Tracked topic
Large language models are machine learning models trained to predict and generate text and other language-based outputs.
If you’d asked me two weeks ago—before OpenAI’s announcement—about the most novel contributions of LLMs to mathematics, I probably would have pointed to the AlphaEvolve system from Google DeepMind. AlphaEvolve harnesses LLMs to be the engine of an optimization process. If you can turn a math problem into a piece of code to optimize, which you often can, the LLM might find better solutions than humans have for certain types of problems. In November, four mathematicians (including Terence Tao) released a paper that analyzed AlphaEvolve’s performance on 67 optimization problems across the mathema
An OpenAI model solved a famous math problem that stumped humans for 80 years… In a recent preprint paper , an international team of university and corporate-sponsored researchers said the finding could help explain why LLMs frequently hallucinate false information and has implications for how quality AI training data should be structured. “Do not accept the following claim…”… …
… What one country sees as propaganda, of course, another might see as a set of important cultural truths that LLMs should support and reflect. …
…The additional verification comes in the form of a second LLM that grades the output from the first LLM. A high score gives developers the same confidence they have when viewing reports…
… Three years ago, LLMs struggled to solve arithmetic problems. It was only last year that LLMs started acing high school mathematics competitions . …
… Who knows what will happen if the AI bubble pops and the frictionless and ubiquitous access to LLMs withers into something much more limited. …
…Most gen AI models—including the other Gemma 4 variants—use dedicated encoders to process non-text inputs and pass that data to the LLM. This works well enough, but it increases…
… LLMs like Gemma or Gemini generate tokens autoregressively—that is, they produce one token at a time based on the previous token. …
…their emotional state (e.g., happiness), suggests relational dynamics (e.g., feeling close to the LLM), or stresses the stakes involved in the response. Across that sample, the average relative gap in…
… This is important because context windows are limited for LLMs, and important information can be lost over lengthy projects. …
…An LLM judge then made pairwise comparisons among the hypotheses, which resulted in relative rankings—a bit like Google’s tournament system. In a similar manner, the system was redeployed to suggest…