InfoQ Homepage Deep Learning Content on InfoQ
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Qwen Team Open Sources State-of-the-Art Image Model Qwen-Image
Qwen Team recently open sourced Qwen-Image, an image foundation model. Qwen-Image supports text-to-image (T2I) generation and text-image-to-image (TI2I) editing tasks, and outperforms other models on a variety of benchmarks.
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Amazon Launches Bedrock AgentCore for Enterprise AI Agent Infrastructure
Amazon announced the preview of Amazon Bedrock AgentCore, a collection of enterprise-grade services that help developers deploy and operate AI agents at scale across frameworks and foundation models. The platform addresses infrastructure challenges developers face when building production AI agents.
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Microsoft Adds Deep Research Capability in Azure AI Foundry Agent Service
Unlock the future of research with Microsoft’s Azure AI Foundry Agent Service, featuring Deep Research—an innovative tool that empowers knowledge workers in complex fields. This advanced AI capability autonomously analyzes and synthesizes web data, automating rigorous research tasks while ensuring traceability and transparency. Sign up for the public preview today!
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Agentica Project's Open Source DeepCoder Model Outperforms OpenAI's O1 on Coding Benchmarks
The Agentica Project and Together AI have released DeepCoder-14B-Preview, an open source AI coding model based on Deepseek-R1-Distilled-Qwen-14B. The model achieves a 60.6% pass rate on LiveCodeBench, outperforming OpenAI's o1 model and matching the performance of o3-mini.
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Amazon Open Sources Strands Agents SDK for Building AI Agents
Amazon has released Strands Agents, an open source SDK that simplifies AI agent development through a model-driven approach. The framework enables developers to build agents by defining prompts and tool lists with minimal code.
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OpenAI’s Stargate Project Aims to Build AI Infrastructure in Partner Countries Worldwide
OpenAI has announced a new initiative called "OpenAI for Countries" as part of its Stargate project, aiming to help nations develop AI infrastructure based on democratic principles. This expansion follows the company's initial $500 billion investment plan for AI infrastructure in the United States.
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DeepSeek Launches Prover-V2 Open-Source LLM for Formal Math Proofs
DeepSeek has released DeepSeek-Prover-V2, a new open-source large language model specifically designed for formal theorem proving in Lean 4. The model builds on a recursive theorem proving pipeline powered by the company's DeepSeek-V3 foundation model.
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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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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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AMD and Johns Hopkins Researchers Develop AI Agent Framework to Automate Scientific Research Process
Researchers from AMD and Johns Hopkins University have developed Agent Laboratory, an artificial intelligence framework that automates core aspects of the scientific research process. The system uses large language models to handle literature reviews, experimentation, and report writing, producing both code repositories and research documentation.
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DeepSeek Open-Sources DeepSeek-V3, a 671B Parameter Mixture of Experts LLM
DeepSeek open-sourced DeepSeek-V3, a Mixture-of-Experts (MoE) LLM containing 671B parameters. It was pre-trained on 14.8T tokens using 2.788M GPU hours and outperforms other open-source models on a range of LLM benchmarks, including MMLU, MMLU-Pro, and GPQA.
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QCon SF: Large Scale Search and Ranking Systems at Netflix
Moumita Bhattacharya spoke at QCon SF 2024 about state-of-the-art search and ranking systems. She gave an overview of the typical structure of these systems and followed with a deep dive into how Netflix created a single combined model to handle both tasks.
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Meta AI Introduces Thought Preference Optimization Enabling AI Models to Think before Responding
Researchers from Meta FAIR, the University of California, Berkeley, and New York University have introduced Thought Preference Optimization (TPO), a new method aimed at improving the response quality of instruction-fine tuned LLMs.
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PyTorch 2.5 Release Includes Support for Intel GPUs
The PyTorch Foundation recently released PyTorch version 2.5, which contains support for Intel GPUs. The release also includes several performance enhancements, such as the FlexAttention API, TorchInductor CPU backend optimizations, and a regional compilation feature which reduces compilation time. Overall, the release contains 4095 commits since PyTorch 2.4.
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Meta Releases Llama 3.2 with Vision, Voice, and Open Customizable Models
Meta recently announced Llama 3.2, the latest version of Meta's open-source language model, which includes vision, voice, and open customizable models. This is the first multimodal version of the model, which will allow users to interact with visual data in ways like identifying objects in photos or editing images with natural language commands among other use cases.