InfoQ Homepage Artificial Intelligence Content on InfoQ
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Google DeepMind Unveils Gemini Robotics
Google DeepMind has introduced Gemini Robotics, an advanced AI model designed to enhance robotics by integrating vision, language, and action. This innovation, based on the Gemini 2.0 framework, aims to make robots smarter and more capable, particularly in real-world settings.
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Google Cloud's AI Protection: a Solution to Securing AI Assets
Google Cloud introduces AI Protection, a solution to safeguard against generative AI threats. Managing AI risks through vulnerability assessments, security policies, and proactive threat management enhances asset protection. Integrating with Google’s Security Command Center offers a centralized view of IT posture and advanced security intelligence for robust AI system defense.
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Google Introduces AI Co-Scientist System to Aid Scientific Research
Google has announced the development of an AI co-scientist system designed to assist scientists in generating hypotheses and research proposals. Built using Gemini 2.0, the system aims to accelerate scientific and biomedical discoveries by emulating the scientific method and fostering collaboration between humans and AI.
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OpenAI Introduces Software Engineering Benchmark
OpenAI has introduced the SWE-Lancer benchmark, to evaluate the capabilities of advanced AI language models in real-world freelance software engineering tasks.
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Google DeepMind Enhances AMIE for Long-Term Disease Management
Google DeepMind has extended the capabilities of its Articulate Medical Intelligence Explorer (AMIE) beyond diagnosis to support longitudinal disease management. The system is now designed to assist clinicians in monitoring disease progression, adjusting treatments, and adhering to clinical guidelines across multiple patient visits.
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How Engineering Teams Are Tackling AI, Platform Engineering & DevEx: InfoQ Dev Summit Boston 2025
The InfoQ Dev Summit Boston 2025 conference (June 9-10) will bring together senior software practitioners to share proven strategies for integrating AI, scaling resilient architectures, and optimizing developer experience - three key areas that will define engineering success in the next 18 months.
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Using Artificial Intelligence for Analysis of Automated Testing Results
Analysis of automated testing results is a very important and challenging part of testing activities. At any given moment we should be able to tell the state of our product according to the results of automated tests, Maroš Kutschy said at QA Challenge Accepted. He presented how artificial intelligence helps them save time spent on analysis, reduce human errors, and focus on new failures.
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ByteDance Launches New AI Coding Tool Trae with DeepSeek R1 and Claude 3.7 Sonnet Free for All Users
ByteDance, the Chinese owner of TikTok, recently launched Trae, a new AI-powered code editor that offers unlimited free access to DeepSeek R1 and Claude 3.7 Sonnet large language models. Trae has both an international and domestic version, supports Visual Studio Code plug-ins, and competes with an increasing line of AI code editors (e.g., Cursor, Windsurf, PearAI, Replit).
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Hugging Face Publishes Guide on Efficient LLM Training across GPUs
Hugging Face has published the Ultra-Scale Playbook: Training LLMs on GPU Clusters, an open-source guide that provides a detailed exploration of the methodologies and technologies involved in training LLMs across GPU clusters.
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Azure AI Foundry Labs: a hub for the Latest AI Research and Experiments at Microsoft
Microsoft's Azure AI Foundry Labs revolutionizes AI development by bridging cutting-edge research with real-world applications. Offering experimental projects like Aurora and MatterSim empowers developers to prototype new technologies. With tools for dynamic learning and multimodal models, Azure Labs accelerates innovation and collaboration.
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Google Cloud Launches Gen AI Toolbox for Databases
Google Cloud has announced the public beta launch of Gen AI Toolbox for Databases, an open-source server developed in collaboration with LangChain. This new tool is designed to help developers seamlessly integrate production-grade, agent-based generative AI applications with databases while ensuring secure access, scalability, and observability.
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Microsoft Releases BioEmu-1: a Deep Learning Model for Protein Structure Prediction
Microsoft Research has introduced BioEmu-1, a deep-learning model designed to predict the range of structural conformations that proteins can adopt. Unlike traditional methods that provide a single static structure, BioEmu-1 generates structural ensembles, offering a broader view of protein dynamics.
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Microsoft Launches Visual Studio 2022 v17.13 with AI-Powered Enhancements and Improved Debugging
Microsoft has released Visual Studio 2022 v17.13, introducing significant improvements in AI-assisted development, debugging, productivity, and cloud integration. This update focuses on refining workflows, enhancing code management, and improving the overall developer experience.
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Azure AI Agent Service Now in Public Preview for Developers in AI Foundry SDK and Portal
Introducing the Azure AI Agent Service: a groundbreaking platform that empowers developers to design, deploy, and manage intelligent AI agents seamlessly integrated within the Microsoft ecosystem. Automate tasks, access real-time data, and monitor performance, all while benefiting from easy setup and advanced orchestration. Transform your business with AI-driven efficiency and innovation.
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OmniHuman-1: Advancing AI-Generated Human Animation
OmniHuman-1, an advanced AI-driven human video generation model, has been introduced, marking a significant leap in multimodal animation technology. OmniHuman-1 enables the creation of highly lifelike human videos using minimal input, such as a single image and motion cues like audio or video.