Allo has partnered with @STP_Network to power AI-driven Autonomous Worlds with AWE.
Together, we’ll simulate tokenized economies and empower AI agents to optimize governance—all onchain.
🎮 Gmicrochains. We're kicking off our Game on Microchains Challenge!
Build a game on Linera’s Testnet for a chance to win 50,000 XP and more.
Here's how to enter 🧵👇
Onchain stocks and cryptocurrencies are often compared, but they differ in purpose and structure.
Onchain stocks offer equity in real assets, unlike crypto’s volatile value. As of March 2025, tokenized RWAs hit $18.86B, up from $8.3B in 2024.
⚛️ Last month, we announced our partnership with @Atoma_Network to bring decentralized AI to Linera.
Now, we have a deeper technical explainer on how Atoma’s AI inference works on Linera’s microchains.
Let's go. 👇🧵
https://t.co/QwvgAsVEoe
Imagine funds managed by AI agents that learn, adapt, and optimize in real-time.
The future of fund management is here—fusing technology with market insights to unlock value like never before.
Private markets are at an inflection point.
To move forward, we need to invest in the underlying systems that make participation easier, safer, and more efficient.
Projections suggest that by 2025, retail investor participation in tokenized assets could increase by 20-30%, while institutional investors are expected to provide 70% of secondary market liquidity.
This means that retail investors will soon have unprecedented access to diversified, tokenized assets, while institutional players bolster market stability and liquidity. We're on the cusp of a financial revolution where democratized investing meets robust, deep-rooted market support.
As we move towards a more digital economy, developing infrastructure that can handle the complexities of onchain transactions is essential.
This requires a deep understanding of the intersection of technology and finance, as well as the development of robust infrastructure that can support the needs of all participants.
Yesterday, @openAI shared the latest Model Spec based on feedback they've received and their own research. It emphasises customisability, transparency, and intellectual freedom, aiming to guide AI behavior in handling complex topics. This is another step towards building AI systems that are more adaptable, open, and aligned with diverse human perspectives—moving beyond rigid constraints to enable deeper reasoning and informed decision-making.