PDF: We made a fancy PDF of this post for printing and offline viewing. Note: The reason this post took three weeks to finish is that as I dug into research on Artificial Intelligence, I could not believe what I was reading. It hit me pretty quickly that what's happening in the world of AI is not just an important topic, but by far THE most important topic for our future. So I wanted to learn as much as I could about it, and once I did that, I wanted to make sure I wrote a post that really explained this whole situation and why it matters so much. Not shockingly, that became outrageously long, so I broke it into two parts. This is Part 1--Part 2 is here. We are on the edge of change comparable to the rise of human life on Earth. It seems like a pretty intense place to be standing--but then you have to remember something about what it's like to stand on a time graph: you can't see what's to your right. So here's how it actually feels to stand there: Imagine taking a time machine back to 1750--a time when the world was in a permanent power outage, long-distance communication meant either yelling loudly or firing a cannon in the air, and all transportation ran on hay. When you get there, you retrieve a dude, bring him to 2015, and then walk him around and watch him react to everything.

Late last year, I lamented that Google didn't make Chromebooks a priority over the holiday season. With Android apps and the Google Play Store coming to the platform, it seemed like a perfect time to push Chrome OS. As this morning's leak showed, I just needed to wait another month: Samsung and Google have just announced the Chromebook Plus and Chromebook Pro, a pair of laptops that strive to present the best Chrome OS experience a user can have. Let's get the difference between the two models out of the way early: The cheaper Chromebook Plus uses an ARM processor while the Chromebook Pro features an Intel Core M3 processor. Neither is the most powerful out there, but in my quick tests, the Chromebook Pro seemed plenty snappy. I will note that an ARM processor is probably never going to provide the best Chromebook experience one can have, but I'll grudgingly reserve judgement until really testing it out.

Toyota revealed the Concept-i at CES on Wednesday, a new concept vehicle that the company built with its Newport Beach CALTY design research group, with tech supplied by the carmaker's SF-based innovation hub. I spoke to CALTY Project Design Manager William Chergosky about the process of creating Concept-i, which he said was about finding a way to bring the excitement people feel about driving now to a potential future in which autonomous driving is much more prevalent. "We've been working on this for approximately two years, and we're trying to create a futuristic vision for the 2030 automobile that's really fun to drive," Chergosky explained. We had a real fundamental belief in this idea of'waku-doki' – getting your heart racing. Is that something that dies with this future?

Machine learning has evolved from science fiction movie plots to everyday reality in just a short time.

For those who don't have the patience to wait for fish to take the bait, a robotics firm has unveiled a device that finds and attracts them to you. Called the PowerRay, the underwater drone uses a precision remote bait drop and blue-hued fishing lures that basically attaches the fish to the dangling hook. The unmanned vehicle also transmits data, fish alerts and live video feed and photos of the underwater world to the fisherman's smartphone via a companion app. PowerRay uses a precision remote bait drop and blue-hued fishing lures that basically attaches the fish to the dangling hook. The unmanned vehicle also transmits data, alters and live video feed and photos of the underwater world to the fisherman's smartphone via a companion app The sonar system can detect fish up to 131ft below the swimming robot and can dive up to 98 feet.

Deep learning is unlocking tremendous economic value across various market sectors. Individual data scientists can draw from several open source frameworks and basic hardware resources during the very initial investigative phases but quickly require significant hardware and software resources to build and deploy production models. Intel Nervana has built a competitive deep learning platform to make it easy for data scientists to start from the iterative, investigatory phase and take models all the way to deployment. Nervana's platform is designed for speed and scale, and serves as a catalyst for all types of organizations to benefit from the full potential of deep learning. Example of supported applications include but not limited to automotive speech interfaces, image search, language translation, agricultural robotics and genomics, financial document summarization, and finding anomalies in IoT data.

Intel has a disastrous history with smartphones. It fumbled a chance to be in Apple's first iPhone, and then quit making its Atom smartphone chip to focus on modems. But the company is now set to ship a groundbreaking modem that will deliver data transfer rates many times faster than most wired internet connections. The chipmaker will start shipping its first 5G modem for testing in the second half this year. Beyond mobile devices, the modem could also be used in autonomous cars, servers, base stations, networking equipment, drones, robots, and other internet-of-things devices.

Now that 2017 has officially started, we are looking forward to exploring the latest technologies and how they will impact our lives. It's clear that AI will infuse everything and it's expected to impact all industries including: healthcare, energy, transportation, and retail! One area expected to grow exponentially are virtual assistants. With the already established existence of Siri, Cortana and Google Now, we will see conversational agents becoming more and more personalized. The market is expected to grow drastically over the next few years and we'll be showcasing advances in virtual assistants and artificial intelligence from the world's leading innovators at the Virtual Assistant Summit on 26-27 January in San Francisco.

Last year was huge for advancements in artificial intelligence and machine learning. The idea has been around for decades, but combining it with large (or deep) neural networks provides the power needed to make it work on really complex problems (like the game of Go). Invented by Ian Goodfellow, now a research scientist at OpenAI, generative adversarial networks, or GANs, are systems consisting of one network that generates new data after learning from a training set, and another that tries to discriminate between real and fake data. The hope is that techniques that have produced spectacular progress in voice and image recognition, among other areas, may also help computers parse and generate language more effectively.

Healthcare is a ripe target for machine learning to both optimize processes and greatly improve care delivery. Take Mercy Health, for instance. When the health system was considering ways to improve care delivery, hospital executives looked at one of the most successful initiatives it had undertaken in the last decade: supply chain management. "We have a lot of experience with operational efficiency," said Todd Stewart, MD, vice president of clinical integrated solutions at Mercy. Using the operative suite as an example, he noted that all the supplies that go into and through it are very expensive.