What is iPhone?

Liquid AI's Apollo App runs a 1B parameter hybrid attention plus gated convolution model on-device on an iPhone for private local data search and classification.

“Even a 1 billion parameter model, which combines a small number of attention layers with a very simple gated learned convolution, while admittedly far from the frontier, can run fast enough on an iPhone to be a real option for basic use cases such as privately searching through and classifying one's own local.”

Joseph Krause on the hard limits of current AI in materials science, from hypothesis to finished consumer product.

“What I don't think you can do is go from like I have this new hypothesis to oh my gosh I have a new material it's scaled it's done it's in products in your iPhone you can't do that today.”

No single AI model can one-shot a new material into a real consumer product such as an iPhone or SpaceX Starship, challenging hype around foundation models for materials science.

“There is no one model that can oneshot a new material that ends up in your iPhone or that ends up on Starship. That's just not the way materials work.”

There is roughly an 18-month lag between a cutting-edge multimodal cloud model capability and being able to run that same capability on an edge device such as a Jetson Orin or iPhone.

“I see maybe an 18-month delay between like a soda capability from multimodal cloud available model to something that you can get to run on an edge device.”