Galactica was supposed to help scientists. Instead, it mindlessly spat out biased and incorrect nonsense.

On November 15 Meta unveiled a new large language model called Galactica, designed to assist scientists. But instead of landing with the big bang Meta hoped for, Galactica has died with a whimper after three days of intense criticism. Yesterday the company took down the public demo that it had encouraged everyone to try out.

Meta’s misstep—and its hubris—show once again that Big Tech has a blind spot about the severe limitations of large language models. There is a large body of research that highlights the flaws of this technology, including its tendencies to reproduce prejudice and assert falsehoods as facts.  Read More

In the world of artificial intelligence (AI) and machine learning (ML), 2022 has arguably been the year of foundation models, or AI models trained on a massive scale. From GPT-3 to DALL-E, from BLOOM to Imagen — another day, it seems, another large language model (LLM) or text-to-image model. But until now, there have been no AI benchmarks to provide a standardized way to evaluate these models, which have developed at a rapidly-accelerated pace over the past couple of years.

LLMs have particularly captivated the AI community, but according to the Stanford Institute for Human-Centered AI (HAI)’s Center for Research on Foundation Models, the absence of an evaluation standard has compromised the community’s ability to understand these models, as well as their capabilities and risks. 

To that end, today the CRFM announced the Holistic Evaluation of Language Models (HELM), which it says is the first benchmarking project aimed at improving the transparency of language models and the broader category of foundation models.  Read More