DeFi runs on human reaction time. Traders scan charts, track liquidity, and execute on instinct. Even automated strategies reset with every transaction, relying on human intervention to adapt.
The Roman Emperor Marcus Aurelius wrote, “The impediment to action advances action, what stands in the way becomes the way.” In DeFi, the lack of onchain memory has been the obstacle—strategies remain disconnected, reactive, and blind to past decisions. But the solution isn’t just to work around it. It’s to make that limitation the reason for progress.
AI is growing fast, but it’s also growing fragmented. The most powerful AI systems today are resource-constrained, limited by the APIs they can access, the accounts they can verify, and the compute power they can afford. Each AI agent exists in isolation, forced to build and maintain its own expensive set of tools.
“Give me a place to stand, and I will move the Earth.”
— Archimedes, describing Irys
In ancient Greece, Archimedes believed that with the right lever and the right fulcrum, he could move anything. It was a physics problem. But the principle holds in finance, too.
You’ve probably seen the number: 82% test coverage.
And thought, Nice. We’re covered.
But here’s the thing, high coverage doesn’t always mean high confidence.
You could be hitting a bunch of lines with zero meaningful assertions. Or worse, missing critical paths entirely while your report still looks green.
It’s 4 PM on Friday and your dev team just pushed a feature update and you are staring at a pull request with 30+ comments just trying to figure out that one conditional statement is a bug or just a coding choice. Sounds like a horror movie?
Today we’re proud to announce that Perplexity will integrate sovereign European AI models into our answer engine, bringing locally-optimized, culturally-aware AI to users worldwide while supporting Europe’s digital sovereignty initiatives.
Speculative decoding speeds up the generation speed of Large Language Models (LLMs) by using a quick and small draft model to produce completion candidates that are verified by the larger target model. Under this scheme, instead of a run of the expensive target producing a single token, multiple are emitted in a single step. Here we present the implementation details of various kinds of speculative decoding, applied at Perplexity to reduce inter-token latency on Sonar models.
We’re thrilled to partner with NODO, a multichain AI-powered yield generation layer supported by the Sui Hydropower Accelerator, to integrate intelligent capital deployment capabilities into the Talus ecosystem. This collaboration represents a significant advancement in AI agent autonomy, enabling Talus Agents to manage and optimize liquidity strategies with unprecedented precision and independence.
“Transforming Healthcare Data into Clear Decisions”
TL;DR: Healthcare organizations are drowning in dashboards they can’t act on – or worse, flying blind because they lack the resources. Kaelio unifies clinical, operational, and financial data for hospitals, health systems, and health plans – giving them an AI copilot that answers business-critical questions, flags operational risks, and recommends actions to improve clinical outcomes and financial performance. They are currently onboarding their first customers.
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