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.

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.

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.

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.

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.

Late last month it was revealed that Apple is quietly working on the iPhone 8 in its Herzliya, Israel offices. Today, it's been revealed that the Cupertino giant is working on its car operating software in its Kanata, Canada facility. The location is somehow strategic, since the tech company hired ex-employees of its former rival, BlackBerry, to work on this project. According to MacRumors, Apple's R&D facility in Canada is focused on the "software core" of its upcoming self-driving car program that is currently being developed by a separate Project Titan team. The car operating system is said to come with many features, such as a heads-up display that would be very useful to drivers who want to access Maps via Apple's digital assistant, Siri.

Slack is going to tap into IBM pet Watson and its cognitive computing skills, covering both bots and other conversation inferences. Slack's own Slackbot will be the first to get the intelligence makeover, with IBM and Slack looking to share what they learn from the experience with other developers. The companies believe integrating Watson will improve accuracy and efficiency of troubleshooting with the bot. IBM is also working on a Watson-powered Slack chatbot specifically for IT and network issues. IBM's Watson is really sharing its wisdom around: it's just joined the Weather Channel's bot on Facebook Messenger, where it will learn your preferences and offer up personalized forecasts and even news for to US-based bot chatters.

The company's scientists think its new AI-based factotum will be the biggest thing since search. It is the day after Google's big hardware event in San Francisco, when the company formally unveiled a new phone (a jab to the iPhone) and a voice-activated speaker (a gut punch to Amazon's Echo). Word of mouth is already tracking positive; a countdown to ecstasy, in the form of upcoming rhapsodic reviews of the Pixel phone, has already begin. But in a conference room on the company's sprawling Mountain View campus, Fernando Pereira, who leads Google's projects in natural language understanding, is less excited about his company's shiny new devices than he is about what will happen when people use them. "Let me tell you a little bit about The Transition," he says.