Top Tweets for #Agrs

Agreed. Probabilistic generation needs deterministic guarantees. What's underexplored: specification languages that are directly executable. Then you're not proving an AI-generated implementation against a spec; you're running the spec itself. The translation problem disappears. https://t.co/nKCN9X2BWp

This tweet is +1y old, but I've said it for much longer. ChatGPT came years ago, and "AI" is still more or less the same. Against all "expert" predictions, it didn't cure cancer, it didn't colonize Mars, it didn't discover new physics, it didn't really improve much. Because I was right all along: machine learning is around its peak, and it is a huge bubble. Nowadays it's obvious, but back then I was a single voice against the whole world. Not only that machine learning is fundamentally incapable of logical reasoning, but the architecture of those giant data centers, is also incapable of logical reasoning. And I keep telling you: the real deal is Logical AI, and we are the leaders of this segment. Machine learning is only for translation.

The AI programming shift is happening, and it's bigger than prompts or LLMs. Across the industry, a new truth is setting in: the most critical aspect of software dev used to be writing code; now, it's about conveying intent accurately in specifications. Tau Net and $AGRS lead, featuring breakthroughs in formal verification and reactive synthesis that enable user readable specifications to be executable for dapps and autonomous system design. Specifications are becoming the new norm in AI coding practices and Tau makes them executable.