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. …
The HPC gurus of the world may have started moving into the hyperscalers and cloud builders in recent years, but they don’t tend to work for vendors and they tend to stay in one place and lean in. …
One of the first tenets of machine learning, which is a very precise kind of data analytics and statistical analysis, is that more data beats a better algorithm every time. …
When it comes to building any platform, the hardware is the easiest part and, for many of us, the fun part. …
Most of the large companies and institutions we cover here at The Next Platform have already been in the AI/ML trenches, particularly the hyperscale web and media companies (where much of this work began) and in high performance computing. …
While Hungarian banks with collective names like OTP Group might not have household recognition here in the U.S., …
When we hear about the massive GPT-3 language model, it is natural to assume it is open source and ready for the taking. …
Argonne National Laboratory has become a must-watch lab for those following the convergence of supercomputing and AI/ML. …
We knew the day would come when an AI chip startup hit the $1 billion funding mark and so it has. …
For neural networks to expand into more areas in traditional supercomputing, especially in areas where image data is key, high image fidelity and accuracy are critical. …
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