How Self-Driving Cars Will Boost Nvidia’s Stock

The driverless vehicle industry is showing signs of accelerating, which is great news for the company leading the way in producing the mechanical brain that aims to one day replace that of the human driver. With its DRIVE PX artificial intelligence (AI) computing platform, as well as being regarded as the market leader in centralized fusion processing by analysts at Needham & Co., Nvidia Corp. (NVDA) is well positioned to be that company, according to Barron’s.

Last week’s $450 million acquisition of self-driving startup NuTonomy by Delphi Automotive is just the most recent sign that the autonomous driving industry is alive and well. But, other big names including Tesla Motors Inc., (TSLA), Alphabet’s Google Inc. (GOOGL), Uber, General Motors (GM), BMW (BMW) and Mercedes (DAI), continue to push for market dominance. The next phase of this push will likely see increasing growth of autonomous vehicle testing fleets. (To read more, see: How Google Will Beat Tesla, GM in Self-Driving Cars.)

Key Partnership

NuTonomy, which operates 60 self-driving test vehicles, was partnered with Nvidia prior to Delphi’s acquisition announcement. According to the analysts at Needham, Nvidia will benefit as Delphi will only help speed up NuTonomy’s ambitious plans of deploying a self-driving taxi service in Singapore sometime next year.

The partnership with Nvidia was key for NuTonomy’s push for the coveted goal of Level 5 autonomy, the highest ranking for driverless vehicles indicating full operational capabilities under any roadway or environmental condition without human aid or intervention. Nvidia’s DRIVE PX Pegasus “is the kind of platform that will be required to support” the systems of a Level 5 autonomous vehicle, according to NuTonomy’s CEO Karl Iagnemma. (To read more, see: Why Nvidia, Intel, AMD, Broadcom Could Surge on Momentum.)

An AI Advantage

The DRIVE PX is an AI system that combines a number of technologies that enable an automobile to sense its surroundings through the fusion of data collected by cameras and other sensors, and then to be able to respond to that data, maneuvering the vehicle in a way that allows passengers to arrive safely at their destination.

Pegasus, unveiled just weeks ago, is Nvidia’s latest DRIVE PX platform. CEO Jensen Huang claims that the new platform has AI performance capabilities of a data center with 100 servers, and will make Level 5 driverless vehicles a reality. That means we could someday be living in a world where human drivers are obsolete. (To read more, see: NVIDIA Launches Chip for Autonomous Vehicles.)

With Pegasus set to be made available to Nvidia’s automotive partners in mid 2018, that world may come a lot sooner than you think.

Nvidia’s GeForce Now turns MacBooks into GTX 1080 gaming machines through the cloud

GeForce Now GPU stack

Yet again, my job is being threatened by a streaming service. First it was Blade’s Shadow PC and now it’s Nvidia’s GeForce Now cloud gaming service. Nvidia are currently carousing Mac users into ditching a potential PC build and opting instead for their latest cloud venture, offering GTX 1080 power with none of the physical components required.

Want the real deal? Here are our picks for the best graphics cards money can buy.

It’s not often we talk about Macs here at PCGamesN – for obvious reason – yet Nvidia’s GeForce Now essentially loans out a GTX 1080-powered PC to Mac users, through the power of the cloud, so they get a pass this time. Thanks to the lack of local device rendering or processing, you can even play PC-only titles through the service such as the enormously popular PlayerUnknown’s Battlegrounds.

I gave PUBG a go myself on my ageing MacBook Pro Early 2011 model – this laptop struggles when opening an email – and GeForce Now not only managed to successfully load PUBG, but I enjoyed the game on full-blast ultra settings. My gigantic Corsair Air 540 PC fitted with an albeit slightly dated AMD R9 390 could barely deal with this game at far less graphical fidelity, and even then it was whirring like a jet engine at takeoff.

Aside from the lower resolution than I’m used to – 1280 x 800 on my particular MacBook – games were smooth and fairly consistent experience overall, with only occasional dips in quality. While I didn’t manage to score particularly high on the PUBG leaderboards, it seemed this was due to personal skill rather than game-breaking lag or latency. Yes, I’m a scrub.

MacBook Pro
There is at least one caveat, however, as you’ll need an internet connection above 25Mbps to download the sheer volume of data that game streaming requires, and Nvidia recommend speeds of 50Mbps for the best experience the service can offer. You’ll also need to be close to Nvidia’s servers in North America or Europe to play, at least until Nvidia launch more servers worldwide.

For the swift connection requirements you gain the benefit of no longer requiring local installations of your preferred games. Just click install on any game you own in Steam while running the service and it will be ready to go in seconds, with the added benefit of keeping your precious storage space free.

Unlike the Nvidia Shield game subscription service, you will need to have purchased any games you choose to play with the GeForce Now for Mac, so be prepared for the cost of purchasing any games you don’t yet own on Steam.

Best 4K graphics card
Pricing for the service is not yet confirmed, and it is possible that the service will ditch the GeForce Now monthly pricing template, as is the case with the Nvidia Shield service, in favour of a pay-per-hour style pricing plan. For the first two months of beta, however, the service will be free.

For PC gamers with limited laptop power, GeForce Now will be available on PC sometime down the line – although a release date has not yet been confirmed.

Giant graphics-championing server farms and speedy internet connections won’t be replacing desktop towers any time soon, at least not for us PC players. Even mid-range cards can push glorious 1440p resolutions and likely even greater with the next generation. Yet, for a Mac fan with a taste for casual gaming – or simply seething jealously for PUBG players – you may no longer feel renegaded to Steam’s big title B-list.

Chipmaker Nvidia’s CEO sees fully autonomous cars within 4 years

TAIPEI (Reuters) – Nvidia Corp chief executive Jensen Huang said on Thursday artificial intelligence would enable fully automated cars within 4 years, but sought to tamp down expectations for a surge in demand for its chips from cryptocurrency miners.

FILE PHOTO: Nvidia co-founder and CEO Jensen Huang attends an event during the annual Computex computer exhibition in Taipei, Taiwan May 30, 2017. REUTERS/Tyrone Siu

Nvidia came to prominence in the gaming industry for designing graphics-processing chips, but in recent years has been expanding into newer technologies including high-performance computing, artificial intelligence, and self-driving cars.

Its expansion has been richly rewarded with a 170 percent stock surge over the past year, boosting its market value to $116 billion.

“It will take no more than 4 years to have fully autonomous cars on the road. How long it takes for the vast majority of cars on the road to become that, it really just depends,” Huang told media after a company event in Taipei.

Global tech firms such as Apple Inc, Facebook, Alphabet Inc, Amazon and China’s Huawei [HWT.UL] are spending heavily to develop and offer AI-powered services and products in search of new growth drivers.

Apple Chief Operating Officer Jeff Williams said earlier this week that the firm sees its mobile devices as a major platform for AI in the future. [nL4N1MY3N5]

“There are many tasks in companies that can be automated… the productivity of society will go up,” said Nvidia’s Huang.

But Huang joined peers taming expectations of strong revenue growth from a wave of interest in cryptocurrencies. Advanced Micro Devices Inc expected this week that there will be some leveling off of cryptocurrency demand. [nL4N1MZ5RP]

“Revenue for us in crypto is over $100 million a quarter. For us, it’s a small percentage… It’s obviously not a target market,” Huang said.

Cryptocurrencies are digital currencies that use encryption techniques for security and can be traded. Miners use computers to process cryptocurrency transactions, and they are rewarded with additional cryptocurrency.

Reporting by Jess Macy Yu; Writing by Miyoung Kim; Editing by Muralikumar Anantharaman

Our Standards:The Thomson Reuters Trust Principles.

Nvidia’s newest chip has a secret weapon in the AI race (NVDA)

nvidia ceo jensen huangEthan Miller / Getty Images

  • Nvidia’s Volta GPU was announced to much fanfare.
  • The company has since started shipping its Volta chips to data centers.
  • The Tensor Core units of the chips provide Nvidia with a distinct advantage over its competition.

 

When Nvidia announced its Volta graphics processing units, the stock jumped about 17.8% in a single day.

Now, as the first chips are being sold into the data center market, their competitive advantage is becoming clear.

“A key differentiator for Volta is its Tensor cores, which enable it to process matrix multiplication operations in a highly efficient manner – key for neural network training,” Mark Lipacis, an analyst at Jefferies, said in a recent note to clients.

The Volta chips are being bought by data centers because the centers are the main training grounds for the growing artificial intelligence trend. GPUs, like Nvidia’s Volta series, help speed up the training process of artificial intelligence systems, specifically by allowing for faster matrix multiplication.

GPUs differ from more traditional CPUs by having hundreds or even thousands of smaller “cores” that can perform small operations, compared to the typically much smaller number of more powerful cores (4-8 in many modern machines) found in CPUs. 

Nvidia’s Tensor cores are specifically designed to be speedy AI system trainers, and are 12 times faster than the company’s previous series of chips, according to Nvidia. It’s AI prowess could lead to an outsized share in the growing data center and AI markets, said Lipacis.

Lipacis estimates that Nvidia’s revenues will grow 30% year over year in 2017, and 15% in 2018. Because of the success of Volta, he raised his price target for Nvidia to $230, about 16.7% higher than the company’s current price.

Nvidia is up 97.75% this year.

nvidia stock priceMarkets Insider

Why Artificial Intelligence Could Be NVIDIA’s Golden Goose — The Motley Fool

NVIDIA (NASDAQ:NVDA) is using its GPUs (graphics processing units) to make a big splash in the field of artificial intelligence (AI). The graphics specialist is leveraging the immense computational capacities of its GPUs, which can perform a huge number of mathematical calculations in a parallel manner, for enabling AI across several applications.

NVIDIA has started witnessing terrific growth in some of its businesses that rely on AI. For instance, NVIDIA’s automotive business increased almost 20% year over year in the last reported quarter; the company’s DRIVE PX2 autonomous vehicle platform uses AI to help cars drive themselves.

Man holding a tablet projecting a brain shape made from lights

Image Source: Getty Images

But this is just one of the many areas where NVIDIA is applying AI to boost its business. The company has been testing the uses of AI across several applications as it tries to take advantage of a technology that’s expected to clock an annual growth rate of over 45% through 2022.

Driving deep learning in data centers

Deep learning is a segment of AI that allows several computers to communicate with each other, using software to make sense of the data that they’re consuming. Grand View Research forecasts that the deep learning market could be worth $10 billion by 2025, growing at a pace of over 52% a year.

NVIDIA definitely doesn’t want to miss this gravy train, so it has launched its DGX-1 supercomputer to train AI models at breathtaking speeds. In fact, NVIDIA claims that a Tesla V100 GPU equipped DGX-1 supercomputer can train AI models three times faster than other GPU-equipped systems. Furthermore, NVIDIA says that this solution is ready to work out-of-the-box, so potential clients can start training their AI models within hours instead of spending months on developing hardware and software of their own.

The plug-and-play nature of NVIDIA’s deep learning solution has helped it land marquee clients of late. Wal-Mart, for instance, has decided to use NVIDIA GPUs in huge data centers. The retail giant will build a “GPU farm” by sourcing graphics chips from NVIDIA, and equipping its cloud computing platform with deep learning capabilities.

Wal-Mart is going in-house to apply deep learning on the huge volumes of customer data it generates to drive its own sales, instead of relying on rival Amazon‘s cloud infrastructure. This deal will give NVIDIA’s data center business a shot in the arm as Wal-Mart is expected to begin deployment in the next six months.

In fact, data center is NVIDIA’s fastest-growing business, clocking 175% year over year revenue growth in the latest quarter. Its deal with Wal-Mart, as well as partnerships with other data center customers, should help NVIDIA sustain this segment’s impressive momentum.

AI in healthcare will be a big deal

The adoption of AI in healthcare is estimated to grow at 40% a year until 2025. This could open up a huge opportunity for NVIDIA.

In May this year, NVIDIA announced that it will train 100,000 developers in deep learning for implementation in the fields of healthcare and cancer research. This is a logical step for the chipmaker as it has already been using its Tesla K80 GPU to train models for breast cancer detection. Training more developers will allow NVIDIA to deploy more of its GPUs into healthcare, setting the company on pace to take advantage of the huge opportunity.

The good news for investors is that NVIDIA’s healthcare business is already getting off the ground. The Center for Clinical Data Science recently bought four DGX-1 supercomputers (costing over $150,000 per unit) so that they can apply deep learning to MR and CT scan analysis, and it won’t be surprising if the company keeps landing more such deals.

The Foolish bottom line

NVIDIA has already made headlines in AI technology by covering as much of the end market as possible, including the drone market. And NVIDIA’s AI application in the automotive space is already quite well-documented given its strong partnerships with marquee automakers and truck makers.

NVIDIA, therefore, could win big as AI application gains momentum.

 

Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool owns shares of and recommends Nvidia. The Motley Fool has a disclosure policy.