Stanford researchers are leveraging GPU-based machines in the Amazon EC2 cloud to run deep learning workloads with the goal of improving diagnostics for a chronic eye disease, called diabetic retinopathy. The disease is a complication of diabetes that can lead to blindness if blood sugar is poorly controlled. It affects about 45 percent of diabetics and 100 million people worldwide, many in developing nations. Final-year Stanford PhD students Apaar Sadhwani and Jason Su got involved in developing the diagnostic solution as part of a class project and corresponding Kaggle competition that was held last year. Sponsor Amazon provided AWS cloud credits in support of the research.

We brought Alexa into our home three months ago with Amazon Echo. Stumping her was our simple pleasure for a couple days. Soon after, we forgot Alexa was there. She became one of our many mute appliances. A month and a half later, however, Alexa came alive of her own accord.

Versace may be linked to high-fashion, but one family member wants the name to also be associated with artificial intelligence and robots. Massimiliano Versace, second cousin to Versace Group vice president Donatella Versace and to the Italian fashion company's late founder, Gianni Versace, is CEO of the Boston-based artificial intelligence startup Neurala. Whereas many of his relatives chose careers in luxury apparel, Versace wanted to pursue science and technology. "They make clothes and I make artificial brains for drones," Versace said. Versace's startup, which on Tuesday said it had landed a $14 million investment round led by Pelion Ventures, specializes in a type of artificial intelligence called deep learning.

Artificial intelligence has captured public imagination, dominated media coverage, and driven furious volumes of investment and acquisition activity. In the midst of this hype cycle, spotting the difference between phony wannabes and true investments can be a challenge. We interviewed seasoned VCs from top firms like CRV, IA Ventures, Two Sigma, and more to find how these successful investors evaluate artificial intelligence startups. If you're a founder thinking of starting an artificial intelligence company, be sure to have solid answers for all of these key questions. "Many companies who can't raise money try to shoehorn themselves as AI companies," warns Varun Jain of Qualcomm Ventures.

For your privacy and protection, when applying to a job online, never give your social security number to a prospective employer, provide credit card or bank account information, or perform any sort of monetary transaction. By applying to a job using CareerBuilder you are agreeing to comply with and be subject to the CareerBuilder Terms and Conditions for use of our website. To use our website, you must agree with the Terms and Conditions and both meet and comply with their provisions.

Education has mostly followed the same structure for centuries -- e.g., the "sage on a stage" and "assembly line" models. As AI continues to disrupt industries like consumer electronics, ecommerce, media, transportation, and healthcare, is education the next big opportunity? Given that education is the foundation that prepares people to pursue advancements in all the other fields, it has the potential to be the most impactful application of AI. The three segments of the education market -- K-12, higher education, and corporate training -- are going through transitions. In the K-12 market, we are seeing the effect of the newer, more rigorous academic standards (Common Core, Next Generation Science Standards) shifting the focus toward measuring students' critical thinking and problem-solving skills and preparing them for college and career success in the 21st century.

Any video gamer knows how boring NPCs (non-playable characters) in digital worlds are. Their behavior is simple and predictable and their words entirely scripted by a staff of writers. This makes them uninteresting opponents and unsatisfying companions. We're far more likely to emotionally attach to lifelike characters, like the emo robot sidekicks in the Star Wars franchise, but crafting believable, autonomous entities you can actually interact with is no easy feat. Character models built by artificial intelligence aim to break out of the uncanny valley and imbue inanimate objects and digital characters with an aura of realism and life.

First it was checkers (draughts to you and me), then chess, then Jeopardy!, then Go and now poker. One after another, these games, all of which require significant amounts of intelligence and expertise if they are to be played well, have fallen to the technology we call artificial intelligence (AI). And as each of these milestones is passed, speculation about the prospect of "superintelligence" (the attainment by machines of human-level capabilities) reaches a new high before the media caravan moves on to its next obsession du jour. Never mind that most leaders in the field regard the prospect of being supplanted by super-machines as exceedingly distant (one has famously observed that he is more concerned about the dangers of overpopulation on Mars): the solipsism of human nature means that even the most distant or implausible threat to our uniqueness as a species bothers us. The public obsession with the existential risks of artificial superintelligence is, however, useful to the tech industry because it distracts attention from the type of AI that is now part of its core business. This is "weak AI" and is a combination of big data and machine-learning – algorithms that ingest huge volumes of data and extract patterns and actionable predictions from them.

You might not expect to find a player named Libratus around a poker table in a high-stakes game of no-limit Texas Hold'em. Yet it was Libratus – an artificial intelligence (AI) – that emerged triumphant from a gruelling 20-day tournament that culminated late last Monday in a dramatic victory over four of the world's top players. The victory – which saw Libratus pocket $1.7m in fake chips at the expense of the quartet of serious pros – stunned the generally unshockable world of poker. But more than that, it reopened the increasingly urgent debate about the potential – and possible dangers – of AI, or intelligent machines. If machines are clever enough to beat humans at a game that requires intuition, bluffing skills, intelligence as well as a capacity to retain data – then what else is possible?