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This reads like Mark Zuckerberg’s answer to the "AI slowdown" push and in-sync with what Jensen Huang is saying over the last couple of days, If your model/product needs more safety work, just slow it down yourself, you don’t need everyone else to stop with you. https://t.co/G5zvu926XA https://t.co/QUdAqc49uc

Jensen Huang pushed back hard against AI labs calling for tighter regulation and slower AI development, at Dreamforce. "If you are not confident about the safety of the products, and you're not confident in its functionality, capability, or safety, then don't just release it. We don't need any new laws. We don't need new regulations. we just need companies to decide that when it's time to run as fast as they can." safety and speed are not mutually exclusive, and new laws are not required to make AI systems safer. Build fast, test aggressively, and pause only when you are no longer confident the product is safe. --- From "Salesforce" YouTube channel, (full video link in comment)

U.S. Vice President JD Vance had some unusually strong words for Anthropic on the All-In Podcast. If an AI company develops technology that can be used for harmful purposes, such as cyberattacks, he believes that company has an obligation to help others defend themselves against those capabilities rather than relying primarily on government regulation. ---- "Why is it that the people who are at the frontier of the AI economy are throwing up their hands and saying, “Well, we’ve built Frankenstein,” and the solution to Frankenstein, apparently, is to create a one-world governance structure for artificial intelligence? What I would say to those people is: if you’re building Frankenstein, stop. Or maybe, if the cat is out of the bag, then build the defensive mechanism against Frankenstein. At the same time, that you have this sort of cyber-hacking tool that’s come out of Anthropic’s newest models, you have companies that are desperate for the defensive mechanisms to defend against that cyber-hacking tool, and they’re being denied access to it. So, if you’re going to create Frankenstein, don’t come to the government and say, “We need regulation.” Look inward and accept that if you’re building Frankenstein, number one, you should stop. And number two, when the companies come to you and say, “We need the tools to fight back against Frankenstein,” give them those tools." ---- full video link in comment on @theallinpod

U.S. Vice President JD Vance had some unusually strong words for Anthropic on the All-In Podcast. If an AI company develops technology that can be used for harmful purposes, such as cyberattacks, he believes that company has an obligation to help others defend themselves against those capabilities rather than relying primarily on government regulation. ---- "Why is it that the people who are at the frontier of the AI economy are throwing up their hands and saying, “Well, we’ve built Frankenstein,” and the solution to Frankenstein, apparently, is to create a one-world governance structure for artificial intelligence? What I would say to those people is: if you’re building Frankenstein, stop. Or maybe, if the cat is out of the bag, then build the defensive mechanism against Frankenstein. At the same time, that you have this sort of cyber-hacking tool that’s come out of Anthropic’s newest models, you have companies that are desperate for the defensive mechanisms to defend against that cyber-hacking tool, and they’re being denied access to it. So, if you’re going to create Frankenstein, don’t come to the government and say, “We need regulation.” Look inward and accept that if you’re building Frankenstein, number one, you should stop. And number two, when the companies come to you and say, “We need the tools to fight back against Frankenstein,” give them those tools." ---- full video link in comment on @theallinpod

Last month I wrote about how we can build a positive and safe future for everyone: https://t.co/eoLGVY8yad Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.

https://t.co/b9k2SW2sGZ

Last month I wrote about how we can build a positive and safe future for everyone: https://t.co/eoLGVY8yad Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.

FastH3 by FastVideo is now available in ComfyUI Video and native stereo audio, generated together, in seconds. Best for: → Previz and animatics that need lots of takes, quickly → Timing and dialogue tests before committing to a full-quality render → Short-form and social work on tight turnarounds Run it locally in ComfyUI and soon on Cloud ⬇️

Last month I wrote about how we can build a positive and safe future for everyone: https://t.co/eoLGVY8yad Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.

Last month I wrote about how we can build a positive and safe future for everyone: https://t.co/eoLGVY8yad Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens. The reality is: - People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned. There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind. - Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well. Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built. - Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators. - Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well. I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.

Jensen Huang completely destroys Jacob Coxon’s (ex-Anthrpic employee) 10% extinction prediction. no data, no scientific grounding, no defensible 10%. "First of all, we shouldn’t [try to explain a 10% chance of extinction], because it’s made up. These are well-educated people. They’re called researchers. Obviously, they’re working in a lab, and so the confluence of these words—and then the prediction—is alarming and troubling. It shouldn’t be done. It’s irresponsible." ---- Full video on "All-In Podcast" YouTube channel (link in comment)

Jensen Huang pushed back hard against AI labs calling for tighter regulation and slower AI development, at Dreamforce. "If you are not confident about the safety of the products, and you're not confident in its functionality, capability, or safety, then don't just release it. We don't need any new laws. We don't need new regulations. we just need companies to decide that when it's time to run as fast as they can." safety and speed are not mutually exclusive, and new laws are not required to make AI systems safer. Build fast, test aggressively, and pause only when you are no longer confident the product is safe. --- From "Salesforce" YouTube channel, (full video link in comment)

This reads like Mark Zuckerberg’s answer to the "AI slowdown" push and in-sync with what Jensen Huang is saying over the last couple of days, If your model/product needs more safety work, just slow it down yourself, you don’t need everyone else to stop with you. https://t.co/G5zvu926XA https://t.co/QUdAqc49uc