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I'm an independent researcher working on EA topics (Global Priorities Research, Longtermism, Global Catastrophic Risks, and Economics).
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Private R&D cannot be protected perfectly because patents expire or industry know-how diffuses to other firms and not all rents from investments can be captured. There was a leaked memo out of Google recently that said that Open source foundation models are very good and don't need much compute to run. Recently, OpenAI's CEO Altman has often highlighted that their models are not based on any one fundamental technical breakthrough, but thousands of little hacks from tinkering- but perhaps this is wrong and a strategic statement to boost the valuation of the company.
Daniel's Heavy Tail Hypothesis (HTH) vs. this recent comment from Brian saying that he thinks that classic piece on 'Why Charities Usually Don't Differ Astronomically in Expected Cost-Effectiveness' is still essentially valid.
Seems like Brian is arguing that there are at most 3-4 OOM differences between interventions whereas Daniel seems to imply there could be 8-10 OOM differences?
And Ben Todd just tweeted about this as well.
Relevant calibration game that was recently posted - I found it surprisingly addictive - maybe they'd be interested in implementing your ideas.
Meta-level: Great comment- I think we should be starting more of a discussion around theoretical high-level mechanisms of why charities would be effective in the first place - I think there's too much emphasis on evidence of 'do they work'.
I think the main driver of the effectiveness of infectious disease prevention charities like AMF and deworming might be that they solve coordination/ public goods problems, because if everyone in a certain region uses a health intervention it is much more effective in driving down overall disease incidence. Because of the tragedy of the commons, people are less likely to buy bed nets themselves.
For micronutrient charities it is lack of information and education - most people don't know about and don't understand micronutrients.
Lack of information / markets
Flagging that that there were charities - DMI and Living Goods - which address these issues, and so, if these turn out to explain most of the variance in differences in cost-effectiveness you highlight then these need to be scaled up. I never quite understood why a DMI-like charity with ~zero marginal cost-per-user couldn't be scaled up more until it's much more cost-effective than all other charities.
Relatedly: "without the gains of stocks that are possible AI winners, the S&P 500 would now be down 2 per cent this year, rather than up 8 per cent." https://archive.ph/KFMJU
This might suggest that the gains from AI might be distributed more evenly amongst different Big Tech companies and that economies of scope are more important than relatively small technical leads.