In the company’s words, Galactica “can summarize academic papers, solve math problems, generate Wiki articles, write scientific code, annotate molecules and proteins, and more.” But the shiny veneer wore through fast.Our models are available for researchers who want to learn more about the work and reproduce results in the paper.” A fundamental problem with Galactica is that it is not able to distinguish truth from falsehood, a basic requirement for a language model designed to generate scientific text.Michael Black, director at the Max Planck Institute for Intelligent Systems in Germany, who works on deep learning, tweeted: “In all cases, it was wrong or biased but sounded right and authoritative.“It gives a false sense of intelligence.” Gary Marcus, a cognitive scientist at New York University and a vocal critic of deep learning, gave his view in a Substack post titled “A Few Words About Bullshit,” saying that the ability of large language models to mimic human-written text is nothing more than “a superlative feat of statistics.” And yet Meta is not the only company championing the idea that language models could replace search engines.They think that this is the future of information access, even if nobody asked for that future.” Deep Dive Artificial intelligence DeepMind’s game-playing AI has beaten a 50-year-old record in computer science The new version of AlphaZero discovered a faster way to do matrix multiplication, a core problem in computing that affects thousands of everyday computer tasks."