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Anthropic study reveals it's actually even easier to poison LLM training data than first thought

Claude-creator Anthropic has found that it's actually easier to 'poison' Large Language Models than previously thought. In a recent blog post, Anthropic explains that as few as "250 malicious ...
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 ...
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 ...
Futurism

If Even 0.001 Percent of an AI’s Training Data Is Misinformation, the Whole Thing Becomes Compromised, Scientists Find

It’s no secret that large language models (LLMs) like the ones that power popular chatbots like ChatGPT are surprisingly fallible. Even the most advanced ones still have a nagging tendency to contort ...
Digi Times

AI poisoning: Anthropic study finds just 250 malicious files can compromise the largest LLMs

Contrary to long-held beliefs that attacking or contaminating large language models (LLMs) requires enormous volumes of malicious data, new research from AI startup Anthropic, conducted in ...
Science X Network

Theoretical Framework for LLM Data Markets Addresses Current Ethical, Societal Challenges

Science X is a network of high quality websites with most complete and comprehensive daily coverage of the full sweep of science, technology, and medicine news ...
Forbes

What Happens When LLM’s Run Out Of Useful Data?

Most of us feel like we’re drowning in data. And yet, in the world of generative AI, a looming data shortage is keeping some researchers up at night. GenAI is unquestionably a technology whose ...
VentureBeat

LiveBench is an open LLM benchmark that uses contamination-free test data and objective scoring

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 A team of Abacus.AI, New York University, ...