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Weekly Tech News: AI, Robotics, Autonomous Vehicles & Cloud Innovations Google’s Gemini 2.5 AI Wins Gold Medal in Global Programming Contest A specialized version of Google DeepMind’s Gemini 2.5 AI model, known as Deep Think, has achieved a gold medal-level ranking at the prestigious International Collegiate Programming Contest (ICPC). Held in Baku, Azerbaijan, the competition featured 139 of the world’s top university programming teams. Gemini 2.5 Deep Think successfully solved 10 of the 12 complex algorithmic problems, placing it second overall compared to the human teams. ...

Tech News Roundup: Anthropic, Quantinuum, and Kubernetes Updates This week’s technology digest highlights major developments across the industry, from a landmark legal settlement in AI that could reshape how models are trained, to massive funding in quantum computing, and crucial updates for cloud-native infrastructure and open-source software. Anthropic’s $1.5B Settlement Over AI Training Data Sets Industry Precedent AI company Anthropic has agreed to a $1.5 billion settlement in a major lawsuit concerning the use of pirated books to train its AI models. The lawsuit, filed by authors, alleged that the company used their copyrighted works without permission to develop its chatbots. This settlement represents a significant moment for the AI industry and could establish new standards regarding the use of copyrighted materials for training large language models (LLMs). ...

Liquid AI Releases LFM2-VL: Open-Weight Vision-Language Models for On-Device AI Liquid AI has released LFM2-VL, a new family of open-weight vision-language foundation models created for low-latency, on-device deployment. The new models are designed to run efficiently on smartphones, laptops, wearables, and other embedded systems without needing to rely on cloud infrastructure. LFM2-VL is available in two versions: LFM2-VL-450M for highly resource-constrained devices and the more powerful LFM2-VL-1.6B. These models can process both text and images, offering up to twice the inference speed on a GPU compared to similar existing models. The models are available on Hugging Face under a license based on Apache 2.0, allowing for free academic and research use, as well as commercial use for smaller companies. ...

MIT Report: 95% of Enterprise GenAI Projects Fail to Deliver ROI A new report from MIT’s NANDA initiative reveals that a staggering 95% of enterprise generative AI pilot programs are failing to produce a significant return on investment. Despite investments totaling between $35 and $40 billion in the US, only 5% of organizations have successfully deployed AI tools into production at scale. The report, titled “The GenAI Divide: State of AI in Business 2025,” is based on interviews with enterprise leaders, analysis of public AI initiatives, and a survey of business professionals. The primary reasons for failure are not a lack of infrastructure or talent, but rather the inability of AI systems to retain data, adapt, and learn over time. The study also found that purchasing AI tools from vendors and forming partnerships has a significantly higher success rate than in-house development. ...

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. ...

OpenAI Reverses Course on Searchable ChatGPT Conversations OpenAI has disabled a feature that allowed users to make their ChatGPT conversations discoverable by search engines. The move comes after reports revealed that private and sensitive user chats were appearing in Google search results. OpenAI’s CISO, Dane Stuckey, called the feature a “short-lived experiment” that created too many risks of accidental sharing. While the feature was opt-in, the incident has sparked significant concern over user privacy and data protection in AI applications. ...