At its annual F8 developer conference this coming week, Facebook Inc. will feature enhanced tools for commerce over its Messenger app, according to people familiar with the matter. The new offerings will use so-called chatbot technology to help users order goods and services through the app, the people said. This will be the second consecutive year Facebook has highlighted Messenger at F8, a sign of messaging's growing prominence inside the company. Last year, Facebook opened Messenger to outside developers, including makers of photo- and video-editing apps, and businesses such as Everlane and Zulily, which use the app to field customer questions and provide shipping updates. Inc., which sells and delivers flowers and food baskets, as a potential partner for the new Messenger services, according to a person familiar with the conversations. Under one scenario, 1-800-Flowers could contact past customers over Messenger about upcoming holidays such as Mother's Day and highlight promotions.

A new hunter is lurking in the deep -- and it's made of metal, silicon, and lots and lots of artificial intelligence. The Defense Advanced Research Projects Agency (DARPA) officially launched its unmanned submarine-hunting ship, holding a christening ceremony on Thursday (April 7) for the "Sea Hunter." The new vessel is part of DARPA's larger initiative to use artificial intelligence (AI) for a wider array of military decisions and tasks. The seafaring drone's task is to find and neutralize enemies' ultraquiet diesel submarines, the agency said. While the Sea Hunter, which is part of DARPA's Anti-Submarine Warfare Continuous Trail Unmanned Vessel (ACTUV) program, is not helmed by a human captain, people are still in the loop (at least for now). "Although ACTUV will sail unmanned, its story is entirely about people," Scott Littlefield, DARPA program manager, said in a statement.

Take a three-year-old to the zoo, and she intuitively knows that the long-necked creature nibbling leaves is the same thing as the giraffe in her picture book. That superficially easy feat is in reality quite sophisticated. The cartoon drawing is a frozen silhouette of simple lines, while the living animal is awash in color, texture, movement and light. It can contort into different shapes and looks different from every angle. Humans excel at this kind of task.

Late last year e-commerce giant, Amazon, added another emerging firm to its list of acquisitions, keeping this information relatively low profile until Bloomberg reported on the move this week. The company in question is Orbeus, which focuses its operations on creating artificial intelligence that is capable of determining what items and objects are present in a picture or photo. This kind of image recognition means that computers are capable of perceiving the world in a similar way to humans and could have obvious applications in terms of safe shopping online. While the takeover has not been officially confirmed, sources claim that it was completed in the autumn of 2015, according to Business Insider. And with recent reports of Amazon working towards introducing selfie-based payment authentication, imaging is clearly an area in which it holds a significant interest.

A team of researchers led by Rajesh Rao, a professor of computer science and engineering at the University of Washington, recently published a paper showing how robots can learn much like children – amassing data by watching adults do something, determining the goal of the action and then deciding how to perform it on their own. "This is a major step in designing robots that can learn from watching humans," said Micah Clark, a program officer in ONR's Warfighter Performance Department who oversees Rao's research. "It could one day result in truly intelligent machines that understand the intent and goals behind certain tasks, and help humans achieve those goals." For decades, scientists, writers, and filmmakers have envisioned a future where robots make human life safer and easier by doing mundane household chores or helping troops in battle. Rao believes this type of artificial intelligence might be achieved with inspiration from the most adorable and inquisitive of humans; babies.

Ensemble methods are techniques that create multiple models and then combine them to produce improved results. Ensemble methods usually produces more accurate solutions than a single model would. This has been the case in a number of machine learning competitions, where the winning solutions used ensemble methods. In the popular Netflix Competition, the winner used an ensemble method to implement a powerful collaborative filtering algorithm. Another example is KDD 2009 where the winner also used ensemble methods.

Too much data and too few people: Firstly, this is a no surprise that machine learning algorithms will work at the pace not matching their counter scientist friends. If trained properly, machine could easily pacify majority of data preparation and analysis demand in data analytics world. Another cool thing about machine learning is that once code is prepped and machine is programmed, you could use it multiple times and multiple places and see the magic happen. The trick is to not overkill first but to use it for overhead tasks first and keep making it more and more sophisticated, so that it will start doing all the heavy lifting and pacifying the resource demand as a result. Hence, machine learning single handedly can reduce big-data resource crunch and make the resource distribution relevant and appropriately.

Before assessing the potential impact Artificial Intelligence can have in the health insurance industry, it's important to understand what the term "AI" really means. In general, AI refers to a series of algorithms that can collect, process and analyze data on their own, without being explicitly programmed, to make predictions and insights far beyond the capabilities of manual processing. Originally conceived back in the 1950's companies have been attempting to design and improve machine learning models for decades only to have seen little commercial success. But thanks to hardware advances and the emergence of big data analytics, companies are recognizing and taking advantage of the true power of AI. In the health insurance space, there are many opportunities where AI and analytics can be applied to increase organizational productivity and drive new competitive advantages in today's fast-paced and complex business environment. One of the channels to increase productivity is through improved fraud detection, which is a major issue in the health insurance industry.

Systems continue to evolve and expand in ways that benefit radiologists, providers, and patients. CT imaging in the emergency department (ED) is increasing rapidly. In fact, it now comprises more than 35% of all CT procedures in the United States. Today's CT scanners include technological developments that enable customers to better manage patient care, including lung cancer screening, dose guidance and regulation, spectral and multienergy imaging, and expansion of cardiac and brain imaging. These scanners and solutions also provide new levels of information to help clinicians make a more confident diagnosis at low dose, without increasing complexity in their routines.

Demis Hassabis, the cofounder and CEO of DeepMind, a Google-owned AI lab in London, is planning to buy a Tesla 3 from Elon Musk -- one of the company's earliest investors. Hassabis congratulated Musk on Twitter after Musk tweeted that 276,000 Model 3 orders had been made by the end of Saturday, just two days after the electric car was launched. He also said he was planning to buy one of the new vehicles. "Really amazing to hear!! Just placing my order...," Hassabis wrote. At 35,000 ( 24,423), the five-seater Model 3 is the cheapest Tesla to date and is due to start shipping in late 2017.