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
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.
When a chatbot types out its answer word by word, the speed you see is often limited by how fast a chip can move data, not by how fast it can calculate. That is why memory bandwidth has become one of the most important specifications in AI hardware.
Every token needs the whole model
Language models generate text one token at a time. For each new token, the chip has to read the model's weights, often billions of numbers, from memory into its compute units. For a single user, the math performed on each weight is small. As a result, the processor spends much of its time waiting for data to arrive.
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