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Quoc Le@quocleixXAI score38AIQuoc Le announced that Google's Gemini team is recruiting for a new Singapore team focused on advanced reasoning and LLM reinforcement learning. The post invites exceptional engineers and researchers to join the team, which is led by Yi Tay and reports into Quoc Le's Mountain View group.
Yi Tay@YiTayMLXAI score38AIYi Tay announced that Google DeepMind's Gemini team is starting a new research team in Singapore focused on advanced reasoning, LLM/RL, and improving frontier models such as Gemini and Gemini Deep Think. The team is led by Tay and reports to Quoc Le's broader team in Mountain View, which recently contributed to IMO and ICPC gold medal results with Gemini Deep Think. The team is starting small and is recruiting exceptionally capable engineers and researchers from the region and beyond.
Ilya Sutskever@ilyasutXAI score44AIIlya Sutskever says scaling current AI methods will keep producing improvements and will not stall. He adds that something important will still be missing.
Reflection@reflection_aiOfficialAI score16AIReflection says it will be at NeurIPS in San Diego next week, with its team staffing a booth and a panel on open AI ecosystems. The panel features speakers from Reflection, Meta, AI2, Berkeley's Ray, and SGLang, and will discuss what building open ecosystems requires, lessons from China, and the meaning of transparency and sovereignty.
AIKarpathy argues that verifiability, not specifiability, is the most predictive feature for AI automation, since verifiable tasks can be optimized directly or through reinforcement learning. He says a task is suited to this approach when the environment is resettable, efficient, and rewardable. This explains the jagged frontier of LLM progress, with verifiable domains like math and code advancing rapidly while creative and strategic tasks lag behind.
Chip Huyen@chiproXAI score14AIChip Huyen responded to Sam Altman's post saying ChatGPT now follows custom instructions to avoid em-dashes. The main post itself only reads "Sam!!!", so its reaction is conveyed mainly through the quoted context.
Chip Huyen@chiproXAI score27AIChip Huyen argues that many AI product failures stem from user experience, data quality, and organizational structure rather than the AI itself. She cites a chatbot whose traction improved after adding pre-populated questions and a voice option for users whose hands were busy, and a lead scoring model that was broken because marketing wasn't asking the right questions. She also notes that senior engineers gain the most from AI coding while resisting it more, and recommends building small tools for daily frustrations to solve the "idea crisis."
Chip Huyen@chiproXAI score22AIA hiring manager told Chip Huyen that a software engineering candidate who has not experimented with vibe coding is a red flag. Huyen posted the remark on X and asked for readers' thoughts.
Geoffrey Hinton@geoffreyhintonXAI score14AIGeoffrey Hinton recorded a podcast with Jon Stewart, whom he describes as a longtime hero, focused on explaining how AI works. Hinton says Stewart was especially eager to understand the underlying mechanics.
ByteDance@BytedanceTalkOfficialAI score4AIJanne, a Research Scientist on ByteDance's Intelligent Creation Team in London, says the energy of a fast-growing company gives her room to experiment creatively with technology. She describes her work as sitting at the frontier of modern music and technology.
