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* GOAL 3 is a social enterprise that created IMPALA, a patient monitoring and digital platform system for low-resource settings. There is also a GOAL 3 foundation that raises funds to ensure underserved communities will be reached.
* A recently completed report from Rethink Priorities calculated IMPALA to have a cost per DALY averted of $7–17 in paediatr...
This month effective altruism has gotten lots of attention, including a cover story in The Economist. It feels pretty surreal to be on the receiving end of it. But I feel grateful these ideas have caught on, and even more grateful for the drive, earnestness, and compassion of so many people who took strange but well-argued ideas seriously and then actually acted on them....
Note: This post was crossposted from the Coefficient Giving Farm Animal Welfare Research Newsletter by the Forum team, with the author's permission. The author may not see or respond to comments on this post.
Subtitle: On vegan advocacy, effective altruism, and FIFA
I turn 40 today. Here are some hot takes.
On factory farming
1. Our biggest challenge is salience. If factory farming led the evening news, it wouldn’t last lo...
Recent opportunities to take action
People often appeal to Intelligence Explosion/Recursive Self-Improvement as some win-condition for current model developers e.g. Dario argues Recursive Self-Improvement could enshrine the US's lead over China.
This seems non-obvious to me. For example, suppose OpenAI trains GPT 6 which trains GPT 7 which trains GPT 8. Then a fast follower could take GPT 8 and then use it to train GPT 9. In this case, the fast follower has a lead and has spent far less on R&D (since they didn't have to develop GPT 7 or 8 themselves).
I guess people are thinking that OpenAI will be able to ban GPT 8 from helping competitors? But has anyone argued for why they would be able to do that (either legally or technically)?
I think the mainline plan looks more like use the best agents/model internally and release significantly less capable general agents/models, very capable but narrow agents/models, or AI generated products.
The lead could also break down if someone steals the model weights, which seems likely.
They could exclusively deploy their best models internally, or limit the volume of inference that external users can do, if running AI researchers to do R&D is compute-intensive.
There are already present-day versions of this dilemma. OpenAI claims that DeepSeek used OpenAI model outputs to train its own models, and OpenAI doesn't reveal their reasoning models' full chains of thought to prevent competitors from using it as training data.