For Mark Zuckerberg, the decision by Meta Platforms – and way back when it was still known as Facebook – to open much of its technology – including server and storage designs, datacenter designs, and most recently its Llama AI large language models – came about because the company often found itself trailing competitors when it came to deploying advanced technologies. …
A scant three months ago, when Meta Platforms released the Llama 3 AI model in 8B and 70B versions, which correspond to the billions of parameters they can span, we asked the question we ask of every open source tool or platform since the dawn of Linux: Who’s going to profit from it and how are they going to do it? …
If you handle hundreds of trillions of AI model executions per day, and are going to change that by one or two orders of magnitude as GenAI goes mainstream, you are going to need GPUs. …
If you have the entire corpus of the Internet scrubbed of nonsense plus whatever else you can scrounge up in whatever language all put into the right format so you can chew on that data one token at a time with trillions of parameters of interconnections between those tokens to build a large language model for generative AI applications, you have an enormous problem. …
We learn a lot of lessons from the hyperscalers and HPC centers of the world, and one of them is that those who control their own software control their own fates. …
Large language models, also known as AI foundation models and part of a broader category of AI transformer models, have been growing at an exponential pace in terms of the number of parameters they can process and the amount of compute and memory bandwidth capacity they require. …
All Content Copyright The Next Platform