Life essentials made better and more affordable." These are the types of startups that partner Paul Buchheit said were demoing today at Y Combinator's Winter 2016 Demo Day 2. Yesterday, we covered the first 60 startups from the batch, and picked our 7 favorites. Buchheit went on to say about today's big aspirations, "Those challenges may seem too large or too complex for a startup to solve. But as Kyle and Dan showed us with Cruise, often the hardest problems are the best investments." He was referring the GM's 1 billion acquisition of Cruise, a YC startup that built self-driving car tech. Today, the room was jam packed, with more chairs brought in for rich investors who were forced to sit on the floor yesterday. Buchheit joked about the first YC batch in summer 2005, saying "Back then no one wanted to go to Demo Day." Someone in the crowd yelled, "15 people wanted to go to Demo Day." Now, there are several hundred VCs avidly watching the presentations. Over the past few years, Y Combinator has expanded to accept startups from a much wider range of industries than traditional apps, including biotech, energy, hardware, and international logistics. When we spoke to investors in the past, some worried they might not have the expertise necessary to evaluate these companies. Now, YC President Sam Altman tells me many VCs have "hired other experts" to fill the gaps. He says "it's become fashionable to hire a Chief Science Officer." As a result, Altman believes that when it comes to funding, these alternative startups "seem to be doing just was well if not a little better" than their traditional software batchmates. Spinal Singularity – Better catheter Last year, over 5 million people were catheterized. Spinal Singularity wants to tap into the 2 billion urinary catheter market with a connected catheter that allows you to control the flow of urine by actuating a magnetic valve. The connected catheter is minimally invasive, and can be inserted or extracted in your own home.

Auto makers need to push regulators around the world for consistent rules to allow autonomous cars to proliferate, the chief executive of Renault SA RNO -1.16 % and Nissan Motor NSANY -1.97 % Co. said Wednesday. Carlos Ghosn, speaking at the New York International Auto Show, said he expects autonomous vehicles to become more commonplace in coming years, eventually changing lanes on highways and driving through cities on their own. His companies plan to offer 10 autonomous-drive models by 2020. But differing regulations could present hurdles to clearing them for operation, he said. "It's very important that we…lobby in every single country with the regulatory authorities to take our eyes off the road and our hands off the wheel," Mr. Ghosn said, noting that his companies are working with U.S. and Japanese regulators.

A practitioner/learner of machine learning (ML) 'potentially' comes from either a computer science (CS) background or more of a Science, Maths and Engineering background. Therefore, there generally tends to be a gap in knowledge, understanding and culture between these two camps. The CS minded people typically value structure, organization, efficacy and replication over speed and scientific achievement and vice versa. An ideal situation would be where this is balanced. Since my class doesn't offer me this luxury, I decided to take a crack at it on my own.

What are we trying to predict? How are we measuring if we are getting it right? Which departments are a part of this Data Science project? Who is my internal customer? When does this have to be completed?

Google made its Cloud Machine Learning platform, which is used by Google Photos, Translate, and Inbox, available to developers today. During the announcement at NEXT 2016, Google's Cloud Platform conference, Alphabet Chairman Eric Schmidt called machine learning "what's next," according to TechCrunch. Machine learning powers features like the Google app's speech recognition and the smart reply feature in the Inbox app, and Google sees the technology as the future of computing. "Cloud Machine Learning will take machine learning mainstream, giving data scientists and developers a way to build a new class of intelligent applications," Fausto Ibarra, Google's director of product management wrote in a blog post. "It provides access to the same technologies that power Google Now, Google Photos, and voice recognition in Google Search as easy to use REST APIs."

I am sure a number of you have heard about machine learning. A dozen of you might even know what it is. And a couple of you might have worked with machine learning algorithms too. You see where this is going? Not a lot of people are familiar with the technology that will be absolutely essential 5 years from now.

There's been a huge amount of progress in machine learning in the last five years, largely due to breakthroughs in deep learning. You might not be directly aware of it, but we're at the beginning of a machine learning boom right now, a neural network renaissance. Google and Facebook are pouring huge amounts of money into deep learning. In the next few years, we're going to see the fruits of these investments. Self-driving cars, automatic closed captions and more accurate machine translation come to mind, but I would argue that the ramifications are going to quickly expand much beyond this.

Robotics companies and academics descended on a resort in Palm Springs this week for an invitation-only conference organized by Amazon.com Inc. to bring together experts in artificial intelligence, robotics, home automation and space exploration. At the event, held at the Parker Palm Springs, there were robotic arms dueling with light sabers from Star Wars, seminars about imbuing machines with human values and a celebrity appearance by film director Ron Howard, known for his portrayal of Richie Cunningham in the sitcom Happy Days. Jeff Bezos mingled with attendees; one said he drank single-malt whiskey with Amazon's chief executive officer. Representatives from companies such as Rethink Robotics, Toyota Motor Corp., and others attended the conference, called MARS, short for Machine-Learning (Home) Automation, Robotics and Space Exploration.

The following is an edited, updated version of an article originally written for IEEE Spectrum. I'm 62, with all that entails. I still play a mean game of hockey, but entropy looms ever larger. So part of me wants very much to believe that we are rapidly approaching "The Singularity." Like heaven, the Singularity comes in many versions, but most involve bionic brain boosting.

A new artificial intelligence chatbot by the name of Tay is here, and wow, I wish it weren't! The bot is the brainchild of Microsoft's Technology and Research and Bing teams, which created it in order to "experiment with and conduct research on conversational understanding." As Microsoft Power User points out, Tay was recently released into the wilds of the internet, where it has been interacting with users in a manner best described as "mid-40s male attempting to sound like a 16-year-old girl." Tay is currently hanging out on Twitter, Kik, and GroupMe. On Twitter, Tay is verified and lists its location as "the internets," while the official bio describes it as "the official account of Tay, Microsoft's A.I. fam from the internet that's got zero chill! The more you talk the smarter Tay gets."