Graphics chip giant Nvidia mopped up the floor with its competition in a benchmark set of tests released Wednesday afternoon, demonstrating better performance on a host of artificial intelligence tasks. The benchmark, called MLPerf, announced by the MLPerf organization, an industry consortium that administers the tests, showed Nvidia getting better speed on a variety of tasks that use neural networks, from categorizing images to recommending which products a person might like. Predictions are the part of AI where a trained neural network produces output on real data, as opposed to the training phase when the neural network system is first being refined. Benchmark results on training tasks were announced by MLPerf back in July. Many of the scores on the test results pertain to Nvidia's T4 chip that has been in the market for some time, but even more impressive results were reported for its A100 chips unveiled in May.
This article is part of "Deconstructing artificial intelligence," a series of posts that explore the details of how AI applications work. One of the things that caught my eye at Nvidia's flagship event, the GPU Technology Conference (GTC), was Maxine, a platform that leverages artificial intelligence to improve the quality and experience of video-conferencing applications in real-time. Maxine used deep learning for resolution improvement, background noise reduction, video compression, face alignment, and real-time translation and transcription. In this post, which marks the first installation of our "deconstructing artificial intelligence" series, we will take a look at how some of these features work and how they tie-in with AI research done at Nvidia. We'll also explore the pending issues and the possible business model for Nvidia's AI-powered video-conferencing platform.
I've often wondered why Google doesn't come out with an answer to Amazon's Echo Dot with Clock. Lenovo must have been on the same wavelength, because that's just what the Lenovo Smart Clock Essential is. Actually, it's a better value than the Echo Dot with Clock, because it simultaneously displays all the information you want most frequently--not just the time--and it does it for $10 less than the 4th-gen Echo Dot with Clock. A shrunken sibling of the Lenovo Smart Clock, the Essential is a smart speaker with a 4-inch LED display that shows the current time (with an a.m./p.m. indicator, unless it's set to 24-hour mode), the day of the week (the date would be more useful), the current outdoor temperature (obtained via the internet), and an indicator for an alarm (if one is set). Four LEDs on its face light up when you say the'Hey Google' wake word.
Most of you are probably familiar with the chip giants like Intel & AMD which command a bigger share of the computing processor market, but this entrant to the chip market in 1993 has solidified its reputation as a big name in the arena. Although most well-known for its graphical processing units (GPUs) -- GeForce is its primary & most popular product line, the company also provides system-on-a-chip units (SoCs) for the mobile computing and automotive market. Since 2014, Nvidia has begun to diversify its business from the niche markets of gaming, automotive electronics, and mobile devices. It is now venturing into the futuristic AI, along with providing parallel processing capabilities to researchers and scientists that allow them to efficiently run high-performance applications. Let's review of some these endeavors.
If you're waiting for Amazon Prime Day to kick off tomorrow, you may want to take advantage of the deals that other retailers already have going on. Walmart has already kicked off its own "anti-Prime Day" savings event and with it comes the best price we've seen on the Lenovo Smart Clock. Right now, Walmart has the smart alarm clock for $39, which is $1 cheaper than its previous low and 50 percent off its normal price. This little gadget has gotten quite popular since its release last year. We gave it a score of 87 for its charming design, ambient light sensor, sunrise alarm feature and lack of camera.
Nvidia has announced a new videoconferencing platform for developers named Nvidia Maxine that it claims can fix some of the most common problems in video calls. Maxine will process calls in the cloud using Nvidia's GPUs and boost call quality in a number of ways with the help of artificial intelligence. Using AI, Maxine can realign callers' faces and gazes so that they're always looking directly at their camera, reduce the bandwidth requirement for calls by up to 90 percent by only transmitting "key facial points," and upscale the resolution of videos. Other features available in Maxine include face re-lighting, real-time translation and transcription, and animated avatars. Not all of these features are new of course.
Avaya said that it will integrate Nvidia's Maxine cloud streaming video AI platform into its Avaya Spaces collaboration app. For Avaya, the partnership with Nvidia will enable it to add more visual and virtual experiences to its collaboration platform. Nvidia's Maxine cloud platform has audio, video and conversational AI software to improve video conferencing. Nvidia outlined Maxine at Nvidia GTC along with a bevy of new platforms including Omniverse, a Nvidia RTX-based 3D simulation and collaboration platform that aims to fuse physical and virtual worlds. Avaya Spaces is a video collaboration app that includes workspaces with messaging, content sharing, task tracking and collaboration.
NVIDIA is sitting pretty in AI (artificial intelligence) right now. For the next few years, most AI systems will continue to be trained on NVIDIA GPUs and specialized hardware and cloud services that incorporate these processors. However, NVIDIA has been frustrated in its attempts to become a dominant provider of AI chips for deployment into smartphones, embedded systems, and other edge devices. To address that strategic gap, NVIDIA this past week announced that it is acquiring processor architecture firm Arm Holdings from SoftBank Group and the SoftBank Vision Fund. Once the acquisition closes in the expected 18 months, NVIDIA will retain Arm's name, brand identity, management team, and base of operations in Cambridge, United Kingdom.
In recent years, Nvidia has ridden one of the biggest waves in technology, selling chips needed to build increasingly clever artificial intelligence algorithms. Now, the company plans to catch another big swell--mobile computing--with a $40 billion acquisition of Arm, which designs the chips found in virtually all smartphones. The deal would reshape the chip industry overnight--putting Nvidia at the center of much of the action. But it will face regulatory scrutiny in the UK, Europe, the US, and China, because it would give Nvidia control over the chip blueprints used by multiple tech companies, including its competitors. The news may be especially concerning in China, since it could allow the US to restrict access to chip designs used in a wide array of products.
Jensen Huang is a big idea guy. He transformed a sleepy computer graphics processor company he founded into an artificial intelligence leader. Now he wants to bring AI everywhere. Nvidia ((NVDA) -Get Report) Monday announced that the company will acquire ARM Holdings for $40 billion in cash and stock. ARM is a designer of the low power microchip architecture used for iPhones, Androids and other devices. He began betting on AI way back in 2006.