Software Engineering

Esaote Unveils AI-Powered Cardiac Ultrasound at ESC 2025 for Enhanced Diagnostics Medical imaging company Esaote is set to introduce significant AI enhancements to its cardiac ultrasound technology at the European Society of Cardiology (ESC) 2025 conference. The system utilizes machine learning algorithms to improve image clarity and diagnostic accuracy. This innovation in AI-driven medical imaging aims to enhance cardiac workflows and enable quicker, more reliable interpretation of results for healthcare professionals. ...

Stellantis Halts Level 3 Autonomous Driving Program, Citing High Costs and Low Demand Stellantis has officially suspended the development and launch of its Level 3 autonomous driving system, known as AutoDrive. The decision to halt the self-driving technology program is attributed to significant development costs, technical complexity, and a perceived lack of consumer demand for the advanced feature. While the company stated the AV technology is ready for deployment, it has been put on hold with no immediate plans for a market launch. This move is seen as a strategic reset for the automaker, which will now increase its reliance on external suppliers and technology partners like aiMotive for future autonomous systems. The work already completed on the Level 3 system will be integrated into future platform developments, reflecting the broader challenges legacy automakers face in the competitive autonomous vehicle sector. ...

Anscer Robotics Launches LBR 500 AMR to Automate Indian Manufacturing Bengaluru-based Anscer Robotics has launched the LBR 500, a low-bed autonomous mobile robot (AMR) designed to automate material movement using trolleys within Indian manufacturing facilities. Developed in response to the widespread use of trolleys for material handling in local factories, the LBR 500 is engineered for compatibility with a diverse range of existing trolleys. The AMR features a 500 kg load capacity, an 8-hour operational runtime on a single charge, and a top speed of 1.2 meters per second. To ensure safe collaboration with human workers, the robot adheres to ISO 13849 and PLd Category 3 safety standards. Anscer Robotics is also making the technology accessible to small and medium-sized enterprises through a Robots-as-a-Service (RaaS) model. ...

Meta and Google Ink Massive $10 Billion Cloud Computing Deal for AI Expansion Meta Platforms and Google have reportedly entered into a six-year cloud computing agreement valued at over $10 billion. This strategic partnership will see Meta leverage Google Cloud’s servers, storage, and networking services to power its expanding AI infrastructure. The deal comes as Meta plans to invest hundreds of billions in building large-scale AI data centers. This agreement marks Google’s second major cloud deal recently, following a similar one with OpenAI, highlighting the surging demand for robust cloud infrastructure to support advanced AI development. To help finance these ambitious projects, Meta is also seeking external partners and plans to offload $2 billion in data center assets. ...

Cyware Launches Open-Source AI Server to Secure Threat Intelligence At the Black Hat USA 2025 conference, cybersecurity firm Cyware announced the launch of its open-source Model Context Protocol (MCP) Server. This new tool is designed to securely connect large language models (LLMs) with threat intelligence and automation systems. The MCP Server allows security teams to use natural language inputs to initiate real-world actions and investigations while maintaining full context and control. The move reflects a broader trend of viewing AI as a practical tool for improving security operations by reducing investigation times and improving data correlation. By open-sourcing the server, Cyware aims to foster collaboration and interoperability within the cybersecurity community. ...

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. ...

Medallion Raises $43M to Streamline Healthcare Credentialing with AI Platform Medallion, a healthcare technology company, has secured $43 million in new funding for its AI-powered platform, CredAlliance. The platform is designed to streamline the complex healthcare credentialing process for both insurers and clinicians. It manages the entire provider lifecycle—including credentialing, enrollment, onboarding, and compliance—aiming to significantly reduce administrative waste and combat clinician burnout. CredAlliance acts as a unified system for provider data management, enabling customers to efficiently verify credentials and maintain up-to-date network information. This latest investment, led by Acrew Capital, elevates Medallion’s total funding to $130 million and will fuel the expansion of the platform’s capabilities. ...

Google Launches Gemma 3 270M: A Compact AI Model for Specialized Tasks Google has introduced Gemma 3 270M, a new and compact AI model featuring 270 million parameters. This model is engineered for efficient, task-specific fine-tuning and offers robust instruction-following capabilities directly out of the box. Its minimal footprint makes it ideal for on-device and research applications, enabling developers to build and deploy multiple custom models for tasks like text classification and data extraction without requiring significant computational overhead. Google is providing both pretrained and instruction-tuned versions of the model through platforms such as Hugging Face, Ollama, and Kaggle. ...

OpenAI Releases GPT-OSS, Its First Open-Source Large Language Models In a significant move for the AI and open-source software communities, OpenAI has released GPT-OSS, its first-ever family of open-source large language models. Licensed under the permissive Apache 2.0, this release introduces two powerful models: gpt-oss-120b and gpt-oss-20b. Both are engineered for efficient inference and strong reasoning, leveraging a Mixture-of-Experts (MoE) architecture. The larger gpt-oss-120b model rivals OpenAI’s proprietary o4-mini and operates on a single 80GB GPU. Meanwhile, the compact gpt-oss-20b model, comparable to o3-mini, is optimized for on-device AI applications, requiring as little as 16GB of memory. Complementing the models, OpenAI also launched ‘Harmony,’ an open-source project defining a new prompt template format. ...

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. ...