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FPGAs, ASICs Seen Driving Machine Learning

#artificialintelligence

As machine learning makes steady progress in enterprise datacenters, industry observers are forecasting the emergence of a new wave of machine learning chips in the coming year, a market currently dominated by graphics processors.


Project Catapult - Microsoft Research

#artificialintelligence

Project Catapult is the code name for a Microsoft Research (MSR) enterprise-level initiative that is transforming cloud computing by augmenting CPUs with an interconnected and configurable compute layer composed of programmable silicon. We are living in an era where information grows exponentially and creates the need for massive computing power to process that information. At the same time, advances in silicon fabrication technology are approaching theoretical limits, and Moore's Law has run its course. Chip performance improvements no longer keep pace with the needs of cutting-edge, computationally expensive workloads like software-defined networking (SDN) and artificial intelligence (AI). To create a faster, more intelligent cloud that keeps up with growing appetites for computing power, datacenters need to add other processors distinctly suited for critical workloads.


Is NVIDIA Unstoppable In AI?

Forbes - Tech

In NVIDIA's Q1 2019 quarter, the company once again exceeded expectations, reporting a 66% growth in total revenue, including 71% growth in its red-hot datacenter business (reaching $701M for the quarter). For NVIDIA, the "Datacenter" segment includes High-Performance Computing (HPC), datacenter-hosted graphics, and AI acceleration. While that is certainly an impressive growth rate, it is smaller than the 2-3x year-over-year growth the company has enjoyed over the last few years. This raises a few interesting questions we will examine here. Is this slow-down in growth a sea change or just the law of large numbers catching up with the business?


Intel reveals its Ponte Vecchio GPU for the datacenter

#artificialintelligence

Intel has revealed its long-awaited graphics processing unit (GPU) architecture, which would be the heart of graphics chips designed to handle heavy data and artificial intelligence loads in datacenters. The new Ponte Vecchio GPUs would compete with rival offerings from Nvidia and Advanced Micro Devices. And eventually, the Intel architecture could serve as the foundation for consumer GPU chips from Intel in the future. Intel made the announcement ahead of the Supercomputing 2019 event in Denver. Intel is targeting the high-performance computing (HPC) and AI segments with both the GPU and a new software initiative that aims to shift away from "single-architecture, single-vendor" programming models.


Intel's present and future AI chip business

#artificialintelligence

The future of Intel is AI. Its books imply as much. The Santa Clara company's AI chip segments notched $1 billion in revenue last year, and Intel expects the market opportunity to grow 30% annually from $2.5 billion in 2017 to $10 billion by 2022. Putting this into perspective, its data-centric revenues now constitute around half of all business across all divisions, up from around a third five years ago. Still, increased competition from the likes of incumbents Nvidia, Qualcomm, Marvell, and AMD; startups like Hailo Technologies, Graphcore, Wave Computing, Esperanto, and Quadric; and even Amazon threaten to slow Intel's gains, which is why the company isn't resting on its laurels.