Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. One advantage of Cassie that has maybe not been properly appreciated? I like the explosives idea.

ALISO VIEJO, CA--(Marketwired - Feb 17, 2017) - BrainChip Holdings Ltd. ("BrainChip" or the "Company") ( ASX: BRN), a leading developer of software and hardware accelerated solutions for Advanced Artificial Intelligence and Machine Learning applications, is pleased to provide an updated Corporate Presentation. The presentation includes information regarding target markets and applications as well as new product development. The presentation will be used in customer and investor meetings. About BrainChip ( ASX: BRN) BrainChip is a leading provider of software and hardware accelerated solutions for Advanced Artificial Intelligence and Machine Learning applications. The Company's Spiking Neural Adaptive Processor (SNAP) can learn autonomously with a small sample set and provide real-time information, data analytics and knowledge in image and video processing applications, high frequency data streams for financial analysis and event, speech, and speaker recognition from audio sources.

The '90s were the era of the PC, and 2006 ushered in the era of the smartphone. Today, we are at the beginning of the third era in end-user devices: the connected car. In some ways, this shift could be even more significant than the previous ones because it combines the digital and physical world in a way we haven't seen before. As cars evolve into computers on wheels, the biggest business opportunities will be less about "metal and rubber" and more about services. McKinsey estimates that the value of connected car data could be worth $1.5 trillion a year by 2030.

Pretty much every company, to some extent, has to power their algorithms with data and machine learning if they're going to be competitive with anyone else in their space. The challenge there, though, is that not everyone can have the massive computational power and data of a company like Google -- especially not startups. Siddharth Mall and his co-founders started Playment in India based on that bet. Playment allows companies to send over sets of training data that need some kind of light analysis, and then divvies it up across a large on-demand workforce that can resolve those tasks on their mobile devices. That, in turn, feeds back additional data to the companies to help refine their algorithms -- whether that's visual search, quality checks of recommendation engines.

The worldwide market for radiology-specific deep learning will soar from around $40 million next year to some $300 million by 2021, largely on the wings of increasing demand for imaging combined with radiologist shortages like the one Scotland is facing. The projection comes from the U.K.-based healthcare market research firm Signify Research. "Radiology is evolving from a largely descriptive field to a more quantitative discipline," a Signify analyst says in a press release. "Intelligent software tools that combine quantitative imaging and clinical workflow features will not only enhance radiologist productivity but also improve diagnostic accuracy." Meanwhile the release, sent to publicize Signify's full report on the topic, notes that doubts over how deep learning arrives at its radiological diagnoses "could lead to legal implications. Whilst none of these problems are insurmountable, healthcare providers are likely to take a'wait and see' approach before investing in deep learning-based solutions."

Have you ever wondered how Facebook collects all the data it has to feed you with the content it presumes you'll like and keep you coming back for more? Well, now there's an app that can answer these questions. Available for free, Data Selfie is an open-source Chrome extension that helps you discover how machine learning algorithms track and process your Facebook activity, and gain insights about your personality and habits. Last year, Facebook's VP of Design thought the TNW Conference main stage was the best she'd ever been on. To accomplish this, the nifty extension monitors your Facebook interactions for patterns and then crunches the collected data into insightful reports. Data Selfie essentially tracks your activity – what you look at, how long you look at it, what you like, what you click and what you type – and then applies natural language processing and machine learning algorithms from IBM Watson and the University of Cambridge to turn this data into insight.

The robots are coming… if you believe everything you read in the news. According to some, AI technology will transform our healthcare system, break into the banking industry, and take over our jobs. But even if that's rue, is it really as scary as it seems? You may not know it, but Artificial Intelligence is already a massive part of our everyday lives – and has been for thirty-plus years. Over the coming weeks, we'll be running a series of blogs, looking at the role of Artifical Intelligence in our modern world.

We are going to move towards a world where I open an app where I talk to my device and I get an answer. I ask a question and I get an answer. I don't do a lot of work, I don't navigate too much. I'm not given too many options.That's going to be fueled by A.R., in particular, and I think A.I. is going to help make a world where you're sort of spending less time being inundated with sort of content and noise and more time sort of focusing on quality and the answers. There might be a moment when Tinder is just so good at predicting the few people that you're interested in, and Tinder might do a lot of the leg work in organizing a date, right?

A Boom with a View is a column about startups and the technology industry, written by Erin Griffith. Find them all here: fortune.com/boom. There's an easy way to tell when the hype around a technology trend has peaked. Ask yourself the following: Are the smartest venture capitalists complaining about valuations? Are big tech companies snapping up startups so young they can barely be considered real businesses?

When Anders Sandberg was a kid in the 1980s, he enjoyed making simulations on his Sinclair ZX81, mocking up mini solar systems. Later, he graduated to designing artificial neural networks that use learning algorithms inspired by the brain. "Some people relax by watching television. I program simulations while listening to philosophy lectures," Sandberg chuckles. One day back in 1999, he recalls, he deleted a copy of a neural network on his computer and got a "tinge of bad conscience." He couldn't help worrying: "Have I just killed a little creation?"