Generative AI Platforms

Aptiv & Vecna Robotics Partner on Next-Gen Autonomous Mobile Robots (AMRs) for Warehouses Global industrial technology company Aptiv has announced a strategic collaboration with Vecna Robotics, a leader in AI-driven autonomous material handling. The two companies will co-develop next-generation Autonomous Mobile Robot (AMR) solutions aimed at providing cost-effective automation for warehouses and factories. This partnership will integrate Aptiv’s advanced perception and machine learning technologies into Vecna Robotics’ autonomy and orchestration platform. The goal is to create safer, more efficient, and scalable material handling systems. The collaboration will utilize Aptiv’s PULSE Sensor for 360-degree sensing and its ML-based technologies for real-time perception and path planning. Vecna’s platform will contribute to workflow orchestration and safe navigation in complex environments. Aptiv is set to showcase Vecna Robotics’ CPJ Co-Bot Pallet Jack at CES 2026. ...

Google Unveils Gemini 3, Ushering in an ‘Agentic Era’ of AI Google has introduced Gemini 3, a foundational model designed to power a new ‘agentic era’ of AI. Unlike previous models accessed through a single interface, Gemini 3 is being deeply integrated across Google’s product suite—including Search, Workspace, Android, and Cloud—to act as a comprehensive ’nervous system.’ This strategic shift focuses on creating AI systems that can execute actions, not just generate responses. To support this, Google is also releasing tools for developers to leverage the model for complex, long-running coding tasks. ...

AI & Machine Learning: Alibaba’s Omni-Modal AI and Quantum Material Discovery This week in AI and Machine Learning, key advancements include the release of Alibaba’s omni-modal AI, Qwen3-Omni, a new tool from MIT called SCIGEN that uses AI to discover quantum materials, a novel AI framework from Florida Atlantic University for managing complex systems, and a breakthrough in healthcare using AI to predict spinal cord injury outcomes from blood tests. ...

MLCommons Releases MLPerf Inference v5.1, Setting New AI Performance Benchmarks MLCommons has released MLPerf Inference v5.1, the latest version of its benchmark suite, introducing new tests to evaluate AI system performance on modern workloads. This update saw a record 27 organizations submitting systems for evaluation. The new version features three new benchmarks, including one for the DeepSeek-R1 reasoning model, and implements tighter latency requirements for certain large language model tests. Notably, the popular Llama 2 70B benchmark demonstrated significant performance gains, with top systems running up to 50% faster than in the previous release. The v5.1 release also marked the first submission of a heterogeneous system that intelligently balances inference workloads across different accelerator types. ...

AI & ML Developments: NVIDIA GPUs, Mozambique’s Tax Strategy, and University Partnerships Today’s top stories in Artificial Intelligence and Machine Learning feature Lambda’s deployment of Supermicro’s NVIDIA Blackwell GPU servers to expand its AI cloud infrastructure. In other news, Mozambique is adopting a new AI-centric strategy to transform its tax system, and Elizabeth City State University is collaborating with Amazon to advance AI and ML education for its students. Sources: ...

How Google AI’s New Method Reduces LLM Training Data by 10,000x Google Research has unveiled a groundbreaking method for fine-tuning large language models (LLMs) that reduces required training data by up to 10,000 times. This innovative approach utilizes active learning to focus expert labeling on the most informative examples, especially “boundary cases” where model uncertainty is highest. In experiments with Gemini Nano models, this technique matched or surpassed the quality of models trained on 100,000 random labels with as few as 250 to 450 targeted examples. This development promises to make AI model development significantly leaner, more agile, and more cost-effective. ...