@ScottAlexander Is it possible to hold on to my current shares? Not interested in selling at the moment.

How much money have you spent so far?

• It’s hard to calculate this but I’d claim it’s about USD 10k. More if you include opportunity costs. I can provide a breakdown of this budget upon request.

Have you gotten more funding from other sources?

• Yes. Janus has provided OpenAI API credits and has reimbursed some of my other expenses. Nuño has been consulting. For the rest, I’ve drawn from savings by selling RSUs. 

How is the project going?

• Got accepted to SPAR under Rubi Hudson, so this project is merging with Avoiding Incentives for Performative Prediction in AI | Manifund

• Plan to continue working on this agenda from Jan to Apr 2024, sent an application to AI Safety Camp

• Ran some basic experiments but bottlenecked on conceptual progress. Some false starts, no publishable artifacts so far, but working on it. Please get in touch directly if you'd like to hear more.

How well has your project gone compared to where you expected it to be? (Score from 1-10, 10 = Better than expected)

• 3.3

Are there any remaining ways you need help, besides more funding?

• A magic wand that reduces bureaucratic inefficiency.

Any other thoughts or feedback?

•  Not for now!

Let me know how this is going. Can maybe fund this.

Updates:

• The Autocast Competition (mlsafety.org) was closed due to the FTX collapse, so we decided to scrap the paper and reorient towards eventually selling the project to Anthropic instead.

• No outputs on the development side in the last two weeks because I needed a break after pushing to wrap up work prior to my vacation and continuous exhaustion isn't sustainable.

• Applied to SERI MATS to get more time to work on this, got an informal accept from the mentor we targeted, but waiting for official decisions to be out.

@Austin thanks! Quick answers:

Deliverables: We'll open source our methods, code, models, data, animations, and any additional information needed to reproduce the experimental results. We aim to submit a paper to NeurIPS 2023 within the next 8-9 weeks. Public release date is currently 14 weeks from now.

Commitment: I am taking 4 weeks off (starting late April) to focus primarily on this project. As far as when to scale: it's hard to give a firm date since the field moves so fast, but this is really a function of how much we raise. Some parts of our architecture are scale invariant, others plug into publicly available LLMs, and some components of the system are traditional software. On the margin, dollars spent on inference and evaluation (for e.g ablation studies/prompt testing) are more useful than dollars spent on training, at least until you get pretty far down the list of ideas. We'll make the decision to scale when we think it's a good idea, and we don't yet know precisely when that will be.

Hi Sheikh! This seems like a neat project - it's awesome to hear that Nuno is involved here too. A couple questions that might help investors evaluating this:

• What are the deliverables if experimentation goes well -- eg published paper? Blog post? Interactive website?

• Roughly how much time do you and Nuno expect to put into this before deciding whether to scale up?

@aaronl yep! Mostly along the lines of [2206.15474] Forecasting Future World Events with Neural Networks (arxiv.org)

I'm curious to learn more about the second primary outcome, "measure information retrieval + architecture tweaks vs crowd performance on prediction markets". This sounds like the main tie-in to forecasting. Is the idea to predict the probability of an event using GPT-3 (either by asking directly or extracting probabilities in a lower-level way) and compare the accuracy of these predictions to prediction markets?