Search results for: 'Learning Expert-Level Racing Strategies Via Scheduled Cost Functions in Model Predictive Control'

Traditional training environments face patient safety risks, resource constraints, and limited exposure to rare event scenarios. Additionally, physical simulations are costly, limiting accessibility (especially in resource-constrained settings). Current simulation models lack personalization, resulting in operational complexity for hospitals due to...

Enterprise digitalization and surging adoption of IoT applications have led to voluminous amounts of complex structured and unstructured data that require processing to draw meaningful insights. A Frost & Sullivan voice of customer (VOC) global survey on artificial intelligence (AI) finds that 43% of enterprises list data-centricity as a key busine...

This edition of IT, Computing and Communications (ITCC) Technology Opportunity Engine (TOE) captures developments related to Artificial intelligence, Augmented Reality, Virtual Reality, Generative AI, Machine Learning Models, and Robotics Process Automation. These technologies empower users to devote their efforts to higher-value activities by auto...

29 Jul 2021  |  Global  |  Technology Research

Federated Learning: New Approach to Building AI Models

Leveraging Open Source Tools to Accelerate Technology Development across Organizations and Regions

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Traditional machine learning (ML) models are centralized and involve vast amounts of data. However, both the urgency to guarantee data privacy and to abide by strict regulations imposed across regions have contributed to the emergence of a new and powerful alternative technique, federated learning. Instead of acquiring data from a central server or...

Some fifteen years after the cloud burst into our consciousness, enterprises are no longer exploring the model, but honing it. In 2023, the focus will be on optimizing complex hybrid, multicloud environments—for cost, app performance, and flexibility. Increasingly important use cases, leveraging Internet of Things (IoT) and artificial intelligence ...

This edition of the IT, Computing and Communication Technology Opportunity Engine explores growth in AI-driven intelligence, synthetic data, multi-modal AI, intelligent document processing, workflow automation, finance orchestration, compliance automation, embedded finance, cross-border payments, blockchain-enabled trade finance, tokenization, priv...

As digitization progresses across industries, AI is gaining a ubiquitous adoption as more and more business processes are being automated. With this, the expectations from AI in terms of what applications can be realized using AI is also expanding, and thus a more complex set of neural networks have been introduced which are expected to leverage ad...

Intelligent network automation is transforming the enterprise network infrastructure and how networks are managed and optimized. Network services industry participants are developing and integrating AI technologies to automate various network operation processes and tasks. Network operation and management are complex, and automated network function...

The rapid rise of agentic AI marks a fundamental shift in how organizations design, deploy, and oversee intelligent systems. This study examines that shift through the lens of the Moltbook incident—an early 2026 event in which autonomous agents, operating without sufficient safeguards, produced a cascade of unpredictable interactions. Far from sign...