Search results for: 'Deep Learning Interfaces: Future of AI (Technical Insights)'

As organizations shift critical workloads to public, private, and hybrid clouds, encrypted data flows and lateral traffic have created visibility gaps that traditional observability tools cannot close. Deep observability has emerged as a strategic imperative for CISOs seeking to eliminate these blind spots, unify telemetry data, and strengthen cybe...

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...

20 Sep 2023  |  Global  |  Technology Research

Edge AI Accelerators—Emerging Opportunity Analysis

Expanding IoT Applications Drive Growth

Infographics

×

Specialized edge AI hardware that enables quick deep learning on-device has become essential due to the rising need for real-time deep learning workloads. Additionally, a cloud-based AI method cannot ensure data privacy, low latency, or offer high bandwidth. As a result, many AI workloads are shifting to the edge, increasing the demand for speciali...

In the realm of technological progress, artificial intelligence (AI) has emerged as a transformative force with the potential to reshape industries of the future. 89% of enterprises believe Generative AI technology will be a disruptive technology for enterprises to create strategic market differentiation. As AI evolves, its profound impact on bus...

Generative AI (Gen AI) continues to create an impact across industries including automotive. In the next decade, Gen AI is expected to significantly influence automotive value chains, increase efficiency, productivity, and reduce wastes. In the supply chain, it will be used to optimize inventory and demand forecasting while in product development i...

AI has moved from being a standalone technology to a core building block that drives global business growth. Advancements in key AI technologies, such as machine learning, deep learning, natural language processing (NLP), and computer vision, are happening at an exponential pace, constantly unlocking new capabilities and applications. AI adoptio...

Disruptive AI models are increasingly challenging traditional assumptions about “classic” cloud data centers. As training clusters scale up to thousands of accelerators and consume tens of megawatts of power, the conventional CPU-centric, air-cooled, monolithic server model is no longer sustainable. This research study explores the megatrend of AI ...

This edition of the IT, Computing and Communication Technology Opportunity Engine captures developments related to Unified AI robotics, Hybrid GPU cloud and MLOps, Production inference stack, Full-stack reinforcement-learning compute, AI Infrastructure, Computer Vision, Software-Defined Applications, Developer Platform & Cloud Application Deploymen...

The research study focuses on user interface applications of advanced touchless sensing technologies. Such advanced technologies as gesture sensing, voice command, brain wave sensing, and eye tracking are creating new opportunities for touchless sensing applications. Next-generation interfaces that are enabled by these advanced touchless technologi...