- I've seen neural nets using int8 for matrix multiplication
to reduce memory size [1]. Do you think something similar could be useful in the ANN space?
- Do you know of any studies using Faiss looking at speed/cost tradeoffs of RAM vs flash vs Disk for storage?
- Are there recommended ways to update Faiss index with streaming data, e.g. updating the vectors continuously?
Seems like more and more use cases for Faiss as neural nets become more and more core to workflows. Would like to try and figure out the configurations that are optimized to minimize carbon usage in addition to latency and recall metrics.
Definitely not unusual. I think it is pretty common for executive team in addition to founders. My feeling is that VCs and founders need to find a way to partially cash out rank and file employees along the way if they want start up model to succeed long term. Many senior engineers are reluctant to to join startups at this point as even if startup is successful it can be a long time before they have the money in their pocket. Employees at Reddit, Stripe, Instacart, Databricks, and many others have been waiting over a decade for company success to hit their wallet.
Sometimes the executive team gets stock options rather than RSUs so they own the stock and can sell to secondary parties. VCs and founders would like them to sell to known parties rather than sell on private market (Facebook crossing 500 investors threshold was one important reason for IPO timing [1]).
Sam has already helped you indirectly by investing in reddit which has all sorts of community sourced help. Check out PeaceH guide to getting discipline[1]
Could you comment on why start ups with remote teams anecdotally do poorly but many open source projects with very remote teams succeed? Do you see any tools on the horizon to help people coordinate remotely at a new level?