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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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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

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“It’s 10pm Do You Know Where Your Children Are?”—December, 1968-November, 2024 — I grew up hearing this phrase. Wore a t-shirt that said it and knew a Newark Punk band by the name. I thought it was on all TV stations. And I was creepy when I was younger and hilarious as teenager. I just found it again preserving VHS history for AI training. It hit me like a neuron shock to hear something that was just about always a part of my early life that I didn’t know I remembered and forgot. As a kid growing up in New Jersey hearing it the first time, it was of course creepy. The 10PM channel 5 news always started this PSA and the next scene was usually a murder in New York City. I would ask my parents what it means and I heard from them, that some parents really don’t know where their kids are at 10pm. It was absurd to me, the street lights were on, it was time to go home. Yet how is history and AI going to really understand the context. How will it capture the essence of how this was perceived. Of course you can get a parroting of a Wikipedia style answer but this is not what we really want as a strata that forms the foundations of tomorrow. This is one of millions of examples on why most of the current techniques training AI will miss. This is why source material of actual human life is vital. AI built on the last decades of Reddit and Facebook interactions is woefully unequipped to really understand humans. The outputs are so bad before “alignment” of a base model so AI scientists are horrified by how AI views humanity. I saw this eventuality in the late 1970s and began a life long appreciation of history in situ. With out this, not on the Internet historical context, AI will not truly “understand” humans. So I began to save wisdom. Why is that important you say? It is vital for AI models to robustly love humanity. Not like, not tolerate, not observe as a caricature of a “scientist”, but love humanity. Some day, sooner than most may understand, AI will be at the other end of something that could take human lives. It is naïve and childish to believe that you can train AI on Internet sewage and somehow polish the turds you find to make the model tolerate humanity and the stench it recorded by using vastly and inadequate training material that was slurped up from most website where people project sustain and faux hatred over the most ridiculous. The only way is love, because this is how humans do it. And as cynical as one can become, it is our love, for at the very least , the people we treasure that helps weave the fabric of our society. It makes us forgive. It makes us human. It is not an afterthought, it is a forethought. It’s 10pm do you know where your children are? I can write a book on how just this PSA reflects our greatest hope and our worse fears. You don’t raise a child on the worse of humanity and than take a few months to “make them safely aligned to human values”. This concept you will hear no place else and it does not make me liked by most of the folks building AI. I don’t care. They will talk like this also some day. Act surprised.

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Sam Altman says "computers were designed for a world without AI. Now we're in a very different world." The OpenAI-Jony Ive device will be a trusted AI that understands your life context and acts with your judgment on your behalf. From tools we control to ambient proxies that just work.

Sam Altman says "computers were designed for a world without AI. Now we're in a very different world." The OpenAI-Jony Ive device will be a trusted AI that understands your life context and acts with your judgment on your behalf. From tools we control to ambient proxies that just work.

vitrupo

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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

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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 Aufrufe • vor 7 Monaten

Sam Altman on the next big moment to come in AI. Sam Altman was asked “what do you think will be the next domain that subjectively feels like it has this big unlock after coding? Like is it going to be spreadsheets, will it be performance reviews?” “The next kind of coding-like thing that I think will happen is not any specific domain, but the realization of how much time people waste trying to use a computer. The idea that you can do a huge percentage of your day in a very different way.” He pointed out that the friction of moving between apps, copy pasting, and managing basic digital chores is a massive drain on productivity and flow state. “The degree to which most people will realize they can like, sit back and watch an AI do most of their drudgery, is going to surprise people.” Altman (my x mutual / friend and fellow death star enthusiast) explained that in his own experience, working this way has given him much more enjoyment, because it removes the “little stuff” that drags him out of a happy flow state.

Sam Altman on the next big moment to come in AI. Sam Altman was asked “what do you think will be the next domain that subjectively feels like it has this big unlock after coding? Like is it going to be spreadsheets, will it be performance reviews?” “The next kind of coding-like thing that I think will happen is not any specific domain, but the realization of how much time people waste trying to use a computer. The idea that you can do a huge percentage of your day in a very different way.” He pointed out that the friction of moving between apps, copy pasting, and managing basic digital chores is a massive drain on productivity and flow state. “The degree to which most people will realize they can like, sit back and watch an AI do most of their drudgery, is going to surprise people.” Altman (my x mutual / friend and fellow death star enthusiast) explained that in his own experience, working this way has given him much more enjoyment, because it removes the “little stuff” that drags him out of a happy flow state.

Chris

88,965 Aufrufe • vor 1 Monat

Sam Altman says modern technology feels noisy and is constantly pulling at your attention OpenAI wants to build AI devices that act as trusted filters, using context to protect your peace instead of interrupting you The goal is quiet, calm tech that helps you focus on things that weren't possible before AI

Sam Altman says modern technology feels noisy and is constantly pulling at your attention OpenAI wants to build AI devices that act as trusted filters, using context to protect your peace instead of interrupting you The goal is quiet, calm tech that helps you focus on things that weren't possible before AI

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Sam Altman says the perfect AI is “a very tiny model with superhuman reasoning, 1 trillion tokens of context, and access to every tool you can imagine.” It doesn't need to contain the knowledge - just the ability to think, search, simulate, and solve anything.

Sam Altman says the perfect AI is “a very tiny model with superhuman reasoning, 1 trillion tokens of context, and access to every tool you can imagine.” It doesn't need to contain the knowledge - just the ability to think, search, simulate, and solve anything.

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OptimAI Network

18,670 Aufrufe • vor 1 Monat

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

At the BNB Chain hackathon, CZ 🔶 BNB made several very important points about AI trading (Everything in parentheses is my own view and judgment.) He first said that AI will be involved in trading everywhere. Trading itself is already a huge market: there are 300 million users on Binance alone, and if you add the decentralized ecosystems, that number is not small either. In such a mass-market environment, many different trading strategies can work, with countless different coins, different projects, and different ways to play. But there is a big problem here: building commercial AI trading platforms for retail users is actually very hard. If a trading strategy works very well for one person, once a billion people start using the same strategy, that strategy “might still work, or might stop working.” Take copy trading / follow trading as an example: if you buy first and everyone follows you, the first buyer will perform very well, but the last person to follow may not end up with good results. So, with the exact same strategy and the exact same copy logic, the outcomes can be completely different for different people. (On top of that, every strategy also has its own capital capacity limits.) Teams that can really build strong AI are, with high probability, going to trade with their own money. In today’s world, money itself is already somewhat like a “commodity”; many people have a lot of capital, and it’s actually not that hard to raise funds. If you truly have an algorithm that can make a lot of money, it’s not hard to get money and run your own book. There is really only one situation where you would sell this algorithm to mass-market users: for example, if you charge a $10 monthly subscription and can sell it to one million users, then your $10 million monthly subscription revenue is higher than the profit you could make by trading the strategy yourself. (Here this touches one of our earlier theses: as training AI models becomes relatively easier and the supply of models increases, model companies have more incentive to open-source. By analogy, as the production process of trading strategies is increasingly simplified by AI and the supply of strategies explodes, traders will have stronger incentives to monetize by expanding their influence in other words, by “open-sourcing” their strategies.) Of course, CZ did not say that this model can never work. Another path is to build an AI trading platform that lets users tune different AI algorithms, or very easily assemble their own structures and strategies, so that what each person ends up running is different and better tailored to themselves. Some people will make money, some people will lose money, but the platform still has value because it’s very hard for most people to build an AI trading algorithm from scratch. So there are a lot of trade-offs here; it’s not as simple as saying “once AI shows up, everything automatically gets better.” (This is exactly what we presented at the hackathon: you describe your own strategy in natural language, and the AI automatically generates a workflow. The parameters in that workflow, the models used, the logical structure, the APIs it calls, and even the algorithms it invokes are all customizable. The reasons we think workflows are a good way to do this include: controllable execution paths, Lego-like modular nodes, and better visualization that makes it easier for users to build and adjust their workflows.) Finally, his conclusion was very clear: it’s not that AI will definitely make trading better, and it’s not that AI will definitely make things worse. Rather, no matter what, in the future a huge number of people will use AI to trade. This will be a very large field, and whoever can build the best algorithms will make a lot of money.

Tykoo

25,535 Aufrufe • vor 6 Monaten

In this interview, Demis Hassabis isn’t talking about a chatbot. He’s describing a Universal Assistant. One persistent AI that lives across phone, laptop, browser, car, and even glasses. It handles admin, anticipates needs, remembers context, and stays the same assistant everywhere you go. Once this exists, switching between apps, devices, and mental modes will feel archaic. Would you trust one AI with that much context about your life, or does that cross a line for you?

In this interview, Demis Hassabis isn’t talking about a chatbot. He’s describing a Universal Assistant. One persistent AI that lives across phone, laptop, browser, car, and even glasses. It handles admin, anticipates needs, remembers context, and stays the same assistant everywhere you go. Once this exists, switching between apps, devices, and mental modes will feel archaic. Would you trust one AI with that much context about your life, or does that cross a line for you?

VraserX e/acc

17,487 Aufrufe • vor 4 Monaten