For the last decade, I have worked closely with families who are trying to find the best senior care facility for a loved one. I am fortunate to work in an area (Portland, OR) that offers a plethora of senior housing options, from traditional Retirement Living, Assisted Living, and Memory Care Communities. Portland also boasts an impressive 900 Adult Care Homes (aka Adult Foster Care or Adult Family Homes) for folks who want/ need a smaller family-style setting. People often ask me what I think the future holds for elder care. I suspect this question stems from fears of what their own future holds or (most likely) that they are terrified of facing their later years in the current senior care model (which is becoming quickly outdated by the social and medical needs of the boomer generation).

Apple is going all-in on artificial intelligence (AI). As it continues to work on Siri, its voice-activated digital assistant, a new interview with Apple CEO Tim Cook sheds a bit of light on just how far the company is willing to go to make Siri a central part of your life. Speaking to Nikkei, Cook waxed philosophical about Siri's intended abilities, saying "AI is horizontal" and should reach across all products. He said the technology should be able to do things like help you manage battery life, recommend music to Apple Music subscribers, and tell you where you parked your car. Cook also discussed Apple's incoming Yokohama research and development center, where it intends to focus on machine learning and AI.

The fun part about thinking about artificial intelligences (AI) – especially for folks with a dark sense of humor – is that it is possible to assess its impact in the short term, the medium term and the very long term. The humor springs from the fact that the long-term view refers to the end of civilization. Overriding the conversation is the idea that the sophistication and capabilities of AI are growing at a very rapid clip. It was mostly discussed by futurists and screenwriters just a few years ago. Now, it is at the center of many corporate and business functions.

One possible framework to think through these topics is this "5P"list: Positioning (finding blue ocean), Product, Petabytes (data), Process (social engineering) and People. I'm approaching this discussion from a VC perspective (and also through the dozens of conversations I've had with founders of AI and Big Data startups at Data Driven NYC, the monthly event I organize). This "5P" framework is just one way of thinking through those issues -- Positioning means "market positioning", while "Petabytes" means "large amounts of data" Just about every major tech company is working very actively on AI. Not only can the large tech companies hire the best talent, they're willing to snap up AI startups quickly when needed.

Just about every major technology player is investing serious financial and human capital in pursuit of advances in cognitive computing. The National Science and Technology Committee on Technology released a much-anticipated report on how to prepare for the future where we have mature artificial intelligence systems. The report, Preparing for the Future of Artificial Intelligence, outlines specific implications that artificial intelligence will have when it comes to transforming our society and outlines twenty-three recommendations for federal agencies to consider. Computers that think and work like humans will change the nature of our public agencies, from how they are designed and managed to the delivery of public services and the management of public goods. We have good reason to believe that there will be significant benefits to be had from cognitive computing solutions.

An ongoing internet outage appears to be spreading and taking down many of the world's biggest websites. Companies including Twitter, Netflix, PayPal and eBay appeared to have their websites broken. And other services like PlayStation Network appeared to be hit by the outage. Almost every major service that isn't part of a major internet provider seemed to be having issues. As such, Google and Facebook appeared to stay up – but almost everything else was down, according to Down Detector's dashboard. Amy Rimmer, Research Engineer at Jaguar Land Rover, demonstrates the car manufacturer's Advanced Highway Assist in a Range Rover, which drives the vehicle, overtakes and can detect vehicles in the blind spot, during the first demonstrations of the UK Autodrive Project at HORIBA MIRA Proving Ground in Nuneaton, Warwickshire Chris Burbridge, Autonomous Driving Software Engineer for Tata Motors European Technical Centre, demonstrates the car manufacturer's GLOSA V2X functionality, which is connected to the traffic lights and shares information with the driver, during the first demonstrations of the UK Autodrive Project at HORIBA MIRA Proving Ground in Nuneaton, Warwickshire In its facilities, JAXA develop satellites and analyse their observation data, train astronauts for utilization in the Japanese Experiment Module'Kibo' of the International Space Station (ISS) and develop launch vehicles The robot developed by Seed Solutions sings and dances to the music during the Japan Robot Week 2016 at Tokyo Big Sight.

Are you just trying to identify (classify) one of your 50 individuals from a new photo, or are you specifically looking to create an embedding representation that can be used to differentiate individuals not in your training set? For classification purposes that might be enough data (esp. For an embedding to differentiate arbitrary individuals not in the training set, I think you'd need a lot more data. It's a bit of an apples and oranges comparison since different models are trained on different datasets, but nonetheless note the significant gain in accuracy of DeepFace and VGGFace over OpenFace, despite having slightly fewer individuals in the training set... it seems that it's the number of photos (as well as model differences) that's making the difference, and maybe that 0.6M (600,000) photos just isn't enough for this domain.

Students can now make their dream of making a robot friend come true. As a collaborative effort of SoftBank Robotics America and the on-campus clothing store the Ave at USC, a humanoid robot named Pepper will be visiting USC and staying on the third floor of the bookstore from Oct. 18 to Oct. 20. Pepper will be greeting the customers, informing them about the Ave and helping them customize shoes.

In 2004, at the end of a long day of classes, I was putting in some extra hours in my school's computer lab perfecting my latest project: Acey Deucey. A program powered using my crude understanding of the Visual Basic coding language, this program felt alive to me. Not just because I'd created an interface that looked sort of like a first grader's drawing of a third-rate casino, but because it was a game that users could play against the computer. It wasn't machine learning--but to me, it sure felt intelligent. I sat before the screen, testing and retesting the code, and feeling almost exactly like Mary Shelley's Victor Frankenstein: "No one can conceive the variety of feelings which bore me onwards, like a hurricane, in the first enthusiasm of success. Life and death appeared to me ideal bounds, which I should first break through, and pour a torrent of light into our dark world."

Colorization of grayscale images is a simple task for the human imagination. Researchers from the Toyota Technological Institute at Chicago and University of Chicago developed a fully automatic image colorization system using deep learning and GPUs. Their paper mentions previous approaches required some level of user input. Using a TITAN X GPU, they trained their deep neural network to predict hue and chroma distributions for each pixel given its hypercolumn descriptor. The predicted distributions then determine color assignment at test time.