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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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20,959 次观看 • 1 个月前 •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

57,874 次观看 • 2 个月前

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

28,084 次观看 • 1 个月前

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 次观看 • 4 个月前

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

33,696 次观看 • 3 个月前

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 次观看 • 2 个月前

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 次观看 • 1 年前

$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 次观看 • 8 个月前

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

13,198 次观看 • 5 个月前

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

357,667 次观看 • 1 年前

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

4,560,891 次观看 • 2 个月前

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 次观看 • 9 个月前

🚨 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 次观看 • 8 个月前

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 次观看 • 26 天前

DeepSeek-R1 shattered the assumption that performant AI models must be built closed source with loss-leading computational costs. This is the reality that Web3 x Crypto firms have been waiting for, leading me to believe that the most performant AI models in the future will be built on-chain. Resource Requirements DeepSeek R1 (671 billion parameters), which took over a billion dollars, 2,000 Nvidia H800 GPUs, and over 55 days, beat benchmarks held by OpenAI’s o1 mode (near 2 trillion parameters)l, which required hundreds of billions of dollars to develop along with over 16,000 advanced GPUs. The idea that AI models must be closed-source and have loss-leading computational costs to succeed is crumbling. The Existing Decentralized AI Narrative AI x Crypto projects believed that crowdsourced, public, decentralized AI would eventually create better models than their centralized counterparts. This had thus far not been true, as the highest-performing models had come from closed-source companies like OpenAI and Anthropic. Crypto x AI companies have adapted to this by specializing in infrastructure rather than model-building. For example, GPU marketplaces like , The Render Network, io.net, and Exabits have developed sustainable revenues. Companies that allow users to share their network bandwidth like touch grass and Gradient have found their niche in supplying services, like distributed web scraping, to web2 clients. Storage networks like Arweave Ecosystem, Filecoin, and Ocean Protocol have also done well by being the platform on which these projects are built. Supply networks have flourished because of their ability to tailor their cheaper and more scalable services to off-chain customers. Renewed Focus Now that GPU and financial resources are no longer limitations to creating quality AI models, web3 AI companies can focus on replicating DeepSeek’s effectiveness while offering new benefits like modality, user ownership, censorship resistance, privacy, and more. Pantera Capital has funded companies in this space like and Sentient that believe they can match or exceed the performance of traditional AI companies while offering additional services or benefits. , for example, is building a platform where anyone can monetize AI models, data sets, and applications in a collaborative space. Users can permissionlessly train models manually, provide training data, and create tailored AI models with no-code tools. They are only able to cater to all these stakeholders (AI developers, users, resource providers) because everything is tied to their native Sahara blockchain. We invested in them precisely for this reason. The Future of AI will be built with Web3 Infrastructure I believe that supply-side projects will continue to grow, while consumer-facing projects can begin competing with web2 competitors by taking advantage of their ability to build networks that invite community involvement. and Sentient, for example, have begun setting up systems for users to train models based on the users’ expertise. These platforms will allow users to pick and choose the data and integrations to whatever they are applying the model towards. Sahara already has over 780,000 users on their waitlist while Sentient has over 1 million interactions. In the near future, I believe that the most performant AI models will be built on-chain. For the full blog post, read my newsletter.
0:32

DeepSeek-R1 shattered the assumption that performant AI models must be built closed source with loss-leading computational costs. This is the reality that Web3 x Crypto firms have been waiting for, leading me to believe that the most performant AI models in the future will be built on-chain. Resource Requirements DeepSeek R1 (671 billion parameters), which took over a billion dollars, 2,000 Nvidia H800 GPUs, and over 55 days, beat benchmarks held by OpenAI’s o1 mode (near 2 trillion parameters)l, which required hundreds of billions of dollars to develop along with over 16,000 advanced GPUs. The idea that AI models must be closed-source and have loss-leading computational costs to succeed is crumbling. The Existing Decentralized AI Narrative AI x Crypto projects believed that crowdsourced, public, decentralized AI would eventually create better models than their centralized counterparts. This had thus far not been true, as the highest-performing models had come from closed-source companies like OpenAI and Anthropic. Crypto x AI companies have adapted to this by specializing in infrastructure rather than model-building. For example, GPU marketplaces like , The Render Network, io.net, and Exabits have developed sustainable revenues. Companies that allow users to share their network bandwidth like touch grass and Gradient have found their niche in supplying services, like distributed web scraping, to web2 clients. Storage networks like Arweave Ecosystem, Filecoin, and Ocean Protocol have also done well by being the platform on which these projects are built. Supply networks have flourished because of their ability to tailor their cheaper and more scalable services to off-chain customers. Renewed Focus Now that GPU and financial resources are no longer limitations to creating quality AI models, web3 AI companies can focus on replicating DeepSeek’s effectiveness while offering new benefits like modality, user ownership, censorship resistance, privacy, and more. Pantera Capital has funded companies in this space like and Sentient that believe they can match or exceed the performance of traditional AI companies while offering additional services or benefits. , for example, is building a platform where anyone can monetize AI models, data sets, and applications in a collaborative space. Users can permissionlessly train models manually, provide training data, and create tailored AI models with no-code tools. They are only able to cater to all these stakeholders (AI developers, users, resource providers) because everything is tied to their native Sahara blockchain. We invested in them precisely for this reason. The Future of AI will be built with Web3 Infrastructure I believe that supply-side projects will continue to grow, while consumer-facing projects can begin competing with web2 competitors by taking advantage of their ability to build networks that invite community involvement. and Sentient, for example, have begun setting up systems for users to train models based on the users’ expertise. These platforms will allow users to pick and choose the data and integrations to whatever they are applying the model towards. Sahara already has over 780,000 users on their waitlist while Sentient has over 1 million interactions. In the near future, I believe that the most performant AI models will be built on-chain. For the full blog post, read my newsletter.

paul.nft

32,465 次观看 • 1 年前

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

12,797 次观看 • 6 个月前

David Sacks: “FDA for AI” is fake news, but here’s why it’s making headlines @jason: “ Who's leading Trump down the path of regulation and creating this AI FDA?” David Sacks: “I think there's several things going on here. The first one is, there's a lot of fake news. This whole idea of an FDA for AI, I don't think any senior official supports it. Certainly, I don't think that's the way the president thinks about these issues. He's the most pro-innovation president we've ever had. And the White House Chief of Staff, Susie Wiles, just put out a statement last night that I think pretty much shoots this down. Second, there's another thing going on, which is a straw manning of what the Trump administration did on AI in its first year. In the same way that they want to spin this FDA for AI, they're also trying to spin what we did as this completely laissez-faire attitude, where there'd be no regulations whatsoever, nor guardrails. It's a way of criticizing what we did. They're trying to portray it as unsafe. In fact, if you look, on March 20th, the White House released a national AI regulatory framework in which we put out a four-page bulleted list of legislation that we would support. So we have not been against every conceivable regulation or every conceivable law, we just believe that there should be specific solutions to specific problems, as opposed to a giant power grab by Washington that would squash innovation. Point number three is, there is a legitimate thing happening here with, let's call it Mythos or cyber. Within 3-6 months, all the major frontier labs, including Chinese models, will have cyber capabilities. In response to that, we do need there to be a hardening of systems, and we do need there to be a scanning of codebases to find these vulnerabilities and patch them before the hackers do it. Because the hackers will have these capabilities in a matter of months. That's a certainty. So we do need a response to that. Now, my view on what should that response be, first of all, we should want the government and the private sector to work cooperatively, and I think they are. What we should be doing, I think, is getting these tools, Mythos, and then the OpenAI model, and others like it, in the hands of our cybersecurity industry. And by the way, not just the public companies like Palo Alto Networks and CrowdStrike, although certainly they're two of the most noteworthy, but there's also some incredibly strong startups on the way up. We need to get these tools into their hands as quickly as possible because they're a force multiplier for all the companies out there that aren't that good at cybersecurity, they can use these companies as vendors. And just one last point on this whole thing is, both Anthropic and OpenAI acted responsibly here. No one was trying to release these super powerful models. So in a way, all the people who are saying that we need pre-release approvals for models, they're trying to solve a problem that didn't exist. Yes, we do have this cyber issue, but that is a problem that we will solve over the next six months. What they're trying to do is use that issue to try and create a permanent new infrastructure in Washington. The classic 'never let a crisis go to waste' strategy.”
2:47

David Sacks: “FDA for AI” is fake news, but here’s why it’s making headlines @jason: “ Who's leading Trump down the path of regulation and creating this AI FDA?” David Sacks: “I think there's several things going on here. The first one is, there's a lot of fake news. This whole idea of an FDA for AI, I don't think any senior official supports it. Certainly, I don't think that's the way the president thinks about these issues. He's the most pro-innovation president we've ever had. And the White House Chief of Staff, Susie Wiles, just put out a statement last night that I think pretty much shoots this down. Second, there's another thing going on, which is a straw manning of what the Trump administration did on AI in its first year. In the same way that they want to spin this FDA for AI, they're also trying to spin what we did as this completely laissez-faire attitude, where there'd be no regulations whatsoever, nor guardrails. It's a way of criticizing what we did. They're trying to portray it as unsafe. In fact, if you look, on March 20th, the White House released a national AI regulatory framework in which we put out a four-page bulleted list of legislation that we would support. So we have not been against every conceivable regulation or every conceivable law, we just believe that there should be specific solutions to specific problems, as opposed to a giant power grab by Washington that would squash innovation. Point number three is, there is a legitimate thing happening here with, let's call it Mythos or cyber. Within 3-6 months, all the major frontier labs, including Chinese models, will have cyber capabilities. In response to that, we do need there to be a hardening of systems, and we do need there to be a scanning of codebases to find these vulnerabilities and patch them before the hackers do it. Because the hackers will have these capabilities in a matter of months. That's a certainty. So we do need a response to that. Now, my view on what should that response be, first of all, we should want the government and the private sector to work cooperatively, and I think they are. What we should be doing, I think, is getting these tools, Mythos, and then the OpenAI model, and others like it, in the hands of our cybersecurity industry. And by the way, not just the public companies like Palo Alto Networks and CrowdStrike, although certainly they're two of the most noteworthy, but there's also some incredibly strong startups on the way up. We need to get these tools into their hands as quickly as possible because they're a force multiplier for all the companies out there that aren't that good at cybersecurity, they can use these companies as vendors. And just one last point on this whole thing is, both Anthropic and OpenAI acted responsibly here. No one was trying to release these super powerful models. So in a way, all the people who are saying that we need pre-release approvals for models, they're trying to solve a problem that didn't exist. Yes, we do have this cyber issue, but that is a problem that we will solve over the next six months. What they're trying to do is use that issue to try and create a permanent new infrastructure in Washington. The classic 'never let a crisis go to waste' strategy.”

The All-In Podcast

150,106 次观看 • 2 个月前

Dario and Demis at Davos on AI jobs impact. Dario says we are headed to “unusual situation of high GDP growth and high unemployment” with 50% unemployment for entry level jobs within 5 years. Demis responds to Dario’s prediction and says he has a “longer timeline”. The models still have to solve for “consistency” and the “jagged intelligence” issue. An agent that can do 95% of a job won’t replace the job, it would have to do 100% and that’s still a ways away.
0:59

Dario and Demis at Davos on AI jobs impact. Dario says we are headed to “unusual situation of high GDP growth and high unemployment” with 50% unemployment for entry level jobs within 5 years. Demis responds to Dario’s prediction and says he has a “longer timeline”. The models still have to solve for “consistency” and the “jagged intelligence” issue. An agent that can do 95% of a job won’t replace the job, it would have to do 100% and that’s still a ways away.

Bearly AI

334,600 次观看 • 6 个月前

Chamath: We have a huge perception issue in AI… here’s how to fix it. “We have a huge perception issue in AI.” “We have a handful of companies, all the PR that you see from those handful of companies is a bunch of circular dealmaking, a bunch of capital that flows from one to the other.” “It causes these stocks to go up, of which a small percentage of people benefit.” “And at the tail end of it, it's accompanied by a completely different set of articles that everybody also reads about this Sword of Damocles that's about to fall on their head, whether it's electricity prices or whether it's their jobs.” “So the question at hand is how do we fix it?” “How do we get back to the place where a video talking about stopping all progress would seem as laughable as it should be?” “We now need to be on the forward foot as an industry.” “We need to start to use a percentage of the balance sheets of these companies in order to benefit as many Americans as possible.” “That is the absolute minimum.” “Andrew Carnegie built 2,500 libraries.” “The idea was, as he built the railroads, you're going to scale GDP, you're going to scale education and knowledge.” “Those libraries are artifacts that allowed people to feel a dividend from that industrial revolution.” “We need to self-organize better, and we need to be more on the forward foot.” “We need to start doing things that are practically measurable by tens of millions of American citizens.”
1:17

Chamath: We have a huge perception issue in AI… here’s how to fix it. “We have a huge perception issue in AI.” “We have a handful of companies, all the PR that you see from those handful of companies is a bunch of circular dealmaking, a bunch of capital that flows from one to the other.” “It causes these stocks to go up, of which a small percentage of people benefit.” “And at the tail end of it, it's accompanied by a completely different set of articles that everybody also reads about this Sword of Damocles that's about to fall on their head, whether it's electricity prices or whether it's their jobs.” “So the question at hand is how do we fix it?” “How do we get back to the place where a video talking about stopping all progress would seem as laughable as it should be?” “We now need to be on the forward foot as an industry.” “We need to start to use a percentage of the balance sheets of these companies in order to benefit as many Americans as possible.” “That is the absolute minimum.” “Andrew Carnegie built 2,500 libraries.” “The idea was, as he built the railroads, you're going to scale GDP, you're going to scale education and knowledge.” “Those libraries are artifacts that allowed people to feel a dividend from that industrial revolution.” “We need to self-organize better, and we need to be more on the forward foot.” “We need to start doing things that are practically measurable by tens of millions of American citizens.”

The All-In Podcast

105,809 次观看 • 7 个月前

Warren Buffett: "It's better to have the talent of the whole world working on things like battery technology or whatever it may be. If we can add the resources of a whole bunch of other people to help solve our problems, I'm all for it." "If we get there first and they copy us — fine. If they get there first and we copy them — fine. It is not like they're going to be able to hoard the technology and we'll never see it." "I like to see the United States come in first on everything, but I don't think it will be terrible if somebody in China or India comes up with something that enables this country to deal with its problems." (Charlie Rose Show || 2009)
0:41

Warren Buffett: "It's better to have the talent of the whole world working on things like battery technology or whatever it may be. If we can add the resources of a whole bunch of other people to help solve our problems, I'm all for it." "If we get there first and they copy us — fine. If they get there first and we copy them — fine. It is not like they're going to be able to hoard the technology and we'll never see it." "I like to see the United States come in first on everything, but I don't think it will be terrible if somebody in China or India comes up with something that enables this country to deal with its problems." (Charlie Rose Show || 2009)

Kevin Carpenter

17,400 次观看 • 1 个月前