// MIT TECH REVIEW — INTELLIGENZA ARTIFICIALE
The Download: climate tech companies to watch and AI’s discovery problem
Plus: OpenAI has scrapped a new AI model over safety concerns.
This is today's edition of The Download, our weekday newsletter that provides a daily dose of what's going on in the world of technology.
With the planet nearing 1.5 °C of warming, climate policies being unraveled, and Big Tech backpedaling on its climate ambitions, it can be tempting to give in to climate doom and defeatism. But despite the headwinds, the world has still made incredible progress. That’s why MIT Technology Review publishes its annual list of Climate Tech Companies to Watch.
Once a year, we compile a list of 10 companies that we believe have done the most, or have the best chance, to make a real dent in emissions or improve public safety and health. We’ve now finalized our 2026 list and will publish it on October 6.
It features companies making strides in energy storage, nuclear power, transportation and other areas despite today’s regressive climate politics. We hope you’ll enjoy the package and perhaps come away feeling a bit more hopeful about our climate’s future. Here’s what to expect.
Subscribe to receive full access to this year’s list, and keep reading The Download to be among the first to see it.
Last week, Anthropic announced that its new molecular biology lab had made its first discovery: its AI agents had flagged a previously uncatalogued pattern surrounding an enzyme, a pattern “reminiscent” of what led to the gene-editing technology CRISPR. But the claims angered biologists.
Some questioned whether merely finding the pattern amounted to a discovery at all. Another said his team had already discovered the same pattern, raising questions about whether Anthropic’s system had learned from his conversations with Claude.
It’s a reminder that what’s novel for AI may be routine, unsurprising or simply not that consequential to a biologist. And the grand claims could make real progress harder to recognize.
Find out why AI companies may be setting the wrong bar for scientific discovery.