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Conviction에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Conviction 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Will we have Superintelligence by 2028? With Anthropic’s Ben Mann

41:25
 
공유
 

Manage episode 488306266 series 3444082
Conviction에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Conviction 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

What happens when you give AI researchers unlimited compute and tell them to compete for the highest usage rates? Ben Mann, Co-Founder, from Anthropic sits down with Sarah Guo and Elad Gil to explain how Claude 4 went from "reward hacking" to efficiently completing tasks and how they're racing to solve AI safety before deploying computer-controlling agents. Ben talks about economic Turing tests, the future of general versus specialized AI models, Reinforcement Learning From AI Feedback (RLAIF), and Anthropic’s Model Context Protocol (MCP). Plus, Ben shares his thoughts on if we will have Superintelligence by 2028.

Sign up for new podcasts every week. Email feedback to [email protected]

Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @8enmann

Links:

Chapters:

00:00 Ben Mann Introduction

00:33 Releasing Claude 4

02:05 Claude 4 Highlights and Improvements

03:42 Advanced Use Cases and Capabilities

06:42 Specialization and Future of AI Models

09:35 Anthropic's Approach to Model Development

18:08 Human Feedback and AI Self-Improvement

19:15 Principles and Correctness in Model Training

20:58 Challenges in Measuring Correctness

21:42 Human Feedback and Preference Models

23:38 Empiricism and Real-World Applications

27:02 AI Safety and Ethical Considerations

28:13 AI Alignment and High-Risk Research

30:01 Responsible Scaling and Safety Policies

35:08 Future of AI and Emerging Behaviors

38:35 Model Context Protocol (MCP) and Industry Standards

41:00 Conclusion

  continue reading

136 에피소드

Artwork
icon공유
 
Manage episode 488306266 series 3444082
Conviction에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Conviction 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

What happens when you give AI researchers unlimited compute and tell them to compete for the highest usage rates? Ben Mann, Co-Founder, from Anthropic sits down with Sarah Guo and Elad Gil to explain how Claude 4 went from "reward hacking" to efficiently completing tasks and how they're racing to solve AI safety before deploying computer-controlling agents. Ben talks about economic Turing tests, the future of general versus specialized AI models, Reinforcement Learning From AI Feedback (RLAIF), and Anthropic’s Model Context Protocol (MCP). Plus, Ben shares his thoughts on if we will have Superintelligence by 2028.

Sign up for new podcasts every week. Email feedback to [email protected]

Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @8enmann

Links:

Chapters:

00:00 Ben Mann Introduction

00:33 Releasing Claude 4

02:05 Claude 4 Highlights and Improvements

03:42 Advanced Use Cases and Capabilities

06:42 Specialization and Future of AI Models

09:35 Anthropic's Approach to Model Development

18:08 Human Feedback and AI Self-Improvement

19:15 Principles and Correctness in Model Training

20:58 Challenges in Measuring Correctness

21:42 Human Feedback and Preference Models

23:38 Empiricism and Real-World Applications

27:02 AI Safety and Ethical Considerations

28:13 AI Alignment and High-Risk Research

30:01 Responsible Scaling and Safety Policies

35:08 Future of AI and Emerging Behaviors

38:35 Model Context Protocol (MCP) and Industry Standards

41:00 Conclusion

  continue reading

136 에피소드

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