Nvidia reported a stellar quarter for the three months ended October 31. Nvidia had $2.6 billion in revenue in the quarter, and $1.5 billion of it came from graphics chips for gaming PCs. But the company's investment in artificial intelligence chips is paying off, with data center growing beyond $500 million in revenue for the first time. Jensen Huang, CEO of Santa Clara, California-based Nvidia, said his company started investing in AI seven years ago, and that its latest AI chips are the result of years of work by several thousand engineers. That has given the company an edge in AI, and other rivals are scrambling to keep up, he said. I interviewed Huang on Thursday, after his company's earnings call, and we talked about everything from self-driving car predictions to cryptocurrency mining.

There is massive excitement -- and some fear -- about AI. The buzz is definitely building, as more and more people start talking about it. But although there is enthusiasm about the potential of AI and its building blocks, there is much less discussion about how organisations should start to invest in AI. Few are talking about their experience of AI, even though we know that there are plenty of organisations out there who are already dipping their toes in the water. We decided to fill this gap in our recent study on enterprise readiness for AI.

Though the industry agrees overwhelmingly that the move to the cloud is the necessary next step to enabling flexible, collaborative ways of working, IT adoption of cloud creeped along much more slowly than expected in 2017. IT leaders struggled with non-technical issues, such as the move to SaaS driving spending as OpEx vs. CapEx, securing buy-in from business unit leaders, and more. The drive in 2018 will continue to push this move toward flexible workspaces ahead. In fact, a recent Citrix-commissioned survey proved the industry's interest in the path to the cloud in 2018: So, while the perspectives of our leaders here at Citrix vary, one commonality holds among them all: the move to the cloud will continue to drive the majority of change in 2018. What will be the key technology innovation in 2018? There is a real convergence happening right now across technologies to bring together the best possible work environments using the cloud. Hybrid cloud technology unifies all the applications from all the platforms, whether they happen to be enterprise or on-premise applications, cloud applications or mobile applications and delivers them in a consistent way across any device. Companies no longer need to even own the applications, they just have to subscribe to an application that someone else is delivering. As things move to the cloud, people have a higher expectation that things will just work, that services will always available and will always help them get things done quickly. There's an expectation that every app is simply going to work, whether they're on the beach, in a plane, or staying at a hotel. So, as rapidly as technology is innovating to create the future of work with the cloud, there's a hungry audience who can see that vision and understand that a hybrid model will get them there the fastest.

Reid Hoffman likes to say, "With great power comes great responsibility." Usually, he's referring to tech companies like the ones he has founded (LinkedIn), helped lead (PayPal), or advised (Microsoft) during his storied career. But he could also be talking about his own clout in the business world and his efforts to finance initiatives that aim to improve the world through civic action, education, and technology. He discussed some of those projects, including two organizations developing artificial intelligence to benefit society and an annual award that honors "responsible disobedience," in a conversation with MIT Media Lab director Joi Ito at the EmTech MIT 2017 conference in Cambridge, Massachusetts, on Wednesday. Hoffman also tries to use his influence to effect societal change.

Every week, we talk about important data and analytics topics with top data scientists. These data science chats are hosted by Mike Delgado. Please reach out if you have recommendations for topics or guests. Mike Delgado: Welcome to Experian's Weekly Data Talk, a show featuring some of the smartest people working in data science. Bill, thank you for being part of today's broadcast. Can you share a bit about your background and what got you started working in data science? In the '90s, I came out of industry and went into management consulting. I ran the consulting shop at JD Power and Associates. Then, I moved over into big four consulting at Ernst and Young and PricewaterhouseCoopers.

As an entrepreneur and AI guru, Trevor O'Brien is deeply engrained in the digital start-up community. He is founder at the innovative design and prototyping studio, theexperiment.io, and has been crucial in a number of ground-breaking start-up initiatives, including thegrid.ai Throughout his career, Trevor has lead sprawling multidisciplinary teams, created award-winning digital campaigns, and proven that technology paves endless paths for communicating and doing business, through the success of his clients. We caught up with our latest scholar to find out more about his thoughts on the role of AI in our future – from minimizing food-waste, to terrible self-creating music! Julie Hough: Contagious are global supporters of brave creative thinking and innovation, especially in the face of daunting new technologies.

Did you ever watch the 2015 movie Chappie? Set in the 22nd Century in South Africa, it's about a robotic police force fighting crime, the development of an artificial intelligence chip, and a robot named Chappie who begins to think like a human. Even since 2001 when Steven Spielberg's science fiction drama AI hit theaters, humanoid robots and artificial intelligence have been considered synonymous. In reality, though, the artificial intelligence industry is much broader. This essential part of the technology sector aims to create intelligent machines of all kinds that work and react like humans.

Recent studies on knowledge base completion, the task of recovering missing facts based on observed facts, demonstrate the importance of learning embeddings from multi-step relations. Due to the size of knowledge bases, previous works manually design relation paths of observed triplets in symbolic space (e.g. random walk) to learn multi-step relations during training. However, these approaches suffer some limitations as most paths are not informative, and it is prohibitively expensive to consider all possible paths. To address the limitations, we propose learning to traverse in vector space directly without the need of symbolic space guidance. To remember the connections between related observed triplets and be able to adaptively change relation paths in vector space, we propose Implicit ReasoNets (IRNs), that is composed of a global memory and a controller module to learn multi-step relation paths in vector space and infer missing facts jointly without any human-designed procedure. Without using any axillary information, our proposed model achieves state-of-the-art results on popular knowledge base completion benchmarks.

Second, our regulatory regime makes it more difficult to build things in the United States and sell them to other countries, creating a market for foreign competitors who would otherwise not stand a chance. For years, the United States curbed exports of encryption technology and basic processors. This only led international competitors to fulfill demand, creating a market for themselves. When U.S. allies like Saudi Arabia, Pakistan, the United Arab Emirates, and Turkey needed access to unmanned aerial systems to prosecute the war on terror, these requests were delayed or denied. We have since lost almost all of these markets to Chinese exports and indigenous development.

What would our computers tell us if we gave them a voice? We'll soon find out thanks to Natural Language Generation which gives computers a written opinion on virtually anything. For now, we must program their responses, but soon they'll form their own opinions and develop a creative voice. This may seem a long way off, so let's consider their progression as a writer in comparison to a human. A child progresses as a writer by starting with basic creative writing exercises: What did you do over summer break?