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) …
Waymo CEO John Krafcik speaks at a press conference at the 2017 North American International Auto Show in Detroit on Jan. 8, 2017. Waymo, the company born from Alphabet's Google Self-Driving Car research project, is designing and building all the sensors, radar and computers used in its automated test vehicles, along with the artificial intelligence programs that control everything. Yet to make its technology affordable for commercial use, it anticipates a manufacturing alliance as it looks ahead to mass-scale production of components, according to Chief Executive Officer John Krafcik. Waymo this week at the North American International Auto Show in Detroit revealed that the latest generation of its hardware and software is being used on Chrysler Pacifica minivans that begin road tests this month. A total of 100 of the vans are getting radar, sensors, cameras and laser Lidar units for 360-degree, high-definition images of a vehicle's surrounding, all made by Waymo.
Artificial intelligence got a big push today as both Google and OpenAI announced plans to open-source their deep learning code. Elon Musk's OpenAI released Universe, a software platform that "lets us train a single [AI] agent on any task a human can complete with a computer." At the same time, Google parent Alphabet is putting its entire DeepMind Lab training environment codebase on GitHub, helping anyone train their own AI systems. DeepMind first burrowed into the public consciousness by defeating a world champion at the notoriously difficult game Go. However, to advance deep learning further, Alphabet says that such AI "agents" require highly detailed environments to serve as laboratories for AI research.
A more plausible explanation: it is proving difficult to convert recently developed digital technologies into meaningful changes in the economy's largest sectors, such as health care, manufacturing, and transportation. Meanwhile, productivity is growing by 2.8 percent a year in what Mandel calls digital industries, which include finance and business services. We need to solve key "bottlenecks" in such sectors as energy, education, and health care to radically improve productivity, says Autor. Our list of 50 Smartest Companies includes Aquion Energy, a Pittsburgh-based company developing batteries for storing electricity on the grid, and 24M, an early-stage startup developing a new type of battery.
Consider: Facebook snapped up shopping search engine TheFind this spring and virtual reality startups Pebbles Interfaces and Surreal Vision last year, building on the social networking leader's 2014 purchase of Oculus VR. E-commerce giant Amazon nabbed cloud computing startups Amiato, 2lemetry, Elemental Technologies and Italy's Nice, as well as chipmaker Annapurna Labs, which brought it new data center technology. Google and its parent Alphabet acquired at least 15 small companies last year, many with mobile technologies. By the 1980s, many were dismantled. Some tech pundits fret that Google, Amazon and Facebook could stray too far from their core businesses as well.
Let's skip to the chase: Self-driving cars are going to be The Next Big Thing (tm). Here's how you can make big money from this revolution, no matter which carmaker or technology platform comes out on top. Since Alphabet started leading this futuristic idea out into the mainstream, the car industry itself has turned in that direction. Name a carmaker, and I bet the company has developed at least the embryo of a self-driving platform. You can already find traces of this upcoming revolution inside current cars, powering automatic parallel-parking systems or highway-speed autopilots.
Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL) Google, Amazon, and Facebook (NASDAQ:FB) are just a few. Meanwhile, its data center revenue, which includes its GPU sales for cloud-based and machine learning services brought in just 143 million in the quarter. I don't expect NVIDIA's revenue to spike from GPU sales for cloud-based machine learning, but rather steadily increase as the company builds out its data center segment. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), Amazon.com, The Motley Fool recommends Intel.
After an up-and-down start to the year, Chinese search giant Baidu issued earnings last week that outperformed on a host of key indicators. As we've come to expect from Baidu, revenue growth remained brisk, increasing at a healthy 31% year-over-year pace to total 2.5 billion. In keeping with its recent quarters, increased spending crimped Baidu's operating profits, which grew only 2.6% compared with the first quarter of 2015. Either way, Baidu's earnings exceeded expectations on the top and bottom line. What's more, Baidu's guidance for second-quarter sales proved better than analysts anticipated, sending the company's shares up in after-hours trading the day of the announcement.
After an up-and-down start to the year, Chinese search giant Baidu (NASDAQ:BIDU) issued earnings last week that outperformed on a host of key indicators. As we've come to expect from Baidu, revenue growth remained brisk, increasing at a healthy 31% year-over-year pace to total 2.5 billion. In keeping with its recent quarters, increased spending crimped Baidu's operating profits, which grew only 2.6% compared with the first quarter of 2015. Either way, Baidu's earnings exceeded expectations on the top and bottom line. What's more, Baidu's guidance for second-quarter sales proved better than analysts anticipated, sending the company's shares up in after-hours trading the day of the announcement.
Researchers from MIT's Computer Science and Artificial Laboratory (CSAIL) alongside machine learning-startup PatternEx have created a new cybersecurity defense system that makes use of both unsupervised and supervised learning methods. Microsoft's research team is working on another related solution that it calls "Crypto Nets", a deep learning software that can analyze encrypted data and output encrypted responses. China's Sunnyvale-based arm of Baidu announced on Friday the assembly of a self-driving car research and development team, part of the company's newly-formed Autonomous Driving Unit (ADU). The ADU-US team, which is actively hiring, will include machine learning researchers, and a wide range of hardware and software engineers, from robotics to onboard computers and sensors.
Answering an analyst query on Google-parent company Alphabet's Q1 2016 earnings call about how the company is leading innovation, rather than simply adapting to changes in technology, Pichai talked about his role in projecting where Alphabet is going in the next 10 years. One of the key insights to pull from the earnings report is that the company's Other Bets category (think self-driving cars and Google Fiber) lost a lot of money - 802 million, up from 633 million in the same quarter last year - but also drew in 166 million, up from 80 million. Alphabet CFO Ruth Porat cited building out Google Fiber as the main money sucker inside Other Bets, but the fact that the category's revenue is growing faster than its losses is a sign Google won't abandon these projects, even if investors murmur that it should. Neither she nor the earnings report offered up any revenue or loss specifics, however, which the analyst/investor world has been clamoring for.