It’s been a little more than half a year since we raised our funding and first off, we want to say a huge thank you to everyone who checked out our project, starred our repo on GitHub, shared, donated, and used SocialPredict for yourselves! It all means so much to us.

Here’s what we’ve been doing in the meantime:

Goals Update:

1. Backend refactoring and testing: We have updated our logic such that profit can be calculated in a stateless manner. This includes updated documentation on how our calculation works. We did this in November/December. 

We also refactored our front end such that we can use static React hosting. Unfortunately, what we did not anticipate is that React comes with a number of built-in security features when you use normal container hosting, and so by eliminating those, we are exposing our backend and database to the web in ways we did not anticipate. Hence, when you redeploy past v.0.0.3 now in production on the web, the application is vulnerable. On the good side, we at least were able to discover this. To mitigate this, we look toward building in basic security into our back end so that this is no longer an issue. The idea here is to make the entire app itself more scalable, because it will not be necessary to run a frontend container, just a backend container.

2. Testing on our machines and the web: This has been our basic flow and how we have achieved what was described in goal 1. We use Vite to deploy React, and are in the process/considering moving to Deno. But overall, our development flow is to have dev mount containers on local, publish code, and then push it into our pipeline to go to staging/production. This is working but there is still room for improvement.

3. Real life applications: We were used by Kenyon College in September through November 2024. So we were actively used in production by a class for teaching, and the students had a positive experience and felt it really motivated them. This shows that free, open-source prediction market infrastructure has real-world applications and leads to real-world positive outcomes. Kenyon and St. Lawrence University may use SocialPredict again in the future. We are still in discussions with how to support them and keep the project going.

Beyond Fundraising

Overall, from December through to now, much of our core team has been busy with life and job transition, and we have dedicated a lot of our time on SocialPredict trying to figure out a good product market fit, as we believe the economic engine for this platform is what is going to sustain it. We have several avenues and conversations we are looking into, but nothing public to report at this time. We have been behind on quashing security issues but will likely come back in and update the software late 2025.

At the moment we’re looking into building evaluation tools for AI-assisted financial predictions. If you work in quant trading and you’re interested in backtesting AI models for quant trading purposes, please come and talk to us!

If you are interested in supporting us please consider sponsoring us on GitHub today!

I want to donate as this cause is close to my heart, but I have some questions.

1) When do you expect the eco-hostel to open?
2) How many animals have the local rescues sterilized and vaccinated this year?
3) You say that the money will be used to sponsor vaccination and sterilization. But you also say that you won't be able to reach the amount of animals you want to help if your project fails. Can you clarify?
4) What will your rationale be for deciding whether or not to develop educational programs?
5) How much have you already raised in other local and international donations?

Looks like you need a lot of funding to pursue this, which is understandable. Do you have a mockup that potential donors could look at?

Also, can I talk to some of your team members? I'm curious about their backgrounds and desires to work on AI-driven dating.

@19jrob46 Thank you incredibly much!

@spenser Thanks! We love helping people spin up their own :D

I've checked out your site, I think you have great UI and UX. I love that you're open-source and I appreciate your transparency. So I very much want PlayMoney to succeed

I think this is cool and beautiful and I look forward to seeing more of Calibration City

@wasabipesto Hi! To answer your questions:

• brierfoxforecast.com does represent the current state of development, I also set up my own instance at openprediction.xyz. Development is ongoing, we're still pushing changes, etc.

• possible use cases for running an independent instance rather than using an established server include: privacy and data protection concerns, wanting to have a fallback solution in case something happens to the established server, wanting to have software that an admin can tinker with and configure for different use cases, wanting to have software that's performant on lower-end machines

• our feature set includes the ability for admins to customize their own setup, decide how much market making should cost, and how much debt a user should be allowed to get into: https://github.com/openpredictionmarkets/socialpredict/blob/main/README/README-CONFIG.md

• down the line we'd love to implement variable economics, but at the moment this is lower priority than backend improvements

• it's intended to be deployed in the cloud, but yes, you can run a local dev instance on your machine. I run a local dev instance on an old laptop with 8 GB of RAM and Ubuntu 22.04 and it's highly performant. My staging instance at openprediction.xyz uses a virtual machine with 4GB RAM and an 80 GB hard drive. These are some load tests we did 3 weeks ago: https://github.com/openpredictionmarkets/socialpredict/issues/227

• though of course we're on a new version of the software now, which means more and different load tests, so thank you for the reminder

@Alyssa the problem is that preexisting real-money prediction-market platforms have their own troubles. To the best of my knowledge, there are 2: Kalshi and Polymarket.

Kalshi is great but has run into regulatory issues with the CTFC, IIRC. Polymarket uses crypto. The intersection of "people who care enough about science to forecast about it" and "people who use crypto" is small. I'm trying to target a bigger market of "people who care enough about science to forecast about it". In an ideal world, I would persuade Betfair - the world's largest online betting exchange - to start taking bets on paper replication, because that seems much easier than creating a new prediction-market platform.

My hunch is that some of the troubles faced by prediction-market platforms arise from them focusing on US customers, and that expanding to Canadian, UK, EU, Chinese markets would help.

@Jason Thanks. This has given me a lot to think about. Hoping to start getting users for a play money version ~May-June, and to talk to some UK research funders about the possibility of using prediction markets to help inform funding decisions, so we will see what happens then.

@Elizabeth unfortunately, yes. There are a couple of ways around this:

1) decide "we're going to be an offshore gambling platform", grit my teeth, and go with the fairly tough but doable process of getting a gambling license or applying to be on someone else's gambling license; doesn't work for the US, means a greater focus on targeting non-US markets (e.g. Canada)

2) if you have an organization stump up a cash pool first and then participants in the org can bet, this has fewer legal difficulties (specifically, it doesn't count as gambling any more), but you also have a product aimed at organizations rather than individuals (internal prediction markets do seem to work where they've been tried, though!)

@adityaarpitha Thank you so much!

@astrosnat OK I have my little update from a brief call with Marcel. Some thoughts:
- My understanding is that part of the bottleneck is that the intersection between "makes news headlines" and "has enough people forecasting/has enough liquidity in the market" can be smaller than ideal
- Integration between metaforecast + seeing what people are talking about on social media is not easy

IMO these are solvable problems. So looking forward to seeing where BRT goes in the future

@saulmunn Hi Saul - how did your meeting with Marcel go? Would be interested in hearing your thoughts about BRT

More thoughts from me:

• BRT is really interesting, and I want to see + learn more

• I also booked a call with Marcel on March 13, and will update

@PatrickDelaney Awesome stuff, just checked it out now! Yes, let's talk more. My email is osnatkatz at protonmail dot com