Google Arts & Culture has partnered with the Courtauld Institute of Art to launch "The Art of Looking," which features 12 art history stories, allowing users to zoom in online to examine brushstroke details in works by Van Gogh, Manet, Claudette Johnson, and others. The two parties also announced a new artist residency program to explore how AI can improve metadata workflows for cultural institutions' collections. There are no follow-up reports on further developments at this time.
On November 3, 2026, Google DeepMind released a cheminformatics skills set (Cheminformatics Skills) for Google Antigravity. The skill is based on RDKit, connects to ChEMBL and PubChem, and has a language model responsible for task orchestration and scientific reasoning, while deterministic chemistry tools perform molecular computations. Taking a lung cancer drug as an example, the agent retrieved thousands of compounds within about one hour, completed matched molecular pair analysis and trained a potency prediction model, and also proposed novel rigidified macrocyclic molecule designs with synthetic routes. Google DeepMind also noted that sparse data, inter-laboratory assay noise and narrow dynamic range can limit prediction accuracy, and that computational design is only a verifiable hypothesis that still requires experimental synthesis for validation. The skill is now live on Antigravity and can be used by installing the Science plugin, and free access to the highest usage tier for six months is being offered to 10,000 scientists.
On November 3, 2026, Google DeepMind released a cheminformatics skills set (Cheminformatics Skills) for Google Antigravity. The skill is based on RDKit, connects to ChEMBL and PubChem, and has a language model responsible for task orchestration and scientific reasoning, while deterministic chemistry tools perform molecular computations. Taking a lung cancer drug as an example, the agent retrieved thousands of compounds within about one hour, completed matched molecular pair analysis and trained
On November 3, 2026, Google DeepMind released a cheminformatics skills set (Cheminformatics Skills) for Google Antigravity. The skill is based on RDKit, connects to ChEMBL and PubChem, and has a language model responsible for task orchestration and scientific reasoning, while deterministic chemistry tools perform molecular computations. Taking a lung cancer drug as an example, the agent retrieved thousands of compounds within about one hour, completed matched molecular pair analysis and trained a potency prediction model, and also proposed novel rigidified macrocyclic molecule designs with synthetic routes. Google DeepMind also noted that sparse data, inter-laboratory assay noise and narrow dynamic range can limit prediction accuracy, and that computational design is only a verifiable hypothesis that still requires experimental synthesis for validation. The skill is now live on Antigravity and can be used by installing the Science plugin, and free access to the highest usage tier for six months is being offered to 10,000 scientists.
On November 3, 2026, Google.org announced that it would provide more than $9.5 million in funding to five organizations building educational AI tools, to develop AI tools for educators. Among them, Fab AI is collaborating with Google DeepMind and the Gates Foundation to build open-source models that help teachers prepare lessons and support early reading; Teaching Lab is piloting Coherence OS to provide real-time support for teachers and administrators. The remaining funds will go to related education projects at the City University of New York, the Krause Center for Innovation, and 1EdTech Global. There are currently no further developments.
On November 3, 2026, Google.org announced that it would provide more than $9.5 million in funding to five organizations building educational AI tools, to develop AI tools for educators. Among them, Fab AI is collaborating with Google DeepMind and the Gates Foundation to build open-source models that help teachers prepare lessons and support early reading; Teaching Lab is piloting Coherence OS to provide real-time support for teachers and administrators. The remaining funds will go to related edu
On November 3, 2026, Google.org announced that it would provide more than $9.5 million in funding to five organizations building educational AI tools, to develop AI tools for educators. Among them, Fab AI is collaborating with Google DeepMind and the Gates Foundation to build open-source models that help teachers prepare lessons and support early reading; Teaching Lab is piloting Coherence OS to provide real-time support for teachers and administrators. The remaining funds will go to related education projects at the City University of New York, the Krause Center for Innovation, and 1EdTech Global. There are currently no further developments.
Google has established a research hub in Singapore and has invested more than US$6 million in research grants to the National University of Singapore (NUS) and Nanyang Technological University (NTU), covering areas such as Alzheimer's disease research, computational efficiency and regional language processing, and AI safety. Among these, NUS received a US$1.5 million AI for Science Google.org Impact Challenge Grant, NTU received US$340,000 for four AI safety research projects, and a further US$750,000 came from the AI for Science Capacity Fund Grant. Google.org and Google DeepMind also provided US$3 million to the INSEAD Singapore Thrive Lab. No further progress has been disclosed at this time.
Google has established a research hub in Singapore and has invested more than US$6 million in research grants to the National University of Singapore (NUS) and Nanyang Technological University (NTU), covering areas such as Alzheimer's disease research, computational efficiency and regional language processing, and AI safety. Among these, NUS received a US$1.5 million AI for Science Google.org Impact Challenge Grant, NTU received US$340,000 for four AI safety research projects, and a further US$7
Google has established a research hub in Singapore and has invested more than US$6 million in research grants to the National University of Singapore (NUS) and Nanyang Technological University (NTU), covering areas such as Alzheimer's disease research, computational efficiency and regional language processing, and AI safety. Among these, NUS received a US$1.5 million AI for Science Google.org Impact Challenge Grant, NTU received US$340,000 for four AI safety research projects, and a further US$750,000 came from the AI for Science Capacity Fund Grant. Google.org and Google DeepMind also provided US$3 million to the INSEAD Singapore Thrive Lab. No further progress has been disclosed at this time.
On November 3, 2026, Google announced the expansion of anti-scam protections in the Asia-Pacific region. According to the Google Blog, Google is strengthening anti-scam efforts in the Asia-Pacific region through Android's Fake Call Detection, which identifies AI-driven phone impersonation, Pixel's built-in scam detection, and sharing threat intelligence with the industry. Google.org also provided $6 million in funding to The Asia Foundation and the Tech for Good Institute to train communities, incubate AI defense prototypes, and expand the educational game Be Scam Ready to Indonesia, Japan, Malaysia, the Philippines, and Vietnam. The original text mentioned that scam losses in East Asia, Southeast Asia, Australia, and New Zealand reached as high as $114.1 billion in 2025. There are currently no subsequent developments.
On November 3, 2026, Google announced the expansion of anti-scam protections in the Asia-Pacific region. According to the Google Blog, Google is strengthening anti-scam efforts in the Asia-Pacific region through Android's Fake Call Detection, which identifies AI-driven phone impersonation, Pixel's built-in scam detection, and sharing threat intelligence with the industry. Google.org also provided $6 million in funding to The Asia Foundation and the Tech for Good Institute to train communities, i
On November 3, 2026, Google announced the expansion of anti-scam protections in the Asia-Pacific region. According to the Google Blog, Google is strengthening anti-scam efforts in the Asia-Pacific region through Android's Fake Call Detection, which identifies AI-driven phone impersonation, Pixel's built-in scam detection, and sharing threat intelligence with the industry. Google.org also provided $6 million in funding to The Asia Foundation and the Tech for Good Institute to train communities, incubate AI defense prototypes, and expand the educational game Be Scam Ready to Indonesia, Japan, Malaysia, the Philippines, and Vietnam. The original text mentioned that scam losses in East Asia, Southeast Asia, Australia, and New Zealand reached as high as $114.1 billion in 2025. There are currently no subsequent developments.
Databricks announced that Lakebase Postgres, its fully managed serverless Postgres database, is now generally available on Google Cloud. According to the Databricks Blog, the service supports automatic scaling, scale-to-zero, second-level branching, and point-in-time recovery; it shares the same storage layer with analytical data, eliminating the need to maintain ETL pipelines, and provides unified governance through Unity Catalog. In terms of availability, multi-availability-zone endpoints offer a 99.99% SLA, while single availability zones offer 99.9%. Lakebase Search delivers vector and full-text search throughput 2 times that of pgvector at 4 times lower cost. There is currently no information on further developments.
Databricks announced that Lakebase Postgres, its fully managed serverless Postgres database, is now generally available on Google Cloud. According to the Databricks Blog, the service supports automatic scaling, scale-to-zero, second-level branching, and point-in-time recovery; it shares the same storage layer with analytical data, eliminating the need to maintain ETL pipelines, and provides unified governance through Unity Catalog. In terms of availability, multi-availability-zone endpoints offe
Databricks announced that Lakebase Postgres, its fully managed serverless Postgres database, is now generally available on Google Cloud. According to the Databricks Blog, the service supports automatic scaling, scale-to-zero, second-level branching, and point-in-time recovery; it shares the same storage layer with analytical data, eliminating the need to maintain ETL pipelines, and provides unified governance through Unity Catalog. In terms of availability, multi-availability-zone endpoints offer a 99.99% SLA, while single availability zones offer 99.9%. Lakebase Search delivers vector and full-text search throughput 2 times that of pgvector at 4 times lower cost. There is currently no information on further developments.
The AI planning tool PlanAssist, developed by Google DeepMind in partnership with the UK government, will be expanded to 12 additional local planning authorities in England, bringing the total number of participants to 15. In early pilots in Barnet, Camden and Dorset, the tool cut the average time planning officers spent assessing household residential applications by 58%, and more than 70% of the generated reports were approved by officers without modification. Built on Gemini, PlanAssist verifies application materials and drawings, checks against heritage protection restrictions and local and national planning policy, reviews past objections, and drafts reports with citations, with the final decision still made by planning officers. The tool has been piloted since June and is now entering a 12-month Beta phase; if testing goes smoothly, the UK government plans to make it available to all local councils in England in 2027.
The AI planning tool PlanAssist, developed by Google DeepMind in partnership with the UK government, will be expanded to 12 additional local planning authorities in England, bringing the total number of participants to 15. In early pilots in Barnet, Camden and Dorset, the tool cut the average time planning officers spent assessing household residential applications by 58%, and more than 70% of the generated reports were approved by officers without modification. Built on Gemini, PlanAssist verif
On October 28, 2026, Google DeepMind released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and scoring 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model is aimed at long-horizon engineering tasks and was first opened to some cybersecurity defenders, then expanded through the Fairwind Program, and afterward made available to developers, enterprises, and consumers. On October 29, Arena.ai said Gemini 4 Carbon ranked 2nd in Agent Arena with a net improvement of 16.2%, and was on the Pareto frontier for cost, time, and output tokens per task; the same day, Yuchen Jin cited Artificial Analysis data saying it was smarter than Opus 5.5 and cheaper per task, but noted that the evaluation used the Antigravity CLI. On October 30, the Artificial Analysis Intelligence Index showed it in first place with 59 points, 1 point higher than Claude Opus 5.5. On October 31, Perplexity CEO Aravind Srinivas shared early evaluations
On October 28, 2026, Google DeepMind released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and scoring 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model is aimed at long-horizon engineering tasks and was first opened to some cybersecurity defenders, then expanded through the Fairwind Program, and afterward made available to developers, enterprises, and consumers. On October 29, Arena
On October 30, 2026, Google said it had received the first AI reply from the Project Suncatcher prototype satellite. The data-center-class TPU aboard the satellite ran the open Gemma 4 model in orbit; after the ground station uploaded a prompt, the model generated a haiku about space and transmitted it back to Earth as the satellite passed over Svalbard, Norway. The satellite launched on October 1 aboard SpaceX Transporter-18 and was built in partnership with Planet; it had previously completed power-on of the host machine and TPU tray as well as early machine learning tests. Google will next test how the TPU performs under orbital thermal stress and radiation exposure, paving the way for the goal of two interconnected satellites in 2027.
Google Developer Groups announced that DevFest 2026 will be held from October 1 to December 31. According to information published on the Google Developers Blog, this year's DevFest covers 115 countries and more than 800 events, with nearly 1 million developers expected to participate. The events revolve around generative AI, autonomous agents, Google Cloud, Android, and the Web, under the theme of building, securing, and scaling in the age of agents. Local events are organized by communities in local languages, with Google Developer Experts and Google engineers participating as speakers.
Google Research releases the SLEEP offline memory consolidation method. According to a report by IT Home · AI, Google's research team has released a continual learning study called the "Sleep Framework," which divides model operation into two phases, awake and sleep, to address the problem of large models having fixed knowledge and difficulty absorbing new information; during the sleep phase, short-term context is written into long-term parameters through parameter expansion, mixture-of-experts memory blocks, and knowledge distillation, and synthetic samples generated through "dreaming" are used for reinforcement learning. Experiments show that the framework can handle contexts of up to about 10 million tokens, that performance degradation is close to zero in multi-stage continual learning on unseen languages, and that it achieves higher accuracy on math benchmarks such as AIME 24/25. Phoenix Technology reported that the study was made public on October 27, and that the paper is titled "Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories." There are currently no subsequent developments.
Google Research releases the SLEEP offline memory consolidation method. According to a report by IT Home · AI, Google's research team has released a continual learning study called the "Sleep Framework," which divides model operation into two phases, awake and sleep, to address the problem of large models having fixed knowledge and difficulty absorbing new information; during the sleep phase, short-term context is written into long-term parameters through parameter expansion, mixture-of-experts mem
The AI planning tool PlanAssist, developed by Google DeepMind in partnership with the UK government, will be expanded to 12 additional local planning authorities in England, bringing the total number of participants to 15. In early pilots in Barnet, Camden and Dorset, the tool cut the average time planning officers spent assessing household residential applications by 58%, and more than 70% of the generated reports were approved by officers without modification. Built on Gemini, PlanAssist verifies application materials and drawings, checks against heritage protection restrictions and local and national planning policy, reviews past objections, and drafts reports with citations, with the final decision still made by planning officers. The tool has been piloted since June and is now entering a 12-month Beta phase; if testing goes smoothly, the UK government plans to make it available to all local councils in England in 2027.
On October 30, 2026, Google said it had received the first AI reply from the Project Suncatcher prototype satellite. The data-center-class TPU aboard the satellite ran the open Gemma 4 model in orbit; after the ground station uploaded a prompt, the model generated a haiku about space and transmitted it back to Earth as the satellite passed over Svalbard, Norway. The satellite launched on October 1 aboard SpaceX Transporter-18 and was built in partnership with Planet; it had previously completed power-on of the host machine and TPU tray as well as early machine learning tests. Google will next test how the TPU performs under orbital thermal stress and radiation exposure, paving the way for the goal of two interconnected satellites in 2027.
On October 30, 2026, Google said it had received the first AI reply from the Project Suncatcher prototype satellite. The data-center-class TPU aboard the satellite ran the open Gemma 4 model in orbit; after the ground station uploaded a prompt, the model generated a haiku about space and transmitted it back to Earth as the satellite passed over Svalbard, Norway. The satellite launched on October 1 aboard SpaceX Transporter-18 and was built in partnership with Planet; it had previously completed
Google Developer Groups announced that DevFest 2026 will be held from October 1 to December 31. According to information published on the Google Developers Blog, this year's DevFest covers 115 countries and more than 800 events, with nearly 1 million developers expected to participate. The events revolve around generative AI, autonomous agents, Google Cloud, Android, and the Web, under the theme of building, securing, and scaling in the age of agents. Local events are organized by communities in local languages, with Google Developer Experts and Google engineers participating as speakers.
Google Developer Groups announced that DevFest 2026 will be held from October 1 to December 31. According to information published on the Google Developers Blog, this year's DevFest covers 115 countries and more than 800 events, with nearly 1 million developers expected to participate. The events revolve around generative AI, autonomous agents, Google Cloud, Android, and the Web, under the theme of building, securing, and scaling in the age of agents. Local events are organized by communities in
Google Research releases the SLEEP offline memory consolidation method. According to a report by IT Home · AI, Google's research team has released a continual learning study called the "Sleep Framework," which divides model operation into two phases, awake and sleep, to address the problem of large models having fixed knowledge and difficulty absorbing new information; during the sleep phase, short-term context is written into long-term parameters through parameter expansion, mixture-of-experts memory blocks, and knowledge distillation, and synthetic samples generated through "dreaming" are used for reinforcement learning. Experiments show that the framework can handle contexts of up to about 10 million tokens, that performance degradation is close to zero in multi-stage continual learning on unseen languages, and that it achieves higher accuracy on math benchmarks such as AIME 24/25. Phoenix Technology reported that the study was made public on October 27, and that the paper is titled "Language Models Need Sleep: Learning to Self-Modify and Consolidate Memories." There are currently no subsequent developments.