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A British government official added a new wrinkle to United Kingdom’s investigation of Nvidia’s proposed $40 billion Arm acquisition by directing the agency to probe the national security implications of the buyout.
The U.K.’s Competition and Markets Authority, which scrutinizes mergers and acquisitions on anti-competition and monopoly grounds, launched an investigation into the deal’s impact on competition back in January. On Monday, the U.K.’s Secretary of State for Digital, Culture, Media and Sport directed the CMA to consider the national security component. The directive is ostensibly because the deal would transfer ownership of Arm, a crown jewel of the U.K.’s high-tech portfolio, to a foreign-owned (in this case, American) entity. The Secretary asked the CMA, whose role is similar to that of the U.S. Federal Trade Commission, to report its findings by July 30.
Arm ecosystem partners I’ve spoken with hope the latest development is a sign regulators are waking up to the notion that the buyout is bad for just about everybody but Nvidia.
It’s an understandable sentiment. The fortunes of hundreds of licensees, developers, and others are so inexorably enmeshed with the Arm platform that they have no choice but to accept the deal and stick with the relationship post-acquisition. Many of them view the acquisition — a transfer of ownership from a neutral third party that benefits when everyone is successful to an aggressive competitor that stands to gain at their expense — as an existential threat. But they are unwilling to speak on the record for fear of retribution from Nvidia, should regulators approve the deal over their objections.
The FTC is reportedly taking a second, more intense look at the deal as well. Which it should.
Bad for everyone but Nvidia
Arm is a foundational building block for myriad electronics markets, including smartphones, wearables, automobiles, industrial robotics, IoT, and — increasingly — the datacenter, as I said in today’s Feibus Tech report, Nvidia and Arm: The Perils of Technology Platform Acquisitions. If Nvidia owned Arm, it could, for example, focus resources on the market it cares most deeply about — specifically, the datacenter, where its high-profit GPUs are a leading source of processing power for artificial intelligence applications. It could forcibly link its own GPUs to Arm cores — whether applications needed them or not — and rationalize much higher licensing fees as a result.
To allow any company with a vested interest to take the reins of an organization that has to date functioned as a neutral standards-setting body is blatantly anti-competitive.
The company underscored its interest in the datacenter last week at its annual GTC developer conference, when it announced a new Arm-based datacenter processor that will feature its own proprietary high-speed link to its GPUs. Project Grace, which is based on a new Arm datacenter platform unveiled last September, won’t hit the market before 2023.
Grace is widely seen as a shot across the bow at Intel, which dominates the datacenter CPU market. But it is far more than that.
Indeed, given that Nvidia hopes to be the eventual owner of Arm, the news of Project Grace should raise questions for regulators. For example, why does Nvidia feel it needs to buy Arm, when it can develop a new CPU as a licensee for a fraction of the cost?
Nvidia also raised eyebrows at GTC 21 when it revealed that Project Grace would feature NVLink, the company’s proprietary high-speed data connection between the CPU and its market-leading GPUs for AI in the datacenter. This means none of the growing number of AI alternatives would work with the new CPU.
As an Arm licensee, Nvidia’s design decision makes absolute sense. But coming from the hopeful owner of the platform, the move smacks of anticompetitive behavior. Once it owned Arm, would Nvidia carry the design choice over to that side of the house, thereby locking AI alternatives out of Arm-based datacenter systems? Would it weave NVLink into an Arm license, raising the price as a result? Might the company also cut competitive graphics designs out of the smartphone market?
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All legitimate questions, and with potentially unsettling answers. The U.S. government should follow Britain’s lead on this investigation. When you get right down to it, allowing a company to buy what is effectively a standards-setting body that so many companies entrust with their livelihoods is a national security issue. We usually evoke national security concerns when a foreign company acquires an American company. But the concerns are just as valid when it’s the reverse, when the target is a foreign-based asset being acquired by a U.S. company.
Mike Feibus is president and principal analyst of FeibusTech, a Scottsdale, Arizona-based technology market research and consulting firm. Reach him at mikef@feibustech.com. Follow him on Twitter @MikeFeibus.
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GTC --NVIDIA today announced availability of the NVIDIA Jarvis framework, providing developers with state-of-the-art pre-trained deep learning models and software tools to create interactive conversational AI services that are easily adaptable for every industry and domain.
Drivers nektar sound cards & media devices. With billions of hours of phone calls, web meetings and streaming broadcast video content generated daily, NVIDIA Jarvis models offer highly accurate automatic speech recognition, as well as superhuman language understanding, real-time translations for multiple languages, and new text-to-speech capabilities to create expressive conversational AI agents.
Utilizing GPU acceleration, the end-to-end speech pipeline can be run in under 100 milliseconds — listening, understanding and generating a response faster than the blink of a human eye — and can be deployed in the cloud, in the data center or at the edge, instantly scaling to millions of users.
“Conversational AI is in many ways the ultimate AI,” said Jensen Huang, founder and CEO of NVIDIA. “Deep learning breakthroughs in speech recognition, language understanding and speech synthesis have enabled engaging cloud services. NVIDIA Jarvis brings this state-of-the-art conversational AI out of the cloud for customers to host AI services anywhere.”
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NVIDIA Jarvis will enable a new wave of language-based applications previously not possible, improving interactions with humans and machines. It opens the door to the creation of such services as digital nurses to help monitor patients around the clock, relieving overloaded medical staff; online assistants to understand what consumers are looking for and recommend the best products; and real-time translations to improve cross-border workplace collaboration and enable viewers to enjoy live content in their own language.
Accton driver download for windows 10. Jarvis has been built using models trained for several million GPU hours on over 1 billion pages of text, 60,000 hours of speech data, and in different languages, accents, environments and lingos to achieve world-class accuracy. For the first time, developers can use NVIDIA TAO, a framework to train, adapt and optimize these models for any task, any industry and on any system with ease.
Developers can select a Jarvis pre-trained model from NVIDIA’s NGC™ catalog, fine-tune it using their own data with the NVIDIA Transfer Learning Toolkit, optimize it for maximum throughput and minimum latency in real-time speech services, and then easily deploy the model with just a few lines of code so there is no need for deep AI expertise.
Broad Industry Support
Netvision techinology driver download for windows 10. Since Jarvis’ early access program began last May, thousands of companies have asked to join. Among early users is T-Mobile, the U.S. telecom giant, which is looking to AI to further augment its machine learning products using natural language processing to provide real-time insights and recommendations.
“With NVIDIA Jarvis services, fine-tuned using T-Mobile data, we’re building products to help us resolve customer issues in real time,” said Matthew Davis, vice president of product and technology at T-Mobile. “After evaluating several automatic speech recognition solutions, T-Mobile has found Jarvis to deliver a quality model at extremely low latency, enabling experiences our customers love.”
NVIDIA is also partnering with Mozilla Common Voice, an open source collection of voice data for startups, researchers and developers to train voice-enabled apps, services and devices. The world’s largest multi-language, public domain voice dataset, Common Voice contains over 9,000 total hours of contributed voice data in 60 different languages. NVIDIA is using Jarvis to develop pre-trained models with the dataset, and then offer them back to the community for free.
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“We launched Common Voice to teach machines how real people speak in their unique languages, accents and speech patterns,” said Mark Surman, executive director at Mozilla. “NVIDIA and Mozilla have a common vision of democratizing voice technology — and ensuring that it reflects the rich diversity of people and voices that make up the internet.”
NVIDIA’s conversational AI tools have had more than 45,000 downloads. These can be combined with technology from hundreds of partners and support leading software libraries, allowing developers worldwide to build innovative and intuitive conversational AI applications.
“Jarvis has a wide selection of pre-trained models, making it a truly end-to-end pipeline for conversational AI — from automatic speech recognition, natural language processing and text-to-speech,” said Harrison Kinsley, YouTuber and founder of PythonProgramming.net. “All of the models are shockingly fast and well optimized and the API is easy for developers to use with examples that apply to many conversational AI tasks.”
Availability
Newly announced features will be released in the second quarter as part of the ongoing NVIDIA Jarvis open beta program. Developers can download it today from NGC with more information available here.
Register for free to learn more about NVIDIA Jarvis during GTC21, taking place online April 12-16. Tune in to watch Huang’s GTC21 keynote address streaming live on April 12 starting at 8:30 a.m. PT.