Karl Freund

Arm Throws Their Axe Into The AI Ocean With Project Trillium

Arm’s OD and ML processors work together to find and identify faces. This blog was co-written by Patrick Moorhead, President and Principal Analyst and Karl Freund, Sr. Analyst, Machine Learning and HPC, Moor Insights & Strategy. Machine learning is the hottest thing in tech right now; hotter than smartphones, hotter than virtual reality, even hotter than …

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Google Announces Expensive Cloud TPU Availability

Google  recently announced that the Google Cloud TPU (announced last May), is now available in limited quantities as a beta on the Google Cloud Platform (GCP) for running TensorFlow-based AI applications. Clearly, the search giant is excited about its shiny new device, which the company has claimed will substantially reduce its datacenter footprint and cost …

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Google, Microsoft, And Amazon Place Bets On AI In The Enterprise

Google just announced significant enhancements to its machine learning services (MLaaS), attempting to close the significant competitive gap that Microsoft  has enjoyed, in my opinion, for the last year or so. Not to be left out, Amazon.com AWS announced the company’s own new MLaaS tools and services at AWS Re:Invent last November, trying to court …

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What’s Hot At SC17: The Synthesis Of Machine Learning & HPC

High Performance Computing (HPC) has historically depended on numerical analysis to solve physics equations, simulating the behavior of systems from the subatomic to galactic scale. Recently, however, scientists have begun experimenting with a completely different approach. It turns out that Machine Learning (ML) models can be far more efficient and even more accurate than the …

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Amazon And NVIDIA Simplify Machine Learning

NVIDIA and Amazon.com have announced new Machine Learning software stacks in the NVIDIA GPU Cloud (NGC), and a new 8 Volta GPU EC2 instance for immediate availability, respectively. While this announcement was completely expected, it is an important milestone along the road to simplifying and lowering the costs of Machine Learning development and deployment for AI …

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Startup Accelize Simplifies FPGA Acceleration

FPGAs have been the hot new topic in data center discussions, ever since Microsoft shared their FPGA successes at the HotChips conference in August. Xilinx  and Amazon Web Services continued to amp up the buzz by partnering with IP providers such as Edico Genome, Ryft Systems Inc., and NGCodec Inc., to deliver acceleration-as-a-service with Amazon …

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NVIDIA Targets Next AI Frontiers: Inference And China

NVIDIA’s meteoric growth in the datacenter, where its business is now generating some $1.6B annually, has been largely driven by the demand to train deep neural networks for Machine Learning (ML) and Artificial Intelligence (AI)—an area where the computational requirements are simply mindboggling. Much of this business is coming from the largest datacenters in the …

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Amazon And Xilinx Deliver New FPGA Solutions

Datacenter adoption of FPGAs for workload acceleration has been a hot topic of late—especially after Microsoft announced significant gains in its datacenter at the Hot Chips conference in August. However, due to the rare skillset these reconfigurable silicon platforms demand, widespread adoption has been slow to materialize outside of Microsoft . I believe that might …

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Microsoft: FPGA Wins Versus Google TPUs For AI

The Microsoft Brainwave mezzanine card extends each server with an Intel Altera Stratix 10 FPGA accelerator, synthesized to act as a “Soft DNN Processing Unit,” or DPU, and a fabric interconnect that enables datacenter-scale persistent neural networks. At the recent Hot Chips conference, three of the world’s largest datacenter companies detailed projects that exploit Field …

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Will ASIC Chips Become The Next Big Thing In AI?

When Google announced its second generation of ASICs to accelerate the company’s machine learning processing, my phone started ringing off the hook with questions about the potential impact on the semiconductor industry. Would the other members of the Super 7, the world’s largest datacenters, all rush to build their own chips for AI? How might …

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Microsoft Finds Its AI Voice

Microsoft held an intimate analyst and press event in London this week, coincident with the 20th anniversary of the founding of the Cambridge Research Lab, the European hub led by Professor Christopher Bishop. Microsoft now employs over 7,000 Artificial Intelligence (AI) research scientists and development engineers around the world under Microsoft Research (MSR) Executive VP …

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Baidu Adds Momentum To NVIDIA’s Lead In AI

It is not much of an exaggeration to say that Artificial Intelligence (AI), in its present form, would not be possible without NVIDIA GPUs. NVIDIA has enjoyed near-universal support from some of the largest adopters of Machine Learning technology, as NVIDIA’s speedy GPUs accelerate the training and use of the Deep Neural Networks that enable …

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ISC17: HPC Embraces Diversity As AMD & ARM Up The Ante Vs. Intel, IBM And NVIDIA

Renewed Competition in HPC Will Enable Workload Optimization Intel has enjoyed a dominant position in High Performance Computing (HPC) processors for nearly a decade now, with only IBM  POWER offering a viable CPU alternative, since Advanced Micro Deviceseffectively, albeit perhaps unintentionally, exited the market in 2010. Meanwhile, NVIDIA has kept things interesting by delivering GPUs as …

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Google Cloud TPU: Strategic Implications For Google, NVIDIA And The Machine Learning Industry

Google  announced the 2nd generation of the company’s TensorFlow Processing Unit (TPU), now called the Cloud TPU, at the annual Google I/O event, wowing the industry with performance for Machine Learning that appeared to eclipse NVIDIA’s Tesla Volta GPU only one week after that chip was launched. (See below why I say “appeared”.) Unlike Google’s …

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RESEARCH BRIEF: AMD Lays The Foundations For Machine Learning With Radeon Vega Frontier & Optimized Software

Advanced Micro Devices (AMD) has shared more details about its upcoming code-named “Vega” family of GPUs, as well as information regarding the progress the company has made with its open-source ROCm software stack for HPC and Machine Learning (ML). Investors and AI practitioners alike would like to see AMD enter this market as a second …

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AMD Targets Machine Learning With New Radeon Vega Frontier & Optimized Software

Advanced Micro Devices  (AMD) has shared more details about its upcoming Vega family of GPUs, as well as information regarding the progress the company has made with its open-source ROCm software stack for HPC and Machine Learning (ML). These new Vega GPUs look like they have sufficient performance to be in the same ballpark as …

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Why NVIDIA Is Building Its Own TPU

The blistering pace of innovation in artificial intelligence for image, voice, robotic and self-driving vehicle applications has been fueled, in large part, by NVIDIA’s GPU chips that deliver the massive compute power required by the underlying math required for Deep Learning. While NVIDIA continues to reap the benefits of its investments in GPUs, there has …

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NVIDIA GPU Cloud: It’s Not What You May Think It Is

NVIDIA made a slew of important announcements at its annual GPU conference today, including new hardware, new software and a new design win (Toyota) for self-driving cars. I will cover these announcements in a separate article. But one announcement in particular has created some confusion that I’d like to help clear up, and that’s the …

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Google’s TPU For AI Is Really Fast, But Does It Matter?

After nearly a year since the introduction of the Google TensorFlow Processing Unit, or TPU, Google has finally released detailed performance and power metrics for its in-house AI chip. The chip is impressive on many fronts, however Google understandably has no plans to sell it to its competitors, so its impact on the industry is debatable. …

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