Gary Marcus bet that hybrid (neurosymbolic) AI models would pull ahead in 2022.

True: during 2022, hybrid (neurosymbolic) AI systems clearly outperformed pure deep-learning systems on the main AI benchmarks and among the most prominent and influential AI systems released that year, and contemporary expert reviews of 2022 recognised hybrid approaches as having moved ahead. Mostly true: hybrids led in most major areas but not all. Mixed: hybrids led clearly in some notable domains, while pure deep learning led in others of similar importance. Mostly false: hybrids gained ground or led only in narrow or niche tasks, while pure deep-learning systems led the most prominent benchmarks and releases. False: pure or mostly deep-learning systems dominated state-of-the-art results and the major releases of 2022, and contemporary reviews did not describe hybrid models as having pulled ahead. Results after 2022-12-31 do not count.

Set before the research began.

1. E1 Biggest AI Headlines in 2022 – At Stanford and Beyond Stanford HAI · 14 December 2022

   “If we distill the biggest advances in AI this year into one headline, it would be generative AI. This year companies launched major models like ChatGPT, DALL-E 2, and others, highlighting impressive capabilities and sparking debate about potential harms.”

2. E2 2023 AI Index: A Year of Technical Achievement, Newfound Public Scrutiny Stanford HAI · 3 April 2023

   “Large language models, which have driven much recent AI progress, are getting bigger and more expensive.”

3. E3 Technical Performance Stanford HAI · 1 January 2023

   “Language models continued to improve their generative capabilities, but new research suggests that they still struggle with complex planning tasks.”

4. E4 2022 in artificial intelligence - Wikipedia Wikipedia · 9 February 2025

   “April 12 – DeepMind introduces Chinchilla, a 70-billion-parameter language model that outperforms larger models, including Gopher, on a range of benchmarks.”

Stanford HAI's review of 2022 (E1) names generative AI as the year's biggest advance, citing ChatGPT and DALL-E 2. It says nothing about hybrid or neurosymbolic systems pulling ahead. The 2023 AI Index (E2, E3) credits large language models with driving recent AI progress. It notes only that they still struggle with complex planning. E4 records Chinchilla, a 70-billion-parameter language model, outperforming larger models on a range of benchmarks in 2022. In these independent sources, generative AI and large language models are named as the main advances of 2022, and none describes hybrid models as having moved ahead.