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) …
A new $240 million center at MIT may help advance the field of artificial intelligence by developing novel devices and materials to power the latest machine-learning algorithms. The project, announced by IBM and MIT today, will research new approaches in deep learning, a technique in AI that has led to big advances in areas such as machine vision and voice recognition. But it will also explore completely new computing devices, materials, and physical phenomena, including efforts to harness quantum computers--exotic but potentially very powerful new machines--to make AI even more capable. And it will study the economic impact of artificial intelligence and automation, a hugely significant issue for society.
"Our vision is to create that Star Trek computer and work backwards from that. And as with Star Trek's prediction of the iPad, the various voice assistants arguably wouldn't have come to be if Gene Roddenberry hadn't dreamed up the ever-present computer for Star Trek: The Next Generation, voiced by his wife, Majel Barrett. If Marvel's Iron Man is to believed, our AI assistants are more likely to be wise-cracking buddies with serious personality, possibly voiced by Paul Bettany, rather than the dulcet tones of Johansson. As Jarvis, Bettany has access to the internet, can control almost everything in Tony Stark's life, including his Iron Man suit, and comes across as having the smarts of a real life personal assistant.
Whether it's making your email smarter, streamlining tasks or solving the riddle of incurable diseases, AI and machine learning will probably have a huge impact in your life. Andrew Ng, former head of AI for Baidu, has said that machine learning and AI "Will also now change nearly every major industry--healthcare, transportation, entertainment, manufacturing." There's no doubt that a lot of people are starting to see how machine learning and AI might change their industries. Whether it's making your email smarter, streamlining tasks or solving the riddle of incurable diseases, AI and machine learning will probably have a huge impact in your life.
In March the company bought a startup cofounded by Geoffrey Hinton, a University of Toronto computer science professor who was part of the team that won the Merck contest. Extending deep learning into applications beyond speech and image recognition will require more conceptual and software breakthroughs, not to mention many more advances in processing power. Programmers would train a neural network to detect an object or phoneme by blitzing the network with digitized versions of images containing those objects or sound waves containing those phonemes. A team led by Stanford computer science professor Andrew Ng and Google Fellow Jeff Dean showed the system images from 10 million randomly selected YouTube videos.
In Australia for a Microsoft Developers conference, Nadella laid out his main theories for the digital future: Mobile-first and cloud-first. To help build'em, Nadella announced the launch of the Azure Bot Service -- a new public cloud-based bot builder -- that will give everyone access to automated systems that understand conversational language. In addition to building a bot army, Microsoft is also hoping to play a role in developing artificial intelligence for good, a project it referred to as "democratising artificial intelligence." "We are going to create an incredibly powerful technology," Altman said in a promotion video.
In November, Google researchers published a paper in JAMA showing that Google's deep learning algorithm, trained on a large data set of fundus images, can detect diabetic retinopathy with better than 90 percent accuracy. Just a couple of months ago, the company launched the Healthcare NExT initiative, which brings together artificial intelligence, cloud computing, research and industry partnerships. Last month, Alphabet-owned Verily launched the Project Baseline Study, a collaborative effort with Stanford Medicine and Duke University School of Medicine to amass a large collection of broad phenotypic health data in hopes of developing a well-defined reference of human health. "If the government did data quality and data sharing initiatives, it would be a lot different," Andrew Maas, chief scientist at Roam Analytics (a San Francisco-based machine learning analytics platform provider focused on life sciences) said at the Light Forum.
Each TPU has four chips that delivers 180 trillion of floating points performance per second, if this was not enough Google combined 64 of these TPUs together using patented high speed network to create machine learning supercomputer called TPU pod. Remember, Google's real innovation has been on hardware patents in high end cloud computing, chips, servers, networking for its own data centers. Google has been unsuccessful in social media space, but is now using machine learning to help users share photos, even suggesting whom to share it with. Google has search data, complete email conversation data, photos, and location data.
Google does not plan to manufacture and sell the chip like Intel (intc) or AMD (amd), but instead will let companies rent access to the chip via Google's cloud computing service. Google's new chip comes amid fierce competition with cloud computing rivals like Amazon (amzn), Microsoft (msft), and IBM (ibm) that sell on-demand computing resources to businesses. The new chip performs two tasks related to artificial intelligence projects, including the training of data and making sense of the data, known as inference, Dean said. Dean also said that Google would give the "top machine learning researchers" access to 1,000 free TPUs via a new cloud computing service for academics who are researching AI.
As the rise of massively distributed computing power, decreased cost of data storage, and a proliferation of open-source frameworks turn conventional computing paradigms on their head, new and lucrative opportunities are being created to develop innovative artificial intelligence applications, writes Ed Chater, COO, Adbrain. Machine Learning, another subset of AI, focuses on building computer programs that can determine'patterns' in data. Artificial intelligence will radically transform industries including healthcare, finance, insurance, and entertainment, and have a profound impact on much more. With many of the technologies underpinning AI (compute, data storage, learning algorithms) becoming commoditised, the focus is shifting from excitement around the'tech' potential of machine learning to practitioners actually building applications and putting them into production.
At the keynote address of this year's I/O developer conference, Google's CEO announced that the company will be selling AI computer chips, called Cloud Tensor Processing Units (TPUs), via Google Cloud service. Bloomberg noted that Google created the chip to address issues around the high cost and high demand on computing power machine learning took up in the company's data centers. The news of the chip comes along with the announcement of machine learning innovations across Google's products, reportedly including a new photo editing tool, features for Google Assistant and a new web portal for the company's AI plays. Buyers will need to sign up for a Google cloud service, run their tasks and store their data on Google equipment, noted Bloomberg, in order to get the Cloud TPU chip.