Technology

Agentic AI Takes Center Stage, Shifting Focus from Generative Models In March 2026, the artificial intelligence landscape is undergoing a pivotal shift from generative AI to more autonomous, agentic AI systems. These advanced AI agents are engineered to execute complex, multi-step workflows with minimal human oversight, fundamentally transforming business operations. This trend is highlighted by the release of new models like OpenAI’s GPT-5.4, which features native computer-use capabilities, allowing it to interact directly with software interfaces. The industry’s focus is evolving from experimentation to implementation, embedding AI as an invisible infrastructure within enterprise environments. Upcoming events like NVIDIA’s GTC 2026 are also expected to heavily feature agentic and physical AI. ...

Artificial Intelligence & Machine Learning AI Industry Sees Major Developments in Early March 2026 The artificial intelligence sector has experienced a flurry of significant activity in early March 2026, marked by major infrastructure adjustments and new AI model advancements. In a notable development, Oracle and OpenAI have reportedly canceled plans to expand a major AI data center in Texas. This facility was a key part of the ‘Stargate’ infrastructure project, but disagreements over financing and evolving demands from OpenAI led to its cancellation. Concurrently, the AI model landscape continues its rapid evolution with OpenAI’s launch of GPT-5.4, a new model boasting enhanced reasoning and coding capabilities. Adding to the industry’s momentum, the Allen Institute for AI (AI2) has released Olmo Hybrid, a new open-source 7B-parameter model demonstrating improved data efficiency. These events highlight the dynamic nature of the AI industry, with simultaneous shifts in both large-scale infrastructure and the continuous innovation of AI models. ...

IIT Kharagpur Launches New School for Applied AI to Boost Industry Innovation The Indian Institute of Technology (IIT) Kharagpur has announced the launch of its new School of Digital Engineering, Applied Artificial Intelligence, and Machine Learning. This new school is designed to be a premier hub for research and innovation, with a strong focus on industry integration to promote the real-world application of AI technologies. According to the institution’s director, Suman Chakraborty, this initiative represents a significant shift in institutionalizing applied AI. The ultimate goal is to position IIT Kharagpur as a leading global center for developing responsible and sovereign AI for key sectors like healthcare and manufacturing. ...

Biotech’s ‘Builder’ Phase: AI Integration Drives R&D Transformation The biotech industry is shifting from standalone artificial intelligence tools to developing fully integrated, AI-native discovery systems. According to the 2026 Biotech AI Report from Benchling, this new “builder” phase sees organizations reshaping their data infrastructure and company structures to make AI a core component of their research and development models. A common trend is to embed AI leadership directly within R&D to ensure technology remains connected to the experimental context. However, the report highlights that poor data quality and availability are the top reasons for the failure of AI pilot projects. These infrastructure issues are creating a significant bottleneck for AI adoption in more complex areas like generative design and biomarker analysis. ...

Telefónica and Nokia Pioneer New AI-Agent API Monetization Models Telefónica is exploring how agentic AI can shift revenue models for network APIs away from traditional per-call pricing. In a collaboration with Nokia, Telefónica has been testing AI software agents to support network API use as part of the GSMA Open Gateway initiative. A key application, showcased with Mavenir, is a ‘No-Show Prediction’ agent designed to forecast attendance and trigger interventions, reducing missed appointments in sectors like healthcare and retail. According to Telefónica’s Alex Harmand, other monetizable use cases include identity orchestration, context-aware risk scoring for payments, and network quality optimization for enterprise clients. ...

AI Hardware Crisis: Data Centers Buy Out Western Digital’s 2026 Hard Drive Supply The insatiable demand for AI hardware is causing a significant supply chain crisis. Reports confirm that AI data centers have pre-purchased Western Digital’s entire hard drive production capacity for 2026. This hardware crunch extends beyond storage, with Phison’s CEO warning of an imminent “AI memory crisis” that could bankrupt some consumer electronics companies. The massive storage and memory requirements for training and deploying large-scale AI models are diverting critical components from the enterprise and consumer markets, establishing AI development as the primary driver of the global hardware industry. ...

India Hosts Inaugural Global AI Impact Summit in New Delhi The India AI Impact Summit 2026 has commenced in New Delhi, marking the first global AI summit to be hosted in the Global South. The five-day event, held at Bharat Mandapam, brings together global leaders, policymakers, technology companies, and researchers to discuss the future of artificial intelligence with a focus on inclusion and responsible development. Prime Minister Narendra Modi inaugurated the expo, which features 600 startups and 13 country pavilions, underscoring India’s ambition to become a global AI hub. The summit is anchored on three foundational pillars: ‘People, Planet and Progress’. The event aims to foster international collaboration and shape a future where AI serves humanity, drives inclusive growth, and promotes sustainable development. ...

ZKBoost Protocol Unveiled for Private, Verifiable XGBoost AI Model Training Researchers have introduced ZKBoost, a groundbreaking cryptographic protocol designed to verify XGBoost machine learning model training on sensitive datasets without revealing the underlying data or model parameters. ZKBoost is the first zero-knowledge proof of training (zkPoT) protocol specifically developed for XGBoost, a widely-used algorithm for tabular data. This innovation addresses the critical need for cryptographic guarantees of model integrity in high-stakes applications. The system employs a fixed-point implementation of XGBoost compatible with arithmetic circuits, enabling efficient zero-knowledge proofs. Research indicates this implementation maintains accuracy within 1% of the standard XGBoost, making practical verification on real-world data a reality. ...

Roborock Unveils Saros Rover, a Stair-Climbing Robotic Vacuum at CES 2026 Roborock, a global leader in home robotics, has introduced its latest product line at CES 2026, where it was recognized as the most awarded Robotic Vacuum Brand. The highlight of the announcement was the Saros Rover, presented as the world’s first robotic vacuum featuring an AI-powered wheel-leg architecture. This innovative design allows the vacuum to navigate stairs and slopes with human-like agility while simultaneously cleaning them. The keynote, led by Roborock’s President, Quan Gang, also unveiled other new products including the Roborock Saros 20, Roborock Saros 20 Sonic, Roborock F25 ACE Pro, and Roborock Qrevo Curv 2 Flow. These launches were made in partnership with the Real Madrid Football Club for the Vacuum Cleaner category. Additionally, Roborock announced its entry into the US market for lawnmower products with the new RockMow X1 LiDAR. Headquartered in Beijing, Roborock currently serves over 22 million households worldwide. ...

AI Model ‘SleepFM’ Predicts Future Disease Risk from a Single Night’s Sleep Researchers have developed a groundbreaking artificial intelligence foundation model, named SleepFM, that can predict the future risk of various diseases by analyzing data from a single night’s sleep. A study published in Nature Medicine details how the model was trained on over 585,000 hours of polysomnography (PSG) data from approximately 65,000 individuals. SleepFM has demonstrated a remarkable ability to predict the risk of numerous conditions—including dementia, heart failure, chronic kidney disease, and mortality—years before a clinical diagnosis might occur. The model analyzes complex physiological signals captured during sleep to identify patterns indicative of a predisposition to future health issues. This innovative approach could serve as a powerful early warning system, enabling proactive healthcare and early disease detection. ...