Apple now has the tech in place to give its digital assistant a big boost thanks to a UK-based company called VocalIQ it bought last year. In fact, it was so impressive that Apple bought VocalIQ before the company could finish and release its smartphone app. After the acquisition, Apple kept most of the VocalIQ team and let them work out of their Cambridge office and integrate the product into Siri. Before Apple bought the company, VocalIQ tested its product against Siri, Google Now, and Cortana, and the results were impressive. Users asked each AI questions using normal language, not the robotic commands you're used to using with digital assistants.

The rise of artificial intelligence makes for sensational headlines. Over the last few months the hype around'bots' has gone into overdrive following Facebook and Microsoft's forays into the area. And while intelligent software agents are not new, we are clearly entering a new wave of innovation around bots and related software that has the potential to impact our personal lives, our business lives and business operations in general. The current blossoming of machine-learning is driven by both technical and environmental factors, and influenced by business and consumer-oriented perspectives. Businesses struggle with the corporate brain drain caused by the continuous churn of employees, and increasingly turn to technology to capture and share information, to somehow retain and capture the knowledge that powers organizational processes.

As we go about our daily lives, we tend to assume that our perceptions -- sights, sounds, textures, tastes -- are an accurate portrayal of the real world. Sure, when we stop and think about it -- or when we find ourselves fooled by a perceptual illusion -- we realize with a jolt that what we perceive is never the world directly, but rather our brain's best guess at what that world is like, a kind of internal simulation of an external reality. Still, we bank on the fact that our simulation is a reasonably decent one. If it wasn't, wouldn't evolution have weeded us out by now? The true reality might be forever beyond our reach, but surely our senses give us at least an inkling of what it's really like. Not so, says Donald D. Hoffman, a professor of cognitive science at the University of California, Irvine. Hoffman has spent the past three decades studying perception, artificial intelligence, evolutionary game theory and the brain, and his conclusion is a dramatic one: The world presented to us by our perceptions is nothing like reality.

In the picture above, you see some dude (it me) taking a picture of himself in his dingy bathroom mirror. A classic mirror selfie, if you will. When even the most advanced artificially intelligent image recognition software sees that image, however, it sees something very different. It might see a man, a phone, a white checkered shirt--this would be a cutting-edge analysis that's only newly possible, by the way--but it wouldn't identify the image as a mirror selfie, or a selfie at all. Solving the mirror selfie problem is one of the most important questions left when it comes to machine vision: Image recognition software can now fairly reliably describe what it's seeing, but it lacks the cultural knowledge or reasoning skills to put it into context.

This is a redacted transcript of a TEDx talk I gave last April at Ecole Polytechnique in France. The video can be seen on Youtube here. Last March, I was in Costa Rica with my girlfriend, spending our days between beautiful beaches and jungles full of exotic animals. There was barely any connectivity and we were immersed in nature in a way that we could never be in a big city. But in the evening, when we got back to the hotel and connected to the WiFi, our phones would immediately start pushing an entire day's worth of notifications, constantly interrupting our special time together.

At a recent financial technology conference I was invited to meet Cleo, a friendly automated spirit living within the confines of an iPhone interface that offers financial advice to those who chose to activate her. Described as an "AI assistant for your money," she playfully answered text message queries about bank balances, spending, and budgeting. Despite the futuristic jargon and growing wave of hype around such bots, automated assistants are not really that new. Our world is full of simple bots, like the automatic hand dryer in a public restroom that jets hot air if you trigger its sensor. By now many of us have experience with some that attempt to mimic basic personality, like the tinny voice of the supermarket self-service checkout machine as it coldly attempts to replicate one half of a stilted, human conversation. There are two new trends emerging, though.

Neural networks require considerable time and computational firepower to train. Previously, researchers believed that neural networks were costly to train because gradient descent slows down near local minima or saddle points. At the RE.WORK Deep Learning Summit in San Francisco, Ian Goodfellow, Research Scientist at Google, will challenge that view and look deeper to find the true bottlenecks in neural network training. Before joining the Google team, Ian earned a PhD in machine learning from Université de Montréal, under his advisors Yoshua Bengio and Aaron Courville. During his studies, which were funded by the Google PhD Fellowship in Deep Learning, he wrote Pylearn2, the open source deep learning research library, and introduced a variety of new deep learning algorithms.

Within a week of Tesla releasing Autopilot to the masses last fall, we started seeing some generally scary videos of people putting a little too much trust in the system. Well, we're continuing to see them, and in the latest video we sadly have a proper collision. As spotted on Tech Insider and Electrek, a European Tesla owner was driving their Model S on the highway in Switzerland last week with Tesla's Adaptive Cruise Control engaged. Tesla's ACC and Autopilot systems use a camera and a series of sensors to monitor surrounding traffic and dynamically adjust speed, even coming to a complete stop. The car ahead changed lanes to avoid a stopped van, which was blocking half the lane.

They have been blamed for bringing worldwide destruction to Earth and triggering the kind of mass extinctions that wiped out the dinosaurs. But it appears we may owe our very existence to a comet that smashed into our planet billions of years ago. A spacecraft that has been orbiting a distant comet as it races through the solar system has sent back compelling evidence that suggests one of these icy objects brought the seeds of life to Earth. Comets are often thought of as harbingers of doom, causing mass extinctions and destruction on Earth. The European Space Agency's Rosetta spacecraft, which has been orbiting the duck-shaped Comet 67P/Churyumov-Gerasimenko since August 2014, has discovered two key building blocks of life on the enormous block of ice and dust.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton rhymers. 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. "The LOw-Cost Unmanned aerial vehicle Swarming Technology (LOCUST) is a prototype tube-launched UAV. The LOCUST program will make possible the launch of multiple swarming UAVs to autonomously overwhelm an adversary."