Title: Advice for a young investigator in the first and last days of the Anthropocene
Abstract: Within just a few years, it is likely that we will create AI systems that outperform the best humans on all intellectual tasks. This will have implications for your research and career! I will give practical advice, and concrete criteria to consider, when choosing research projects, and making professional decisions, in these last few years before AGI.
This is my current go-to academic talk. It's mostly targeted at early career scientists. It gets diverse and strong reactions. Let's try it here. Posting slides with speaker notes...
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The title is a play on a very opinionated and pragmatic book by the nobel prize winner ramon y cajal, who is one of the founders of modern neuroscience.
To get you in the right mindset, on the right we have a plot of GDP vs time.
That is you, standing precariously on the top of that curve.
You are thinking to yourself -- I live in a pretty normal world.
Some things are going to change, but the future is going to look mostly like a linear extrapolation of the present.
And the plot should suggest that this may not be the right perspective on the future.
This plot by the way looks surprisingly similar even if you plot it on a log scale. We didn't stabilize on our current rate of growth until around 1950.
The bitter lesson in 26 words:
Don’t be distracted by human knowledge, as AI has been historically.
Instead focus on methods for creating knowledge that scale with computation, like search and learning.
@CharlesWHarper@EvergreenAction crazy how much time the interconnection study takes in proportion to the amount of actual engineering time that goes behind it
Many people do not seem to want data centres built near them, despite the fact that they don't cause that much traffic and often generate a lot of local tax revenue. I suspect it's partly because they're ugly! My proposal:
@ArushiSF 2gw 2026 willingness to pay per year for queue-bypass being more than $1b makes sense
Bloom is $130-180/MWh
Gas turbine $50-80/MWh
Spread x 2.45GW x 8760h ≈ $1.5-2B/yr queue-bypass premium
considering ~1m Blackwell GPUs x $2/hr = $17b/yr, 30% margin -> $5b/yr
Start vibe-coding -> the model does wonders -> the codebase grows with low code quality -> the spaghetti code builds up to the point where the model stops working -> attempts to fix the codebase with AI actually make it worse -> complain online "model is nerfed"