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) …
With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend 21st Cloud Expo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. With major technology companies and startups seriously embracing Cloud strategies, now is the perfect time to attend @CloudExpo @ThingsExpo, October 31 - November 2, 2017, at the Santa Clara Convention Center, CA, and June 12-4, 2018, at the Javits Center in New York City, NY, and learn what is going on, contribute to the discussions, and ensure that your enterprise is on the right path to Digital Transformation. Join Cloud Expo @ThingsExpo conference chair Roger Strukhoff (@IoT2040), October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, for three days of intense Enterprise Cloud and'Digital Transformation' discussion and focus, including Big Data's indispensable role in IoT, Smart Grids and (IIoT) Industrial Internet of Things, Wearables and Consumer IoT, as well as (new) Digital Transformation in Vertical Markets. Accordingly, attendees at the upcoming 21st Cloud Expo @ThingsExpo October 31 - November 2, 2017, Santa Clara Convention Center, CA, and June 12-14, 2018, at the Javits Center in New York City, NY, will find fresh new content in a new track called FinTech, which will incorporate machine learning, artificial intelligence, deep learning, and blockchain into one track.
Barely a day goes by without a story taking the internet by storm about the use of Artificial Intelligence (A.I.), Machine Learning and Big Data, how these technologies will impact marketing, advertising agencies and nearly every type of company and industry. What's lesser discussed, is why these technologies are gaining so much traction. Digerati sat down with technology observer Cami Rosso to ask why, and why now. What do you think is driving this interest in A.I., Big Data and Machine Leaning? One aspect of this demand is that machine learning has quickly become the new'must-have' capability for forward-thinking software providers, principally because Machine Learning, a subset of A.I., enables computers to learn without hard-coding.
LESLIE FAUGHNAN finds that while automation, augmented intelligence and artificial intelligence are developing at a furious pace in today's enterprise, we are a long way from replacing people and the things they are good at One of the many dictionary definitions of the word'smart' includes the phrase "quick-witted intelligence", which seems as good a way as any of describing what we currently mean by a smart enterprise. Definition is a challenge yet to be met because there is no tech spec for smart. But both the IT industry and its corporate clients share a broad vision of what we are aiming for -- an organisation that is fully joined up digitally and capable of realising the benefits of that synergy. That in turn means corporate agility based on the ability to utilise all of its collected data, complemented by relevant external data, in real time. A useful term in the ether now is'Augmented Intelligence', which will help us somewhat limited humans to make better decisions.
Enterprises collect large amounts of data and analyze it to obtain a competitive advantage. Some are using machine learning techniques to create predictive applications for fraud detection, demand forecasting, click prediction, and other data-intensive analyses. Recent advancements in machine learning make it possible to go even further, bringing deep learning within reach of developers everywhere. Now, computer vision, speech recognition, natural language processing, and audio recognition applications are being developed to give enterprises a competitive advantage. Processing large amounts of data for deep learning requires large amounts of computational power.
The enterprise, as always, is at the forefront of virtually all the multiple technology revolutions taking place today. From Big Data and the Internet of Things to virtual infrastructure and digital business processes, IT is driving the transformation from old-style systems and infrastructure to highly available, highly intelligent applications and services. But sometimes it helps to stop for a moment and see where all this is headed and what work, and life, would be like if all of these developments come to fruition. To my mind, the most consequential advancements are coming in the areas of the IoT and artificial intelligence. How, exactly, will the world function once it has access to a global, interconnected computing environment that touches every device on the planet?
With the rapid pace of technological innovation, the need for greater market responsiveness, and the rising cost of labor in nearly all economies, many companies are revisiting age-old manufacturing strategies. They recognize there is a growing need to introduce innovative products faster to meet customer demands while maintaining aggressive cost and quality objectives. Traditional manufacturing approaches can no longer keep pace with this dynamic new consumer-driven age. Meeting these demands will instead require a complete reinvention to how we approach manufacturing, and this reinvention will need to unfold on a scale that amounts to a new industrial revolution. Welcome to the era of digital manufacturing, which can be defined simply as the growing application and impact of digital connectivity linking automation, workers and decision-makers.
Most major technology companies are knee-deep in machine learning these days. Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL) Google, Amazon, and Facebook (NASDAQ:FB) are just a few. Machine learning allows the tech companies' computers to learn information on their own that they weren't programmed to know. For example, Google uses its own TensorFlow machine learning systems for its Google Translate speech recognition app, Google Photos, Gmail, and its Web searches. And as these companies dive further into machine learning, they're building their own complex computers using graphics processing units (GPUs) to power them -- and that could be particularly beneficial for NVIDIA (NASDAQ:NVDA).
Looking at the performance of IBM shares over the past five years, it is clear that a change in strategy is needed. IBM's share price is down approximately 9% since 2011 compared to a 54% gain in the S&P 500. The goal of this article is to develop a strategy for IBM to leverage the power of IBM Watson artificial intelligence to stage a comeback. The proliferation of cloud, social and mobile technologies have led to the most successful and innovative companies becoming increasingly concerned with the ability to successfully build a digital platform. Apple, Google, Facebook and Amazon each created platforms that co-create value by connecting to other business who can build products and services on their platforms.
Artificial intelligence* is developing much faster than we thought. Just last month, Google's DeepMind AI beat Lee Sedol, a legendary Go player, at his own game in a defining moment for the industry. What enabled this win is a relatively new AI technique called deep learning, which is transforming AI. Until deep learning was introduced, even the best AI systems were always highly tuned for specific problems and required many rules to operate successfully. But deep learning has changed that, causing many researchers to abandon classical AI approaches.
Google executives on Tuesday took turns extolling the capabilities and potential of the company's cloud computing infrastructure, with an eye toward dethroning cloud computing leader Amazon. "In the future, almost everything will be done in the cloud because it simply is a better way of doing computing," said Google CEO Sundar Pichai in opening remarks at the Google Cloud Platform Next 2016 conference. Such sentiment is expected at a cloud evangelism event. But Google wrapped its hard sell in an alluring package, the promise of machine learning. "This platform is not the end, it's the bottom," said Eric Schmidt, chairman of Google parent company Alphabet.