In the post How to Train Neural Networks With Backpropagation I said that you could also calculate the gradient of a neural network by using dual numbers or finite differences. The post I already linked to explains backpropagation. Since the fundamentals are explained in the links above, we'll go straight to the code. We'll be getting the gradient (learning values) for the network in example 4 in the backpropagation post: Note that I am using "central differences" for the gradient, but it would be more efficient to do a forward or backward difference, at the cost of some accuracy. I didn't compare the running times of each method as my code is meant to be readable, not fast, and the code isn't doing enough work to make a meaningful performance test IMO.

IBM recently announced that it reached a new industry record in conversational speech recognition, which could have big implications for the future of artificial intelligence (AI). The IBM team's system achieved a 5.5% word error rate--down from 6.9% last year. The benchmark was measured on a difficult speech recognition task, with the machine deciphering recorded conversations between humans discussing day-to-day topics such as buying a car. This recording is known as SWITCHBOARD, and has been used for more than two decades to test speech recognition systems, according to a blog post by George Saon, a principal research scientist at IBM. IBM used deep learning technologies to reach the 5.5% record.

A report from research firm IDC has thrown more light on the emerging importance of Artificial Intelligence (AI). According to a new Worldwide Semiannual Cognitive/Artificial Intelligence Systems Spending Guide, spending on AI technologies is all set to surge from $8 billion in 2016 to $47 billion in 2020. With healthcare being one of the industries that will invest the most on cognitive/ AI systems, it is apparent that this industry is betting big on AI technologies. Virtual assistants, intelligent automation and cognitive computing all are going to impact various facets of healthcare – from operations to patient-centric care to precision medicine. Data is a huge driving force in the world of healthcare today.

Interventional radiologists at the UCLA Medical Center are leveraging artificial intelligence to create a "chatbot" that automatically communicates with referring clinicians, providing them with evidence-based answers to frequently asked questions. Currently, the AI-powered prototype is being tested by a small UCLA team of hospitalists, radiation oncologists and interventional radiologists. The machine learning application, which acts like a virtual radiology assistant, enables clinicians to rapidly access valuable information while enabling them to perform other duties and to focus on patient care. The information is delivered in multiple formats, including relevant websites, infographics, and subprograms within the application. And if the tool determines that an answer requires a human response, contact information for an actual interventional radiologist is provided.

MOBILE WORLD CONGRESS, Barcelona and REDWOOD CITY, California, February 27, 2017 -- Aricent, a global design and engineering company, today announced the launch of Cognitive Services to enhance customer engagement and brand loyalty in a digital era. Artificial Intelligence (AI) is top of mind today for most business leaders who seek to provide unique value around their products and services for a truly compelling customer experience. AI is a wide ranging category containing many capabilities including Natural Language Processing, Natural Language Understanding, Machine Learning, Deep Learning and Computer Vision. However, launching successful products and services powered by AI is challenging. As per Gartner Research report titled Top 10 Strategic Technology Trends for 2017*, "Significant investment in skills, process and tools is needed to successfully exploit these techniques in terms of setup, integration, algorithm/approach selection, data preparation and model creation."

Artificial intelligence has a long history of boom and bust cycles. During A.I. booms, money flows through universities and industry labs, fueling promised advances that often sound like magic, if not panacea. Extreme optimism was particularly common in the field's early years. In 1960, for example, A.I. pioneer Herbert Simon suggested that "machines will be capable, within twenty years, of doing any work that a man can do," a claim echoed by the founder of the field, Marvin Minsky, in 1961. Despite the advances that have occured since that time -- most recently, breakthroughs in neural networks, a form of machine learning inspired by the biological structure of the brain -- today's leading researchers tend to be more circumspect about the potential of artificial intelligence in the near-term.

Students of artificial intelligence are getting recruited like star athletes, but could a rush to get new technology on the field cause ethical lapses? You walk into a gigantic auditorium. Folding chairs are lined up in evenly spaced rows, with a cold black awning behind the stage and uniform white or yellow lights pouring down on the sea of seats below. A couple of huge screens are to either side of the stage with a third in the center in the middle of the room for those who can't see the presentation. What's about to happen is one of the most important annual gatherings in tech.

Messaging app Viber has introduced a new feature called'Secret Chats', designed to protect users from the prying eyes of CIA agents. It takes tips from Snapchat, with messages self-destructing after a specific amount of time, which users set themselves. Secret Chats also features screenshot restrictions. Only iOS users can capture screenshots of conversations, and Viber will notify users when this happens. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Swarms of robots scouring enemy terrain ahead of ground troops in'Iron Man' exoskeletons with built in weapons may sound like it is straight from the pages of a sci-fi novel, but Army experts believe this is actually a glimpse of war in 2025. The US Army has revealed a 30 page vision of the future of battle, described as a'mad scientist' concept. It says that while robots will play a vital role, humans will still be at the heart of battle - albeit heavily augmented by technology. According to the strategy, the Army envisions that, by 2025, ground troops will conduct foot patrols in with robots called'squad multipurpose equipment transport vehicles' that carry rucksacks and other equipment. Overhead, unmanned aircraft will serve as spotters to warn troops of nearby enemy forces.

The global technology sector is on the brink of an explosion of data, according to top executives at Intel, who say the growth of cloud computing will be accelerated by new technologies like artificial intelligence (AI), the Internet of Things, virtual reality, drones, robots and autonomous vehicles. "This explosion of data will usher in an era of profound transformation," said Murthy Renduchintala, President of Intel's IoT and Client Businesses. "It will create a need for new infrastructure and drive demand for a new interconnectedness of everything." At the heart of this revolution is the data center. At its Analyst Day Thursday, Intel outlined a "Data Center First" strategy that looks beyond the CPU to a product portfolio that spans the data center, including memory, networking and emerging technologies like the IoT and AI.