TechCrunch

Refining pre- and post-training data strategy for LLM success

TechCrunch was proud to host TELUS Digital at Disrupt 2024 in San Francisco. Here’s an overview of their Roundtable session. Large language models (LLMs) have revolutionized AI, but their success ...
NextBigFuture

AI LLM Improvement Rate Slows on Pre-training but Memory and Actions Make AI More Useful

Super Venture Capitalists Bill Gurley and Brad Gerstner analyze the future of AI. The rate of improvement of large language models is slowing for pre-training. However, it is still improving and AI ...
Ars Technica

Researchers show that training on “junk data” can lead to LLM “brain rot”

On the surface, it seems obvious that training an LLM with “high quality” data will lead to better performance than feeding it any old “low quality” junk you can find. Now, a group of researchers is ...
NextBigFuture

Test Time Training Will Take LLM AI to the Next Level

MIT researchers achieved 61.9% on ARC tasks by updating model parameters during inference. Is this key to AGI? We might reach the 85% AGI doorstep by scaling and integrating it with COT (Chain of ...
VentureBeat

ServiceNow open sources Fast-LLM in a bid to help enterprises train AI models 20% quicker

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Training a large language model (LLM) is ...
Hosted on MSN

9 reasons why you should consider onsite LLM training and inferencing

Running large language models at the enterprise level often means sending prompts and data to a managed service in the cloud, much like with consumer use cases. This has worked in the past because ...
VentureBeat

Nvidia researchers unlock 4-bit LLM training that matches 8-bit performance

Researchers at Nvidia have developed a novel approach to train large language models (LLMs) in 4-bit quantized format while maintaining their stability and accuracy at the level of high-precision ...