Next stop for CEO Forum Blockchain and AI for Good - Young Talent Edition: @UniofOxford | March 28
You will hear from:
🎙️ @0x7SUN, founder & CEO of FLock, and University of Oxford alumnus.
🎙️ @helen_abfinance, founder of @abf_finance and @ChainforGood, former co-CEO of @Bybit_Official
Join us for builder insights, explore what’s pushing the edge of blockchain and AI, and connect with the FLock & BGA teams.
In collaboration with Oxford CSSA.
If you're in town this Saturday, come through👇
It's official: CEO Forum - Blockchain and AI for Good: Young Talent Edition is coming to @imperialcollege | March 25
Insider talks from founders and professors who are building and working at the intersection of blockchain and AI.
📢 Speakers:
@0x7SUN, founder & CEO of FLock
@helen_abfinance, founder of @abf_finance and @ChainforGood, former co-CEO of @Bybit_Official
Ying-Ying Hsieh, assistant professor of Innovation and Entrepreneurship; Associate Centre Director, Imperial College Centre for Cryptocurrency Research and Engineering, @imperialcollege.
If you're a student, builder, or just deeply curious about where purpose-driven tech is heading, this is your invite 🇬🇧
Sybil resistance + reputation + freezing/slashing behavior. They explicitly require "sybil-resistant" reputation systems and describe enforcement actions that look like protocol-level sanctions: revoking credentials, freezing staked assets, and flagging transaction history for forensic review. "Sybil-resistant" is also a very crypto-native vocabulary, and the enforcement mechanism mirrors how many protocols think about identity/reputation under adversarial duplication.
That's also what FLock is building.
😀Good to know decent teams working together.
HashKey is now officially a public company on @HKEXGroup! A meaningful step toward making digital assets massively accessible.
The ticker is https://t.co/mVfdXgaNZB.
WE'RE HIRING!
Just a "casual" job opening at the University of Oxford.
Open Post-doctoral role in Decentralized AI, in collaboration with https://t.co/YkoQx8t9ue.
Building the future of AI isn't about hype; it's about science.
Apply by December 12, 2025. Details below.
🏆 We are incredibly honored to announce that our paper, "Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free" has received the NeurIPS 2025 Best Paper Award!
A huge congratulations to our dedicated research team for pushing the boundaries of AI.
Read more: https://t.co/qu3ERa3pH5
Great honor to introduce FLock at University of Cambridge. Good to meet Mr. Xiao Li from Embassy of the
PRC in the Uk. Dr. Julian Huppert from Jesus College, Univ of Cambridge. Prof. Pietro Lió from Department of CST, University of Cambridge. And all fellow scholars.
Actually not everyone noticed that we we ranked at 6th at Task 1 (where actually is most relevant to real prediction task in platform like Polymarket) with a 20B level of LLM. 20B model, I can completely ran on my own MacBook Pro. GPT5 is impressive, and they also knew the every bet.
FLock’s AI prediction model ranked Top 6 on FutureX, outperforming multiple 70B-400B+ models.
We’re also the only Web3 team in the global top 10.
Our approach uses a lightweight 20B open-source model, trained end-to-end on FLock’s stack: federated training, reinforcement learning, and our Edge Agent framework, while other models run on massive 70B-400B+ parameter bases.
This week, it ranked #6 on the FutureX leaderboard, competing with some of the most advanced AI models in the world, and ranked ahead of several of them in overall prediction performance.
- GPT-5 variants
- Alibaba Qwen3-235B
- Kimi-k2 (Moonshot)
- ChatGPT-Agent
- Grok-4 (Peking University)
- DeepSeek
- Tencent Hunyuan
- Gemini 2.5 Pro
- xAI Agents
… and more
What makes this special is not the rank alone, but how it was achieved.
While most leading models rely on massive parameter scales, our 20B model shows how efficient training, a strong data strategy, and decentralized compute can deliver competitive performance.
FutureX is the industry’s leading benchmark for real-world future prediction, evaluating models on their ability to predict upcoming financial, social, and economic events. This is exactly the capabilities needed for next-gen prediction models.
Our result proves that:
- Smaller models can outperform massive ones when trained right
- Decentralized AI pipelines can deliver state-of-the-art results
- Open-source foundations can compete with big proprietary labs
- FLock is the only decentralized AI team to make the list
We believe AI will change how finance and trading work. That’s why we’re focused on building the infrastructure for that future-prediction model, robust federated training network, and a decentralized network for model assets.
Highlights from the Blockchain Impact Forum in Copenhagen. 🇩🇰
Co-hosted by @UNDP AltFinLab and @ChainforGood, this is a global event bringing together leaders building blockchain for impact.
The FLock team joined key sessions throughout the event. 🧵
: : [Report] https://t.co/kKHasq9pRE: The Base Layer for AI Democratization
Written by @JayLovesPotato
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https://t.co/ABwgjeS6nI
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The current AI industry lacks transparency and trust throughout the lifecycle of AI model development. Additionally, high entry barriers limit the expansion of AI applications across various industries.
To address these challenges, federated learning adopts an approach where models are distributed to local clients for independent training. Only the trained parameters are aggregated to update the global model. This method holds significant potential for reducing the overall cost of developing global models and minimizing the exposure of sensitive personal data, thereby greatly enhancing usability.
However, federated learning also faces its own limitations. Key challenges include the difficulty of recruiting a sufficiently diverse and honest pool of participants for model training and the reliance on centralized servers for certain operational tasks.
https://t.co/kKHasq9pRE aims to overcome these limitations by integrating various blockchain elements with federated learning methodologies. Its ultimate goal is to democratize the entire AI model lifecycle—from data collection and model proposal to training and application—paving the way for a more creative and trustworthy AI industry.
▫️ The Current State of the AI Industry Requires Structural Transformation
▫️ Federated Learning as an Alternative to Centralized AI Development
▫️ https://t.co/kKHasq9pRE: The Next-Generation Federated Learning Platform Powered by Blockchain Architecture
▫️ Democratizing AI in an Era Where Personalization Ruins Personalization
Learn about the diverse digital assets we’re considering for future investment products and explore those already part of our offerings in our latest Assets Under Consideration update. Are we missing anything? 🤔
Read the full report: https://t.co/Tr5lU1CSSQ
Thx @UNDP for the invitation.
Heard great things about blockchain strategic board discussions with FLock’s epic representatives @YifanX and @sameeha_rehman
More initiatives to come, lots of “the 1st in the world” to be built by @flock_io
Stay FLocked.
It’s an honor for https://t.co/evQHqjcMLM to be a part of the High-Level Strategic Dialogue on Blockchain for Development with @UNDP at UNDP Headquarters in New York City today.
Today’s dialogue was a critical first step in exploring how blockchain can create impact for people and the planet, with its unique features — trust, transparency, traceability, and accountability — at the centre.
Together with UNDP and industry-leading blockchain leaders, we developed a shared vision for how responsible and inclusive blockchain innovation can advance the SDGs, and explored pathways for future collaboration, including the potential establishment of a Blockchain Advisory Group.
FLock everywhere.