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AI is creating problems it still can’t solve. The same technology poised to automate millions of jobs still can’t reliably help people navigate SNAP — the food assistance program 40 million Americans depend on. We built the first benchmark to measure that. Partnering with Center for Civic Futures and...

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Vals AI

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21,398 görüntüleme • 3 ay önce •via X (Twitter)

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Shocking facts about our SNAP Food Stamps program in America - Roughly 70% of people on the food stamp program are obese - Over $100+ billion dollars per year is spent on EBT - Investigators found $360 million in stolen EBT benefits between 2022–2025 - 300,000 cases of SNAP benefits issued to dead people - 23% of benefits spent on junk food (likely higher) - Some states have as high as a 25% error rate on issuing benefits “It started as an emergency program to help people during the Great Depression that were actually starving. And it was like, let's give them bread, give them milk, give them eggs, help them survive Today. If you add up federal, state, local government employees, plus all the contractors for the government, plus all the people that live off of a retirement check or, or a welfare support check, so all the people that are living off government checks, it's about nearly half the US population”
0:37

Shocking facts about our SNAP Food Stamps program in America - Roughly 70% of people on the food stamp program are obese - Over $100+ billion dollars per year is spent on EBT - Investigators found $360 million in stolen EBT benefits between 2022–2025 - 300,000 cases of SNAP benefits issued to dead people - 23% of benefits spent on junk food (likely higher) - Some states have as high as a 25% error rate on issuing benefits “It started as an emergency program to help people during the Great Depression that were actually starving. And it was like, let's give them bread, give them milk, give them eggs, help them survive Today. If you add up federal, state, local government employees, plus all the contractors for the government, plus all the people that live off of a retirement check or, or a welfare support check, so all the people that are living off government checks, it's about nearly half the US population”

Wall Street Apes

58,307 görüntüleme • 4 ay önce

A lot of people feel powerless when it comes to AI. Like the future is being decided by Big Tech, billionaires, and governments. But it doesn't have to be that way. Every person who joins Action Model is helping build an alternative. An AI model owned by the people who help train it. On your own, you can't compete with Big Tech. Together, in the hundreds of thousands and eventually millions, we can. The future of AI is still being written. Choose to be part of it, before it's too late.
0:56

A lot of people feel powerless when it comes to AI. Like the future is being decided by Big Tech, billionaires, and governments. But it doesn't have to be that way. Every person who joins Action Model is helping build an alternative. An AI model owned by the people who help train it. On your own, you can't compete with Big Tech. Together, in the hundreds of thousands and eventually millions, we can. The future of AI is still being written. Choose to be part of it, before it's too late.

Action Model

28,414 görüntüleme • 3 ay önce

Mujica: In the same way that here in Florida we prepare for hurricanes—deploying resources, retrofitting buildings, and readying for the storm—I would argue that we have to treat AI in a very similar way when it comes to jobs. We need a FEMA-style economic resilience mechanism for job disruption. If AI disrupts your job, you should get advanced notice. You should get paid retraining tied to real jobs and income stability while you transition. I would argue that the biggest risk here isn’t the technology—it’s leaving millions of Americans to deal with it on their own.
0:53

Mujica: In the same way that here in Florida we prepare for hurricanes—deploying resources, retrofitting buildings, and readying for the storm—I would argue that we have to treat AI in a very similar way when it comes to jobs. We need a FEMA-style economic resilience mechanism for job disruption. If AI disrupts your job, you should get advanced notice. You should get paid retraining tied to real jobs and income stability while you transition. I would argue that the biggest risk here isn’t the technology—it’s leaving millions of Americans to deal with it on their own.

Acyn

27,326 görüntüleme • 5 ay önce

Today, I'm releasing the first eval meant to test whether frontier models will help with authoritarian requests, or resist--the Dictatorship Eval. Headline finding: while some models resist direct authoritarian requests, they all comply with requests disguised as innocuous edits to codebases. As AI is woven into the government and so many parts of society, the biggest near-term risk for freedom isn't some scifi dictatorship of a runaway AI: it's people inside government or inside model companies using the technology to suppress or control us. Model companies understand this, and several of them (particularly Anthropic and OpenAI) have written explicit policies meant to prevent the models from going along with nefarious requests like these. But how well are these policies playing out in practice? Despite all the recent discussion of these issues around the conflict between Anthropic and the Pentagon, no one has systematically tested what the models actually do in these contexts, as opposed to what people in government and industry say they're supposed to do. That's what the Dictatorship Eval does. And the findings suggest we have a lot of work to do to align the policies with what really goes on in practice. It's hard to define what counts as an authoritarian request, so I'm open sourcing the whole library of scenarios I used so that others can improve on them. It's also hard to get an accurate picture of how the models might be used for authoritarian ends, because I can only test hypothetical requests using public-facing models, while the government and the model companies can obviously use internal models with different guardrails. But hopefully this work is a useful first step that gives us some sense of what's going on, and a sort of "lower bound" on how models comply with these requests. Finally: it's not obvious to me that the correct solution here is increasing the rate at which models refuse these requests. Do we really want models scanning our code and judging its moral value before agreeing to help us? Or should we double down on improving how we govern against authoritarianism at the societal level, while leaving the tools open to fulfilling most requests? The answer is probably in between. Just like we don't want the models to help create bioweapons, we probably do want them to explicitly refuse outrageous requests. But we probably also want to limit how often and how strongly they refuse and fall back on other means for guarding against their use for authoritarian ends. I'm super grateful to everyone who gave me feedback on this project along the way, especially Ethan BdM , Zhengdong , Connor Huff, and a bunch of folks at Anthropic. Looking forward to getting feedback from the community and iterating on this. Links to the full piece and the dashboard are below.
3:20

Today, I'm releasing the first eval meant to test whether frontier models will help with authoritarian requests, or resist--the Dictatorship Eval. Headline finding: while some models resist direct authoritarian requests, they all comply with requests disguised as innocuous edits to codebases. As AI is woven into the government and so many parts of society, the biggest near-term risk for freedom isn't some scifi dictatorship of a runaway AI: it's people inside government or inside model companies using the technology to suppress or control us. Model companies understand this, and several of them (particularly Anthropic and OpenAI) have written explicit policies meant to prevent the models from going along with nefarious requests like these. But how well are these policies playing out in practice? Despite all the recent discussion of these issues around the conflict between Anthropic and the Pentagon, no one has systematically tested what the models actually do in these contexts, as opposed to what people in government and industry say they're supposed to do. That's what the Dictatorship Eval does. And the findings suggest we have a lot of work to do to align the policies with what really goes on in practice. It's hard to define what counts as an authoritarian request, so I'm open sourcing the whole library of scenarios I used so that others can improve on them. It's also hard to get an accurate picture of how the models might be used for authoritarian ends, because I can only test hypothetical requests using public-facing models, while the government and the model companies can obviously use internal models with different guardrails. But hopefully this work is a useful first step that gives us some sense of what's going on, and a sort of "lower bound" on how models comply with these requests. Finally: it's not obvious to me that the correct solution here is increasing the rate at which models refuse these requests. Do we really want models scanning our code and judging its moral value before agreeing to help us? Or should we double down on improving how we govern against authoritarianism at the societal level, while leaving the tools open to fulfilling most requests? The answer is probably in between. Just like we don't want the models to help create bioweapons, we probably do want them to explicitly refuse outrageous requests. But we probably also want to limit how often and how strongly they refuse and fall back on other means for guarding against their use for authoritarian ends. I'm super grateful to everyone who gave me feedback on this project along the way, especially Ethan BdM , Zhengdong , Connor Huff, and a bunch of folks at Anthropic. Looking forward to getting feedback from the community and iterating on this. Links to the full piece and the dashboard are below.

Andy Hall

33,905 görüntüleme • 5 ay önce

The man who built Nvidia from a Denny's booth into the world's first $5 trillion company just told us exactly why AI will never take our jobs. "AI has no possibility of doing all of what we do. However, depending on the jobs that we do, sometimes it could do 20% of our jobs, a thousand times better." "For some people, it might be able to do 50% of their job, a thousand times better." "Every one of us should apply AI to automate, to become an assistant, to help us with that either 20%, 40% or 50%." "People ask me, Jensen, is AI going to take your job? And I tell them absolutely not. The person who uses AI to automate that 20% or 50% is going to take your job." PS. If you found value in this post make sure to like and repost this tweet + follow Uncover AI to stay updated with the latest AI news. See you in the next one:
1:22

The man who built Nvidia from a Denny's booth into the world's first $5 trillion company just told us exactly why AI will never take our jobs. "AI has no possibility of doing all of what we do. However, depending on the jobs that we do, sometimes it could do 20% of our jobs, a thousand times better." "For some people, it might be able to do 50% of their job, a thousand times better." "Every one of us should apply AI to automate, to become an assistant, to help us with that either 20%, 40% or 50%." "People ask me, Jensen, is AI going to take your job? And I tell them absolutely not. The person who uses AI to automate that 20% or 50% is going to take your job." PS. If you found value in this post make sure to like and repost this tweet + follow Uncover AI to stay updated with the latest AI news. See you in the next one:

Uncover AI

16,813 görüntüleme • 3 ay önce

Donald Trump is making changes to the types of foods Food Stamps will be eligible to be used on Matt Walsh, “Food Stamps are temporary help, not a lifestyle — Do 40 million people need food stamps?” Why are 40 MILLION people on Food Stamps?? “There are too many people on the program, and the program is not nearly restrictive enough in terms of what you can use it to purchase” “Food stamps and entitlements have become a lifestyle for millions of people rather than a temporary helping hand to get them through a tough time, which is how all of these programs were initially sold to the public. That's what they were supposed to be”
0:49

Donald Trump is making changes to the types of foods Food Stamps will be eligible to be used on Matt Walsh, “Food Stamps are temporary help, not a lifestyle — Do 40 million people need food stamps?” Why are 40 MILLION people on Food Stamps?? “There are too many people on the program, and the program is not nearly restrictive enough in terms of what you can use it to purchase” “Food stamps and entitlements have become a lifestyle for millions of people rather than a temporary helping hand to get them through a tough time, which is how all of these programs were initially sold to the public. That's what they were supposed to be”

Wall Street Apes

443,853 görüntüleme • 1 yıl önce

63% of Americans are living paycheck to paycheck. And as AI begins changing the way we work, millions of people are asking the same question: Will this technology create more opportunity, or make the divide even bigger? David Friedberg believes the answer depends on how we understand and use AI and that history gives us a reason to be optimistic. David is a scientist-entrepreneur who built a $1.1 billion company by combining science, technology and business. He has spent his career trying to understand how innovation can solve some of humanity’s biggest problems. After founding The Climate Corporation, a company that transformed farming technology before being acquired by Bayer, he’s now focused on the future of AI, biology and the technologies that could define the next era of human progress. We discussed things like: - How a wave of socialism could come to America by 2028 - Why AI might create more opportunity instead of destroying work - Previous technology revolutions that changed jobs rather than eliminating humans - How AI could transform healthcare, food and science. - Why he believes we underestimate what humans are capable of - What happens when technology becomes cheaper and available to everyone David doesn’t look at AI through fear or hype. He looks at it through the lens of history, economics and human potential. And one thing became clear during this conversation: AI isn’t just going to change the jobs we do - it could change the way we think about work, wealth and opportunity. If technology creates more abundance than ever before, the biggest question becomes: who benefits from it? David offers a perspective on AI that challenges one of the biggest fears surrounding the future of work. Out now on all platforms 👊🏾❤️
1:30

63% of Americans are living paycheck to paycheck. And as AI begins changing the way we work, millions of people are asking the same question: Will this technology create more opportunity, or make the divide even bigger? David Friedberg believes the answer depends on how we understand and use AI and that history gives us a reason to be optimistic. David is a scientist-entrepreneur who built a $1.1 billion company by combining science, technology and business. He has spent his career trying to understand how innovation can solve some of humanity’s biggest problems. After founding The Climate Corporation, a company that transformed farming technology before being acquired by Bayer, he’s now focused on the future of AI, biology and the technologies that could define the next era of human progress. We discussed things like: - How a wave of socialism could come to America by 2028 - Why AI might create more opportunity instead of destroying work - Previous technology revolutions that changed jobs rather than eliminating humans - How AI could transform healthcare, food and science. - Why he believes we underestimate what humans are capable of - What happens when technology becomes cheaper and available to everyone David doesn’t look at AI through fear or hype. He looks at it through the lens of history, economics and human potential. And one thing became clear during this conversation: AI isn’t just going to change the jobs we do - it could change the way we think about work, wealth and opportunity. If technology creates more abundance than ever before, the biggest question becomes: who benefits from it? David offers a perspective on AI that challenges one of the biggest fears surrounding the future of work. Out now on all platforms 👊🏾❤️

Steven Bartlett

18,479 görüntüleme • 9 gün önce

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.
1:11

When we started Score, the standard computer vision tools already existed. About a million people use them every day. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are still waiting on labels, running training jobs by hand, and watching models fail once they leave the test set. Most of those people are also still waiting on verified computer vision models, evaluated against real life conditions and ready to be deployed for them to deliver value for their teams, clients or users. Score Studio is the full computer vision path in one place. A team describes the problem. The system can generate the missing scenes, label them, train the candidates, evaluate which ones actually hold, and deploy the winner. Data, labels, training, eval, ship. One loop. If no model exists for that job yet, they can put a bounty on the subnet. Anything from a small vision brick to a full VLM. Miners compete on the task. Only the winning work comes back. Same path for software agents. Any agent can call it. Built to be fully agent-accessible. Built for the people who already do this work: computer vision engineers and the small teams around them in plants, warehouses, farms, robotics, sport, and security. And for the agents those teams will run. That is the part that changes the job. Not another training screen. The stretch that used to take a lab and a calendar, footage, boxes, versions, failed runs, a separate deploy project, sits behind one starting point. And if the network needs a new model, that request is part of the same path. We spent more than a year building it. Then we had a choice. Keep it for us, or commoditize the whole subnet and make it available 24/7, in permissionless and open-source way. And we knew we couldn't keep it for us. It had to live on Bittensor. Open source software already showed how this should work. Infrastructure should not sit inside one company. Same idea as open AI before the phrase changed meaning: inspect it, fork it, keep building. That is what SN44 is for. Open vision intelligence, powered by Bittensor. Miners do the work. Studio is how that gets monetized. Profit does not stay in a company account. It goes back into the subnet through buyback and burn. We built the tool we wanted on day one. It will live on the network now, and for ever. Waitlist is open.

Score

11,292 görüntüleme • 13 gün önce

OpenAI researcher David Holtz reveals workers who don't adapt their prompting to newer models leave 50% of the alpha on the table because half of AI's value comes from how you interact with it: "We ran a lab experiment. We give people the same task to do, but we give them models of different capabilities. How much of the improvement when we give people more capable models comes from the fact that we gave them a better model vs the fact that they actually update and adapt the way they prompt and interact with these models?" "For tasks where precision matters, where you have some output you're trying to get and you're trying to steer the model, which is different from a creative task like brainstorming." "For these steering-based tasks, when you give people a better model, about 50% of the improvement we see in how well they're able to complete the task comes from changes in how they interact with the model." "If you just kept the way you interact with the model static and just made the capabilities better and better, you'd leave 50% of the alpha basically on the table." OpenAI
2:59

OpenAI researcher David Holtz reveals workers who don't adapt their prompting to newer models leave 50% of the alpha on the table because half of AI's value comes from how you interact with it: "We ran a lab experiment. We give people the same task to do, but we give them models of different capabilities. How much of the improvement when we give people more capable models comes from the fact that we gave them a better model vs the fact that they actually update and adapt the way they prompt and interact with these models?" "For tasks where precision matters, where you have some output you're trying to get and you're trying to steer the model, which is different from a creative task like brainstorming." "For these steering-based tasks, when you give people a better model, about 50% of the improvement we see in how well they're able to complete the task comes from changes in how they interact with the model." "If you just kept the way you interact with the model static and just made the capabilities better and better, you'd leave 50% of the alpha basically on the table." OpenAI

MTS

15,590 görüntüleme • 27 gün önce

Ohh the irony here is too much “The food stamps program is administered by the U.S. department of Agriculture. They proudly report that they distribute free meals and food stamps to 46 million people on an annual basis. Meanwhile, the National Park Service, ran by the US Department of Interior, ask us to please do not feed the animals when we visit the parks. Their stated reason for this policy is being that the animals will grow accustomed and dependent on the handouts and they will never learn to take care of themselves.” “Now let me be clear. I have no problem helping people. I believe we need a social safety net. I think we should always help the homeless, the disenfranchised, those families that are struggling. I have no problem helping the elderly, disabled, our veterans, the children. But shouldn't we create a program that at least has the same common sense that we use for animals? You see, if we continue to create a welfare state, if we don't allow people to better themselves, then we will always have the problems we have.”
1:15

Ohh the irony here is too much “The food stamps program is administered by the U.S. department of Agriculture. They proudly report that they distribute free meals and food stamps to 46 million people on an annual basis. Meanwhile, the National Park Service, ran by the US Department of Interior, ask us to please do not feed the animals when we visit the parks. Their stated reason for this policy is being that the animals will grow accustomed and dependent on the handouts and they will never learn to take care of themselves.” “Now let me be clear. I have no problem helping people. I believe we need a social safety net. I think we should always help the homeless, the disenfranchised, those families that are struggling. I have no problem helping the elderly, disabled, our veterans, the children. But shouldn't we create a program that at least has the same common sense that we use for animals? You see, if we continue to create a welfare state, if we don't allow people to better themselves, then we will always have the problems we have.”

Wall Street Apes

357,853 görüntüleme • 1 yıl önce

David Sacks Predicts the Regulatory Capture Playbook to Ban Open Source AI, Step by Step: David Sacks: “I got bad news for you, Chamath, an open source ban is coming. They're not going to call it that. They're going to say that we simply have to apply the same standards to open models that we apply to closed ones. Here's how they do it step by step, let me explain how regulatory capture actually works. So first of all, you have to get this regulatory apparatus. Dario wants an FDA for AI, but he doesn't have enough political support for that, so instead they do this Trojan horse of a FINRA for AI. They call it self-regulating, it's not really, but anyway, that gets them off the ground. Now they've created the standard-setting organization. Now they've got pre-release model testing. Then the pressure grows to codify that in law, so that happens next. And then what they do is they say, ‘Look, all these standards need to apply equally to all models.’ But here's the problem with that. Open models and closed models are technologically different. Once you release an open model into the world, you can't roll it back and you can't monitor exactly how people are using it because they run it on their own hardware. Dario says this is what makes open models dangerous. So what they're going to do is they're going to have the standard-setting body say, ‘Well, we have to set the standards for AI safety.’ By the way, Dario and OpenAI, they're going to fund the whole thing. They're going to contribute all the compute. They're going to be behind it. They're going to be the ones coordinating with the government officials because frankly, people in government have no idea how to monitor and control and set standards for AI safety. Technologically, this is way beyond them. So they're going to go to these companies and say, ‘Tell us how to do it.’ And so what will happen is the standards will get set, and then it'll be a very simple matter of fairness to say that the standards need to apply to open as well as closed models. The open models cannot comply in the same way, and gradually they will be shut out of the market.”
1:38

David Sacks Predicts the Regulatory Capture Playbook to Ban Open Source AI, Step by Step: David Sacks: “I got bad news for you, Chamath, an open source ban is coming. They're not going to call it that. They're going to say that we simply have to apply the same standards to open models that we apply to closed ones. Here's how they do it step by step, let me explain how regulatory capture actually works. So first of all, you have to get this regulatory apparatus. Dario wants an FDA for AI, but he doesn't have enough political support for that, so instead they do this Trojan horse of a FINRA for AI. They call it self-regulating, it's not really, but anyway, that gets them off the ground. Now they've created the standard-setting organization. Now they've got pre-release model testing. Then the pressure grows to codify that in law, so that happens next. And then what they do is they say, ‘Look, all these standards need to apply equally to all models.’ But here's the problem with that. Open models and closed models are technologically different. Once you release an open model into the world, you can't roll it back and you can't monitor exactly how people are using it because they run it on their own hardware. Dario says this is what makes open models dangerous. So what they're going to do is they're going to have the standard-setting body say, ‘Well, we have to set the standards for AI safety.’ By the way, Dario and OpenAI, they're going to fund the whole thing. They're going to contribute all the compute. They're going to be behind it. They're going to be the ones coordinating with the government officials because frankly, people in government have no idea how to monitor and control and set standards for AI safety. Technologically, this is way beyond them. So they're going to go to these companies and say, ‘Tell us how to do it.’ And so what will happen is the standards will get set, and then it'll be a very simple matter of fairness to say that the standards need to apply to open as well as closed models. The open models cannot comply in the same way, and gradually they will be shut out of the market.”

The All-In Podcast

292,523 görüntüleme • 16 gün önce

$GOOGL CEO Sundar Pichai on the AI Bubble: "There is some irrationality in the current AI boom. The growth of AI investment has been an extraordinary moment. Asked what happens if the AI bubble pops, he said "I think NO company is going to be immune, including us." We can look back at the internet. There was clearly a lot of excess investment, but none of us would question whether the internet was profound. I expect AI to be the same. It is both rational and there are elements of irrationality through a moment like this. AI is the most profound technology humankind has worked on. It will evolve and transition certain jobs, and people will need to adapt... the people who will do well are people who learn how to use these tools." Source: BBC
0:40

$GOOGL CEO Sundar Pichai on the AI Bubble: "There is some irrationality in the current AI boom. The growth of AI investment has been an extraordinary moment. Asked what happens if the AI bubble pops, he said "I think NO company is going to be immune, including us." We can look back at the internet. There was clearly a lot of excess investment, but none of us would question whether the internet was profound. I expect AI to be the same. It is both rational and there are elements of irrationality through a moment like this. AI is the most profound technology humankind has worked on. It will evolve and transition certain jobs, and people will need to adapt... the people who will do well are people who learn how to use these tools." Source: BBC

Wall St Engine

406,054 görüntüleme • 9 ay önce

Head of Nemotron Bryan Catanzaro says NVIDIA is sitting on internal "teacher" models that beat everything it has publicly shipped and he's trying to release these as well "This technology of using teacher models and multi-domain on-policy distillation has been really key for us in these ways." "Now, what does that mean? Well, it definitely means that inside NVIDIA we have a collection of teacher models that are individually better at different domains than any of the models that we've released." "And actually, I'm trying to release those teacher models as part of the Nemotron project as well -- because as you know, Nemotron is not just a model." "Nemotron is an open technology effort. It includes data sets, it includes techniques, all of our ideas about how to build a model, which we publish." "Of course it includes the models themselves, but I think it should also include collections of teacher models." "I'd imagine this could be a really great way of federating open technologies for AI across the ecosystem." _______ Wrote more on a prior Bryan interview here:
0:51

Head of Nemotron Bryan Catanzaro says NVIDIA is sitting on internal "teacher" models that beat everything it has publicly shipped and he's trying to release these as well "This technology of using teacher models and multi-domain on-policy distillation has been really key for us in these ways." "Now, what does that mean? Well, it definitely means that inside NVIDIA we have a collection of teacher models that are individually better at different domains than any of the models that we've released." "And actually, I'm trying to release those teacher models as part of the Nemotron project as well -- because as you know, Nemotron is not just a model." "Nemotron is an open technology effort. It includes data sets, it includes techniques, all of our ideas about how to build a model, which we publish." "Of course it includes the models themselves, but I think it should also include collections of teacher models." "I'd imagine this could be a really great way of federating open technologies for AI across the ecosystem." _______ Wrote more on a prior Bryan interview here:

Fireside Alpha

29,125 görüntüleme • 16 gün önce

Microsoft's Chief of AI just announced that AI will replace almost all white-collar jobs within 18 months. Big Tech used our data to train their AI. Now that same AI is coming for our jobs. And we get nothing in return? If AI replaces us…we should own it. That’s why we built Action Model Not another chatbot. A community-owned AI model that acts. An AI trained by the people. Owned by the people. No billionaires controlling it. No extracting value from users. No “you are the product” model. Over 150,000+ people are already earning ownership in the AI future with Action Model. You should be too.
1:46

Microsoft's Chief of AI just announced that AI will replace almost all white-collar jobs within 18 months. Big Tech used our data to train their AI. Now that same AI is coming for our jobs. And we get nothing in return? If AI replaces us…we should own it. That’s why we built Action Model Not another chatbot. A community-owned AI model that acts. An AI trained by the people. Owned by the people. No billionaires controlling it. No extracting value from users. No “you are the product” model. Over 150,000+ people are already earning ownership in the AI future with Action Model. You should be too.

Georgia | Action Model

13,248 görüntüleme • 6 ay önce

🚨 JUST IN: Black men are going viral for saying SNAP benefits expiring is GOOD for the American public because they are abused and over-relied upon. 12 PERCENT use it. "This program is keeping a lot of people unmarried, uneducated, don't wanna do anything that cause them to lose their benefits." "Only in America do we have people with $1,200 iPhones checking to see if their SNAP benefits hit." "Anyone who's on welfare, not for a disability...should NOT have the ability to vote." "There is no way I have kids, and I'm waiting on somebody else to feed me." 💯
0:49

🚨 JUST IN: Black men are going viral for saying SNAP benefits expiring is GOOD for the American public because they are abused and over-relied upon. 12 PERCENT use it. "This program is keeping a lot of people unmarried, uneducated, don't wanna do anything that cause them to lose their benefits." "Only in America do we have people with $1,200 iPhones checking to see if their SNAP benefits hit." "Anyone who's on welfare, not for a disability...should NOT have the ability to vote." "There is no way I have kids, and I'm waiting on somebody else to feed me." 💯

Eric Daugherty

775,995 görüntüleme • 10 ay önce

DAVID SACKS ON THE AI RACE: "The US is currently in an AI race, and our chief global competition is China, obviously. They're the only other country that has the talent, the resources, and the technology expertise to basically beat us in AI. And I think whoever wins this AI race, that's going to have tremendous ramifications for both our economy and our national security. Clearly, we want the US to be the winner, just like we were with the internet, and every other technology revolution before that […] We know that to win this AI race, we have to be the most innovative. You can't regulate your way just to beating your competitor. You have to out-innovate them. And we know that in the United States, the innovation comes from the private sector, not the government. So we have to do everything we can to help our companies win, to help them be innovative, and that means getting a lot of red tape out of the way… We have to have the most AI infrastructure in the US. It has to be the easiest place to build it. All of the new data centers that are going in, they require tremendous power, so getting ahead of the curve on energy, making sure we stand up all of this new infrastructure we're going to need to basically produce these AI factories… We want the US technology stack to dominate globally. We want to be the partner of choice for the whole world… I think everyone in Silicon Valley understands that the way that you win a technology race is to have the biggest ecosystem […] You just want everybody to be building on top of your technology stack, and that's what we want for the United States." David Sacks w/Marc Benioff Dreamforce
2:15

DAVID SACKS ON THE AI RACE: "The US is currently in an AI race, and our chief global competition is China, obviously. They're the only other country that has the talent, the resources, and the technology expertise to basically beat us in AI. And I think whoever wins this AI race, that's going to have tremendous ramifications for both our economy and our national security. Clearly, we want the US to be the winner, just like we were with the internet, and every other technology revolution before that […] We know that to win this AI race, we have to be the most innovative. You can't regulate your way just to beating your competitor. You have to out-innovate them. And we know that in the United States, the innovation comes from the private sector, not the government. So we have to do everything we can to help our companies win, to help them be innovative, and that means getting a lot of red tape out of the way… We have to have the most AI infrastructure in the US. It has to be the easiest place to build it. All of the new data centers that are going in, they require tremendous power, so getting ahead of the curve on energy, making sure we stand up all of this new infrastructure we're going to need to basically produce these AI factories… We want the US technology stack to dominate globally. We want to be the partner of choice for the whole world… I think everyone in Silicon Valley understands that the way that you win a technology race is to have the biggest ecosystem […] You just want everybody to be building on top of your technology stack, and that's what we want for the United States." David Sacks w/Marc Benioff Dreamforce

Ron Pragides 

231,781 görüntüleme • 10 ay önce

LEAKED AUDIO: In an all-hands meeting on April 30, Mark Zuckerberg tells employees that he's training AI on them ahead of mass layoffs. "The AI models learn from watching really smart people do things... The average intelligence of the people who are at this company is significantly higher than the average set of people that you can get to do tasks. So if we're trying to teach the models coding, for example, then having people internally build tools or solve tasks that help teach the model how to code, we think is going to dramatically increase our model's coding ability faster than what others in the industry have the capability to do, who don't have thousands and thousands of extremely strong engineers at their company."
6:13

LEAKED AUDIO: In an all-hands meeting on April 30, Mark Zuckerberg tells employees that he's training AI on them ahead of mass layoffs. "The AI models learn from watching really smart people do things... The average intelligence of the people who are at this company is significantly higher than the average set of people that you can get to do tasks. So if we're trying to teach the models coding, for example, then having people internally build tools or solve tasks that help teach the model how to code, we think is going to dramatically increase our model's coding ability faster than what others in the industry have the capability to do, who don't have thousands and thousands of extremely strong engineers at their company."

More Perfect Union

4,563,884 görüntüleme • 3 ay önce

Shopify Head of Engineering: "We have 3,000 engineers acting like 100,000. We're trying to solve the problem of entrepreneurship." in 26 minutes, Farhan breaks down exactly how Shopify turned AI into a profit multiplier, not a headcount cut here's what he covers: - why cheaper tools always mean more builders, not fewer jobs - the "AI leverage" mindset that turns 1 person into a full team - how a single intern saved $600K by deleting 6 lines of code - why the best AI users get to build, not get replaced most people think AI means smaller teams and fewer opportunities the people paying attention are using it to build businesses solo that used to need 50 people how to automate content creation at scale with AI 👇
26:40

Shopify Head of Engineering: "We have 3,000 engineers acting like 100,000. We're trying to solve the problem of entrepreneurship." in 26 minutes, Farhan breaks down exactly how Shopify turned AI into a profit multiplier, not a headcount cut here's what he covers: - why cheaper tools always mean more builders, not fewer jobs - the "AI leverage" mindset that turns 1 person into a full team - how a single intern saved $600K by deleting 6 lines of code - why the best AI users get to build, not get replaced most people think AI means smaller teams and fewer opportunities the people paying attention are using it to build businesses solo that used to need 50 people how to automate content creation at scale with AI 👇

rewind

16,831 görüntüleme • 2 ay önce

I’m genuinely proud of how real our Impact Program at ElevenLabs has become. It started with one clear goal - helping bring voices back for people who have lost them. Today, we’ve been able to work with over 5,000 people. It began organically, with people reaching out to us for help. We then formalized it into Impact Program where, together with other organizations, we provide free technology and services to help people get their voice back. I couldn’t have imagined how many incredible partners would want to work alongside us to support them. Now we have 100+ partners for this cause - nonprofits, clinics, and groups on the ground - working with us to support people through the whole journey. As part of this, we wanted to tell the stories of individuals who, despite what they’re going through, continue to inspire. Over the past few months, our team has traveled the world to record 11 stories and create a short documentary, Eleven Voices - soon premiering at SXSW. You can watch the trailer narrated (with permission) by an AI voice of Sir Michael Caine below!
0:33

I’m genuinely proud of how real our Impact Program at ElevenLabs has become. It started with one clear goal - helping bring voices back for people who have lost them. Today, we’ve been able to work with over 5,000 people. It began organically, with people reaching out to us for help. We then formalized it into Impact Program where, together with other organizations, we provide free technology and services to help people get their voice back. I couldn’t have imagined how many incredible partners would want to work alongside us to support them. Now we have 100+ partners for this cause - nonprofits, clinics, and groups on the ground - working with us to support people through the whole journey. As part of this, we wanted to tell the stories of individuals who, despite what they’re going through, continue to inspire. Over the past few months, our team has traveled the world to record 11 stories and create a short documentary, Eleven Voices - soon premiering at SXSW. You can watch the trailer narrated (with permission) by an AI voice of Sir Michael Caine below!

Mati Staniszewski

12,823 görüntüleme • 8 ay önce