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) …
NVIDIA (NASDAQ:NVDA) is primarily known as the company that revolutionized computer gaming. The debut of the Graphics Processing Unit (GPU) in 1999 provided gamers with faster, clearer, and more lifelike images. The GPU was designed to quickly perform complex mathematical calculations that were necessary to accelerate the creation of realistic graphics. It achieved this feat by performing many functions at the same time, known as parallel computing. This resulted in faster, smoother motion in game graphics and a revolution in modern gaming.
More important to me is how this will change our lives. I spent some time last week talking to IBM about how its partnership with NVIDIA and its advancements with Watson and OpenPOWER will be changing the world around us. We spoke about a number of artificial intelligence trends and several stood out for me. Artificial Intelligence and Credit Card Security Every year, financial institutions write of billions in losses due to credit card fraud, and a great deal of focus has been placed on stopping this steady drip, drip, drip of illegal cost. Currently, systems are advanced enough to do four fraud checks at the time of the transaction, but they simply aren't enough to stop the flood of people cloning, stealing and skimming credit cards to steal money.
While AI (artificial intelligence) has been around since the 50's, IBM was the pioneer in the latest AI cycle with their own custom solution dubbed Watson. Ever since the introduction of Watson and its ability to beat Jeopardy Champion Ken Jennings, the company has been increasing its investment in the space. IBM Watson is now an entire division of the company which indicates the importance they put on the future of AI. Watson is only one part of IBM's AI investment which I consider the "easy button" for those enterprise who don't want to create everything from scratch. IBM also has DIY (do it yourself) infrastructure for cloud providers through POWER8, OpenPOWER, OpenCAPI, designed for cloud giant rolls their own AI software. But what about enterprises who are in the middle, those who want solid infrastructure and want to invest in the latest deep neural network frameworks?
The rise of artificial intelligence, or AI, services -- one of the fastest-growing markets in tech --should be a boon for consumers and investors alike. In fact, researcher IDC predictsAI and cognitive systems technology sales are primed to simply explode in the years to come, rising from an estimated $8 billion this year to $47 billion in 2020. Though by no means the only names interested in this space, Amazon.com Here's how these particular artificial intelligence stocks have performed so far in 2016. Forget GE! Heres how to play the largest growth opportunity in history Forget GE! Heres how to play the largest growth opportunity in history Importantly, each of the tech giants named above has its own strategy to tap into the growth in the artificial intelligence market.
On Monday, IBM announced that it collaborated with Nvidia to provide a complete package for customers wanting to jump right into the deep learning market without all the hassles of determining and setting up the perfect combination of hardware and software. The company also revealed that a cloud-based model is available as well that eliminates the need to install local hardware and software. To trace this project, we have to jump back to September when IBM launched a new series of "OpenPower" servers that rely on the company's Power8 processor. The launch was notable because this chip features integrated NVLink technology, a proprietary communications link created by Nvidia that directly connects the central processor to a Nvidia-based graphics processor, namely the Tesla P100 in this case. Server-focused x86 processors provided by Intel and AMD don't have this type of integrated connectivity between the CPU and GPU.
Just over five years ago, IBM's Watson supercomputer crushed opponents in the televised quiz show Jeopardy. It was hard to foresee then, but artificial intelligence is now permeating our daily lives. Since then, IBM has expanded the Watson brand to a cognitive computing package with hardware and software used to diagnose diseases, explore for oil and gas, run scientific computing models, and allow cars to drive autonomously. The company has now announced new AI hardware and software packages. The original Watson used advanced algorithms and natural language interfaces to find and narrate answers.
At Supercomputer 16 (SC16) IBM and NVIDIA have announced what they call the fastest deep learning enterprise solution. The system is based on IBM Power System S822LC platforms that were announced in September. These systems contain the latest version of the IBM POWER8 processor that has NVIDIA NVLink embedded in it. IBM has also released a new deep learning toolkit called IBM PowerAI. The solution is capable of running AlexNet with Caffe up to 2x faster than equivalent systems.
Nvidia's (NVDA) spectacular earnings and guidance last week provided good evidence that the GPU leader is on its way to making the powering of artificial intelligence workloads a 10-figure annual business. Since then, it hasn't wasted time announcing moves that grow its AI ecosystem and could help keep hungry rivals at bay. On Monday, Nvidia and IBM (IBM) announced the latter is rolling out a software toolkit called IBM PowerAI for IBM servers containing Nvidia's Tesla accelerator cards, which are widely used to handle a popular type of AI known as deep learning. IBM also rolled out a new server, the Power S822LC, that's optimized for AI and other high-performance computing (HPC) workloads: It pairs Big Blue's mammoth Power8 CPUs with Tesla accelerators and Nvidia's NVLink high-speed GPU interconnect. That day, Nvidia also announced it's teaming with Microsoft (MSFT) on a solution that lets businesses create AI workloads by using Microsoft's Cognitive Toolkit software on systems containing Tesla GPUs.
As GPU maker Nvidia's CEO stressed at this year's GPU Technology Conference, deep learning is a target market, fed in part by a new range of their GPUs for training and executing deep neural networks, including the Tesla M40, M4, the existing supercomputing-focused K80, and now, the P100 (Nvidia's latest Pascal processor, which is at the heart of a new appliance specifically designed for deep learning workloads). While cloud rival Amazon Web Services, among others, are sporting GPU cards for high performance computing (HPC) and deep learning users, the partnership between Nvidia and IBM is giving Big Blue a leg up in terms of making a wider array of GPUs available to suit different workloads. Today that suite of GPU options was enriched with the addition of the virtualization-ready Nvidia M60 cards, which can support a wider range of workloads--from HPC applications, to machine learning workloads, to virtual services and gaming platforms. As our own Timothy Prickett Morgan noted earlier this year, at the moment, Nvidia identifies six cloud providers that provide cloud-based GPU capacity or hosted GPU capacity.
By adopting Nvidia's Tesla solution, IBM is making inroads in supporting AI and cognitive across a variety of enterprises. HPC (high performance computing) need powerful GPUs to do data analytics, AI, and graphical computations. To accelerate adoption for IBM's Watson, the company offers 30 API's (Watson services). This gives developers using Google's cloud infrastructure AI machine learning functionality for their apps.