Google releases Deep Review for analyzing complex technical documents
Google Research has publicly released Deep Review, an agentic AI system for technical verification and feedback on research papers and other complex documents, including legal and financial materials. Evolving from the Paper Assistant Tool, which provided optional feedback on more than 16,000 manuscripts, it combines document segmentation, adaptive compute budgets, parallel verification, and global synthesis. Users worldwide receive two complimentary reviews per day, with higher limits and API integration available through a Gemini API key; uploaded documents are never used to train, fine-tune, or improve Google models.
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Google DeepMindFirst-partyReported by 1 other sourcesGoogle DeepMind and Singapore GovTech deliver on-device Gemma model for scam detection
Google DeepMind and Singapore’s Government Technology Agency (GovTech) have delivered a Gemma model fine-tuned on local scam conversations and optimized for typical smartphones in Singapore. A lightweight classifier screens incoming messages before the model evaluates broader conversation context and triggers warnings about suspected manipulation, with conversation processing kept on the device. Training excluded private or personally identifiable information, using anonymized datasets derived from scam reports and intelligence feeds.
Google ResearchFirst-partyResearch@ 2026: 10 Ways Google Research Is Amplifying Human Ingenuity
Google Research presented 10 updates at Research@ spanning geospatial intelligence, scientific agents, document verification, edge hardware, numerical models, healthcare, disaster forecasting, education, and collaborative prototyping. It is expanding early access to experimental Google Earth AI capabilities and opening Deep Review to the general public after an early version reviewed over 16,000 research publications. Other updates include an upcoming TimesFM and TabFM integration into Gemini for business and an AMIE study involving 98 patients, in which clinicians reported that AI summaries helped them prepare in 75% of cases.
Research
HiRO-ACEv2 simulates extreme weather at 3 km resolution for a fraction of the cost
Ai2 introduced HiRO-ACEv2, an updated climate emulator that generates global 3 km rain, wind, and pressure data at about 1/300th the cost of X-SHiELD. Given coarsened X-SHiELD data, its HiROv2 downscaling model matches high-resolution statistics to within 3%, even for events occurring once in a million data points. The system currently works only with ACE tuned to match X-SHiELD and cannot yet generate high-resolution data for other climates; downloadable models, tutorial notebooks, and a web demo are available.