What progress have you made since your last update?

We're now on v0.0.4, with an improved UI and security fixes: https://github.com/openpredictionmarkets/socialpredict

We also reached 100 stars on GitHub, which qualifies us for free hosting credits on Digital Ocean. This is a huge step forward for us.

What are your next steps?

Going forward we want to streamline our registration flow and mobile experience, as well as push releases more frequently.

Is there anything others could help you with?

Yes! We need help streamlining and improving our positions math for the last bettor: https://github.com/openpredictionmarkets/socialpredict/issues/499

We'd also love to talk to people who work in forecasting for business and education about your pain points, as our goal is to make something broadly useful.

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!

Thanks @FranklinBaldo for your contribution!

Thanks @such for your contribution!

Thanks @marktwse for your contribution!

I’ve spent much more money on things that are sillier and of less value than this, a scientific endeavor that would be something good and worthwhile. Good luck!

Thanks @NunoSempere for pushing us over the $1000 mark!!! Awesome.

Love seeing more prediction markets!

Contingency planning in case Manifold goes under one day.

Nice to see this project is still going, I haven’t heard much about it recently.

Some questions:

• Does https://brierfoxforecast.com/ represent the current state of development? Are there any other currently-active instances?

• What’s the advantage to running an independent instance? Why would a small group go through the trouble to run an instance instead of using an already-established server?

• Do you have any changes to market structure or feature set planned to differentiate you from competitors? Are you implementing the same AMM used by Manifold?

• If the application is intended to be run locally, have you tested the resource usage for a typical instance? Could it run from, say, a laptop or home computer? What size is the DigitalOcean server used for the demo instance?

Let's go! :)

Awesome!