Udacity is partnering with IBM Watson, Didi Chuxing, and Amazon for a new "Nanodegree" program. Artificial intelligence, the machine learning technology that allows "smart" machines to take over human tasks like driving cars or ordering pizza, is quickly becoming the go-to technology for many industries to hire talent for, including health care, auto, and finance. Research firm Markets and Markets estimates the AI market will grow to more than $5 billion by 2020, given the rising adoption of AI across these industries. That's why online education company Udacity is debuting a new way for workers to learn skills needed to be experts in developing artificial intelligence for the likes of IBM and others. Udacity originally launched "Nanodegrees" to train people hoping to land technical jobs, such as software developing.

Clarifai, a startup providing an application programming interface (API) that offers a type of artificial intelligence (A.I.) known as "deep learning," is announcing a $30 million round of funding today. Beyond its core application programming interface (API) for image and video recognition, Clarifai has launched the Forevery photo storage app for iOS and recently introduced Custom Training and Visual Search services. To date, Clarifai has raised $41.25 million, including the $10 million round from last year.

The descendants of Alexa and Siri might come with a surprisingly good sales pitch. I met an early version of such a persuasive chatbot at a tech conference in Pittsburgh recently. After some small talk and jokes, the bot, called Sara, recommended some other people for me to meet. The suggestions were in fact excellent, and if I hadn't just met with them already, I would've followed her lead. Sara was developed by Justine Cassell, director of human-computer interaction at Carnegie Mellon University, who is studying ways for virtual agents to use subtle cues in conversation to build rapport with people and become more effective at conveying information or persuading them to do something.

TensorFlow is a framework created by Google for creating Deep Learning models. Deep Learning is a category of machine learning models that use multi-layer neural networks. The idea of deep learning has been around since 1943 when neurophysiologist Warren McCulloch and mathematician Walter Pitts wrote a paper on how neurons might work and they modeled a simple neural network using electrical circuits. Many, many developments have occurred since then. These highly accurate mathematical models are extremely computationally expensive.

SINCE THE EARLY 1800s, several waves of technological change have transformed how we work and live. Each new technological marvel -- the steam engine, railroad, ocean steamship, telegraph, harvester, automobile, radio, airplane, TV, computer, satellite, mobile phone, and now the Internet -- has changed our home lives, communities, workplaces, schools, and leisure time. For two centuries we've asked whether ever-more-powerful machines would free us from drudgery or would instead enslave us. The question is becoming urgent. IBM's Deep Blue and other chess-playing computers now routinely beat the world's chess champions.

Parag Mital is director of machine intelligence at Kadenze, as well as an artist and interdisciplinary researcher obsessed with the nature of information, representation and attention. Artificial intelligence allows machines to reason and interact with the world, and it's evolving at a breakneck pace. Many advances in AI can be attributed to machine learning, which works by tapping massive computing power to crunch through enormous amounts of digitized data. Now consider that most of our data, the best minds in the business and more computing power than you could ever imagine sit with just a handful of companies. For these reasons, only a few companies in the world are best situated to understand the true potential -- and the current limits -- of AI.

Times Higher Education recently asked whether universities needed to rethink what they do and how they do it, given that artificial intelligence is beginning to take over many post-university careers. With that in mind, here are four examples of how AI can benefit universities. First, there is a new role for higher education, which is to equip graduates to work effectively alongside artificially intelligent systems. The onslaught of AI on white-collar jobs is likely to lead to the AI augmentation of human intelligence, rather than the total replacement of human workers with machine workers. We need workers who understand how to make the best use of the power that AI automation can bring to industry and commerce.

It seems to me that the hype about AI makes really difficult for experienced investors to understand where the real value and innovation are. I would like then to humbly try to bring some clarity to what is happening on the investment side of the artificial intelligence industry. We have seen as in the past the development of AI has been stopped by the absence of funding, and thus studying the current investment market is crucial to identify where AI is going. First of all, it should be clear that investing in AI is extremely cumbersome: the level of technical complexity goes out of the pure commercial scope, and not all the venture capitalists are able to fully comprehend the functional details of machine learning. This is why the figures of the "Advisors" and "Scientist-in-Residence" are becoming extremely important nowadays.

Apple CEO Tim Cook says you won't have to give up your privacy to have a great AI assistant Tim Cook on A.I.: "I Don't Think We Have to Throw Our Privacy Away" Now AI is Deliberately Trying to Scare Us, if We Aren't Already TIM COOK: Here's why assistants on phones are better than home speakers like the Echo Machine Learning Veterans Launch'Element AI' - A Montreal Based Artificial Intelligence Startup ... Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.