Fortnightly AI-wealth tracker — 11 September 2026
AIS/EA: median modeled end-2027 disbursement $0.83B; 80% model interval $0.16B–$3.0B. Review status: reviewed; unchanged. Named public AI-linked commitments tracked: $0.86B. Tracker and sources.
Global health and development: median $0.54B; 80% model interval $0.16B–$2.8B. Review status: adjusted. Named public GH&D commitments tracked: $0.31B. GH&D tracker and sources.
Latest news: OpenAI Foundation commits $60M to AI forecasting for smallholder farmers. The confirmed three-year portfolio spans South and Southeast Asia and East Africa. It is a named commitment, not a cash-paid total; the public announcement does not specify the share disbursed by end-2027.
The intervals are deterministic model percentiles, not empirical confidence intervals. Commitment totals may include credits, technical support, cofunding, and multi-year plans; they are not cash-paid totals. Automated fortnightly update from the maintained model.
Following up on more from your email, which you said was okay to share here. I give my impressions below, but I think your own insights and experience are themselves helpful, so I’m sharing them.
Very tangibly, what I would propose (and this may already have been done) is to choose one route (at a time) and then go through that process, end-to-end, unit operation by unit operation, from RM sourcing to finished product in stores, and look at the costs, challenges and uncertainties of each one.
That makes sense. I think that’s largely consistent with what we’ve done and are planning to do more of, but my own modeling tended to isolate each input and use it interchangeably in each of the different process paths. (See here for a mapping and explainer for a few different processes.)
I see value in treating each possible process as potentially its own thing. In one sense, it might seem reasonable to model the cost of certain inputs in one process as the cost of those same inputs in another process. On the other hand, there may be subtleties here. E.g., , in a process that uses certain inputs more extensively, this might foster a larger-scale market with lower average costs.
IMHO doing this for one process is already a huge job, not something you do in one session, unless you already have a very aligned and technically detailed analysis of the full process.
We have done quite a bit of scoping and mapping, as linked above, and we’ve brought in some people with real expertise, but I still do take this point. I find a synchronous group session a good coordinating and motivation tool for pushing things forward. But I agree it might be worth stretching it out over a few separate sessions targeting different approaches or focuses, to avoid our being overwhelmed.
Where I’ve done this it’s been for processes like making detergents (in Procter & Gamble) and synthesising MOF’s (at Immaterial). We would try to get at least one person with an intimate deep technical knowledge of each process step in the room (maybe not all together) and we would run it almost like a devil’s advocate panel where we’d intentionally challenge all the assumptions. For example, how to get material from one step to the next – does it have to be transported? Does it have to change temperature or pressure? Is it stable? Does it need to be sterilized? Etc.
Sounds very promising and potentially worth our emulating. Naturally, it needs the physical, scientific expertise, rather just modelers and economists. Maybe easier to do in contexts where people don’t seem to have strong interests, agendas, or “positions” on the issues. In the CM context, I think it’s something in between. Certainly, there are people in groups with a strong attachment to seeing this work and maybe occasional lapses into “soldier” rather than “scout” mode. And perhaps also some motivated/entrenched skeptics (which we’ve had a harder time engaging in the workshops themselves, although we’ve been able to get some anonymous input). On the other hand, even among those ~advocating for CM and trying to make it work, there seems to be some decent open-mindedness about which processes are cheaper, how much everything will cost, etc.
It’s important that the moderator NOT have strong opinions, the point is to passively collect and combine the wisdom of the room, but also to highlight questions and disagreements (not necessarily to solve them at the time while 12 other people wait!).
I’ve been trying to do that, and I’ve been putting myself forward as not having strong opinions, beliefs, or any sort of dog in this fight. I think the same applies to David Manheim and others on our team.
I don’t know what timeline you have in mind. However, if you plan to do it very soon, I would definitley push back and propose instead that you might want to do a pre-meeting soon, in which you would capture what information is needed, and how it should be shared, and then identify who will get that information for each topic, before you’d run the definitive session(s).
Good ideas—as mentioned, we’ve done some of the pre-work, in a certain sense, but I think there’s more to do, and this seems like a good framing of it. As long as the participants are willling to show up for multiple sessions (or weigh in async).
Timeline is probably in the next few months. Hopefully, we make something happen before the end of the year.
Again, maybe all this information is freely available and I’m wrong, so feel free to ignore that.
GFI has made a lot available, but I think there’s still more of this preparation to do. And GFI could be argued to have a particular agenda, or at least solutions that they consistently tend to support and to stake in the research. So it’s good to have some independent vetting to make things more legibly credible.
Obviously, you can do a BOTEC with whatever level of accuracy you want. Maybe I’m overestimating the accuracy you want. Any chemical engineer in the field could do a BOTEC in 10 minutes. The question is: how valid will that BOTEC be if it’s not based on informed knowledge about what this will actually be like when you consider three things
This all makes sense to me. I think the value of precision is probably less here than for things like making detergents, where you’re trying to perhaps decide between a few very similar options on the basis of cost and profitability. The fundamental question here is more about the probability that each type of cultured meat and process (and with what mixing proportions etc.) will be roughly cost-comparable to “organic” (animal) meat. An order-of-magnitude difference in the forecasts and TEAs, which seems to make a big difference in the decision whether to invest in CM R&D vs other interventions.