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) …
Over at the Lenovo Blog, Dr. Bhushan Desam writes that the company just updated its LiCO tools to accelerate AI deployment and development for Enterprise and HPC implementations. The newly updated Lenovo Intelligent Computing Orchestration (LiCO) tools are designed to overcome recurring pain points for enterprise customers and others implementing multi-user environments using clusters for both HPC workflows and AI development. LiCO simplifies resource management and makes launching AI training jobs in clusters easy. LiCO currently supports multiple AI frameworks, including TensorFlow, Caffe, Intel Caffe, and MXNet. Additionally, multiple versions of those AI frameworks can easily be maintained and managed using Singularity containers.
One of the recent cover stories of'The Economist' emphasized on the importance that data has been gaining, stating "the world's most valuable resource is no longer oil, but data." Machine learning, which is bringing about the most dramatic advancements in artificial intelligence, is a data intensive technique. Lots of data is required to create, test and train the AI. As AI is gaining importance in the business world, so is data. AI is being leveraged by financial firms to advice customers on their investment choices, automakers are using it to build autopilot systems, and virtual assistants similar to Siri, Cortana are being introduced.
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Artificial intelligence (AI) promises to deliver the most significant productivity boost and labor disruption since the industrial revolution. The news offers polarizing viewpoints on AI that range from curing cancer to overtaking the human race. Before we work ourselves into a tizzy over the destruction of humanity, we need to understand what AI can and can't do. Technology leaders have been debating AI concepts since 1950 when Alan Turing published his seminal paper on "Computing Machinery and Intelligence". However, in the past year, the AI discussion reached the top of the hype cycle.
Almost a quarter century ago, a book was written about how organizations would focus on share of customer as opposed to share of market, building a personalized collaboration driven by big data. With advanced analytics, banking may finally getting close to realizing this vision. In 1993, a then revolutionary book, "The One to One Future: Building Relationships One Customer at a Time" was published, proposing the idea that as technology makes it affordable to track individual customers, marketing shifts from finding customers for products to finding products for customers. According to the authors, Don Peppers and Martha Rogers, Ph.D., a company could use technology to gather information about, and to communicate directly with, individuals to form a commercial bond. The book became a bestseller, and was on every marketer's bookshelf … almost a quarter century ago.
The first wave of cloud computing is attributed to platforms. Google App Engine, Engine Yard, Heroku, Azure delivered Platform as a Service (PaaS) to developers. The next big thing in the cloud was Infrastructure as a Service where customers could provision virtual machines and storage all by themselves. The third wave of cloud was centered around data. From relational databases to big data to graph databases, cloud providers offered data platform services covering a wide range of offerings. Whether it is AWS or Azure or GCP, compute, storage and databases are the cash cows of the public cloud.
A maturity model is considered a useful tool to assess the current effectiveness of any organization in a particular area. Big Data is no exception; there are multiple models from software vendors such as IBM, Hortonworks, and professional communities like TDWI. While they are mostly focused on capabilities and readiness from an executive sponsorship and organizational standpoint, it's also helpful to assess the company's unrealized potential from an uncovered Big Data value perspective.
The hyper-competitiveness of the e-commerce industry has turned it into one of the biggest drivers of technology innovation. Today, the need for differentiation and the pressure to discount is driving e-commerce companies to look more closely at big data innovations such as predictive and prescriptive analytics, as well as artificial intelligence solutions, to remain competitive. The challenge lies in vast amounts of data.