We all enjoy sharing jokes with friends, hoping a witty one might elicit a smile--or maybe even a belly laugh. A lawyer opened the door of his BMW, when, suddenly, a car came along and hit the door, ripping it off completely. When the police arrived at the scene, the lawyer was complaining bitterly about the damage to his precious BMW. "Officer, look what they've done to my Beeeeemer!" he whined. "You lawyers are so materialistic, you make me sick!" retorted the officer.

We all enjoy sharing jokes with friends, hoping a witty one might elicit a smile--or maybe even a belly laugh. A lawyer opened the door of his BMW, when, suddenly, a car came along and hit the door, ripping it off completely. When the police arrived at the scene, the lawyer was complaining bitterly about the damage to his precious BMW. "Officer, look what they've done to my Beeeeemer!" he whined. "You lawyers are so materialistic, you make me sick!" retorted the officer.

For seven years, AI researchers have been struggling with an unusual challenge: shooting cartoon birds at cartoon pigs. An annual competition tests their ability to craft an AI agent that can play the popular video game Angry Birds. This month two researchers posted a paper on arXiv.org It's an example of the kind of weird obstacles that all AI researchers face as they attempt to adapt cutting-edge technologies to some very human endeavors. Teams around the world are tackling much more sophisticated problems, persevering to overcome the obstacles on the path to our shiny technology-enhanced future.

Microsoft and Chinese retailer Alibaba independently announced that they had made software that matched or outperformed humans on a reading-comprehension test devised at Stanford. Microsoft called it a "major milestone." Media coverage amplified the claims, with Newsweek estimating "millions of jobs at risk." Those jobs seem safe for a while. Closer examination of the tech giants' claims suggests their software hasn't yet drawn level with humans, even within the narrow confines of the test used.

Lip reading, an essential tool that helps the hearing-impaired to better understand the world, is now conducted by artificial intelligence with a better accuracy than done by humans, University of Oxford reveals. In an article currently published by Quartz we learn that a new paper issued by the University of Oxford with funding from Alphabet's Deepmind, reveals that they have developed an artificial intelligence system called LipNet that can read lips with an accuracy of 93.4%. University of Oxford has previously released a system that operated word-by-word with an accuracy of 79.9%, but their new system has now developed a new and different way of approaching the problem. "Instead of teaching the AI each mouth movement using a system of visual phonemes, they built it to process whole at a time. That allowed the AI to teach itself what letter corresponds to each slight mouth movement", Quartz writes. The new system was exposed to 29 000 3-second-videos videos labelled with the correct text to train the system, and in comparison with human lip-readers that had an average error rate of 47.7%, the AI's error rate was only 6.6%.

AI has achieved a win experts once thought wasn't possible. Harvard University was recently awarded a 28 million grant to discover why human brains are so much better at learning and pattern recognition than artificial intelligence (AI). Dispensed by the Intelligence Advanced Research Projects Activity (IARPA), the funding will fuel a quest to make AI systems faster, smarter, and match or outperform human neural networks. The steep challenge in this quest is the enormous complexity of the human brain and its billions of neurons and trillions of synaptic interconnections with electrochemical signaling. The other challenge: There is no accepted theory of mind that describes what thought--the gist of intelligence--actually is.

AlphaGo, Google's artificially intelligent computer program, beat a professional human Go player last October in 4 out of 5 matches. Go is a very complex board game to master and has been around since the 1000s. The game requires the players to think ahead a few moves and consider what the opponent might or might not do. Tasks that involve a lot of decision-making or snap decisions have typically been difficult for computers to achieve. AlphaGo is helping to break that barrier.

If you happen to have a free 30 hours or so, I would highly recommend watching Google's AlphaGo program take on one of the best players in the world at the ancient Chinese board game Go. If you don't have that much time, you could instead just watch the 6-hour third match, where the program wrapped up the best of five series. It's literally history being made. Some news outlets have covered this feat, but I don't think many people understand how monumental this actually is. Back in 1997, when Garry Kasparov was beaten by IBM's Deep Blue in chess, people were more excited about the future of computing.