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 latest proprietary Power servers from IBM, armed by the long-awaited IBM Power9 processors, look for relevance among next-generation enterprise workloads, but the company will need some help from its friends to take on its biggest market challenger. IBM emphasizes increased speed and bandwidth with its AC922 Power Systems to better take on high-performance computing tasks, such as building models for AI and machine learning training. The company said it plans to pursue mainstream commercial applications, such as building supply chains and medical diagnostics, but those broader-based opportunities may take longer to materialize. "Most big enterprises are doing research and development on machine learning, with some even deploying such projects in niche areas," said Patrick Moorhead, president and principal analyst at Moor Insights & Strategy. "But it will be 12 to 18 months before enterprises can even start driving serious volume in that space."
Companies running AI applications often need as much computing muscle as researchers who use supercomputers do. IBM's latest system is aimed at both audiences. The company last week introduced its first server powered by the new Power9 processor designed for AI and high-performance computing. The powerful technologies inside have already attracted the likes of Google and the US Department of Energy as customers. The new IBM Power System AC922 is equipped with two Power9 CPUs and from two to six NVIDIA Tesla V100 GPUs.
An arms race over artificial intelligence and machine learning among chip makers continued to heat up on Tuesday, with IBM announcing its latest microprocessor aimed at the fast-growing market niche. Among the highlights of IBM's new Power9 line up of chips for servers are faster connections intended to help the processors work closely with graphics processing chips from Nvidia. IBM is including the second generation of Nvidia's proprietary NVLink technology and a connection known as PCI-Express 4.0. Using the NVLink technology leads to a system that is almost 10 times faster at moving data than an Intel-based system, IBM claimed, though it provided no third party test results to back the boast. "We can lift up the entire Library of Congress and run it around the chip in less than five seconds-tremendous bandwidth," Bob Picciano, IBM senior vice president for cognitive systems, said.
IBM is ready to start shipping the first commercial server systems built around its recently released Power9 processor. Dubbed the AC922 Power Systems, these servers will ship by the end of December, and are specifically designed for artificial intelligence (AI) workloads, reports Enterprise Cloud News (Banking Technology's sister publication). The AC922 is the commercial version of the same severs that IBM, along with Nvidia and Mellanox Technologies is using to build two new supercomputers for the US Department of Energy. The "Summit" and "Sierra" supercomputers are expected to go online in 2018, and could reinvigorate the US's standing in the world of high-performance computing. At the heart of the AC922 is IBM's recently released Power9 processor.
INSTANCES of artificial intelligence (AI), machine learning (ML), or deep learning are appearing across all sorts of enterprise service offerings. While there's a certain amount of bandwagon-jumping and overuse of the terms to grab headlines, machine-learning (et al) implementations are becoming quite the norm. Combined with a rise in the numbers of massive public networks of computing power (hyperscale data centers) offering everything-as-a-service (XaaS) from the cloud, it's no surprise that the big enterprise-level server vendors are responding with AI-centric technologies. The first into the fray is IBM, which has announced a new microprocessing chip and a server powered by it, the Power9 and the AC922 respectively. The chip is optimized for the particular demands of AI computation: in tests, it runs workloads on common AI frameworks such as Chainer and TensorFlow at four times the speed of existing systems.
In a world that requires increasing amounts of compute power to handle the resource-intensive demands of workloads like artificial intelligence and machine learning, IBM enters the fray with its latest generation Power chip, the Power9. The company intends to sell the chips to third-party manufacturers and to cloud vendors including Google. Meanwhile, it's releasing a new computer powered by the Power9 chip, the AC922 and it intends to offer the chips in a service on the IBM cloud. "We generally take our technology to market as a complete solution," Brad McCredie, IBM fellow and vice president of cognitive systems explained. The company has designed the new chip specifically to improve performance on common AI frameworks like Chainer, TensorFlow and Caffe, and claims an increase for workloads running on these frameworks by up to almost 4x.
IBM launched its first systems based on its Power9 processor and optimized for artificial intelligence workloads. Big Blue's Power Systems Servers can improve training times of deep learning frameworks by 4x, according to IBM. The Power9 processors and systems built on them are partly the product of collaboration in the OpenPower Foundation, which includes IBM, Google, Mellanox, Nvidia and a bevy of other players. Those technologies are designed to boost bandwidth and throughput in data movement. That movement is what boosts model training time.
There's a big connection between my love for water sports and hardware design -- both involve observing waves and planning several moves ahead. Four years ago, when we started sketching the POWER9 chip from scratch, we saw an upsurge of modern workloads driven by artificial intelligence and massive data sets. We are now ready to ride this new tide of computing with POWER9. It is a transformational architecture and an evolutionary shift from the archaic ways of computing promoted by x86. POWER9 is loaded with industry-leading new technologies designed for AI to thrive.
IBM is doubling down on AI: releasing new software to help train machine-learning models and talking up the potential for its new Power9 systems to accelerate intelligent software. Today IBM unveiled new software that will make it easier to train machine-learning models to take decisions and extract insights from big data. The Deep Learning Impact software tools will help users develop AI models using popular open-source, deep-learning frameworks, such as TensorFlow and Caffe, and will be added to IBM's Spectrum Conductor software from December. Alongside the software reveal, IBM has been talking up new systems based around its new Power9 processor -- which are on display at this year's SC17 event. IBM says these systems are tailored towards AI workloads, due to their ability to rapidly shuttle data between between Power9 CPUs and hardware accelerators, such as GPUs and FPGAs, commonly used both in training and running machine-learning models.
It's been nearly a year since I published my first Special Report on artificial intelligence and urged readers to buy the processor maker NVIDIA (NVDA) at $68.80. With US annual auto production at 17 million, and global car and commercial vehicle production at a record 94.64 million, that is a lot of processors. All new AI startups comprise small teams of experts from private labs and universities financed by big venture capital firms like Sequoia Capital, Kleiner Perkins, and Andreeson Horowitz. The global artificial intelligence market is expected to grow at an annual rate of 44.3% a year to $23.5 billion by 2025.