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India is looking beyond AI models to the hardware that feeds them. Electronics and Information Technology Secretary S. Krishnan said India may need stronger oversight of devices connected to AI and biometric authentication systems, including sensors, cameras, biometric scanners, IoT devices, and other data-collecting equipment. Companies serving Indian users may need to review more than model governance and privacy notices. Device sourcing, trusted-vendor requirements, data flows, and audit trails could become part of the compliance work for regional systems built across shared cloud, identity, and security infrastructure. The hardware beyond India’s AI concerns Speaking June 5, Krishnan framed the issue…
The Science Based Targets initiative’s first major overhaul of its influential Corporate Net Zero Standard includes significant changes that prioritize five-year decarbonization milestones and provide additional options for reducing value-chain emissions. Today’s release of Version 2 of the standard, the de facto rulebook for many companies’ decarbonization efforts, arrives close to five years after the original was published and is the second key document in the tenure of former EY consultant and U.K. government climate advisor David Kennedy, who has led SBTi for around a year. The initiative’s new strategic plan, released last month, signaled a shift in emphasis from…
To help models gain expertise for specific development patterns that follow our best practices, we are continuing to expand our repository of Android skills, available through Android CLI and GitHub.Android skills ground LLMs in specialized workflows and domain knowledge, for the most common and more complex user journeys they might struggle with. We’ve shipped a fresh new batch of skills, with now more than 17 skills for areas such as:You can browse skills and install using the Android CLI commands: android skills listandroid skills add –skill= For more information, check out the official documentation. 3. Android Bench adds new modelsEarlier…
Jure Leskovec, Professor of Computer Science at Stanford University and Chief Scientist at Kumo.ai, speaks with host Sriram Panyam about relational and graph language models and their transformative impact on enterprise decision-making and predictive modeling. Jure begins by establishing the critical importance of predictive modeling across industries – from fraud detection in financial institutions to customer churn prediction, lifetime value estimation, product recommendations, and healthcare risk assessment. He notes that while AI has made remarkable advances in natural language understanding and computer vision, predictive modeling over enterprise operational data stored in relational databases has been largely left behind, still relying…
Ingber, D. E. Mechanobiology and diseases of mechanotransduction. Ann. Med. 35, 564–577 (2003).Article PubMed Google Scholar Hannezo, E. & Heisenberg, C. P. Mechanochemical feedback loops in development and disease. Cell 178, 12–25 (2019).Article CAS PubMed Google Scholar van Helvert, S., Storm, C. & Friedl, P. Mechanoreciprocity in cell migration. Nat. Cell Biol. 20, 8–20 (2018).Article PubMed Google Scholar Roca-Cusachs, P., Conte, V. & Trepat, X. Quantifying forces in cell biology. Nat. Cell Biol. 19, 742–751 (2017).Article CAS PubMed Google Scholar Stewart, M. P. et al. Hydrostatic pressure and the actomyosin cortex drive mitotic cell rounding. Nature 469, 226–230 (2011).Article CAS …
Apple’s chip design transforms Mac reliability The success of Apple Silicon hardware is attributed to its simpler design, which integrates multiple components into a single chip, reducing the number of potential failure points. Additionally, Apple Silicon Macs run cooler, leading to less wear and tear on components such as batteries and USB-C ports, the report says. Across the wider laptop market, most studies show hardware faults affect one in five non-Apple machines over their first three years in use. This builds on Apple’s enduring record for making good hardware as independent reliability surveys consistently rank the company as the most…
In January, there was a lot of hype around an announcement from Finnish company Donut Lab: It claimed to have created the world’s first production-ready solid-state battery.The Donut battery, marketed as the energy source behind the Verge TS Pro motorcycle, was allegedly a “pioneer” in bringing this new battery technology to a production-ready electric vehicle. During CES 2026, Donut Lab’s phone-size powerhouse was even a finalist for CNET’s Best Transportation category, where we noted that the cell promised “huge improvements in energy density, charging speed and safety.”But it now appears to be a wolf in sheep’s clothing. The battery is allegedly…
PLDT is set to join Asia’s data center real estate investment trust (REIT) wave with plans for a listing that could be worth as much as $400 million. The board of the Philippines’ telco on Tuesday approved a proposal to float its data center arm Vitro via a REIT.Chairman and CEO Manny Pangilinan said the company aimed to raise between $300 million and $400 million, with the proceeds to be used to pay down debt. He told a shareholder meeting PLDT believed it was “not getting the kind of values we think we ought to get for the data centers.”The operator had explored selling…
AI isn’t coming for HR. It’s already here. Payroll engines are auto-processing tax compliance. Natural language processing (NLP) tools are scanning thousands of resumes in seconds. Conversational AI bots are fielding first-level employee queries around the clock. As HR shifts toward a more data-driven, technology-enabled function, investing in AI and automation skills is becoming essential for long-term career growth and strategic relevance. The HR professionals who treat this as a spectator sport are already falling behind. Those who are actively building AI fluency are earning bigger tables and bigger decisions. This isn’t about replacing human judgment in HR. It’s about…
Announcing the Databricks storage ecosystem: Governing the enterprise data estate, wherever it lives
The Data That Can’t MoveFor years, the enterprise data strategy was simple: move everything to the cloud. Migrate the data lakes and the warehouses to the cloud, and then governance follows. It was a clean story — until it wasn’t.Today, some of the world’s most sophisticated enterprises are telling us clearly: they cannot — and will not — move all of their data to the cloud. Leading semiconductor manufacturers are training models on engineering-classified datasets that must never leave their premises. Global trading firms sit on massive volumes of historical tick data where the economics of cloud egress make migration…
