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Machine translation has significantly evolved over time, especially in terms of accuracy levels in its output.

Our cities, streets, homes, and businesses are built for beings that walk on two legs (biped). From stairs to the shape of hallways to the placement of kitchen cabinets, all have been designed for bipeds. The fact that a society of two-legged creatures designed everything around them for bipeds is so obvious most people don’t even think about it, but it becomes a serious issue when talking about the future of robotics.

The following article about artificial intelligence for UX has been written by Paul Daugherty, Chief Technology and Innovation Officer at Accenture. Accenture is a Fortune 500 consulting and services firm with nearly 400,000 global employees. Editing and quotes added by the Emerj team. For information about our contributed material and publishing arrangements with brands, please visit our partnerships page.

While in previous decades military unmanned aerial vehicles (UAV) were very simple pieces of equipment, the technology has advanced rapidly. They are now used all over the world and are a multi-billion dollar industry. According to the Teal Group, current worldwide military UAV production stands at around $2.8 billion, and they project it will grow to $9.4 billion in 2025.

The market for military robotics is massive, and many developments can be observed in public competitions, university campuses, and DARPA's own announcements.

It’s no secret that e-tailer Amazon has an army of robots at its warehouses to fulfill orders; currently its robot detail is 45,000 strong. The company also wants to put a fleet of airborne drones into service for fast deliveries. The question that traditional retailers face is whether or not investing in robots to operate inside their stores can actually improve business and help them stay relevant with consumers.

Real estate is a cost for nearly every business, whether leasing, owning or managing.

Process automation from AI offers a tremendous opportunity to lower costs associated with commercial real estate, especially those associated property management.

Episode Summary: The upsurge of malware and sophisticated attacks continue to keep cybersecurity in the spotlight, but new developments in AI and deep learning offer more advanced solutions to combat security threats. This week, we catch up with Eli David, CTO of Deep Instinct—a company founded in Israel with US headquarters in San Francisco—that applies deep learning in malware defense and information security. David spoke with us about why and how the deep-learning approach to AI is relevant to the future of cybersecurity.

Episode Summary: Uday Veeramachaneni is taking a new approach to machine learning in infosecurity aka infosec. Traditionally, infosec has approached predicting attacks in two ways: 1—through a system of hand-designed rules and 2—through anomaly detection, a technique that detects statistical outliers in the data. The problem with these approaches, Veermachaneni says, is that the signal-to-noise ratio is too low. In this episode, Veermachaneni discusses how his company, PatternEx, is using machine learning to provide more accurate attack prediction. He also discusses the cooperative role of man and machine in building robust automated cyberdefense systems and walks us through a common security attack scenario.

Episode Summary: Market research and trends is important when discussing AI and business, but it's also worthwhile to contemplate the ethical and social implications further down the line. How will countries deal with potential unemployment problems? How might countries collaborate to hedge against the risks that AI poses to the future of work and other economic facets? A relatively small group is helping people do just that i.e. getting organizations and countries to think through how they could hedge against the grander risks inherent in a world powered by AI.
In this episode, we speak with Jerome Glenn, head of the Millennium Project, a global participatory think tank with 60 Nodes around the world that that focuses on research implementing the organizational means, operational priorities, and financing structures necessary to address 15 Global Challenges. Glenn talks about how he gets principalities of the world to bring their big industrial players and the public to talk through possible scenarios that are 30, 40, even 50 years in the future, and about ways we might potentially hedge against risks and make the most of the upsides of AI in a global economy. If you enjoyed listening to our recent podcast with OpenAI's Ilya Sutskever on preparing for the future of AI, then you may find Glenn's ideas and the mission of The Millennium Project to be an interesting and useful perspective on this issue as well.