New information on AI and Machine Learning

08 Feb NVIDIA’s Upcoming GTC 2018 Is The Place To Be If You Are Anyway Involved In AI Or ML

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GTC 2017 opening keynote Every year, NVIDIA holds a series of GPU Technology Conferences, commonly referred to as GTC and gets kicked off with a big event in San Jose and is followed up by regional eventsin places like Beijing, Munich, Tel Aviv, Taipei, Washington DC, and Tokyo. If you or your company is involved […]

27 Jan Don’t Forget About Storage When Planning For AI And ML

Artificial Intelligence (AI) and Machine Learning (ML) are without a doubt the hottest things happening out there in the tech world.  They are changing the way virtually every industry is approaching solving their biggest problems. AI and ML leaders currently span from healthcare to transportation to social media and it’s hard to attend a major tech […]

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

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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 […]

16 Jan Intel Dazzles At CES 2018 Keynote And Gives Progress On Neuromorphic And Quantum Computing

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  Intel CES 2018 This past week, I and several other members of the Moor Insights & Strategy team camped out at CES 2018 in Las Vegas to learn as much as we can about the latest in consumer electronics technology, trends and company strategies. The conference is not only a great opportunity for startups to […]

16 Jan Bowling For AI: Booz Allen Hamilton And Kaggle Launch Data Science Bowl 2018

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This year’s Data Science Bowl focus Anyone who is plugged into the tech world knows that AI and big data is big business right now.  Our technological ability to process and analyze large troves of data grows every year, unlocking new doors at every turn. Big data and AI is big business, but it’s also […]

08 Jan NVIDIA Reinforces Automotive AI Lead With Uber And Volkswagen Announcements At CES 2018

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Under the chaos and fog that is the Customer Electronics Show (CES) this week in Las Vegas, few companies break through the noise and stand out.  CES is the preeminent show for consumer technology vendors.  This year the primary focus of this mega conference is on advancements in robotics (machine intelligence), drones, medical devices, gaming, […]

17 Jul Microsoft Finds Its AI Voice

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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 […]

10 Jul Baidu Adds Momentum To NVIDIA’s Lead In AI

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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 […]

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

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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 […]

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

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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 […]

15 May Why NVIDIA Is Building Its Own TPU

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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 […]

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

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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 […]

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

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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. […]

24 Mar NVIDIA Scores Yet Another GPU Cloud For AI With Tencent

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NVIDIA’s speedy GPUs and Machine Learning software have unquestionably become the gold standard for building Artificial Intelligence (AI) applications. And today, NVIDIA added TenCent to their list of cloud service providers that offer access to NVIDIA hardware in their clouds for AI and other compute intensive applications. This marks a significant milestone in the global […]

17 Mar Why Intel Is Buying Mobileye, And What Does It Need To Do To Be Successful?

In a move that Intel hopes can propel it to the forefront of The Next Big Thing, Intel announced it would purchase Mobileye, an Israeli company that makes sensors and cameras for driverless vehicles. Buying a leader to become a leader is never cheap: Intel will pay $13.3B for the firm, a 34% premium over […]

03 Mar RESEARCH PAPER: A Machine Learning Application Landscape

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2016 was a strong year for Machine Learning (ML) and Artificial Intelligence (AI) with many high tech firms claiming that they are now an “AI Company”, notably Amazon, Baidu, Facebook, Google, IBM, Intel, Microsoft, NVIDIA, and Tesla. In 2017, the field will broaden to include AMD, Qualcomm, and Xilinx. Moor Insights & Strategy (MI&S) expects Machine Learning based AIs […]

03 Mar A Machine Learning Landscape: Where AMD, Intel, NVIDIA, Qualcomm And Xilinx AI Engines Live

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Without a doubt, 2016 was an amazing year for Machine Learning (ML) and Artificial Intelligence (AI) awareness in the press. But most people probably can’t name 3 applications for machine learning, other than self-driving cars and perhaps their voice activated assistant hiding in their phone. There’s also a lot of confusion about where the Artificial […]

06 Jan What To Expect in 2017 From AMD, INTEL, NVIDIA, XILINX And Others For Machine Learning

Without a doubt, 2016 was an amazing year for Machine Learning (ML) and Artificial Intelligence (AI). I have opined on the 5 things to watch in AI for 2017 in another article, however the potential dynamics during 2017 in processor and accelerator semiconductors that enable this market warrant further examination. It is interesting to note […]

06 Jan Five Things To Watch In AI And Machine Learning In 2017

Without a doubt, 2016 was an amazing year for Machine Learning (ML) and Artificial Intelligence (AI). During the year, we saw nearly every high tech CEO claim the mantel of becoming an “AI Company”. However, only a few companies were actually able to monetize their significant investments in AI, notably Amazon, Baidu, Facebook, Google, IBM, […]

13 Dec Amazon’s Xilinx FPGA Cloud: Why This May Be A Significant Milestone

Datacenters, especially the really big guys known as the Super 7 (Alibaba, Amazon, Baidu, Facebook, Google, Microsoft and Tencent), are experiencing significant growth in key workloads that require more performance than can squeezed out of even the fastest CPUs. Applications such as Deep Neural Networks (DNN) for Artificial Intelligences (AIs), complex data analytics, 4K live […]