Girouard: With a third of our management team from Google, we're the first consumer platform to leverage machine learning and modern technology to power our platform. A lot of other lenders give lip service to being technology companies when they're really finance companies who hired a few Web developers. We're the real deal when it comes to data science and technology. We have a team of data scientists who are predominantly math and statistics PhDs - they don't come from traditional credit modeling backgrounds. If you looked inside 99% of lenders, you would see fairly simple modeling techniques that amount to look-up tables, or at best simple linear regression.

Artificial intelligence (AI) already plays a major role in human economies and societies, and it will play an even bigger role in the coming years. To ponder the future of AI is thus to acknowledge that the future is AI. This will be partly owing to advances in "deep learning," which uses multi-layer neural networks that were first theorized in the 1980s. With today's greater computing power and storage, deep learning is now a practical possibility, and a deep-learning application gained worldwide attention in 2016 by beating the world champion in Go. Commercial enterprises and governments alike hope to adapt the technology to find useful patterns in "Big Data" of all kinds.

JPMorgan has developed machine learning software that saves the company 360,000 lawyer hours per year. Normally it takes a team of lawyers many hours interpreting the 12,000 commercial-loan agreements that JPMorgan processes per year. With the new Contract Intelligence software nicknamed COIN; JPMorgan is finding far less mistakes being made and it only takes seconds to process a form. JPMorgan invests heavily into technology by budgeting 9% of their projected revenue into development of new technology. This amount exceeded $1 billion dollars of technology investment over the past two years.

The writer William Gibson once said that the future is here, just not evenly distributed. That was the case with the World Wide Web 20 years ago, when some business models – notably e-commerce and new media – took off faster than others. Now a similar trend is happening with artificial intelligence, or AI. The promise of AI has seemingly been just on the horizon for years, with little evidence of change in the lives of most consumers. A few years ago, buzzwords like "big data" hinted at the potential, but ending up generating little actual impact.

Google's Perspective API, created in conjunction with Alphabet incubee Jigsaw, is supposed to provide an automated way to detect "toxic" language in social media. "Through different experiments, we show that an adversary can deceive the system by misspelling the abusive words or by adding punctuations between the letters," the four academics wrote in their recently published paper, "Deceiving Google's Perspective API Built for Detecting Toxic Comments." The API is intended to allow digital publishers to assess the sentiment expressed in online posts in real time. Words get sent to a server for analysis and scores get returned, ideally allowing publishers to detect trolls as they type and to take the necessary steps to keep online interaction civil. In practice, just like other automated content filtering, malware detection, and spam detection systems, Perspective can be fooled.

Researchers have discovered a number of security vulnerabilities in existing robots, which they say can be used by criminals to cause serious harm to their owners. IOActive tested robot operating systems and other software in order to identify nearly 50 flaws in robots from vendors including SoftBank Robotics, UBTECH Robotics, ROBOTIS, Universal Robots, Rethink Robotics, and Asratec Corp. Insecure communications, authentication issues, weak cryptography, memory corruption and privacy problems were just some of the issues named by the firm's senior security consultant Lucas Apa. The research paper says that criminals could exploit the flaws to gain control of robots in homes and workplaces, using them to spy on people and cause physical damage. 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, ...

Gartner says 85% of customer interactions will be managed without a human by 2018. The prognostications of analysts are to be taken with a pinch of salt, but those working in the eCommerce field are hardly less enthusiastic. "Online retailers are scrambling to partner with or adopt new AI technologies to help facilitate customer interaction to try and match and even surpass the typical in-store experience" Let's have a look at two of the ways eCommerce merchants are already using AI to augment the experience of both retailers and their customers.

But first, let's start with some background. Two major tasks in computer vision are object classification and object detection. In the first case the system is supposed to correctly label the dominant object in an image. In the second case it should provide correct labels and locations for all objects in an image. Of course there are other interesting areas of computer vision, such as image segmentation, but today we're going to focus on detection.

If you work in the tech sector or have interest in the tech scene, you've probably heard the term "deep learning" floating around quite a bit. It's the emerging area of computer science that is revolutionizing artificial intelligence, allowing us to build machines and systems of the future. Although deep learning is making our lives easier, understanding how it works can be hard. Having spent quite some time exploring the world of deep learning, mostly for computer vision applications, I learned a thing or two on what it's all about and therefore I'm here to share what I learned. Firstly, before you understand deep learning, it's important that you know what machine learning is.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)