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2025-06-29

AI timelines (presentation on 2025-06-29)

Pre-reqs

My top-level views

Samuel

The numbers are guesses and they're approximate, 25% actually means 25 +- 10%

Definition of superintelligent AI: AI that is better than the best humans at every task humans care about completing.

Relevant intuitions for what I actually imagine when I imagine superintelligent AI: Humans from 1900s experiencing entire 1900-2025 inventions in one year, chimpanzees being exposed to a human being

In this talk

Summary of all datapoints

Datapoint 1: Other experts

You will find experts on all ends of spectrum:

I'm selectively presenting doomer views here because I am also somewhat doomer. Message me for resources on expert views that are different.

Other people predicting ASI in next few years, and high estimate of risk

Other people predicting ASI in next few years

Longer list of experts with views in similar cluster

Datapoint 2: Scaling pre-training, try the models yourself

Don't trust benchmark datasets, don't trust what some expert has said, actually go try some of the older models yourself.

number of params, depends on model size

Datapoint 3: Scaling pre-training, chinchilla scaling law, historical data

Chinchilla scaling law (wikipedia)

Epoch AI trends based on chinchilla scaling law

Datapoint 4: Scaling pre-training, chinchilla scaling law, forecasts of future compute and capabilities

More disagreement on future since we don't have hard data about the future.

How much compute will be used in future datacentres?

How much capabilities will this increased compute translate into?

Datapoint 5: Scaling RL/Inference, try the models yourself

Datapoint 6: Scaling RL/inference, log curve for historical data

Benchmarks

I have less trust in benchmarks personally, due to data being leaked publicly.

We have only 1 year (2024 to 2025) since RL/inference scaling has been tried.

Some published curves

Cost per task

I (samuel) don't have strong opinion on which curve is exactly true.

Datapoint 7: Scaling RL/inference, forecasts of future compute and capabilities

Two competing factors

EpochAI article on forecasting scaling RL/inference


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