If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The obvious choice here isn't actually the "Price is no object" pick in our graphics cards buying guide. If you demand the pinnacle of PC gaming performance no matter the cost, you'll want to pick up Nvidia's Titan Xp ($1,200 on Nvidia's website). This second revision of the "Pascal" GPU generation's Titan uses Nvidia's full-blown GP102 graphics processor to power the most graphically demanding games of today without breaking a sweat, even at 4K resolution. The even more potent Titan V ($3,000 on Nvidia's website) pushes further with a next-gen "Volta" GPU and HBM2 memory, but it's specialized for machine learning tasks and data science. Realistically, most gamers should pick up the still-ridonkulously powerful GeForce GTX 1080 Ti ($800 for an EVGA GTX 1080 Ti FTW3 on Amazon).
Nvidia just announced the Titan V, the most powerful graphics processing unit (GPU) of all time. This isn't the type of graphics card your gamer friends all bought on Black Friday, either. This is a graphics card powerful enough for use on research in artificial intelligence and machine learning. SEE ALSO: Nvidia's AI machine generates fake faces from celebrity images The GPU contains 21.1 billion (yes, billion) transistors, and delivers 110 teraflops of horsepower, 9 times that of any other Nvidia processor. For perspective, the Xbox One X delivers only six teraflops, and that was really impressive when it was announced earlier this year.
Seven long months after the next-generation "Volta" graphics architecture debuted in the Tesla V100 for data centers, the Nvidia Titan V finally brings the bleeding-edge tech to PCs in traditional graphics card form. But make no mistake: This golden-clad monster targets data scientists, with a tensor core-laden hardware configuration designed to optimize deep learning tasks. You won't want to buy this $3,000 GPU to play Destiny 2. But that doesn't mean we humble PC gamers can't glean information from Volta's current AI-centric incarnations. Here are five key things you need to know about the Titan V and Nvidia's Volta GPU. Editor's note: This article was originally published on May 11, 2017 but was updated on December 8 to include information from the Titan V.
High-performance graphics chip pioneer NVidia reported better than expected fiscal Q3 earnings after the market close on Thursday. NVidia raised the dividend 7 percent to 15 cents a share and intends to return $1.25 billion to shareholders during the next fiscal year. NVidia consistently trumps analysts' expectations and comes just after Sony and gaming stocks Take Two Interactive $TTWO and Activision Blizzard $ATVI delivered strong earnings. NVIDA chips, graphics processors are gaming industry standouts for personal computers and video game consoles. Earnings: EPS $1.33 way ahead of analysts expected EPS of 94 cents on Revenue of $2.64 Billio beats expected 18% revenue growth to $2.36 billion.. "We had a great quarter across all of our growth drivers.
Nvidia reported earnings that beat expectations and showed that the company's focus on artificial intelligence is still paying off. For the past decade, Nvidia has been rising above graphics chips for gamers, expanding to parallel processing in data centers and lately to artificial intelligence processing for deep learning neural networks and self-driving cars. The company reported earnings per share of $1.33 (up 60 percent from a year ago) on revenue of $2.6 billion (up 32 percent), beating Wall Street's expectations. The company's stock price is up more than 100 percent in the past year on the popularity of artificial intelligence. But it slumped during the day on Thursday, along with the broader market.
Imagine Wolfgang Amadeus Mozart as an algorithm. At our annual GTC Technology Conference in May, our video from the keynote, titled "I Am AI," featured music that was composed by AI itself. To accomplish this, we enlisted the help of Pierre Barreau and his startup, Aiva Technologies, which uses deep learning to create music. Barreau credits growing up in a "family of artists" as his reason for wanting to bring AI into music. "I'm a self-taught pianist and I also studied computer science at university," Barreau said in conversation with AI Podcast host Michael Copeland. "So basically, I got this idea of using my technical background and my musical background and bringing them together to build this artificial intelligence." How AI Makes Music The process for using AI in music composition is as follows: The algorithm will compose themes, which may or may not be curated, depending on the client's briefing. The algorithm can also be trained to create different themes if the client wants something different. This quick turnaround is made possible because of how fast the system can compose themes. An algorithm can create a theme in four minutes, Barreau said. However even music composed by an AI system faces some of the same barriers faced by human composers, because it must be played by humans. By listening to great music, however, the AI has learned how to work within our human limitations. "Essentially, you could create a lot of different compositions where human players wouldn't be able to stretch their hands," Barreau said. "Indirectly, the algorithm learns those features because the compositions that it learns from were created by humans that have these constraints." Beyond scoring videos, Barreau hopes Aiva can solve "use-cases that humans alone cannot solve."
These simulators, most recently announced by Nvidia as a project called Isaac's Lab but also pioneered by Alphabet's DeepMind and Elon Musk's OpenAI, are 3D spaces that have physics just like reality, with virtual objects that act the same way as their physical counterparts. "We imagine that one of these days, we'll be able to go into the Holodeck, design a product, design the factory that's going to make the product, and design the robots that's going to make the factory that makes the products. Alphabet's DeepMind has had similar ideas: The AI research lab is most well-known for applying its AI to games, notably AlphaGo, which continues to beat human world-champions at Go, but also building AI that beats video games like Atari and Starcraft. While Nvidia's Isaac's Lab is meant to help build robots and products that do specific tasks in the real world, DeepMind's Lab is geared more towards research, or finding ways to build AI that can learn about its surroundings with little input.
That downright dwarfs Pascal's flagship data center GPU, the Tesla P100, which packs 15 billion transistors and 3,840 CUDA cores running at a slightly faster 1,480MHz maximum clock speed. Nvidia's GeForce GTX 1080 Ti is the most powerful graphics card ever, capable of no-compromises 4K gaming. Like the Radeon Fury series and AMD's imminent Radeon Vega graphics cards, this data center GPU includes high-bandwidth memory technology--16GB of second-gen HBM2, in fact, with peak speeds of 900GB/s. By comparison, plus-sized GPUs found in Radeon's Fury cards and recent high-end GeForce chips clock in at roughly 600mm.
Though it's just reaching the radar of mainstream investors, eSports have quietly risen to become a global phenomenon over the past several years. In fact, eSports revenues are expected to rise from $463 million last year to nearly $1.1 billion by 2019, according to market research firm Newzoo. However, it's important to remember that most companies involved in the budding eSports ecosystem are largely tech and media companies, which traditionally do not pay dividends. As such, I included both pure-play eSports names, as well as their suppliers, in the stock screen to research this piece. Now that this quick bit of housekeeping is out of the way, let's examine why game designer Activision Blizzard (NASDAQ:ATVI) and chipmaker NVIDIA (NASDAQ:NVDA) are two of the best income investments across the eSports landscape.
NVIDIA's (NASDAQ:NVDA) graphic cards have long been favorites among hardcore gamers, but who would've thought the chipmaker's stock would explode the way it has in recent times? The share price has more than tripled in just the past year, turning NVIDIA into a near eight-bagger in just five years. Of course, there's more to its run than just graphics processors. It's more an artificial intelligence computing company today, having made huge headway in two of the hottest technology fields of our times: AI and self-driving cars. For investors looking to find the "next NVIDIA," the trick is to find a company that is sitting on a big growth opportunity, or is already tapping into a soon-to-heat-up trend, but that is still flying under Wall Street's radar.