New End of the Year Blog Posts

In the first week of a new year, many researchers summarize their thoughts about the past and future. In addition to the previous post reflecting on GraphML in 2022 and 2023, a few new ones appeared:

1. AI in Drug Discovery 2022 by Pat Walters (Relay Therapeutics) on most inspiring papers in molecular and protein ML.

2. The Batch #177 includes predictions for 2023 by Yoshua Bengio (on reasoning), Alon Halevy (on personal data treatment), Douwe Kiela (on practical aspects of LLMs), Been Kim (on interpretability), and Reza Zadeh (on active learning)

3. Using Graph Learning for Personalization: How GNNs Solve Inherent Structural Issues with Recommender Systems by Dylan Sandfelder and Ivaylo Bahtchevanov (kumo.ai) - on applying GNNs in RecSys with examples from Spotify, Pinterest and UberEats.

4. Top Language AI research papers from Yi Tay (Google) - on large language models, the forefront of AI that does have an impact on Graph ML (remember protein language models like ESM-2 and ESM Fold, for instance).