For all its heat, the fire that is Uber in 2017 hasn't scorched everything. While the nigh-apocalyptic past six months have felled founder and CEO Travis Kalanick, and sparked questions about its ability to keep its employees safe, let alone happy, Uber's self-driving car program seems to be doing just fine. It's a rare but vital bit of good news for Uber, for which autonomy is an existential question. If another company figures out how to operate a taxi service without paying drivers and Uber cannot, it's lights out, unicorn. "What would happen if we weren't a part of that future? Kalanick told Business Insider last year. "Then the future passes us by." Now, Uber's self-driving program hasn't been unscathed. It faces a vicious lawsuit from Waymo, Google's self-driving car spinoff, which accuses it of using stolen IP to advance its autonomy research. Last month, Uber fired Anthony Levandowski, its self-driving car lead who allegedly brought that IP over from Google.

It takes up to 24 minutes for a signal to travel between Earth and Mars. If you're a Mars rover wondering which rock to drill into, that means waiting at least 48 minutes to send images of your new location to NASA and then receive marching orders. It's a lot of idle time for a robot that cost $2.6 billion to build. That's why engineers are increasingly giving spacecraft the ability to make their own decisions. Space robots have long been able to control certain onboard systems--to regulate power usage, for example--but artificial intelligence is now giving rovers and orbiters the ability to collect and analyze science data, then decide what info to send back to Earth, without any human input.

Rats are nimble navigators, able to find their way around, under, and over obstacles, and through the tightest spaces. Roboticists have long dreamed of giving their creations similar navigation skills. To be useful in the real world, robots must be able to find their way around on their own. Some are already learning to do that in homes, offices, warehouses, hospitals, and hotels--and in the case of self-driving cars, entire cities. Despite that progress, robots still struggle to perform the tasks for which they're designed even under mildly challenging conditions.

That is until last year, when Microsoft built one that could. Automatic speech recognition, or ASR, is an area that has gripped the firm's chief speech scientist, Xuedong Huang, since he entered a doctoral program at Scotland's Edinburgh University. "I'd just left China," he says, remembering the difficulty he had in using his undergraduate knowledge of the American English to parse the Scottish brogue of his lecturers. "I wished every lecturer and every professor, when they talked in the classroom, could have subtitles." In order to reach that kind of real-time service, Huang and his team would first have to create a program capable of retrospective transcription.

In March the company bought a startup cofounded by Geoffrey Hinton, a University of Toronto computer science professor who was part of the team that won the Merck contest. Extending deep learning into applications beyond speech and image recognition will require more conceptual and software breakthroughs, not to mention many more advances in processing power. Programmers would train a neural network to detect an object or phoneme by blitzing the network with digitized versions of images containing those objects or sound waves containing those phonemes. A team led by Stanford computer science professor Andrew Ng and Google Fellow Jeff Dean showed the system images from 10 million randomly selected YouTube videos.

It was billed as one of the most important company-wide meetings in the history of Uber. Yet as staff gathered on Tuesday morning at Uber's headquarters in San Francisco, there was one very conspicuous absence. "Let us address the elephant in the room," said Arianna Huffington, perhaps the most high-profile member of Uber's board. The answer: Travis Kalanick, Uber's 40-year-old co-founder and chief executive, was taking a leave of absence from the taxi-hailing app he has transformed into a global behemoth valued at almost $70bn. Huffington told Uber's staff that the company would not await Kalanick's return, choosing instead to act immediately on the findings of a damning investigation, accepted by the board, into the company's workplace culture amid claims of sexual harassment. "Uber is his life," she said of Kalanick.

Now select users will get to test it. One of the most anticipated new features of the Samsung Galaxy S8 and S8 prior to the phone's launch in March was an artificial intelligence assistant named Bixby that you were supposed to be able to control by voice. Unfortunately while some of Bixby's capabilities made into onto the phones, the voice-based commands that would make Bixby respond more like the Google Assistant, Apple's Siri, Microsoft's Cortana and Amazon's Alexa was delayed, at least in the U.S. (Bixby is fully operational in South Korea, where Samsung is based). On Friday, Samsung Electronics America announced it will give "select" Galaxy S8 and S8 users early access to Bixby's vocal capabilities as part of what it still considered an early preview test. Samsung hasn't disclosed how many Bixby testers will gain access to this sneak preview, which will let you hold down a Bixby button and start speaking to get the phone to send texts, change settings and make calls.

Artificial intelligence is ascendant in medicine--from AI eye doctors to chatbot therapists. As medical databases balloon in size and complexity, researchers are teaching computers to sift through and identify patterns, hinting at a future in which machine learning algorithms diagnose disease all on their own. Sometimes, algorithms pick up on early signs of disease that humans wouldn't even know to look for. Last week, researchers at the University of North Carolina and Washington University reported an AI that can identify autistic infants long before they present behavioral symptoms. It's a thrilling opportunity: Early detection gives autism neuroscience a big leg up, as researchers try to understand what goes wrong during development.

In 2012, Google created an'artificial neural network' and fed it millions of pictures from the internet. Could your computer now identify your cat more accurately than you?

A buried line in a new Facebook report about chatbots' conversations with one another offers a remarkable glimpse at the future of language. In the report, researchers at the Facebook Artificial Intelligence Research lab describe using machine learning to train their "dialog agents" to negotiate. At one point, the researchers write, they had to tweak one of their models because otherwise the bot-to-bot conversation "led to divergence from human language as the agents developed their own language for negotiating." They had to use what's called a fixed supervised model instead. In other words, the model that allowed two bots to have a conversation--and use machine learning to constantly iterate strategies for that conversation along the way--led to those bots communicating in their own non-human language.