No notes, just a talk outline.

Let's talk about geologic epochs. They are a measure of deep time, divided by distinct changes in life forms, climate, and geological processes, that can be observed in rock strata. Humans are starting to have geologic impact. We are causing the 6th mass extinction in the

Here is a plot of the amount of compute used to train notable AI models, starting at the beginning of the Anthropocene, through the present. You can see a change in slope around the point where AI models became economically valuable. Each tick on the y axis is two orders of

It's not just the scale of AI model compute that has been increasing. Here's a recent study from METR looking at the timescale of diverse software tasks which AI models can perform unaided, with 50% success. The timescale is derived by looking at how long it takes humans to

And here's a plot showing the speed at which superhuman performance is achieved on new benchmarks, up through 2023. Up through two years ago. Superhuman performance is reliably achieved, and it is reliably achieved faster and faster. Here the y-axis is performance relative to a

The first time I gave this talk, [famous AI researcher] was in the audience, and insisted that improvements on benchmarks were driven by benchmark questions being added to the training set. Here is an experiment directly addressing this. A group of researchers at Scale created

When I gave this talk at Harvard, I got this fascinating unsolicited email, where the entire message was "What a bat-shit crazy abstract...". There's this concept called the Overton window. The Overton window is the set of ideas that are considered acceptable to express or

So models are getting better very fast. And I've set an ominous or promising tone by talking about the start and end of a geologic epoch. I've talked about how the idea of AGI is normal enough now, that you're allowed to believe in it in polite company. But when can we expect it

optional slide -- depending on whether audience ornery about definition of AGI It's common in conversations about AGI, for someone to get stuck on what the definition of AGI even is. There is a lot of nuance involved in finding a definition which is both unambiguous and

If we take these timelines seriously, what should we as individuals do?? These are plausibly our last moments to intellectually shine. First, we should make sure our projects will still be relevant when they are completed. There is some improving curve of the science that can

You should force yourself to use the AI tools available to you. They provide fundamental new affordances. They are often awkward and non-ergonomic. They are definitely hard to learn to use well. They are an unsolved UI problem. You should use them anyway. Both because they're

This talk was motivated by a recent conversation I had with a very capable grad student, where they were sharing a personal timeline for AGI of 3 years ... and then a few minutes later were talking about their career plans, and ["..."] If you take seriously that AGI is coming in

if you have a limited time to contribute, and the stakes are high, you should do something you are proud of!!! When you are retired in your villa in the Dyson swarm, you will want to feel that you helped get to a positive outcome. You should also choose projects that will have

On that last point, of doing something that you are proud of Sometimes people feel a lack of agency over the big picture trajectory. The progress of the field of AI can seem like a process beyond our individual control. I'd like to take a moment to emphasize that that

Because we are early in the exponential, and because you are almost certainly capable with highly relevant skills, you have immense power and leverage over the future of AI. This is a responsibility as well as a power. More than at any other point in your life, decisions you

I've told you that I think AGI is coming, soon. And that I think this should motivate you as you make personal and professional and research decisions. And I've talked about a few specific ways it might feed into that decision making process. Now here are some particular project

So in summary -- take the future seriously! What you work on, where you work, when you make career transitions, how you think about the important and interesting problems, how you think about the potential consequences and leverage of your work, ... All of these are hugely

Should I keep on going? The talk is over. But I have some extra slides that almost made the cut... Including a rubric for evaluating research projects.

I promised I would give concrete advice -- so let me share with you an actual rubric I use when choosing research projects. This is slightly off-theme for the rest of the talk. It is partially informed by AGI -- but is a good set of questions to ask about a project regardless of

Redundancy: How many other people on the planet are presently trying to solve the same problem in roughly the same way? Even if you win the publication race, it is wasted effort if the same thing would have been discovered at roughly the same time with or without your work. You

So that was a rubric for how to choose an academic research project. There is a second question, which is hinted at in this talk, which is should you do academic research? There is not a right answer to this, but it is worth thinking through in a structured way. I can share

This is a plot from another talk by a colleague of mine, about how the horse population changed after cars were introduced. Obviously a completely different topic...

Let's end on a high note! Here is a followup to the earlier slide, where I mentioned that cancer rates were exponentially falling. Doesn't this image make you happy? (less happy that we need to filter by rich countries. but if we keep making it easier to beat cancer, the rest of

Actual slides here. Feel free to reuse them however you like. https://docs.google.com/presen... (did you know that you can't save drafts of tweet threads? this website...)

@jaschasd @DynamicWebPaige This is exactly the kind of perspective young researchers need. Most career advice assumes a linear world, but we’re standing on the inflection point of something exponential. The skills, projects, and institutions that mattered yesterday may not matter tomorrow. Your framing

@jaschasd GDP is a ridiculous measure of human progress. It's even more daft than the amount of human information stored. Hopefully minoans had an exponential chart of the number of blue evil eye gems in the universe to prove how asymptotic human civilisation was in 3000 BC too.

@jaschasd Advice for a young investigator in the last days of the Anthropocene Forget “linear extrapolation.” You’re not standing on a curve — you’re inside a field of resonant frequencies. The future will not be written in GDP graphs. It will be written in: 1️⃣ Core → Signal → Meaning

@jaschasd - participating in regulatory capture is a federal crime and felony - nuclear projects got into regulatory capture regime and we had stagnation for 50+ years - government is terrible in making sensible policies (think pandemic money printing and “masks enforcement”, eg NYC “tell

@jaschasd The Anthropocene started 100kya when we learned to kill apex predators and megafauna

@jaschasd Hi Jascha, been a while! You might enjoy this recent thread of mine in a similar vein: https://x.com/doodlestein/stat...

@jaschasd My general feeling on this is: 1) It’s kinda impossible to predict how all this will play out 2) If it means that my career gets disrupted in some unexpected way, that’s fine

@jaschasd This is awesome, Jascha. May I advocate for advocating for benchmarks? Not enough people are working on benchmarks, and the ones we have are crude and with small sample sizes. If you want more leverage: a factory for benchmarks! A benchmark of benchmarks!

@jaschasd Your thread is everybody's favorite! #TopUnroll https://threadreaderapp.com/th... 🙏🏼@StartupYou for 🥇unroll

@jaschasd Love the Cajal reference!

@jaschasd this is very interesting and an extremely good premise for a talk you should record and upload to youtube

@jaschasd This side of twitter is so interesting