Michael Nielsen – Why aliens will have a different tech stack than us

𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒 * Transcript: https://www.dwarkesh.com/p/michael-nielsen * Apple Podcasts: https://podcasts.apple.com/us/podcast/michael-nielsen-how-science-actually-progresses/id1516093381?i=1000760075027 * Spotify: https://open.spotify.com/episode/1JTv7Le8s5Mf0hDcXDOJYl 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 - Labelbox researchers built a new safety benchmark. Why? Well, current safety benchmarks claim that attacks on top models are successful only a few percent of the time, but the prompts in those benchmarks don't reflect how real bad actors actually write. You can read Labelbox's research here: https://labelbox.com/blog/the-ai-safety-illusion-why-current-safety-datasets-fool-us-on-model-safety/. If this could be useful for your work, reach out at https://labelbox.com/dwarkesh - Mercury has an MCP that lets you give an LLM access to your full transaction history, including things like attached receipts and internal notes. I just used it to categorize my 2025 transactions, and it worked shockingly well. Modern functionality like this is exactly why I use Mercury. Learn more at https://mercury.com - Jane Street's ML engineers presented some of their GPU optimization workflows at GTC, showing how they use CUDA graphs, streams, and custom kernels to shave real time off their training runs. You can watch the full talk here: https://www.nvidia.com/en-us/on-demand/session/gtc26-s82065/. And they open-sourced all the relevant code: https://github.com/janestreet/gtc2026/. If this kind of stuff excites you, Jane Street is hiring — learn more at https://janestreet.com/dwarkesh To sponsor a future episode, visit https://dwarkesh.com/advertise. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00:00 – How scientific progress outpaces its verification loops 00:17:51 – Newton was the last of the magicians 00:23:26 – Why wasn’t natural selection obvious much earlier? 00:29:52 – Could gradient descent have discovered general relativity? 00:50:54 – Why aliens will have a different tech stack than us 01:15:26 – Are there infinitely many deep scientific principles left to discover? 01:26:25 – What drew Michael to quantum computing so early? 01:35:29 – Does science need a new way to assign credit? 01:43:57 – Prolificness versus depth 01:49:17 – What it takes to actually internalize what you learn

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