Building Game Bot with OpenAI's Gym (Live Coding starts at 15:00) (youtube.com) I'm really loving what this guy has been doing for making deep learning and machine learning more accessible and fun.

We consider the problem of multiple agents sensing and acting in environments with the goal of maximising their shared utility. In these environments, agents must learn communication protocols in order to share information that is needed to solve the tasks. By embracing deep neural networks, we are able to demonstrate end-to-end learning of protocols in complex environments inspired by communication riddles and multi-agent computer vision problems with partial observability. We propose two approaches for learning in these domains: Reinforced Inter-Agent Learning (RIAL) and Differentiable Inter-Agent Learning (DIAL). The former uses deep Q-learning, while the latter exploits the fact that, during learning, agents can backpropagate error derivatives through (noisy) communication channels.

Apple has refused to join the likes of Google and Facebook on a new consortium that will aim to ensure artificial intelligence (AI) technology is developed in a safe, ethical, and transparent manner. The consortium -- announced on Wednesday and called Partnership on AI -- also counts Amazon, Microsoft, and IBM among its founding members. But Apple's playing hard to get. Eric Horvitz, technical fellow and managing director at Microsoft Research, said: "We've been in discussions with Apple and they're enthusiastic about the effort. I personally hope to see them join."

Too often, machine learning requires a massive investment of time and terabytes of data before it can deliver meaningful insights. But that doesn't have to be the case. A well-configured machine learning analytics tool can rapidly provide initial results -- a key advantage for developers who can then start using those results to create value. To understand this dynamic, companies have to start taking a data approach that embraces the fact that what is driving companies in today's connected world is not data, but insight. And the volume of data being created in today's connected world is not just what powers this insight…but also blocks you from finding it.

On this episode, I am so happy to have Pedro Domingos who is a professor at the University of Washington. He's the leading researcher in machine learning and recently wrote an amazing book called The Master Algorithm. I was fortunate enough to have a long and fascinating conversation with him over dinner one night which I hoped would never end but that ended up leading to this episode which I think you will love. In this conversation we explore the sources of knowledge, the five major schools of machine learning, why white collar jobs are easier to replace than blue collar jobs, machine wars, self-driving cars and so much more. Transcript: A complete transcript is available for members.

Google's latest advance in machine learning could make the world a little smaller. The company is reëngineering its translation service after Google researchers invented a system that is significantly more accurate. In a competition that pitted the new software against human translators, it came close to matching the fluency of humans for some languages, such as when translating from English to Spanish. Google has already begun rolling out the new system for translations from Chinese to English (see examples showing the improvement). The company expects to replace its current translation system altogether.

Apple has refused to join the likes of Google and Facebook on a new consortium that will aim to ensure artificial intelligence (AI) technology is developed in a safe, ethical, and transparent manner. The consortium -- announced on Wednesday and called Partnership on AI -- also counts Amazon, Microsoft, and IBM among its founding members. But Apple's playing hard to get. Eric Horvitz, technical fellow and managing director at Microsoft Research, said: "We've been in discussions with Apple and they're enthusiastic about the effort. I personally hope to see them join."

These days, a lot of workers are worried about robots taking their jobs, but now robots are taking jobs that literally no one else was doing--like poring through every inch of people's dense expense reports. AppZen, a startup that provides automated auditing services, has just expanded its software, which can now not only read basic items on attached receipts, but also scan entire documents to look for clues about invalid charges. Anant Kale, the company's CEO, tells Fast Company that the new offering, called ReceiptIQ, can audit 100% of the expense reports that employees submit, spotting them for "accidental fraud . . . The upgrade required moving beyond optical character recognition to computer vision that can understand the entire receipt, such as recognizing company logos. Many hotels put their logos on receipts rather than spelling out their name, says Kale. ReceiptIQ analysis goes deeper by looking for context, such as whether car rental bills include a fuel service charge--a penalty for not returning the car with a full gas tank.

The world's largest technology companies hold the keys to some of the largest databases on our planet. Much like goods and coins before it, data is becoming an important currency for the modern world. The data's value is rooted in its applications to artificial intelligence. Whichever company owns the data, effectively owns AI. Right now that means companies like Facebook, Amazon, Alphabet, IBM and Microsoft have a ton of power.

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