To kick off the year, I've finally been able to complete the draft of this AI Research Highlights of 2024 article. It covers a variety of topics, from mixture-of-experts models to new LLM scaling laws for precision.
Reflecting on all the major research highlights of 2024 would probably require writing an entire book. It's been an extraordinarily productive year, even for such a fast-moving field. To keep things reasonably concise, I decided to focus exclusively on LLM research this year. But even then, how does one choose a subset of papers from such an eventful year? The simplest approach I could think of was to highlight one paper per month: January through December 2024.
So, in this article, I'll share research papers that I personally found fascinating, impactful, or, ideally, both. However, note that this article is just Part One, focusing on the first half of 2024 from January through June. Part 2 of this series, covering July to December, will be shared later in January.
The selection criteria are admittedly subjective, based on what stood out to me this year. I've also aimed for some variety, so it's not all just about LLM model releases.