Nikolai Yakovenko: OpenAI in chaos, the future of artificial intelligence and effective accelerationism

Razib Khan's Unsupervised Learning - A podcast by Razib Khan

Today, Razib interviews Nikolai Yakovenko, already a three-time guest on his podcasts (A Twitter engineer on machine learning and his former company's prospects, GPT-3 and the rise of the thinking machines and AI and Biology). An artificial intelligence researcher based in Miami who has worked at Google and Nvidia, Yakovenko is the founder of DeepNews where he currently works. 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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