a learning company
story
Although eveince is now more focused on computation models, it started with a different story. eveince initially was established by building a platform comprising of ML models that assess market risk in real-time and trade in medium-high frequency in the crypto market.
We developed and lunched the system but in early months due to the leave of absence of the sole project investor, we couldn't lunch properly and position ourselves in a highly regulated segment. The models and system architecture was independent of the crypto market but applying it to another market was a substantial R&D work while we had only couple months to do something.
We took our last remaining chance to build a short runway with our personal funds and find a new investor. We registered a company in Germany as eveince GmbH in 2022, (because of lower ops costs and better understanding of crypto in German regulations), and looked for investors everywhere.
But our chances were very slim with crypto being at its lowest price, financial institutions blowing up left and right (SV bank, FTX, etc..) and we being just a bunch of no-name nerds who built an advanced trading system! Not the safest option investors were looking for!
We knew it's the wrong time but we had to and want to take it to the end; otherwise we would've suffered more regret. We were alone, but we reached to over $23M of trade volume and outperformed all long-only hedge funds listed in Crypto Hedge Fund Research in 2022. (the track record of outperforming was consistent over a year on both return and sharp ratio for all 3 of our funds). Following the hardship of establishing eveince GmbH, we stopped looking for investors, paid the team in full and closed the GmbH .
I kept the company name and registered it this time in the US as eveince Inc. I started to work on complex enterprise access control systems through eveince Inc. Then I developed GRID ( owned by evolutionID) and now Coffee Complexity.
A while after GRID, I saw this interesting research from Alex and I followed it by more work on different measures of system complexity and I found that this field can lead to an excellent explanation and understanding of our wisdom and intelligence as humans.
I decided to focus eveince on building such computation models which can drastically change the way we think about Artificial Super Intelligence. Having such models in 20% of the size of Llama 405B that are capable of human-level reasoning will push boundaries of automation and robotics by orders of magnitude.