Much of the attention in AI drug discovery goes to models that design molecules from scratch. Enveda starts somewhere else: with the chemistry that plants and microbes have already produced.
Investors have now backed that approach with more money. The biotech startup has raised a $311 million Series E at a $2 billion valuation. Catalio Capital Management led the round, and Iconiq was among the other participants. The new valuation is double the one Enveda reached 12 months ago.
Nature as the starting library
Conventional drug discovery often means building a compound in the lab and then testing whether it does anything useful. Enveda's premise is that many powerful medicines may already exist in plants and microbes, waiting to be found and put to use.
Most talk about AI on phones has so far centred on the chatbot: a box you type into, an answer that comes back. That works for looking up facts. It is less useful for someone whose train has been cancelled and who now needs to rebook the journey, move a meeting and tell a friend they will be late.
That is the kind of problem Alibaba is aiming at with Qwen Intelligence. It is not a single app you download. It is a platform that smartphone makers can build into their own system assistants, so its AI functions sit inside the phone rather than on top of it. The stated goals are practical: replanning trips, adjusting appointments and creating images.
The AI industry has mostly measured progress by size: more parameters, more data centres, more compute. That makes sense for a frontier lab. It makes less sense for a pair of glasses that has to answer a simple question: what am I looking at right now?
PrismML is building for the second case. The AI lab was founded by researchers from Caltech and counts UC Berkeley's Ion Stoica among its advisers. It has now produced a version of its compact language models for smart glasses that run on Qualcomm's Snapdragon chips.
From the data centre to the frame: what Qualcomm showed at Snapdragon Summit
Most safety checks on frontier AI models have so far been brief. An outside group gets access shortly before launch, runs its tests, and the model ships. That approach can catch obvious problems. It is less useful for judging whether a company's safety claims hold up across training, testing and real-world deployment.
OpenAI now wants to change that picture. In a framework titled "Priorities and principles for effective third party assessments," the company sets out how independent reviewers could get far deeper access to the way its models are built, evaluated and used. The idea is that assessors verify safety claims themselves rather than taking the company's word for it, and form their own view on whether safeguards actually work.
The push to build more AI capacity has mostly been a story about land, power lines and cooling on the ground. Google is now testing a different route: taking part of that infrastructure off the planet altogether.
The company's project is called "Suncatcher". The idea is to run AI computing in orbit and power it with solar energy rather than a terrestrial grid. It is an early-stage effort, and the first hardware is about to leave the ground.
A fridge-sized first step
According to The New York Times, Google's first experimental satellite, named "MVP", is scheduled to launch on 1 October. It will fly on a SpaceX Falcon 9 rocket from Vandenberg Space Force Base in California.
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