GPT-5.2 is the latest model family in the GPT-5 series. The comprehensive safety mitigation approach for these models is largely the same as that described in the GPT-5 System Card and GPT-5.1 System Card. Like OpenAI’s other models, the GPT-5.2 models were trained on diverse datasets, including information that is publicly available on the internet, information that we partner with third parties to access, and information that our users or human trainers and researchers provide or generate.

GPT-5.2-Codex is OpenAI’s most advanced coding model, offering long-horizon reasoning, large-scale code transformations, and enhanced cybersecurity capabilities.

OpenAI introduces FrontierScience, a benchmark testing AI reasoning in physics, chemistry, and biology to measure progress toward real scientific research.

GPT-5.2-Codex is OpenAI’s most advanced coding model, offering long-horizon reasoning, large-scale code transformations, and enhanced cybersecurity capabilities.

GPT-5.2 is our most advanced frontier model for everyday professional work, with state-of-the-art reasoning, long-context understanding, coding, and vision. Use it in ChatGPT and the OpenAI API to power faster, more reliable agentic workflows.

This system card outlines the comprehensive safety measures implemented for GPT‑5.2-Codex. It details both model-level mitigations, such as specialized safety training for harmful tasks and prompt injections, and product-level mitigations like agent sandboxing and configurable network access.

GPT-5.2 is OpenAI’s strongest model yet for math and science, setting new state-of-the-art results on benchmarks like GPQA Diamond and FrontierMath. This post shows how those gains translate into real research progress, including solving an open theoretical problem and generating reliable mathematical proofs.

OpenAI is updating its Model Spec with new Under-18 Principles that define how ChatGPT should support teens with safe, age-appropriate guidance grounded in developmental science. The update strengthens guardrails, clarifies expected model behavior in higher-risk situations, and builds on our broader work to improve teen safety across ChatGPT.

December 18, 2025 Science Google DeepMind supports U.S. Department of Energy on Genesis: a national mission to accelerate innovation and scientific discovery Pushmeet Kohli and Tom Lue Share Copied Your browser does not support the audio element. Listen to article  6 minutes We stand at an inflection point where the convergence of advanced AI and scientific research promises to unlock a new golden age of discovery . Recognizing this, we’re pleased to support the White House’s Genesis Mission - a historic national effort to use AI to transform how scientific research is conducted and accelerate the speed of American science. The Genesis Mission will mobilize the U.S. Department of Energy’s (DOE) 17 National Laboratories, industry and academia to build an integrated discovery platform, accelerating breakthroughs across the nation’s most pressing challenges including energy, scientific discovery, and national security. At Google DeepMind, our mission is to build AI responsibly to benefit humanity. There is perhaps no clearer expression of this than the application of AI within science. Scientists today face significant obstacles of unprecedented scale and complexity — from shaping and simulating the intricate dynamics of fusion plasma, to exploring the vast search space of new materials, and finding a way to process and understand ever-growing volumes of data and literature. Modern deep learning methods are uniquely suited to address these challenges and compress the time new discoveries would otherwise require. To help realize the ambitious vision in the Genesis Mission, Google and the DOE are partnering to support the Administration's goal of harnessing the AI and advanced computing revolution to dramatically expand the productivity and impact of American research and innovation within a decade. We see this as the beginning of an enduring partnership in AI for Science that we will look to grow and expand in the months and years ahead. Putting our advanced AI tools into the hands of American scientists Google DeepMind will provide an accelerated access program for scientists at all 17 DOE National Laboratories to our frontier AI for Science models and agentic tools, starting today with AI co-scientist on Google Cloud. AI co-scientist is a multi-agent virtual scientific collaborator built on Gemini, which is trained on Google's world class TPUs. This system is designed to help scientists synthesize vast amounts of information to generate novel hypotheses and research proposals, and accelerate the pace of scientific and biomedical discoveries. AI co-scientist is already showing its potential across diverse biomedical applications. It proposed novel drug repurposing candidates for liver fibrosis that were validated through laboratory experiments and predicted complex antimicrobial resistance mechanisms that matched experiments before they were even published, demonstrating the potential to accelerate hypothesis development from years to days. It’s also showing early promise in additional fields like physics, chemistry, computer science, and more. In early 2026, we will expand our accelerated access program for National Laboratories to include: AlphaEvolve - a Gemini-powered coding agent for designing advanced algorithms that is showing incredible promise for application across many areas in computing and math and, we believe, could be transformative across many more areas such as material science, drug discovery and energy. For example, AlphaEvolve enhanced the efficiency of Google's data centers, chip design and AI training processes — including training the large language models underlying AlphaEvolve itself. AlphaGenome - an AI model to help scientists better understand the non-coding part of DNA, speeding up research on genome biology and improving disease understanding. With more data on plant genomes, AlphaGenome could potentially be extended to help improve crop resistance and other applications including sustainable biofuels and advanced biomaterials. WeatherNext - a state-of-the-art family of weather forecasting models. Our partnership with the U.S. National Hurricane Center already supports their cyclone forecasts and warnings, helping communities prepare for disasters earlier. DOE and all National Laboratories can also access Gemini for Government , which brings together the best of Google’s AI-optimized and accredited commercial cloud with our industry-leading Gemini models - including our most intelligent model Gemini 3 with state-of-the-art reasoning capabilities and multimodal understanding. We’re excited to see what America’s leading researchers will be able to do with our frontier AI models and agentic tools. A history of collaboration for scientific progress We've seen what’s possible when industry-leading technology can build upon the work of the National Laboratories. The foundational work by DOE's Brookhaven National Laboratory on the Protein Data Bank was crucial for the development of AlphaFold, our AI system that can predict the 3D structure of proteins, the development of which was recognized through Demis Hassabis and John Jumper’s co-award of the 2024 Nobel Prize in Chemistry. The AlphaFold Protein Database has now been used by more than three million scientists in over 190 countries to accelerate research, from effective malaria vaccines to groundbreaking gene therapies. Looking ahead Through the Genesis Mission, we'll be accelerating American scientific leadership by also exploring research collaborations with National Laboratories in areas including fusion energy , new materials discovery and earth science . The challenges facing our world—from energy to disease to security—demand unprecedented scientific innovation. By combining human ingenuity with advanced AI capabilities, we believe we can help America's scientists achieve discoveries that would have seemed impossible just years ago. Related posts A new golden age of discovery Learn more AlphaFold Learn more WeatherNext 2 Learn more AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms May 2025 Science Learn more AlphaGenome: AI for better understanding the genome June 2025 Science Learn more How we're supporting better tropical cyclone prediction with AI June 2025 Research Learn more A new era of intelligence with Gemini 3 November 2025 Models Learn more Bringing AI to the next generation of fusion energy October 2025 Science Learn more Millions of new materials discovered with deep learning November 2023 Science Learn more

A data-driven look at enterprise AI adoption, showing how organizations move from experimentation to real productivity gains and new capabilities.

Developers can now submit apps for review and publication in ChatGPT, with approved apps appearing in a new in-product directory for easy discovery. Updated tools, guidelines, and the Apps SDK help developers build powerful chat-native experiences that bring real-world actions into ChatGPT.

OpenAI is launching the OpenAI Academy for News Organizations, a new learning hub built with the American Journalism Project and The Lenfest Institute to help newsrooms use AI effectively. The Academy offers training, practical use cases, and responsible-use guidance to support journalists, editors, and publishers as they adopt AI in their reporting and operations.

OpenAI introduces a new framework and evaluation suite for chain-of-thought monitorability, covering 13 evaluations across 24 environments. Our findings show that monitoring a model’s internal reasoning is far more effective than monitoring outputs alone, offering a promising path toward scalable control as AI systems grow more capable.

OpenAI and the U.S. Department of Energy have signed a memorandum of understanding to deepen collaboration on AI and advanced computing in support of scientific discovery. The agreement builds on ongoing work with national laboratories and helps establish a framework for applying AI to high-impact research across the DOE ecosystem.

OpenAI introduces a real-world evaluation framework to measure how AI can accelerate biological research in the wet lab. Using GPT-5 to optimize a molecular cloning protocol, the work explores both the promise and risks of AI-assisted experimentation.

More than one million customers around the world now use OpenAI to empower their teams and unlock new opportunities. This post highlights how companies like PayPal, Virgin Atlantic, BBVA, Cisco, Moderna, and Canva are transforming the way work gets done with AI.

The new ChatGPT Images is powered by our flagship image generation model, delivering more precise edits, consistent details, and image generation up to 4× faster. The upgraded model is rolling out to all ChatGPT users today and is also available in the API as GPT-Image-1.5.

OpenAI is strengthening ChatGPT Atlas against prompt injection attacks using automated red teaming trained with reinforcement learning. This proactive discover-and-patch loop helps identify novel exploits early and harden the browser agent’s defenses as AI becomes more agentic.

December 19, 2025 Responsibility & Safety Gemma Scope 2: helping the AI safety community deepen understanding of complex language model behavior Language Model Interpretability Team Share Copied Your browser does not support the audio element. Listen to article 5 minutes Announcing a new, open suite of tools for language model interpretability Large Language Models (LLMs) are capable of incredible feats of reasoning, yet their internal decision-making processes remain largely opaque. Should a system not behave as expected, a lack of visibility into its internal workings can make it difficult to pinpoint the exact reason for its behaviour. Last year, we advanced the science of interpretability with Gemma Scope , a toolkit designed to help researchers understand the inner workings of Gemma 2, our lightweight collection of open models. Today, we are releasing Gemma Scope 2 : a comprehensive, open suite of interpretability tools for all Gemma 3 model sizes, from 270M to 27B parameters. These tools can enable us to trace potential risks across the entire "brain" of the model. To our knowledge, this is the largest ever open-source release of interpretability tools by an AI lab to date. Producing Gemma Scope 2 involved storing approximately 110 Petabytes of data, as well as training over 1 trillion total parameters. As AI continues to advance, we look forward to the AI research community using Gemma Scope 2 to debug emergent model behaviors, use these tools to better audit and debug AI agents, and ultimately, accelerate the development of practical and robust safety interventions against issues like jailbreaks, hallucinations and sycophancy. Our interactive Gemma Scope 2 demo is available to try, courtesy of Neuronpedia. What’s new in Gemma Scope 2 Interpretability research aims to understand the internal workings and learned algorithms of AI models. As AI becomes increasingly more capable and complex, interpretability is crucial for building AI that is safe and reliable. Like its predecessor, Gemma Scope 2 acts as a microscope for the Gemma family of language models. By combining sparse autoencoders (SAEs) and transcoders, it allows researchers to look inside models, see what they’re thinking about, and how these thoughts are formed and connect to the model’s behaviour. In turn, this enables the richer study of jailbreaks or other AI behaviours relevant to safety, like discrepancies between a model's communicated reasoning and its internal state. While the original Gemma Scope enabled research in key areas of safety, such as model hallucination , identifying secrets known by a model , and training safer models , Gemma Scope 2 supports even more ambitious research through significant upgrades: Full coverage at scale : We provide a full suite of tools for the entire Gemma 3 family (up to 27B parameters), essential for studying emergent behaviors that only appear at scale, such as those previously uncovered by the 27b-size C2S Scale model that helped discover a new potential cancer therapy pathway. Although Gemma Scope 2 is not trained on this model, this is an example of the kind of emergent behavior that these tools might be able to understand. More refined tools to decipher complex internal behaviors: Gemma Scope 2 includes SAEs and transcoders trained on every layer of our Gemma 3 family of models. S kip-transcoders and Cross-layer transcoders make it easier to decipher multi-step computations and algorithms spread throughout the model. Advanced training techniques : We use state-of-the-art techniques, notably the Matryoshka training technique , which helps SAEs detect more useful concepts and resolves certain flaws discovered in Gemma Scope. Chatbot behavior analysis tools : We also provide interpretability tools targeted at the versions of Gemma 3 tuned for chat use cases. These tools enable analysis of complex, multi-step behaviors, such as jailbreaks, refusal mechanisms, and chain-of-thought faithfulness. This visual shows Gemma Scope 2 using sparse autoencoders and transcoders to show researchers how the model is determining a potential fraudulent email. Advancing the field By releasing Gemma Scope 2, we aim to enable the AI safety research community to push the field forward using a suite of cutting-edge interpretability tools. This new level of access is crucial for tackling real-world safety problems that only arise in larger, modern LLMs. Learn more about Gemma Scope Download Gemma Scope 2 View our models on Neuronpedia Read our technical report Try our Colab tutorial View our Gemma Scope page Related posts Gemma Learn more Gemma Scope Learn more Gemma Scope: helping the safety community shed light on the inner workings of language models July 2024 Models Learn more

Breadcrumb Innovation & AI Products Google's year in review: 8 areas with research breakthroughs in 2025 Dec 23, 2025 · Share x.com Facebook LinkedIn Mail Copy link This was a year of AI agents, reasoning and scientific discovery. Jeff Dean Chief Scientist Demis Hassabis CEO, Google DeepMind James Manyika SVP, Research, Labs, Technology & Society Read AI-generated summary General summary In 2025, Google made significant AI research breakthroughs with models like Gemini 3 and Gemma 3. These advancements improved AI's reasoning, multimodality, and efficiency, leading to new products and features across Google's portfolio. Expect more AI-driven innovations in science, computing, and tools for global challenges as Google prioritizes responsible AI development and collaboration. Summaries were generated by Google AI. Generative AI is experimental. Bullet points "Google's year in review: 8 areas with research breakthroughs in 2025" highlights AI advancements and more. Gemini 3 models showed big leaps in reasoning, multimodality, efficiency, and creative abilities. AI is transforming Google's products, from Pixel 10 to Search, with agentic capabilities. AI is boosting science, from genomics and healthcare to math, coding, and quantum computing. Google is prioritizing AI safety, collaboration, and addressing global challenges like climate change. Summaries were generated by Google AI. Generative AI is experimental. Basic explainer Google had a super productive year with AI research. They made their AI models way better at thinking and understanding things. Google also made AI more useful in everyday products and helped people be more creative. Plus, they used AI to make big steps in science and to tackle global problems. Summaries were generated by Google AI. Generative AI is experimental. Explore other styles: General summary Bullet points Basic explainer Share x.com Facebook LinkedIn Mail Copy link In this story In this story AI models AI in our products AI and creativity Science & mathematics Computing Global impact Safety & responsibility Collaborations Your browser does not support the audio element. Listen to article This content is generated by Google AI. Generative AI is experimental [[duration]] minutes Voice Speed Voice Speed 0.75X 1X 1.5X 2X 2025 has been a year of extraordinary progress in research. With artificial intelligence, we can see its trajectory shifting from a tool to a utility: from something people use to something they can put to work. If 2024 was about laying the multimodal foundations for this era, 2025 was the year AI began to really think, act and explore the world alongside us. With quantum computing, we made progress towards real-world applications. And across the board, we helped turn research into reality, with more capable and useful products and tools making a positive impact on people's lives today. Here’s a look back at some of the breakthroughs, products and scientific milestones that defined the work of Google, Google DeepMind and Google Research in a year of relentless progress . Delivering breakthroughs on world-class models This year, we significantly advanced our model capabilities with breakthroughs on reasoning, multimodal understanding, model efficiency, and generative capabilities, beginning with the release of Gemini 2.5 in March and culminating in the November launch of Gemini 3 and the December launch of Gemini 3 Flash. Built on a foundation of state-of-the-art reasoning, Gemini 3 Pro is our most powerful model to date, designed to help you bring any idea to life. It topped the LMArena Leaderboard and redefined multimodal reasoning with breakthrough scores on benchmarks like Humanity’s Last Exam — a fiendishly hard test for AI models to see if AI can truly think and reason like humans — and GPQA Diamond. It also set a new standard for frontier models in mathematics, achieving a new state-of-the-art of 23.4% on MathArena Apex. We followed shortly with Gemini 3 Flash, which combines Gemini 3's Pro-grade reasoning with Flash-level latency, efficiency and cost, making it the most performant model for its size. Gemini 3 Flash's quality surpasses our previous Gemini 2.5 Pro-scale model's capabilities at a fraction of the price and substantially better latency, continuing our Gemini-era trend of 'the next generation's Flash model is better than the previous generation's Pro model'. Learn more about our progress on our world-class AI models this year: Gemini 3 Flash: frontier intelligence built for speed (Dec 2025) A new era of intelligence with Gemini 3 (Nov 2025) Introducing Nano Banana Pro (Nov 2025) Introducing Veo 3.1 and new creative capabilities in the Gemini API (Nov 2025) Gemini 2.5: Our most intelligent AI model (March 2025) Gemini 3 Flash price & benchmark table.  We’re committed to making useful AI technology accessible, with state-of-the-art open models. We built our Gemma family of models to be lightweight and open for public use; this year we were able to introduce multimodal capabilities, significantly increase the context window, expand multilingual capabilities, and improve efficiency and performance. Learn more about this year’s advances in Gemma models: Introducing Gemma 3: The most capable model you can run on a single GPU or TPU (March 2025) Introducing Gemma 3 270M: The compact model for hyper-efficient AI (Aug 2025) Innovating and transforming our products with AI Throughout 2025, we continued to advance the trajectory of AI from tool to utility, transforming our portfolio of products with new, powerful agentic capabilities. We reimagined software development by moving beyond tools that assist coding to introducing powerful, agentic systems that collaborate with developers. Key advances, such as the impressive coding capabilities in Gemini 3 and the launch of Google Antigravity , mark a new era in AI-assisted software development. Learn more about this year’s advances building developer tools: Start building with Gemini 3 (Nov 2025) Introducing Google Antigravity, a New Era in AI-Assisted Software Development (Nov 2025) This evolution was also clear across our core products, from AI-enabled features on the Pixel 10 and updates to AI Mode in Search like generative UI, to AI-first innovations like the Gemini app and NotebookLM, which gained advanced features like Deep Research. Learn more about how we’ve transformed our products with AI: 9 ways AI makes Pixel 10 our most helpful phone yet (Aug 2025) Expanding AI Overviews and introducing AI Mode (March 2025) Gemini 3 brings upgraded smarts and new capabilities to the Gemini app (Nov 2025) NotebookLM adds Deep Research and support for more source types (Nov 2025) Generative UI: A rich, custom, visual interactive user experience for any prompt (Nov 2025) Empowering creativity and co-creating with AI 2025 was a transformative year for generative media, giving people new and unprecedented capabilities to realize their creative ambitions. Generative media models and tools for video, images, audio and worlds became more effective and broadly used, with breakouts Nano Banana and Nano Banana Pro offering unprecedented capabilities for native image generation and editing. We worked with people in creative industries to develop tools like Flow and Music AI Sandbox, making them more helpful for creative workflows, and we expanded creative possibilities for people with new, AI-powered experiences in the Google Arts & Culture lab, major upgrades to image editing within the Gemini app, and the introduction of powerful new generative media models like Veo 3.1, Imagen 4 and Flow. Learn more about how we’re building AI to enhance creativity: Art, science, travel: 3 new AI-powered experiences this holiday season (Nov 2025) Introducing Veo 3.1 and advanced capabilities in Flow (Oct 2025) Nano Banana: Image editing in Gemini just got a major upgrade (Aug 2025) Veo 3, Imagen 4, and Flow: Fuel your creativity with new generative media models and tools (May 2025) Music AI Sandbox, now with new features and broader access (April 2025) As research breakthroughs continue to expand AI’s capabilities, Google Labs is where we share AI experiments as we develop them – hearing from users and evolving as we learn. Some of this year’s most engaging experiments from Labs: Pomelli, an AI experiment for on-brand marketing content; Stitch, which introduced a way to turn prompt and image inputs into complex UI designs and frontend code in minutes; Jules, an asynchronous coding agent that acts as a collaborative partner for developers; and Google Beam, a 3D video communications platform that used AI to advance the possibilities of remote presence. Learn more about how we’re experimenting in Labs: Create on-brand marketing content for your business with Pomelli (Oct 2025) Google Beam: Our AI-first 3D video communication platform (May 2025) From idea to app: Introducing Stitch, a new way to design UIs (May 2025) Build with Jules, your asynchronous coding agent (May 2025) Advancing science and mathematics 2025 was also a banner year for scientific advances with AI, marked by breakthroughs in life sciences, health, natural sciences, and mathematics. In the space of a year, we made progress in building AI resources and tools that empower researchers and help them understand, identify, and develop treatments in healthcare. In genomics, where we’ve been applying advanced technology to research for 10 years, we moved beyond sequencing, using AI to interpret the most complex data. We also marked the 5-year anniversary of AlphaFold, the Nobel-winning AI system that solved the 50-year-old protein folding problem. AlphaFold has been used by over 3 million researchers in more than 190 countries, including over 1 million users in low- and middle-income countries. Learn more about how we’re using AI to advance life sciences and health: AlphaFold: Five years of impact (Nov 2025) Using AI to identify genetic variants in tumors with DeepSomatic (Oct 2025) AI as a research partner: Advancing theoretical computer science with AlphaEvolve (Sept 2025) AlphaGenome: AI for better understanding the genome (June 2025) Accelerating scientific breakthroughs with an AI co-scientist (Feb 2025) Gemini’s advanced thinking capabilities, including Deep Think, also enabled historic progress in mathematics and coding. Deep Think was able to solve problems that require deep abstract reasoning – achieving gold medal-standard in two international contests. Learn more about how we’re advancing natural sciences and mathematics: Gemini achieves gold-medal level at the International Collegiate Programming Contest World Finals (Sept 2025) Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the International Mathematical Olympiad (July 2025) Shaping innovations in computing and the physical world We’re also leading major discoveries and shaping the future of science in areas like quantum computing, energy and moonshots. Research in this area drew new levels of public attention, with progress towards real-world applications of quantum computing as demonstrated by Quantum Echoes and, notably, Googler Michel Devoret becoming a 2025 Physics Nobel Laureate along with former Googler John Martinis and UC Berkeley’s John Clarke, for their foundational 1980s quantum research. Learn more about our work on space infrastructure and quantum computing: Project Suncatcher: Exploring a space-based, scalable AI infrastructure system design (Nov 2025) Googler Michel Devoret awarded the Nobel Prize in Physics (Oct 2025) Our Quantum Echoes algorithm is a big step toward real-world applications for quantum computing (Oct 2025) In 2025, we continued to advance the core infrastructure that powers our AI, focusing on breakthroughs in hardware design and improving energy efficiency. This included the introduction of Ironwood, a new TPU built for the age of inference, which was designed using a method called AlphaChip , alongside a commitment to measuring the environmental impact of our technology. Learn more about how we’re using AI to develop chips, infrastructure and improve energy efficiency: 3 things to know about Ironwood, our latest TPU (Nov 2025) How much energy does Google’s AI use? We did the math (Aug 2025) Ironwood: The first Google TPU for the age of inference (April 2025) Our work in robotics and visual understanding brought AI agents into both the physical and virtual worlds, with advancements like the foundational Gemini Robotics models, the more sophisticated Gemini Robotics 1.5, and the introduction of Genie 3 as a new frontier for general-purpose world models. Learn more about our work with world models and robotics: Gemini Robotics 1.5 brings AI agents into the physical world (Sept 2025) Genie 3: A new frontier for world models (Aug 2025) Gemini Robotics brings AI into the physical world (March 2025) Tackling global challenges and opportunities at scale Our work throughout 2025 demonstrates how AI-enabled scientific progress is being directly applied to address the world's most critical and pervasive challenges. By leveraging state-of-the-art foundational models and agentic reasoning, we are significantly increasing our understanding of the planet and its systems, while also delivering impactful solutions in areas vital to human flourishing, including climate resilience, public health and education. For example, we are using state-of-the-art foundational models and agentic reasoning to help increase our understanding of the planet, helping enable work that is making a difference in people’s lives now from weather predictions to urban planning to public health. For example, our flood forecasting information now covers more than two billion people in 150 countries for severe riverine floods. And our most advanced and efficient forecasting model, WeatherNext 2 can generate forecasts 8x faster and with resolution up to 1-hour. Using this technology, we’ve supported weather agencies in making decisions based on a range of scenarios through our experimental cyclone predictions. Learn more about our work in weather, mapping and wildfires: WeatherNext 2: Our most advanced weather forecasting model (Nov 2025) New updates and more access to Google Earth AI (Oct 2025) Google Earth AI: Our state-of-the-art geospatial AI models (July 2025) AlphaEarth Foundations helps map our planet in unprecedented detail (July 2025) How we're supporting better tropical cyclone prediction with AI (June 2025) Inside the launch of FireSat, a system to find wildfires earlier (March 2025) We are working with partners to apply AI-enabled scientific progress closer to patients, opening up new avenues for disease management and therapeutic discovery. Learn more about our health-related work: Cell2Sentence-Scale 27B: How a Gemma model helped discover a new potential cancer therapy pathway (Oct 2025) From diagnosis to treatment: Advancing AMIE for longitudinal disease management (March 2025) AI is proving to be a powerful tool in education, enabling new forms of understanding and expanding curiosity through initiatives like LearnLM and Guided Learning in Gemini. We brought Gemini’s most powerful translation capabilities to Google Translate, enabling much smarter, more natural and accurate translations and piloting new speech to speech translation capabilities. Learn more about how we’re using AI to enable learning: Bringing state-of-the-art Gemini translation capabilities to Google Translate (Dec 2025) Guided Learning in Gemini: From answers to understanding (Aug 2025) How generative AI expands curiosity and understanding with LearnLM (May 2025) Prioritizing responsibility and safety We couple our research breakthroughs with rigorous and forward-looking work on responsibility and safety. As our models grow more capable, we’re continuing to advance and evolve our tools, resources and safety frameworks to anticipate and mitigate risk. Gemini 3 demonstrated this approach in action: it's our most secure model yet, and has undergone the most comprehensive set of safety evaluations of any Google AI model to date. And we’re looking further ahead, exploring a responsible path to AGI, prioritizing readiness, proactive risk assessment, and collaboration with the wider AI community. Learn more about our responsibility and safety work: You can now verify Google AI-generated videos in the Gemini app (Dec 2025) How we’re bringing AI image verification to the Gemini app (Nov 2025) Strengthening our Frontier Safety Framework (September 2025) Taking a responsible path to AGI (April 2025) Evaluating potential cybersecurity threats of advanced AI (April 2025) Leading frontier collaborations with industry, academia and civil society Advancing the frontier of AI responsibly demands collaboration across all parts of society. In 2025, we worked with leading AI labs to help to form the Agentic AI Foundation and support open standards to ensure a responsible and interoperable future for agentic AI. In education, we’ve partnered with school districts like Miami Dade County and education groups like Raspberry Pi to equip students and educators with AI skills. Our research partnerships with universities like UC Berkeley, Yale, the University of Chicago and many more have been instrumental to some of this year’s most exciting frontier research, and we’re working with the US Department of Energy’s 17 national laboratories to transform how scientific research is conducted. And we’re working with filmmakers and other creative visionaries to put the best AI tools in their hands and explore storytelling in the age of AI. Learn more about our work on frontier collaboration: Google DeepMind supports U.S. Department of Energy on Genesis: a national mission to accelerate innovation and scientific discovery (Dec 2025) Formation of the Agentic AI Foundation (AAIF), Anchored by New Project Contributions Including Model Context Protocol (MCP), goose and AGENTS.md (Dec 2025) Announcing Model Context Protocol (MCP) support for Google services (Dec 2025) Our latest commitments in AI and learning (Nov 2025) Partnering to power Miami’s AI-ready future (Oct 2025) AI on Screen premiere: “Sweetwater” short film explores new AI narratives (Sept 2025) Behind “ANCESTRA”: combining Veo with live-action filmmaking (Jun 2025) How Indian music legend Shankar Mahadevan experiments with Music AI Sandbox (April 2025) Looking ahead As we look towards 2026, we’re looking forward to continuing to advance the frontier, safely and responsibly, for the benefit of humanity. POSTED IN: AI Products Google Research Google DeepMind

OpenAI shares new AI literacy resources to help teens and parents use ChatGPT thoughtfully, safely, and with confidence. The guides include expert-vetted tips for responsible use, critical thinking, healthy boundaries, and supporting teens through emotional or sensitive topics.

Podcast LWiAI Podcast #228 - GPT 5.2, Scaling Agents, Weird Generalization 14 1 1× 0:00 Current time: 0:00 / Total time: -1:26:42 -1:26:42 Audio playback is not supported on your browser. Please upgrade. LWiAI Podcast #228 - GPT 5.2, Scaling Agents, Weird Generalization GPT-5.2 is OpenAI’s latest move in the agentic AI battle, Towards a Science of Scaling Agent Systems, and more! Last Week in AI Dec 17, 2025 14 1 Share Transcript Our 228th episode with a summary and discussion of last week’s big AI news! Recorded on 12/12/2025 Hosted by Andrey Kurenkov and Jeremie Harris Feel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai In this episode: OpenAI’s latest model GPT-5.2 demonstrates improved performance and enhanced multi-modal capabilities but comes with increased costs and a different knowledge cutoff date. Disney invests $1 billion in OpenAI to generate Disney character content, creating unique licensing agreements across characters from Marvel, Pixar, and Star Wars franchises. The U.S. government imposes new AI chip export rules involving security reviews, while simultaneously moving to prevent states from independently regulating AI. DeepMind releases a paper outlining the challenges and findings in scaling multi-agent systems, highlighting the complexities of tool coordination and task performance. Timestamps: (00:00:00) Intro / Banter (00:01:19) News Preview Tools & Apps (00:01:58) GPT-5.2 is OpenAI’s latest move in the agentic AI battle | The Verge (00:08:48) Runway releases its first world model, adds native audio to latest video model | TechCrunch (00:11:51) Google says it will link to more sources in AI Mode | The Verge (00:12:24) ChatGPT can now use Adobe apps to edit your photos and PDFs for free | The Verge (00:13:05) Tencent releases Hunyuan 2.0 with 406B parameters Applications & Business (00:16:15) China set to limit access to Nvidia’s H200 chips despite Trump export approval (00:21:02) Disney investing $1 billion in OpenAI, will allow characters on Sora (00:24:48) Unconventional AI confirms its massive $475M seed round (00:29:06) Slack CEO Denise Dresser to join OpenAI as chief revenue officer | TechCrunch (00:31:18) The state of enterprise AI Projects & Open Source (00:33:49) [2512.10791] The FACTS Leaderboard: A Comprehensive Benchmark for Large Language Model Factuality (00:36:27) Claude 4.5 Opus’ Soul Document Research & Advancements (00:43:49) [2512.08296] Towards a Science of Scaling Agent Systems (00:48:43) Evaluating Gemini Robotics Policies in a Veo World Simulator (00:52:10) Guided Self-Evolving LLMs with Minimal Human Supervision (00:56:08) Martingale Score: An Unsupervised Metric for Bayesian Rationality in LLM Reasoning (01:00:39) [2512.07783] On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models (01:04:42) Stabilizing Reinforcement Learning with LLMs: Formulation and Practices (01:09:42) Google’s AI unit DeepMind announces UK ‘automated research lab’ Policy & Safety (01:10:28) Trump Moves to Stop States From Regulating AI With a New Executive Order - The New York Times (01:13:54) [2512.09742] Weird Generalization and Inductive Backdoors: New Ways to Corrupt LLMs (01:17:57) Forecasting AI Time Horizon Under Compute Slowdowns (01:20:46) AI Security Institute focuses on AI measurements and evaluations (01:21:16) Nvidia AI Chips to Undergo Unusual U.S. Security Review Before Export to China (01:22:01) U.S. Authorities Shut Down Major China-Linked AI Tech Smuggling Network Synthetic Media & Art (01:24:01) RSL 1.0 has arrived, allowing publishers to ask AI companies pay to scrape content | The Verge Discussion about this episode Comments Restacks Podcast Weekly AI summaries and discussion about Last Week's AI News! Subscribe over at https://www.lastweekinai.com/ Weekly AI summaries and discussion about Last Week's AI News! Subscribe over at https://www.lastweekinai.com/ Subscribe Authors Last Week in AI Recent Episodes LWiAI Podcast #237 - Nemotron 3 Super, xAI reborn, Anthropic Lawsuit, Research! Mar 16   •   Last Week in AI LWiAI Podcast #236 - GPT 5.4, Gemini 3.1 Flash Lite, Supply Chain Risk Mar 13   •   Last Week in AI LWiAI Podcast #235 - Sonnet 4.6, Deep-thinking tokens, Anthropic vs Pentagon Mar 5   •   Last Week in AI LWiAI Podcast #234 - Opus 4.6, GPT-5.3-Codex, Seedance 2.0, GLM-5 Feb 17   •   Last Week in AI LWiAI Podcast #233 - Moltbot, Genie 3, Qwen3-Max-Thinking Feb 6   •   Last Week in AI LWiAI Podcast #232 - ChatGPT Ads, Thinking Machines Drama, STEM Jan 28   •   Last Week in AI LWiAI Podcast #231 - Claude Cowork, Anthropic $10B, Deep Delta Learning Jan 21   •   Last Week in AI LWiAI Podcast #230 - 2025 Retrospective, Nvidia buys Groq, GLM 4.7, METR Jan 7   •   Last Week in AI