bcroesch
Joined 16 years ago
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Comment · 1 year ago
Comment · 9 years ago
Another Cultivate Labs person here. You're absolutely right re: predicting stock prices. A prediction market isn't going to beat the market consistently. People looking for that use case end up disappointed.
Prediction markets are more valuable to companies for things where there isn't already a large, liquid source of information flow. E.g. all the on-the-ground workers know a project is going to be late, but no one speaks up due to fear/office politics. Management thinks all is well since no one said otherwise.
A PM is an effective way of taking a bunch of siloed information/knowledge (in employee's brains), aggregating it, and presenting it to decision makers.
Comment · 11 years ago
Kinda depends on which platform you were on (GJP used several). Some were prediction markets while some were opinion pools, both of which are scored/rewarded differently.
Our company (Cultivate Labs) recently acquired Inkling Markets (a very early YC company that built prediction market software) and have been building a new version of the PM platform, which will hopefully address some of the risk/reward quirks.
If you're interested in this stuff, you might be interested in the two topical PM sites we're launching: -https://sportscast.cultivateforecasts.com/ (obviously focused on sports) -https://alphacast.cultivateforecasts.com/ (officially launching later this week, focused on global finance, politics, & tech).
Comment · 11 years ago
There was an article in NPR a while back about the Good Judgment Project (which was run by Dr. Tetlock - mentioned in the article). In some cases, betting/prediction markets (& other similar tools) were beating intelligence analysts - http://www.npr.org/sections/parallels/2014/04/02/297839429/-...
Comment · 11 years ago
For anyone who is interested in this topic, Dr. Tetlock just released a new book about it (http://www.amazon.com/Superforecasting-The-Art-Science-Predi...).
We're also hosting a public forecasting tournament for him and his team that focuses on geo-political forecasting: https://www.gjopen.com/
For anyone not familiar, Raif is a Rails engine for building LLM powered apps. Highlights include: - adapters for various LLM providers - high-level abstractions/models for working with LLM's (Raif::Task for single-shot tasks, Raif::Conversation for chat interfaces, and Raif::Agent for building agentic features) - web admin for viewing/debugging LLM requests/responses
v1.1.0 highlights include: - Support for images and files/PDF's in Raif::Task's - Embedding generation - OpenRouter, GPT-4.1, and Claude 4 support - Stats section in the web admin - Automatic retries for LLM requests that resulted in server errors
Full changelog is here: https://github.com/CultivateLabs/raif/blob/main/CHANGELOG.md