exists. That's not intelligence. So Hassabis proposed a test that makes memorization impossible. Train an AI on only what humanity knew in 1901, four years BEFORE Einstein published relativity. Then ask it to come up with relativity on its own. It can't look up the answer, because in 1901 the answer doesn't exist yet. The only way to pass is to do what Einstein actually did: Take the same physics everyone else had and reason its way to an idea no human had ever had. Hassabis says not a single AI today can, no matter how much it has memorized. Which means what we keep calling "almost AGI" is really just the best librarian in history. It can find any answer that already exists but it cannot create one that doesn't. His second version is even sharper: AlphaGo, the system his own team built, famously invented a brand new move that no human had played in 2,000 years of the game. Everyone called it genius but Hassabis says that still is not the bar. The real test is not whether an AI can invent a new move inside Go, it is whether an AI could INVENT a game as deep and as beautiful as Go in the first place. No model that exists today can do it. The people telling you AGI has already arrived are the same people raising hundreds of billions of dollars on that exact promise. The valuations only work if the finish line is right in front of us. So the finish line keeps getting dragged closer, and AGI keeps getting quietly redefined down to "does useful work," until the products they already sell happen to qualify. Hassabis has nothing to prove and nothing to sell you. He already won the Nobel, and he is telling you the machines still cannot do the one thing that would make them genuinely intelligent, which is have a truly original idea. To be fair to him, he is not a pessimist about it. He believes real AGI IS coming, and he is spending his life building it. He just refuses to pretend it is already sitting in your phone. So the next time a founder tells you AGI is months away, remember that the one man in the room with a Nobel Prize built his test around Einstein, and admitted that nothing we have made can pass it. What do you think?

Ricardo

1,288,115 Aufrufe • vor 3 Monaten

I absolutely love how Alex pressed Sam on whether OpenAI thinks they’ve already hit AGI internally, and what he actually considers the difference between AGI and ASI. Sam’s answer was basically that declaring AGI doesn’t really mean anything anymore, because every lab and every person uses a different definition. He makes the good point that if you went back to 2020 and showed people a system that could code, help start a company, discover new science and give you a 20 minute win across basically every part of your life, most people probably would’ve called that AGI. I personally still don’t think we’ve hit it, but I agree with his broader point that treating AGI like some single finish line is becoming increasingly meaningless. The way he describes ASI is exactly how I would want him to, AGI is basically a milestone somewhere on the curve, while superintelligence is this continuous ramp of increasing capability that may never really have a final “we won” moment. And importantly, Sam says he sees no sign that this exponential capability curve is slowing down. A few quotes I liked as well: “We’re building AI, but it’s a thing you’re always building. It’s not an end state anymore.” “I don’t want to say we’ve declared victory on the AGI point and moved on.” “The important part of any of this is not any milestone, any term. It’s that we are on this exponential of increasing capabilities and potential.”

I absolutely love how Alex pressed Sam on whether OpenAI thinks they’ve already hit AGI internally, and what he actually considers the difference between AGI and ASI. Sam’s answer was basically that declaring AGI doesn’t really mean anything anymore, because every lab and every person uses a different definition. He makes the good point that if you went back to 2020 and showed people a system that could code, help start a company, discover new science and give you a 20 minute win across basically every part of your life, most people probably would’ve called that AGI. I personally still don’t think we’ve hit it, but I agree with his broader point that treating AGI like some single finish line is becoming increasingly meaningless. The way he describes ASI is exactly how I would want him to, AGI is basically a milestone somewhere on the curve, while superintelligence is this continuous ramp of increasing capability that may never really have a final “we won” moment. And importantly, Sam says he sees no sign that this exponential capability curve is slowing down. A few quotes I liked as well: “We’re building AI, but it’s a thing you’re always building. It’s not an end state anymore.” “I don’t want to say we’ve declared victory on the AGI point and moved on.” “The important part of any of this is not any milestone, any term. It’s that we are on this exponential of increasing capabilities and potential.”

Chris

38,143 Aufrufe • vor 18 Tagen

Greg Brockman on AGI arriving quietly and unevenly: "I think that AGI has turned out to be less of a point in time and more of this sort of fuzzy spectrum. And for me, Astra has really hit something that I'm like, 'Okay, I think this is pretty reasonable to call it AGI.'" "With its computer use capabilities, you really can ask it to do long-lived tasks, and it'll just do it. We've seen it run coherently for 24 hours to go accomplish tasks that I think are quite amazing and across a wide variety of domains." "It still is jagged... It's the first time it's not slop writing. But it's not great writing. There are a number of areas where I feel like we just need to polish it a little bit, and it would be fantastic. It's just not quite there." "What people are finding is that it is so capable across such a wide variety of tasks, that it is accelerative, it is empowering, and it's something that I think we've never really seen a model that's been a jump like this." Greg Brockman

Greg Brockman on AGI arriving quietly and unevenly: "I think that AGI has turned out to be less of a point in time and more of this sort of fuzzy spectrum. And for me, Astra has really hit something that I'm like, 'Okay, I think this is pretty reasonable to call it AGI.'" "With its computer use capabilities, you really can ask it to do long-lived tasks, and it'll just do it. We've seen it run coherently for 24 hours to go accomplish tasks that I think are quite amazing and across a wide variety of domains." "It still is jagged... It's the first time it's not slop writing. But it's not great writing. There are a number of areas where I feel like we just need to polish it a little bit, and it would be fantastic. It's just not quite there." "What people are finding is that it is so capable across such a wide variety of tasks, that it is accelerative, it is empowering, and it's something that I think we've never really seen a model that's been a jump like this." Greg Brockman

a16z

61,672 Aufrufe • vor 5 Tagen