Five major technology companies said Wednesday that they had created an organization to set the ground rules for protecting humans -- and their jobs -- in the face of rapid advances in artificial intelligence. The Partnership on AI, unites Amazon, Facebook, Google, IBM and Microsoft in an effort to ease public fears of machines that are learning to think for themselves and perhaps ease corporate anxiety over the prospect of government regulation of this new technology. The organization has been created at a time of significant public debate about artificial intelligence technologies that are built into a variety of robots and other intelligent systems, including self-driving cars and workplace automation. The industry group introduced a set of basic ethical standards for engineering development and scientific research that its five members have agreed upon. In a conference call on Wednesday, five artificial intelligence researchers representing the companies said they thought the technology would be a major force in the world for social and economic benefits, but they acknowledged the potential for misuse in a wide variety of ways.

Silicon Valley powerhouses are trying to calm public fears about the rise of artificial intelligence. A new non-profit coalition that counts Google, Facebook and Amazon as members is hoping to demystify the emerging technology -- one tech giants believe has the potential to transform their businesses. "They care how these technologies will influence people and [about] the social and societal consequences more broadly." Artificial intelligence is a field that encompasses many different technological developments. It's seen in innovations like self-driving cars, helping them navigate the roads, and in the personal assistant apps on smartphones that answer queries, organize calendars and more.

The gig: Kirstin Harper-Smith, 32, is senior project manager at Boston-based Suffolk Construction, where she is supervising the building of a 525-unit apartment tower on Hope Street in downtown Los Angeles. The 888 Grand Hope Lofts project by L.A. developer CIM Group will eventually rise 34 stories, consuming 27,000 cubic yards of concrete and 3,500 tons of rebar along the way. As head of the 10-person office side of the project, she oversees the budget, ensures safety requirements are met and directs who should do what jobs when -- all while trying to keep the project on schedule to wrap in about two years. She anticipates 10-hour days until then. An early start: Harper-Smith caught the engineering bug while growing up in San Diego.

On weekdays, Daisuke Kuramoto, 36, is just another computer engineer who develops education materials for an e-learning content provider. But once a month, he becomes Qramo, organizer of a computer programming workshop for children. "If you say I am'teaching' programming, that's incorrect," said Kuramoto, who heads the Tokyo-based volunteer group Otomo. "At the workshop, I'm just a participant who loves to play around with programming." Kuramoto started the workshop in 2008 and launched Otomo the following year, recruiting professional programmers, computer science students, parents and others with a knack for the activity.

The Data Science team at Greenhouse Group is steadily growing and continuously changing. This also implies new Data Scientists and interns starting regularly. Each new Data Scientist we hire is unique and has a different set of skills. What they all have in common though is a strong analytical background and the practical ability to apply this on real business cases. The majority of our team for example studied Econometrics, a study which provides a strong foundation in probability theory and statistics. As the typical Data Scientist also has to work with lots of data, decent programming skills are a must-have.

Clicking this link will start the download. I first heard the term "machine learning" a few years ago, and to be honest, I basically ignored it that time. I knew that it was a powerful technique, and I knew that it was in vogue, but I didn't know what it really was-- what problems it was designed to solve, how it solved them and how it related to the other sorts of issues I was working on in my professional (consulting) life and in my graduate-school research. But in the past few years, machine learning has become a topic that most will avoid at their professional peril. Despite the scary-sounding name, the ideas behind machine learning aren't that difficult to understand. Moreover, a great deal of open-source software makes it possible for anyone to use machine learning in their own work or research.

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.

A competition pitting artificial intelligence (AI) against human players in the classic video game Doom has demonstrated just how advanced AI learning techniques have become – but it's also caused considerable controversy. While several teams submitted AI agents for the deathmatch, two students in the US have caught most of the flak, after they published a paper online detailing how their AI bot learned to kill human players in deathmatch scenarios. The computer science students, Devendra Chaplot and Guillaume Lample, from Carnegie Mellon University, used deep learning techniques to train their AI bot – nicknamed Arnold – to navigate the 3D environment of the first-person shooter Doom. By effectively playing the game over and over again, Arnold became an expert in fragging its Doom opponents – whether they were other artificial combatants, or avatars representing human players. While researchers have previously used deep learning to train AIs to master 2D video games and board games, the research shows that the techniques now also extend to 3D virtual environments.

IBM's aggressive push into the data analytics market continued today with the announcement of Project DataWorks, a Watson initiative that IBM said is the first cloud-based data and analytics platform to integrate all types of data and enable AI-powered decision-making. Project DataWorks is designed to lower the complexity for business managers and data professionals to collect, organize, govern, secure and generate insight from multi-sourced, multi-format data. The goal: become what IBM calls "a cognitive business." "It's a system that will on-board data, tools, users, apps, all in a scalable and governed way," Rob Thomas, VP of Products, IBM Analytics, told EnterpriseTech. "The purpose is simple: we are preparing all data within a company for use by AI. We're helping people leap in to the future around AI and machine learning."

Cooperation is one of the hallmarks of being human. We are extremely social compared to other species. On a regular basis, we all enter into helping others in small but important ways, whether it be letting someone out in traffic or giving a tip for good service. We do this without any guarantee of payback. Donations are made at a small personal cost but with a bigger benefit to the recipient. This form of cooperation, or donation to others, is called indirect reciprocity and helps human society to thrive.