
It's the data, stupid.
A biotech startup argues that AI drug discovery has a fundamental problem: existing AI models lack the kind of biological data needed to meaningfully advance medicine, instead relying on animal testing or studies of isolated cells rather than living human tissue. The startup has built robotic laboratory systems that can grow multiple types of human tissue, automatically test drug candidates on them, and generate data about how drugs affect actual human biology, which the company says is essential for training AI models that truly understand human biological processes. This matters because many AI leaders have made bold claims about AI curing cancer, but actual progress has been limited, with most drugs that succeed in animal testing still failing in human trials. The startup's approach represents a different strategy: using better biological data to train AI models and to predict drug effectiveness before expensive human clinical trials begin.

Millions have downloaded Meta’s AI agent Muse. But getting it to do your bidding comes with privacy costs.

We created a list of the most notable AI agents that can live in your text messages, from general assistants to agents designed for families, travel, and work.

TL;DR: Meta’s Muse, OpenAI’s Dots and Uber’s driver assistant share one bet: the agent speaks first. That moves the hard problem from what to answer to when to interrupt, on which channel, and with what offer. Classic ML and new decision models can solve it. Three launches, one pattern Meta Muse (Sept 8). A personal agent that books, emails and keeps working with the app closed. It remembers details, makes unprompted suggestions and checks in for approval, in its own ap
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