Three military veterans once involved in the U.S. drone program have thrown their support behind a Yemeni man's legal fight to obtain details about why his family members were killed in a 2012 strike. The former soldiers' unusual decision to publicly endorse the lawsuit against President Obama and other U.S. officials adds another twist to Faisal bin Ali Jaber's four-year quest for accountability in the deaths of his brother-in-law and nephew, who he believes needlessly fell victim to one of the most lethal covert programs in U.S. history. The former enlisted service members told the U.S. Court of Appeals for the District of Columbia Circuit in a recent filing that they believe the 2012 drone strike serves as a case study of how mistakes frequently occur in the nation's targeted-killing program, where life-or-death decisions are based upon top-secret evidence. The veterans say they "witnessed a secret, global system without regard for borders, conducting widespread surveillance with the ability to conduct deadly targeted killing operations." Though the veterans did not disclose any personal knowledge of the strike that is alleged to have killed Jaber's relatives, they claim the military frequently labels the deaths of unknown victims as "enemy kills."

SYSPRO is unveiling the new capabilities to 24 leading enterprise software analysts from 12 different global firms during a two week roadshow. It has labeled its tour, "Going for the Gold in Best of Class ERP" and is showcasing sophisticated leading-edge technology advances, such as bots, predictive search, and product integrations to the Internet of Things (IoT), plus a host of powerful new, role-based data access for users. Industry analysts have been predicting for the last 12 months or more that such technologies will erase some of the key competitive barriers that might otherwise impede newer or mid-sized manufacturing firms from competing as effectively as they'd like. "To compete effectively today in a global market, manufacturers and distributors of all sizes need to leverage state-of-the-art technologies that can optimize profit margins while delivering a better customer experience," said Predrag Jakovlevic, Principal Analyst, Enterprise Applications, for Technology Evaluation Centers. "While giant ERP companies often dominate the news, companies like SYSPRO are now announcing delivery of some of the hottest new IT capabilities embedded within their software, like bots and predictive search, and have made commitments to bringing machine learning, artificial intelligence and IoT to market in 2017. The point is, very affordable ERP solutions like SYSPRO can give even small and mid-sized manufacturers the ability to be very successful against much larger market competitors."

A few years ago, Scott Fortmann-Roe wrote a great essay titled "Understanding the Bias-Variance Tradeoff." As data science morphs into an accepted profession with its own set of tools, procedures, workflows, etc., there often seems to be less of a focus on statistical processes in favor of the more exciting aspects (see here and here for a pair of example discussions). While this will serve as an overview of Scott's essay, which you can read for further detail and mathematical insights, we will start by with Fortmann-Roe's verbatim definitions which are central to the piece: Error due to Bias: The error due to bias is taken as the difference between the expected (or average) prediction of our model and the correct value which we are trying to predict. Of course you only have one model so talking about expected or average prediction values might seem a little strange. However, imagine you could repeat the whole model building process more than once: each time you gather new data and run a new analysis creating a new model.

Gradient boosting (GB) is a machine learning algorithm developed in the late '90s that is still very popular. It produces state-of-the-art results for many commercial (and academic) applications. This page explains how the gradient boosting algorithm works using several interactive visualizations. We take a 2-dimensional regression problem and investigate how a tree is able to reconstruct the function \( y f(\vx) f(x_1, x_2) \). Play with the tree depth, then look at the tree-building process from above!

That's what disruptive technology is about. Olli is built by Local Motors, the start-up famous for creating the first 3D printed car. However, the brains for Olli were provided by IBM, which contributed its Watson artificial intelligence technology to the vehicle. Together, IBM and Local Motors have produced a vehicle that does far more than simply drive a predetermined route. Instead, Olli combines the capabilities of a chauffeur, a tour guide and a technology expert to communicate with passengers using spoken conversational language.

Businesses have recently realized how effectively Chatbot Strategy can be used for their Brands. Chatbots are now helping people in reducing work load, reducing staff and performing redundant daily tasks. All these helps in reducing human error, efforts and ultimately reducing costs for the organizations. Automating repetitive & mundane work will definitely increase the productivity, creativity, and efficiency of the employees. Bots have an edge over Apps.

In their seminal 2013 paper, Frey and Osborne estimated that nearly 47% of U.S. employment is susceptible to computerization and automation. Insurance agents, salespeople, underwriters and claims adjusters are among the jobs that have high potential for automation. And in recent years, many investors have poured money and attention into digital wealth management solutions such as robo and bionic advice. While some industry observers interpret this as the beginning of the end for financial advisers, others believe financial advisers will continue to play a relevant role in the foreseeable future. However, the next generation of digital wealth management solutions may use more advanced AI to supplement and improve human financial decision-making.

IBM has launched a new range of Linux-based servers which have been specifically engineered for high performance in tasks related to artificial intelligence, deep learning and advanced analytics – with a central mission to increase data centre efficiency. Early tests with Tencent reveal a threefold performance increase, even at 2/3rds deployment. The perhaps inelegantly named IBM Power Systems S822LC for High Performance Computing represents a collaboration with Nvidia, with the latter's NVLink high-speed interconnect facilitating a far greater CPU/GPU throughput than is currently possible over a PCIe bus. The servers have been developed in collaboration with the OpenPower Foundation (OPF), which was set up in 2013 as an accelerator for innovation of custom data centre systems, with a particular remit for workload acceleration via GPU, FPGA or advanced I/O, as well as platform optimisation for SW appliances and advanced hardware technology exploitation. IBM conducted preliminary tests on the new OpenPOWER servers in China with Tencent and was able to run workloads three times faster than on its previous x86-based infrastructure even whilst running a third fewer total number of servers.

With the increasing need for individualized, context-rich Customer Care Banks are increasingly investing into service automation. That's why Chatbot is a revolution in banking. Bots help serve Clients faster, at lower costs, wherever they are and whenever they wish. Co-called'chatbots' are computer systems that simulate human conversations. They represent a text-based dialog system.

In the first blog post of this series we introduced the topic of machine learning and discussed why there is a lot of excitement around the topic. In this blog we explore different types of machine learning. Let's start with a simple example that everyone can relate to. You want to teach a three year old some basic discipline of keeping their toys in the right place. The room is full of interlocking blocks and soft toys.