Thoughts on AI in academia - by Sasha Gusev
theinfinitesimal.substack.com · 5,271 words · saved by 4 readers
PhD-level thinking, LLM bias, alignment, AGI, data centers, and AI politics
Herbert Bayer, Convolution, 1948 I keep a list of a few dozen projects ideas that might be of interest and technical ability for a PhD rotation project in statistical genetics. To get a better understanding of what the frontier models are capable of, I rewrote nine projects as LLM prompts and then asked Codex (GPT-5.5-high) and Claude (Opus-4.7-high) to implement them. As you can see from an example prompt1, I described these projects at a high level and without excessive context, similar to how I might explain the project to a colleague who was already somewhat familiar with the research…
saved by
related reading
- The machines are fine. I'm worried about us.ergosphere.blog
- Sara Fish • LLM Evals Research Advicesarafish.com
- As Rocks May Think | Eric Jangevjang.com
- GenAI Handbookgenai-handbook.github.io
- What We’ve Learned From A Year of Building with LLMs – Applied LLMsapplied-llms.org
- AI in 2025: gestalt — LessWronglesswrong.com
- 2025: The year in LLMssimonwillison.net
- Find the stable and pull out the bolt – Natalie B. Hoggnataliebhogg.com
- Thoughts — Jason Weijasonwei.net
- Taking LLMs Seriously (As Language Models) — LessWronglesswrong.com
- Automated Alignment Researchers: Using large language models to scale scalable oversight \ Anthropicanthropic.com
- The Future of Everything is Lies, I Guessaphyr.com