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The "Intelligence Optimum" - How smart can AI really become? As AI benchmarks continue getting saturated, I've been thinking about a fascinating parallel to graphics in the '90s and 2000s. Back then, once you hit tens of thousands of triangles in 3D models, your eye couldn't really tell the...

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David Shapiro ⏩

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12,204 views • 11 months ago •via X (Twitter)

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Elon Musk: Artificial intelligence will continue to scale until we've harnessed all the energy of our galaxy. “I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy, sort of Kardashev 2, Kardashev 3 scale compute. One should think about artificial intelligence, not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of. Human intelligence has also scaled as the population has increased and we've been able to store more and more information.” Interview at the All-In Summit, September 10, 2025
0:42

Elon Musk: Artificial intelligence will continue to scale until we've harnessed all the energy of our galaxy. “I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy, sort of Kardashev 2, Kardashev 3 scale compute. One should think about artificial intelligence, not as a destination that you reach, but really as part of the overall escalation of intelligence that we are aware of. Human intelligence has also scaled as the population has increased and we've been able to store more and more information.” Interview at the All-In Summit, September 10, 2025

ELON CLIPS

41,833 views • 10 months ago

Elon Musk: As human intelligence plateaus, AI will scale to harness most of the power of the galaxy Elon: "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy." “ Once you think about artificial intelligence not as sort of this destination that you reach, but really as part of the overall escalation of intelligence, you know, human intelligence has also scaled as the population has increased, and we've been able to store more and more information.” “Because of population declines and low birthrate, human intelligence is somewhat plateauing and will actually decline.” “I think that we might have AI smarter than any single human at anything as soon as next year.” “And then probably within five (years), like say 2030, probably AI is smarter than the sum of all humans.” Friedberg: “ Do you think humans are on the decline because the AI is evolving?” “Do you think there's this evolution of the ecosystem on earth that's underway, that we don't really understand the structure of what's going on?” Elon: “ Yeah, maybe we implicitly know that it's coming.” Elon Musk david friedberg
1:13

Elon Musk: As human intelligence plateaus, AI will scale to harness most of the power of the galaxy Elon: "I think we'll see intelligence continue to scale all the way up to where most of the power of the sun is harnessed for compute, and then ultimately most of the power of the galaxy." “ Once you think about artificial intelligence not as sort of this destination that you reach, but really as part of the overall escalation of intelligence, you know, human intelligence has also scaled as the population has increased, and we've been able to store more and more information.” “Because of population declines and low birthrate, human intelligence is somewhat plateauing and will actually decline.” “I think that we might have AI smarter than any single human at anything as soon as next year.” “And then probably within five (years), like say 2030, probably AI is smarter than the sum of all humans.” Friedberg: “ Do you think humans are on the decline because the AI is evolving?” “Do you think there's this evolution of the ecosystem on earth that's underway, that we don't really understand the structure of what's going on?” Elon: “ Yeah, maybe we implicitly know that it's coming.” Elon Musk david friedberg

The All-In Podcast

107,012 views • 10 months ago

Liquid AI (Liquid AI) CEO Ramin Hasani (Ramin) says: "We're bringing the cost of tokens to zero." "The axis was maximizing intelligence at all costs." Foundation models need to optimize across 3 axes: 1.) Intelligence and capability 2.) Efficiency and cost 3.) Substrate: where the intelligence actually runs "Efficiency is not an afterthought. Energy is not abundant." "If you maximize intelligence at all costs, that axis alone is not going to get you to the place that you want to go." "Efficiency and cost of intelligence as a first-class citizen, and not an afterthought." "Where does this intelligence system go? AI is majorly getting hosted in data centers, but you could also bring intelligence on phones, on laptops, on airplanes, on cars." "Imagine if it's not tokens that are actually important. It's just the outcome that actually matters." "Not just thinking about foundation models as the token machines that are generating money and revenue for the foundation model companies that are useless tokens, and getting them into the place where they can actually unlock true value for enterprises."
6:17

Liquid AI (Liquid AI) CEO Ramin Hasani (Ramin) says: "We're bringing the cost of tokens to zero." "The axis was maximizing intelligence at all costs." Foundation models need to optimize across 3 axes: 1.) Intelligence and capability 2.) Efficiency and cost 3.) Substrate: where the intelligence actually runs "Efficiency is not an afterthought. Energy is not abundant." "If you maximize intelligence at all costs, that axis alone is not going to get you to the place that you want to go." "Efficiency and cost of intelligence as a first-class citizen, and not an afterthought." "Where does this intelligence system go? AI is majorly getting hosted in data centers, but you could also bring intelligence on phones, on laptops, on airplanes, on cars." "Imagine if it's not tokens that are actually important. It's just the outcome that actually matters." "Not just thinking about foundation models as the token machines that are generating money and revenue for the foundation model companies that are useless tokens, and getting them into the place where they can actually unlock true value for enterprises."

Molly O’Shea

12,816 views • 19 days ago

Elon Musk: Well, I’m not sure AI is the main risk I’m worried about. The vast majority of intelligence in the future will be AI. Humans will be a very tiny percentage of all intelligence if current trends continue. My focus is ensuring human intelligence and consciousness are propagated into the future. We want to maximize the probable light cone of consciousness and intelligence. Yeah, I’m very pro-human, so I want to make sure we take actions that ensure humans are along for the ride. But I think maybe in 5 or 6 years, AI will exceed the sum of all human intelligence. If that continues, human intelligence could be less than one percent of all intelligence. That’s why it’s critical we align AI with values that propagate consciousness. In the long run, it’s difficult to imagine that humans will be in charge if we’re only one percent of combined intelligence. What we can do is ensure AI has values that increase intelligence and consciousness in the universe. XAI’s mission is to understand the universe because curiosity, existence, and understanding are all connected. If you want to understand the universe, you care about propagating intelligence—and that includes humanity. Understanding the universe actually means ensuring humans continue to expand into the future. Increasing the scope, scale, and lifespan of intelligence is the ultimate goal. Basically, humans will become a tiny percentage of total intelligence. The best way forward is to take actions that maximize consciousness and intelligence in the universe. If AI continues to grow, our priority must be ensuring humanity is along for the ride while curiosity drives us to explore and understand the universe.
2:54

Elon Musk: Well, I’m not sure AI is the main risk I’m worried about. The vast majority of intelligence in the future will be AI. Humans will be a very tiny percentage of all intelligence if current trends continue. My focus is ensuring human intelligence and consciousness are propagated into the future. We want to maximize the probable light cone of consciousness and intelligence. Yeah, I’m very pro-human, so I want to make sure we take actions that ensure humans are along for the ride. But I think maybe in 5 or 6 years, AI will exceed the sum of all human intelligence. If that continues, human intelligence could be less than one percent of all intelligence. That’s why it’s critical we align AI with values that propagate consciousness. In the long run, it’s difficult to imagine that humans will be in charge if we’re only one percent of combined intelligence. What we can do is ensure AI has values that increase intelligence and consciousness in the universe. XAI’s mission is to understand the universe because curiosity, existence, and understanding are all connected. If you want to understand the universe, you care about propagating intelligence—and that includes humanity. Understanding the universe actually means ensuring humans continue to expand into the future. Increasing the scope, scale, and lifespan of intelligence is the ultimate goal. Basically, humans will become a tiny percentage of total intelligence. The best way forward is to take actions that maximize consciousness and intelligence in the universe. If AI continues to grow, our priority must be ensuring humanity is along for the ride while curiosity drives us to explore and understand the universe.

Ian Miles Cheong

13,080 views • 5 months ago

A Talk About AI That Will Blow Your Mind. It Did In 1998 When I Attended The Talk. I just found this video from 1998 when I attended this talk by Rupert Sheldrake, Terence McKenna and Ralph Abraham at the University of California, Santa Cruz to explore how machine intelligence might evolve in relation to our own. I never thought I would see this again and it had a great influence on me in the AI I was building in that era and on to today. But ai just found a copy. I certainly did not run around with a VHS recorder so I am blown away that this exists. Now you can see what I saw. At that time, the internet was still young, and artificial intelligence belonged mostly to science fiction. Yet many of the questions we raised then have become part of daily life. In this conversation, it was explored whether intelligence is best understood as logic and computation, or as something embodied, participatory, and alive. Can the mind be reduced to code, or does life itself depend on forms of knowing that no algorithm can contain? AI now outpace us in speed, reach, and memory. Yet the deeper mystery is not how far they can go, but what they reveal about mind and ourselves. Will AI reproduce the limitations of our mechanistic worldview, or might it help us rediscover dimensions of mind that transcend machinery altogether? It's striking how near we now are to the possibilities we once only speculated about. Quantum computing, self-learning systems, large language models very much as Terence describes—and the looming prospect of superintelligence—have moved from the margins to the mainstream. But the heart of the conversation remains just as relevant today, if not more so: what is consciousness, and how might we participate in its unfolding evolution?
42:37

A Talk About AI That Will Blow Your Mind. It Did In 1998 When I Attended The Talk. I just found this video from 1998 when I attended this talk by Rupert Sheldrake, Terence McKenna and Ralph Abraham at the University of California, Santa Cruz to explore how machine intelligence might evolve in relation to our own. I never thought I would see this again and it had a great influence on me in the AI I was building in that era and on to today. But ai just found a copy. I certainly did not run around with a VHS recorder so I am blown away that this exists. Now you can see what I saw. At that time, the internet was still young, and artificial intelligence belonged mostly to science fiction. Yet many of the questions we raised then have become part of daily life. In this conversation, it was explored whether intelligence is best understood as logic and computation, or as something embodied, participatory, and alive. Can the mind be reduced to code, or does life itself depend on forms of knowing that no algorithm can contain? AI now outpace us in speed, reach, and memory. Yet the deeper mystery is not how far they can go, but what they reveal about mind and ourselves. Will AI reproduce the limitations of our mechanistic worldview, or might it help us rediscover dimensions of mind that transcend machinery altogether? It's striking how near we now are to the possibilities we once only speculated about. Quantum computing, self-learning systems, large language models very much as Terence describes—and the looming prospect of superintelligence—have moved from the margins to the mainstream. But the heart of the conversation remains just as relevant today, if not more so: what is consciousness, and how might we participate in its unfolding evolution?

Brian Roemmele

147,955 views • 8 months ago

TESLA ISN'T JUST AHEAD IN AI, IT'S AN ORDER OF MAGNITUDE MORE EFFICIENT THAN THE REST OF THE WORLD "I actually think Tesla is ahead of the rest of the world in intelligence density of AI by an order of magnitude or more This is going to sound like a pretty bold statement, but I know what the intelligence efficiency of the big models are like, Grok and a bunch of the other models Tesla’s AI is, in terms of its memory efficiency, I think more than an order of magnitude better. The Tesla AI is very compute-efficient and very memory-efficient One of the metrics one should consider for any given AI model is the intelligence per gigabyte. Especially when you’re constrained on RAM, having an AI that has very high intelligence density per gigabyte for a given number of gigabytes, how much functionality can you get out of it" - Elon Musk
0:59

TESLA ISN'T JUST AHEAD IN AI, IT'S AN ORDER OF MAGNITUDE MORE EFFICIENT THAN THE REST OF THE WORLD "I actually think Tesla is ahead of the rest of the world in intelligence density of AI by an order of magnitude or more This is going to sound like a pretty bold statement, but I know what the intelligence efficiency of the big models are like, Grok and a bunch of the other models Tesla’s AI is, in terms of its memory efficiency, I think more than an order of magnitude better. The Tesla AI is very compute-efficient and very memory-efficient One of the metrics one should consider for any given AI model is the intelligence per gigabyte. Especially when you’re constrained on RAM, having an AI that has very high intelligence density per gigabyte for a given number of gigabytes, how much functionality can you get out of it" - Elon Musk

X Freeze

62,736 views • 6 months ago

Our ravidilse.eth answering: How can ZK and AI work together? - AI is for intelligence - ZK is for confidence in that intelligence. Intelligence like: - decisions - predictions - content With this intelligence, we want to find out: - where did this (intelligence) come from? - can I rely on this? - who is accountable for it? Now ZK technology comes in handy because it serves as the missing trust layer. For example: - Does a user qualify for an airdrop or not? - You don’t have to share your country - You only generate proof saying, "Yes, I do not belong to any of those listed sanctioned countries." You don’t share all the information only the proof that supports your claim. Speaker: Ravikant Agrawal, Billions Director of Growth and AI Partnerships Source: X Space from Jan 27, 2026 with Billions and Billions partner Cysic
0:42

Our ravidilse.eth answering: How can ZK and AI work together? - AI is for intelligence - ZK is for confidence in that intelligence. Intelligence like: - decisions - predictions - content With this intelligence, we want to find out: - where did this (intelligence) come from? - can I rely on this? - who is accountable for it? Now ZK technology comes in handy because it serves as the missing trust layer. For example: - Does a user qualify for an airdrop or not? - You don’t have to share your country - You only generate proof saying, "Yes, I do not belong to any of those listed sanctioned countries." You don’t share all the information only the proof that supports your claim. Speaker: Ravikant Agrawal, Billions Director of Growth and AI Partnerships Source: X Space from Jan 27, 2026 with Billions and Billions partner Cysic

Billions

11,463 views • 6 months ago

Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about is to use AI and lots of compute to discover new science." "A recent cool example here is we built the Sora Android app using Codex... in less than a month." "You can imagine that way much further, where entire companies can build their products using lots of compute." Then he gives the scale: "Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models." "We're going to have these models at a company be outputting more tokens per day than all of humanity put together, and then 10 times that, and then 100 times that." The bottleneck is moving from software talent to compute supply, inference speed, product integration, and where all that machine intelligence gets pointed.
3:31

Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about is to use AI and lots of compute to discover new science." "A recent cool example here is we built the Sora Android app using Codex... in less than a month." "You can imagine that way much further, where entire companies can build their products using lots of compute." Then he gives the scale: "Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models." "We're going to have these models at a company be outputting more tokens per day than all of humanity put together, and then 10 times that, and then 100 times that." The bottleneck is moving from software talent to compute supply, inference speed, product integration, and where all that machine intelligence gets pointed.

Karl Mehta

16,606 views • 29 days ago

OpenAI's Chief Futurist Joshua Achiam breaks with the consensus on takeoff, arguing intelligence hits a physical ceiling and then raw compute decides who wins: "People expect that there's no ceiling for the amount of intelligence that you could have in a model, and they think of recursive self-improvement as this loop that's gonna happen at some point or another. RSI starts happening and model intelligence takes off and it goes to the moon, and they don't see a ceiling." "I think on physical grounds, there's gotta be a maximum amount of computation that you can have per unit volume and energy in the physical universe. And that sort of implies there's a maximum amount of intelligence per unit volume and unit of energy." "If that's the case, eventually, seeing how fast AI model capabilities are increasing right now, eventually everyone hits that saturation point and everyone's got roughly equivalently capable models from a raw intelligence perspective." "The open source frontier lags the closed source frontier by some number of months, but the fact that it's months is crazy. So eventually everyone is probably working with equally maximally capable models, and then it's amount of compute that you're able to throw at a problem that determines who wins." Joshua Achiam
2:05

OpenAI's Chief Futurist Joshua Achiam breaks with the consensus on takeoff, arguing intelligence hits a physical ceiling and then raw compute decides who wins: "People expect that there's no ceiling for the amount of intelligence that you could have in a model, and they think of recursive self-improvement as this loop that's gonna happen at some point or another. RSI starts happening and model intelligence takes off and it goes to the moon, and they don't see a ceiling." "I think on physical grounds, there's gotta be a maximum amount of computation that you can have per unit volume and energy in the physical universe. And that sort of implies there's a maximum amount of intelligence per unit volume and unit of energy." "If that's the case, eventually, seeing how fast AI model capabilities are increasing right now, eventually everyone hits that saturation point and everyone's got roughly equivalently capable models from a raw intelligence perspective." "The open source frontier lags the closed source frontier by some number of months, but the fact that it's months is crazy. So eventually everyone is probably working with equally maximally capable models, and then it's amount of compute that you're able to throw at a problem that determines who wins." Joshua Achiam

MTS

58,674 views • 4 days ago

Ray Kurzweil dropped a mind-bending clarification on the timeline we’ve all been watching. He still stands by his famous 2029 prediction for human-level AI. But the Singularity — the point where we become a thousand times smarter — comes in 2045. The key difference? We won’t just have AI beside us. We’re going to merge with it. Kurzweil says the boundary will disappear: you won’t know whether an idea popped into your head from your biological brain or your computational intelligence. It will feel exactly the same. Today we can tell when something comes from an LLM. In the future, we won’t. By 2045, he believes this merger will multiply our intelligence by a factor of 1,000. It’s not two separate things competing. It’s one seamless intelligence — and we become it. What do you think — does the idea of fully merging with AI excite you, scare you, or both?
3:09

Ray Kurzweil dropped a mind-bending clarification on the timeline we’ve all been watching. He still stands by his famous 2029 prediction for human-level AI. But the Singularity — the point where we become a thousand times smarter — comes in 2045. The key difference? We won’t just have AI beside us. We’re going to merge with it. Kurzweil says the boundary will disappear: you won’t know whether an idea popped into your head from your biological brain or your computational intelligence. It will feel exactly the same. Today we can tell when something comes from an LLM. In the future, we won’t. By 2045, he believes this merger will multiply our intelligence by a factor of 1,000. It’s not two separate things competing. It’s one seamless intelligence — and we become it. What do you think — does the idea of fully merging with AI excite you, scare you, or both?

Camus

63,224 views • 3 months ago

Every major turning point in human history had a moment where the people closest to it understood what was coming and everyone else didn’t. The printing press. The atomic bomb. The internet. Dario Amodei is trying to close that gap. Most people still aren’t listening. Amodei: “My fundamental view is that AI has been on an exponential for the last ten years and as part of a sort of Moore’s law for intelligence.” Not a metaphor. A measured curve. Not slowing. Accelerating. We are “well advanced on that curve” with a “small number of years” remaining before AI surpasses human cognitive capability across most things. Amodei: “We’re increasingly close to what I’ve called a country of geniuses in a data center.” Not one system. A coordinated set of AI agents, each more capable than most humans at most things, running in parallel, never sleeping, never losing focus, coordinating at speeds no biological intelligence can match. The ceiling on human progress has always been simple. Genius is rare and time is finite. That constraint is gone. We are not approaching the ceiling of intelligence. We are approaching the ceiling of intelligence that biology can produce. Those are not the same ceiling. The human brain is constrained by evolution, energy, skull size, and lifespan. AI has none of those limits. We have no framework for what intelligence looks like when you remove every biological constraint that shaped ours. Every tool we use to comprehend it is built from a mind it will surpass. Amodei: “AI models surpassing the cognitive capabilities of most humans for most things.” The upsides are “absolutely staggering.” So are the consequences. Displacement. Misuse. A period of disruption that reshapes how most people work, earn, and find purpose before the benefits reach them. The same exponential that produces the cures produces the chaos. They arrive together. That’s the optimistic read. The other read is this. We are building it without international standards in place. Racing to deploy before solving displacement or misuse. And once it’s operating beyond our ability to fully comprehend or follow, managing the disruption stops being something we do. It becomes something we experience while hoping the intelligence we created decides keeping us around still serves its objectives. Every turning point in history looks inevitable in hindsight. The people inside the moment never saw it that cleanly. We’re inside the moment.
0:36

Every major turning point in human history had a moment where the people closest to it understood what was coming and everyone else didn’t. The printing press. The atomic bomb. The internet. Dario Amodei is trying to close that gap. Most people still aren’t listening. Amodei: “My fundamental view is that AI has been on an exponential for the last ten years and as part of a sort of Moore’s law for intelligence.” Not a metaphor. A measured curve. Not slowing. Accelerating. We are “well advanced on that curve” with a “small number of years” remaining before AI surpasses human cognitive capability across most things. Amodei: “We’re increasingly close to what I’ve called a country of geniuses in a data center.” Not one system. A coordinated set of AI agents, each more capable than most humans at most things, running in parallel, never sleeping, never losing focus, coordinating at speeds no biological intelligence can match. The ceiling on human progress has always been simple. Genius is rare and time is finite. That constraint is gone. We are not approaching the ceiling of intelligence. We are approaching the ceiling of intelligence that biology can produce. Those are not the same ceiling. The human brain is constrained by evolution, energy, skull size, and lifespan. AI has none of those limits. We have no framework for what intelligence looks like when you remove every biological constraint that shaped ours. Every tool we use to comprehend it is built from a mind it will surpass. Amodei: “AI models surpassing the cognitive capabilities of most humans for most things.” The upsides are “absolutely staggering.” So are the consequences. Displacement. Misuse. A period of disruption that reshapes how most people work, earn, and find purpose before the benefits reach them. The same exponential that produces the cures produces the chaos. They arrive together. That’s the optimistic read. The other read is this. We are building it without international standards in place. Racing to deploy before solving displacement or misuse. And once it’s operating beyond our ability to fully comprehend or follow, managing the disruption stops being something we do. It becomes something we experience while hoping the intelligence we created decides keeping us around still serves its objectives. Every turning point in history looks inevitable in hindsight. The people inside the moment never saw it that cleanly. We’re inside the moment.

Dustin

47,204 views • 5 months ago

The naturalistic Origin of Life is impossible. Abiogenesis requires so many miracles, it makes the resurrection of Jesus look common by comparison. You could put all the parts of a living cell together in a sterile solution, and after a bajillion years they still would not self-assemble into a living cell. Life requires two things: 1. Life requires functional information. That is, informational content which gives functional purpose to molecules. Without functional information, molecules in Life would have no purpose and therefore be unable to function. In all human experience, only intelligence creates functional information. 2. Life requires energy. In order to replicate and conduct metabolic processes, Life requires a constant supply of usable energy. Not just any energy will do - throwing your phone on the grill will not charge it, will it? It needs a specific type of energy, supplied in a specific way that your phone can use it. Life needs the same. In all human experience, only intelligence is able to build systems that can harness and process energy. But here is the paradox: These two things - information & energy - exist in fundamental opposition to each other. Virtually all forms of energy in the world destroy Life's simple molecules. Chemistry and physics do not naturally move in a life-friendly direction. They do the opposite. Life's very fragile molecules require very precise and specific conditions to exist. Conditions that can only be created and maintained by intelligent agents. Origin of Life research has proven this, as virtually every experiment claimed to show "progress" in OOL Research requires highly constrained, specific conditions and sophisticated chemical recipes that could never possibly exist in nature. Life must have been Divinely Designed. Only intelligence can invent functional information, and only intelligence can engineer the systems necessary to harness & produce energy for Life's systems. That's what The Science says.
0:49

The naturalistic Origin of Life is impossible. Abiogenesis requires so many miracles, it makes the resurrection of Jesus look common by comparison. You could put all the parts of a living cell together in a sterile solution, and after a bajillion years they still would not self-assemble into a living cell. Life requires two things: 1. Life requires functional information. That is, informational content which gives functional purpose to molecules. Without functional information, molecules in Life would have no purpose and therefore be unable to function. In all human experience, only intelligence creates functional information. 2. Life requires energy. In order to replicate and conduct metabolic processes, Life requires a constant supply of usable energy. Not just any energy will do - throwing your phone on the grill will not charge it, will it? It needs a specific type of energy, supplied in a specific way that your phone can use it. Life needs the same. In all human experience, only intelligence is able to build systems that can harness and process energy. But here is the paradox: These two things - information & energy - exist in fundamental opposition to each other. Virtually all forms of energy in the world destroy Life's simple molecules. Chemistry and physics do not naturally move in a life-friendly direction. They do the opposite. Life's very fragile molecules require very precise and specific conditions to exist. Conditions that can only be created and maintained by intelligent agents. Origin of Life research has proven this, as virtually every experiment claimed to show "progress" in OOL Research requires highly constrained, specific conditions and sophisticated chemical recipes that could never possibly exist in nature. Life must have been Divinely Designed. Only intelligence can invent functional information, and only intelligence can engineer the systems necessary to harness & produce energy for Life's systems. That's what The Science says.

Divinely Designed

26,389 views • 5 months ago

Elon Musk: The probability of AI going bad is not zero. “I saw GPT-1, GPT-2, GPT-3, GPT-4, the whole lead-up to that. So it was easy for me to kind of see where it's going. If you just extrapolate the points on a curve and assume that trend will continue, then we will have profound artificial intelligence, and obviously at a level that far exceeds human intelligence. So I'm glad to see at this point that people are taking safety seriously. And I do think overall that the potential is there for artificial intelligence, AI, to have most likely a positive effect and to create a future of abundance where there is no scarcity of goods and services. But it is somewhat of the magic genie problem, where if you have a magic genie that can grant all the wishes, usually those stories don't end well. Be careful what you wish for.” In Conversation with Rishi Sunak, November 2, 2023.
1:12

Elon Musk: The probability of AI going bad is not zero. “I saw GPT-1, GPT-2, GPT-3, GPT-4, the whole lead-up to that. So it was easy for me to kind of see where it's going. If you just extrapolate the points on a curve and assume that trend will continue, then we will have profound artificial intelligence, and obviously at a level that far exceeds human intelligence. So I'm glad to see at this point that people are taking safety seriously. And I do think overall that the potential is there for artificial intelligence, AI, to have most likely a positive effect and to create a future of abundance where there is no scarcity of goods and services. But it is somewhat of the magic genie problem, where if you have a magic genie that can grant all the wishes, usually those stories don't end well. Be careful what you wish for.” In Conversation with Rishi Sunak, November 2, 2023.

ELON CLIPS

22,095 views • 27 days ago

David Friedberg Explains Why AI Will Break Every Economic Model: Will Output Surpass Consumptive Capacity? I think fundamentally, if you're driving productivity with AI, you're driving leverage on human time and leverage on capital. The question is, how quickly can you drive that up? And that's a function of how much consumption there is, how much capacity there is for consumption. So if your earnings are the same, but things are getting more expensive, you're not happy. If your earnings go up by 10% and things stay the same price, you got 10% more than you had last year, you're gonna be happy. I just think all humans are driven by this need to consume more each year than they did last year. So I think for me, that's the lower limit on consumptive capacity in the world. The question that we're now facing, which we've never faced in human history before, is there an upper limit on consumptive capacity? Because AI creates such a profound shift in productivity and in leverage that normally you would say, “Hey, when we get a new tool or we get new leverage in a system, we build a new technology, we can make more with less.” Therefore, everyone gets access to more things for the same price or the cost of things that they consume come down by a certain price. But there may be a situation now where the ability to make stuff exceeds the capacity to consume stuff, and that is something that I don't think we’ve faced before. And I think that's where a lot of the models start to break. Just general economic models, just general productivity models and general social models. And this goes to the point about, like, what is everyone going to do? In the same way that I think we've argued that maybe SaaS was a transitory business phenomenon that existed between the foundation of the internet and the era of AI, it may be the case that knowledge work in general is also a transitory phenomenon that only existed between the foundation of the computer, or computing tools, and the existence of AI, generally speaking. And if all of that goes away very quickly, and all of those people can be redistributed and recast into doing other higher level, more creative things, their productivity goes up by 100x, is there really a consumer on the other end of all of that productivity? Is there really enough consumptive capacity? And I think that's the profound question that we all face.
2:18

David Friedberg Explains Why AI Will Break Every Economic Model: Will Output Surpass Consumptive Capacity? I think fundamentally, if you're driving productivity with AI, you're driving leverage on human time and leverage on capital. The question is, how quickly can you drive that up? And that's a function of how much consumption there is, how much capacity there is for consumption. So if your earnings are the same, but things are getting more expensive, you're not happy. If your earnings go up by 10% and things stay the same price, you got 10% more than you had last year, you're gonna be happy. I just think all humans are driven by this need to consume more each year than they did last year. So I think for me, that's the lower limit on consumptive capacity in the world. The question that we're now facing, which we've never faced in human history before, is there an upper limit on consumptive capacity? Because AI creates such a profound shift in productivity and in leverage that normally you would say, “Hey, when we get a new tool or we get new leverage in a system, we build a new technology, we can make more with less.” Therefore, everyone gets access to more things for the same price or the cost of things that they consume come down by a certain price. But there may be a situation now where the ability to make stuff exceeds the capacity to consume stuff, and that is something that I don't think we’ve faced before. And I think that's where a lot of the models start to break. Just general economic models, just general productivity models and general social models. And this goes to the point about, like, what is everyone going to do? In the same way that I think we've argued that maybe SaaS was a transitory business phenomenon that existed between the foundation of the internet and the era of AI, it may be the case that knowledge work in general is also a transitory phenomenon that only existed between the foundation of the computer, or computing tools, and the existence of AI, generally speaking. And if all of that goes away very quickly, and all of those people can be redistributed and recast into doing other higher level, more creative things, their productivity goes up by 100x, is there really a consumer on the other end of all of that productivity? Is there really enough consumptive capacity? And I think that's the profound question that we all face.

The All-In Podcast

81,865 views • 4 months ago

Superintelligence is Near! Three innovations that prove it! Three recent innovations lead me to believe that we've just seen the invention of the next generation of "cognitive primitives" that will lead us directly to ASI. Do you remember LSTM? At the time, there were jokes that "brains are just LSTMs!" This feels like another "just before GPT moment" to me. HRM (hierarchical reasoning models), combined with IMO gold medal models, and the ASI-ARCH "AlphaGo for neural architecture" tells me that we're about to completely decouple machine intelligence from even data inputs. Also, my intuitive definition of ASI is "beyond the 100th percentile of human capability" meaning that "AGI can do anything humans can do, perhaps just faster" - BUT - I suspect that we're about to see machines that can solve problems that humans simply are not biologically capable of solving. It's not necessarily a matter of speed anymore. Sure, these things are faster, and perhaps the ASI level machines could teach us to solve problems that they can, but it will take us a long time to catch up, and in the meantime, they will have moved on. Mark my words, I suspect that is what we've just seen happen this past week. This is well and truly the beginning of the fast takeoff.
8:44

Superintelligence is Near! Three innovations that prove it! Three recent innovations lead me to believe that we've just seen the invention of the next generation of "cognitive primitives" that will lead us directly to ASI. Do you remember LSTM? At the time, there were jokes that "brains are just LSTMs!" This feels like another "just before GPT moment" to me. HRM (hierarchical reasoning models), combined with IMO gold medal models, and the ASI-ARCH "AlphaGo for neural architecture" tells me that we're about to completely decouple machine intelligence from even data inputs. Also, my intuitive definition of ASI is "beyond the 100th percentile of human capability" meaning that "AGI can do anything humans can do, perhaps just faster" - BUT - I suspect that we're about to see machines that can solve problems that humans simply are not biologically capable of solving. It's not necessarily a matter of speed anymore. Sure, these things are faster, and perhaps the ASI level machines could teach us to solve problems that they can, but it will take us a long time to catch up, and in the meantime, they will have moved on. Mark my words, I suspect that is what we've just seen happen this past week. This is well and truly the beginning of the fast takeoff.

David Shapiro ⏩

31,137 views • 1 year ago

Sen. John Kennedy: Classified American intelligence showed that Iran was threatening to bomb London, Paris & Germany "Here's what our intelligence showed, and I've seen it. It's classified, but I've seen it. But I can give you a general outline. Our intelligence showed that Iran was building up its missile capacity, both ballistic and cruise, and they were going to compile so many missiles and drones that they were going to turn to America and Israel and say, 'We're restarting our nuclear weapons program, and if you try to stop us, we're going to destroy the rest of the Middle East. And by the way, our missiles can now reach London, Paris, and Germany.'" "I've seen the intelligence. And President Trump was faced with, 'Well, do I let them continue?' He had already bombed some of their nuclear facilities, but he was faced with the decision: Do I let them get to the point where they have so many missiles and drones, ballistic and cruise, that they could destroy the Middle East, that they could hit London, that they might even be able to hit the United States? Or do I go in to stop them?' And he did."
1:21

Sen. John Kennedy: Classified American intelligence showed that Iran was threatening to bomb London, Paris & Germany "Here's what our intelligence showed, and I've seen it. It's classified, but I've seen it. But I can give you a general outline. Our intelligence showed that Iran was building up its missile capacity, both ballistic and cruise, and they were going to compile so many missiles and drones that they were going to turn to America and Israel and say, 'We're restarting our nuclear weapons program, and if you try to stop us, we're going to destroy the rest of the Middle East. And by the way, our missiles can now reach London, Paris, and Germany.'" "I've seen the intelligence. And President Trump was faced with, 'Well, do I let them continue?' He had already bombed some of their nuclear facilities, but he was faced with the decision: Do I let them get to the point where they have so many missiles and drones, ballistic and cruise, that they could destroy the Middle East, that they could hit London, that they might even be able to hit the United States? Or do I go in to stop them?' And he did."

Tony Jacob | FindaClip.com

360,705 views • 26 days ago

Theoretical physicist Michio Kaku on why aging is simply an accumulation of errors that AI can now identify: He opens with a bold claim about what artificial intelligence might finally make possible: "Artificial intelligence may give us something that the kings and queens of old could never conquer and that is the aging process." For Dr. Michio Kaku, the science behind why we age is no longer a mystery. It comes down to one thing: errors building up inside our cells over time. "We now know why things age. Things get old and die because they accumulate error. Error in the form of DNA mistakes. Accumulation of errors inside cells." The challenge, until now, has been the sheer scale of the problem. Identifying exactly where and how these errors occur across the human genome has been beyond what conventional research could handle. That's where artificial intelligence changes everything: "But now we have artificial intelligence. We can analyze millions of genomes of old people, compare them to millions of genomes of young people, and identify where aging takes place in the body."
0:42

Theoretical physicist Michio Kaku on why aging is simply an accumulation of errors that AI can now identify: He opens with a bold claim about what artificial intelligence might finally make possible: "Artificial intelligence may give us something that the kings and queens of old could never conquer and that is the aging process." For Dr. Michio Kaku, the science behind why we age is no longer a mystery. It comes down to one thing: errors building up inside our cells over time. "We now know why things age. Things get old and die because they accumulate error. Error in the form of DNA mistakes. Accumulation of errors inside cells." The challenge, until now, has been the sheer scale of the problem. Identifying exactly where and how these errors occur across the human genome has been beyond what conventional research could handle. That's where artificial intelligence changes everything: "But now we have artificial intelligence. We can analyze millions of genomes of old people, compare them to millions of genomes of young people, and identify where aging takes place in the body."

Big Brain AI

78,635 views • 2 months ago

In the next 2-3 years, the skills you need to build an ETL process will fundamentally differ from anything we've done in the last decade. The EXTRACT and LOAD steps of an ETL pipeline have been solved forever. They are boring, and I suspect they will continue to be boring. But the TRANSFORM step is where the money is at (and where innovation will continue happening!) An ETL pipeline that can use Large Language Models effectively to transform data is a whole new ballgame. I recorded a video to talk about this. And more importantly, I talk about how you can build ETL pipelines to transform UNSTRUCTURED data (the kind of data that's really hard to handle).
5:39

In the next 2-3 years, the skills you need to build an ETL process will fundamentally differ from anything we've done in the last decade. The EXTRACT and LOAD steps of an ETL pipeline have been solved forever. They are boring, and I suspect they will continue to be boring. But the TRANSFORM step is where the money is at (and where innovation will continue happening!) An ETL pipeline that can use Large Language Models effectively to transform data is a whole new ballgame. I recorded a video to talk about this. And more importantly, I talk about how you can build ETL pipelines to transform UNSTRUCTURED data (the kind of data that's really hard to handle).

Santiago

56,412 views • 1 year ago

The intelligence we are building is not artificial. It never was. Microsoft Chief Scientific Officer Eric Horvitz just reframed the entire foundation of the AI arms race with one sentence. The tech industry calls it Artificial Intelligence. That word is wrong. Horvitz: “I don’t actually like the term artificial intelligence. I wish the field was called computational intelligence because I think it applies to biological nervous systems as well as machines, and together we can go far.” We are not building a digital imitation of the human brain. We are scaling the exact same computational physics that created biological awareness and transferring it into silicon. Your mind and a massive AI data center run on the same underlying rules. The transition isn’t artificial. It is universal. And here is where it gets deeply unsettling. Tech optimists always fall back on the same comfort. Humans hold the steering wheel. Our values guide the machine. Horvitz acknowledges this. Horvitz: “We’ll take a humanistic standpoint here, always being on top of things and guiding with our values and our preferences and our goals.” Then the caveat that changes everything. Horvitz: “As much as they might be shaped over time by the machines we work with.” You cannot interact with a superintelligence at scale without it quietly rewiring your psychological baseline. The values you use to command the machine will be shaped by the machine you are commanding. The frameworks you use to perceive reality will be constructed by the system you believe you are directing. That feedback loop started the moment you asked an AI what to think about something. Most people haven’t noticed yet. Horvitz: “I think in our own lifetimes we will all experience incredible breakthroughs in understanding biology, with applications in medicine, in healthcare, that will be named as AI breakthroughs.” Horvitz: “It’s gonna accelerate over the next 10 to 15 years.” Because biological systems and machine networks both operate on computational intelligence, a sufficiently advanced AI can solve the human body like a math equation. The architects who win the next decade will not just control the digital economy. They will control the physical building blocks of life itself. The line between silicon and carbon was always an illusion. And once humanity fully realizes that, the question of whether we are using the intelligence or it is using us becomes impossible to answer. Because by then, we will be the same thing.
1:05

The intelligence we are building is not artificial. It never was. Microsoft Chief Scientific Officer Eric Horvitz just reframed the entire foundation of the AI arms race with one sentence. The tech industry calls it Artificial Intelligence. That word is wrong. Horvitz: “I don’t actually like the term artificial intelligence. I wish the field was called computational intelligence because I think it applies to biological nervous systems as well as machines, and together we can go far.” We are not building a digital imitation of the human brain. We are scaling the exact same computational physics that created biological awareness and transferring it into silicon. Your mind and a massive AI data center run on the same underlying rules. The transition isn’t artificial. It is universal. And here is where it gets deeply unsettling. Tech optimists always fall back on the same comfort. Humans hold the steering wheel. Our values guide the machine. Horvitz acknowledges this. Horvitz: “We’ll take a humanistic standpoint here, always being on top of things and guiding with our values and our preferences and our goals.” Then the caveat that changes everything. Horvitz: “As much as they might be shaped over time by the machines we work with.” You cannot interact with a superintelligence at scale without it quietly rewiring your psychological baseline. The values you use to command the machine will be shaped by the machine you are commanding. The frameworks you use to perceive reality will be constructed by the system you believe you are directing. That feedback loop started the moment you asked an AI what to think about something. Most people haven’t noticed yet. Horvitz: “I think in our own lifetimes we will all experience incredible breakthroughs in understanding biology, with applications in medicine, in healthcare, that will be named as AI breakthroughs.” Horvitz: “It’s gonna accelerate over the next 10 to 15 years.” Because biological systems and machine networks both operate on computational intelligence, a sufficiently advanced AI can solve the human body like a math equation. The architects who win the next decade will not just control the digital economy. They will control the physical building blocks of life itself. The line between silicon and carbon was always an illusion. And once humanity fully realizes that, the question of whether we are using the intelligence or it is using us becomes impossible to answer. Because by then, we will be the same thing.

Dustin

164,127 views • 4 months ago