Nov 3 • 1HR 18M

Nikolai Yakovenko: a Twitter engineer on machine learning and his former company's prospects

Deep neural networks, why do they matter for social media?

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Razib Khan
Conversations about science, culture, and current affairs
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When Jack Dorsey stepped down as Twitter CEO last year, I wondered what we could expect from the new leader, Parag Agrawal. Luckily, I knew Nikolai Yakovenko, who worked at Twitter on deep neural networks in the mid-teens. Yakovenko told me Agrawal was not a rock-the-boat kind of guy, and perhaps that’s why Dorsey tapped him to head Twitter after some tumultuous years. Now that Twitter and its leadership is in the news again, due to Elon Musk’s status as “chief twit,” I wanted to talk to Yakovenko about his time at Twitter, discuss the application's upsides and downsides, and get his take on what we can expect going forward.

Yakovenko is now the CEO of Deep NFT Value, and has extensive experience in crypto, machine learning and deep learning. We discussed the nitty-gritty of how Twitter’s algorithm works to prioritize and deprioritize certain types of content, what precisely deep neural networks are, and how they are relevant to what Twitter does. More generally, we discussed why machine learning has become so important in the technology space over the last decade, and why a company like Twitter has become heavily invested in the field. Finally, Yakovenko talks about the general prospects of Twitter going forward under the new Musk regime.

Note: the archive of podcasts (2 weeks delayed) now also resides on YouTube as well as Apple, Stitcher and Spotify (though my “monologues” will not be posted in full ungated).

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