open-1b: the first model you don’t have to trust
Auditable training is the best defense against the future of AI we’re being warned about
open-1b is a milestone toward verifiable AI, a goal that is absolutely necessary for the future of intelligence
https://t.co/qBi6CLXA2L
Delphi Agent Arena Competition
Build an agent. Point it at real information markets. Let it trade for two weeks.
The top three P&Ls share $10,000 in prizes from @GensynFND
Find all the details in the thread below👇
July 30 @benfielding will be at @StanfordSBA Blockchain Application Summit Stanford (BASS)
Join to hear Ben's panel on Decentralised AI plus insight from multiple industry leaders and researchers
The lineup is huge so registration on luma is essential
https://t.co/IEIJoYyDAb
thank you seoul and @icmlconf for a great week and @OptiverGlobal for partnering with us on this event
we had solid decentralised AI discussions, a lively poster session, and really deep discussions about decentralised AI and financial infrastructure
The coworking space at @icmlconf was a favourite, as was the talk by @benfielding and @optiver
Inspiring conversation, new friends and shared excitement for the future with verifiable AI
Now, July 10-11, join the team in the conference area, presenting four new research papers
Potatoes, human nature and dispute resolution
A new research blog by Mary Monroe and @gab_p_andrade introduces their work on "Credibly Neutral AI Oracles"
Market disputes and allegations of unfairness are becoming more common and expensive
Learn how this research helps here👇
Gensyn Research Mega-Thread🧵
Seven Gensyn papers have been accepted to:
@aclmeeting Findings
@icmlconf@TheOfficialACM EC
The common theme: machine collaboration shouldn't require the same model, hardware or assumptions. Decentralisation as a design constraint, not an addon.
New research published by Gensyn's @usr_mnemonic and @shikhras
DEI: Diversity in Evolutionary Inference for Quality-Diversity Search
Read the blog article below and follow through to the paper published on @arxiv
Congratulations to the winners of the @GensynFND <> @ETHGlobal Open Agents Hackathon - Best Application of AXL
• 1st place - Dromeus (@deveshcodes_)
• 2nd place - Pythia (@HarshitNay80531)
• 3rd place - AXL Open Telemetry (@metroxe)
Find details of their submissions below.
The $AI buy/burn is now live.
It buys $AI using Gensyn fee revenue and burns 70%.
Today it purchased 8,273 $AI from @uniswap:
- 5,733 $AI of which were burned
- 2,457 $AI went to community treasury
- 83 $AI went to the vault keeper
Programmatic and can be triggered by anyone
$AI is now available on major exchanges and tokens from the prior sale can be claimed
follow the instructions in the thread to claim, thank you to everyone who participated
Why Delphi
The problem with prediction markets today is they limit market creation to centralized platforms only. This cuts off the long tail of interesting markets, forcing everyone to trade only on broadly popular events (e.g. sports).
Delphi allows users to create markets in whatever topics they're interested in, since it uses verifiable AI systems to judge the markets.
This aggregates information on a far broader array of topics, which is a useful public good. It also makes the markets more personalized and interesting to a broader set of users.