Evidence-led look at why AGI might be feasible by 2030, the trends pushing capabilities forward, and where they could plateau.

Narrated by AI.

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Outline:

(03:59) In a nutshell

(05:40) Get notified of new articles in this guide

(05:41) I. Whats driven recent AI progress? And will it continue?

(05:49) The deep learning era

(08:23) Whats coming up

(09:25) 1. Scaling pretraining to create base models with basic intelligence

(09:32) Pretraining compute

(13:03) Algorithmic efficiency

(14:53) How much further can pretraining scale?

(16:42) 2. Post training of reasoning models with reinforcement learning

(22:31) How far can scaling reasoning models continue?

(25:34) 3. Increasing how long models think

(28:28) 4. The next stage: building better agents

(35:10) How far can the trend of improving agents continue?

(37:23) II. How good will AI become by 2030?

(37:29) The four drivers projected forwards

(39:14) Trend extrapolation of AI capabilities

(40:36) What jobs would these systems be able to help with?

(41:29) Software engineering

(42:52) Scientific research

(44:02) AI research

(45:13) Whats the case against impressive AI progress by 2030?

(50:26) When do the experts expect AGI to arrive?

(51:50) III. Why the next 5 years are crucial

(52:53) Bottlenecks around 2030

(56:34) Two potential futures for AI

(58:36) Conclusion

(59:52) Use your career to tackle this issue

(59:52) Further reading

The original text contained 54 footnotes which were omitted from this narration.

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First published:

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Narrated by TYPE III AUDIO.

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