January 20 – DeepSeek releases DeepSeek-R1, a large language model based on DeepSeek-V3 utilising a chain-of-thought, stating it achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.[1] DeepSeek-R1 is open-source.
January 23 – Humanity's Last Exam, a benchmark for large language models, is published. The dataset consists of 3,000 challenging questions across over a hundred subjects.[4]
January 27
Nvidia's stock falls by as much as 17–18%, after the release of DeepSeek-R1.[5]
DeepSeek-R1 surpasses ChatGPT as the most-downloaded free app on the iOS App Store in the United States.[6]
February
February 3 – OpenAI releases ChatGPT Deep Research, an artificial intelligence system integrated into ChatGPT,[7] which generates cited reports on a user-specified topic by autonomously browsing the web for 5 to 30 minutes.[8]
February 6 – Mistral AI releases Le Chat, an AI assistant able to answer up to 1,000 words per second.[9]
27 March – Engineers in the fields of electrical and computer science creates a groundbreaking AI system known as "Super-Turing AI," designed to function more similarly to the human brain. Unlike conventional models that isolate tasks and shuttle massive volumes of data between components, this innovative AI merges key processes, streamlining operations and enhancing efficiency.[15]
April
16 April – OpenAI announces the launch of two new AI models, o3 and o4-mini.[16]
May
14 May – Google DeepMind announces AlphaEvolve, a Gemini-powered coding agent for designing advanced algorithms.[17]
Google launches A.I. Mode, which will be a feature on their search engine, and uses the Gemini model.[19]
Google DeepMind announces Veo 3, a new state-of-the-art video generation model.[20] The company also boosts the performance of Gemini 2.5 Pro, its flagship AI model.[21]
22 May – Anthropic releases Claude 4, with two models: Claude Opus 4 and Claude Sonnet 4. According to Anthropic, Claude 4 can function on its own for hours.[22]
8 September - Artificial intelligence uses vast energy, but University of Florida researchers develops a chip that replaces electricity with light for key AI tasks. Using microscopic lenses etched onto silicon, it performs laser-powered computations with drastically lower energy and near-perfect accuracy.[24]
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