Today @MeckaAI is announcing $60M in funding to become the data and deployment layer for physical AI
This raise will allow us to scale our data infrastructure, invest into new verticals, and deploy robots into the real world
Introducing THEA, the most advanced prediction AI for Risk Markets on @Solana
We’ve spent the past decade building the most powerful behavioral and predictive AI to amplify human performance in volatile environments. Today marks the beginning of THEA’s journey on-chain, tokenizing AI infrastructure with ecosystem applications generating over $100,000,000 annually, serving 3,000+ clients across 30+ countries.
🧵Let’s dive in
Mecka is excited to power EgoVerse: a growing ecosystem for robot learning from egocentric human data
Proven across 4 leading research labs, EgoVerse data consistently boosts robot performance
We release the tools for anyone to collect data, inference/train, and contribute! 🧵
We’re hiring across hardware, software and operations to build the data layer for Physical AI.
Roles across Toronto/NYC/Shenzhen.
Some of our roles:
- Senior Full Stack Engineer
- Computer Vision Engineer
- ML engineer
- VLA & LLM Engineers
- Robotocists
We’ve got some of the best customers in the world and get to glimpse into the future… Come join us to build on the frontier!
Apply below or send a DM of anything of extraordinary talent you’ve built.
https://t.co/6icvJE5q1F
Think the larger issue is RL doesn’t do too great with sparse, noisy, or delayed rewards; that is sort of the default you have in markets. Applying these highly parametrized models to markets with the expectation money will pop out seems to be a fetish nearly every new entrants has, I don’t know why
Research is never a linear process. It is usually a zig-zag of many failures and few successes but in the successes you find the highest highs; immediately followed by "can it be improved?". Below you can see an annotated version of this from a research project I had during my studies
Excited to announce our $8M seed round led by @neo to further our work as the data layer for robotics
Heres why we bet early on human data advancing autonomous robotics:
Socially probably adds a lot of noise, but for specific solo tasks I agree it is a multiplier; that is if you can trust the output. Analog to this is someone who knew how to “google” for information early on, they were much more efficient at their tasks. Same for these gpt tools, there are better ways to prompt that produce significantly higher quality results. With the added benefit that these tools can do additional aggregation and processing of the retrieved information.
if you value anonymity, I'd be cautious of how you claim $PENGU
their public API returns all linked eth wallets of the solana claim
you can go to https://t.co/QQeqtkPA8O
and see which eth wallets were linked to each claim
(not FUD just a headsup)