Nikolai Yakovenko: OpenAI in chaos, the future of artificial intelligence and effective accelerationism
Nov 21, 2023
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Razib interviews Nikolai Yakovenko, an AI researcher and founder of DeepNews. They discuss the leadership chaos at OpenAI and its implications, the future of AI, and the likelihood of AI becoming a corporate oligopoly. They also talk about the differences between OpenAI and Google, data center locations, and differing opinions on the timeline and impact of AGI.
OpenAI's leadership turmoil may give competitors like Google an opportunity to catch up in AI advancements.
The mix of for-profit and nonprofit entities on OpenAI's board structure may necessitate a new board.
Effective accelerationism promotes using AI as a tool for advancing human progress, despite potential risks.
Deep dives
Leadership shakeup at OpenAI
The podcast discusses the recent ousting of OpenAI CEO Sam Altman and the subsequent leadership changes at the company.
Challenges with OpenAI's board structure
The podcast explores the challenges with OpenAI's board structure, which includes a mix of for-profit and nonprofit entities, and the potential need for a new board.
Implications for the future of OpenAI
The podcast delves into the potential impact of the leadership shakeup on the future of OpenAI and the company's ability to continue its advancements in artificial intelligence research and development.
Opportunities for competitors like Google
The podcast discusses the potential opportunities for competitors like Google to capitalize on the disruption at OpenAI and further push the boundaries of AI research and development.
The Rise of Llama and Nusstrow: More Efficient Language Models
Llama and Nusstrow are language models that have gained popularity as alternatives to GPT4. Llama stands out for its improved encoding, using a combination of bytes, digits, and word parts. Nusstrow, an improvement on llama, is even more efficient. These models have attracted attention and are being used in the open-source community, showing that there is potential for multiple high-quality language models to coexist without a clear winner.
Effective Altruism and Effective Accelerationism
Effective altruism focuses on making the most impact with available resources, aiming to reduce suffering and address long-term risks. Effective accelerationism, a newer concept, argues for embracing AI as a tool for doing great things and advancing human progress. It promotes a utilitarian view, suggesting that the benefits of AI outweigh potential risks. While effective altruism and effective accelerationism have their critics and differing viewpoints, they continue to shape discussions and influence thinking in the AI community.
Razib and Yakovenko talk about the economic, technological and socio-political implications of the leadership turmoil at OpenAI, the $86 billion dollar company that has supercharged the field of artificial intelligence with their product, ChatGPT. Yakovenko digs deep into the nuts and bolts of how artificial intelligence works today, from transformers to GPUs and different compute needs of training vs. inference. They also discuss the importance of shipping products at a tech company, in contrast to simply publishing papers as the measure of productivity in academic basic science research for example, and how on this count OpenAI succeeded where Google has not. Razib asks Yakovenko if OpenAI might now fall behind Google, whose corporate risk-aversion had squandered it an early lead in technology like transformers. Now that OpenAI is seized by such organizational chaos as to stop development, Google may have time to catch up. Yakovenko also talks about the likelihood of artificial intelligence becoming a corporate oligopoly due to the field's colossal compute needs. Finally, Razib and Yakovenko address the cleavages that arose at OpenAI due to the board’s adherence to effective altruism, while leadership and employees instead charted a shift toward effective accelerationism.
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