Bank bots are on their way. Text a question like "What's my credit card debt?" or "How much did I spend on gas this month?" "Let's see," it begins, before listing the requested information. This is a banking chatbot, a software program that understands and responds to questions and commands about your bank account. It's like your bank's customer service representative -- powered by artificial intelligence.

The field of artificial intelligence was born at Dartmouth College in 1956 at a conference where the leading experts in the field of computer science met. A feeling of optimism pervaded the conference at attendees were confident that within 20 years, machines would be doing all our work for us. But by the 70's humans were no closer to creating artificial intelligence and money and interest in the field dried up. It was only recently that interest in AI was renewed and it has led to the current artificial intelligence revolution that we are in the midst of. Now that the day dream about at the Dartmouth conference of 1956 is just around the corner, here are four ways businesses can be benefiting from artificial intelligence.

The field of artificial intelligence was born at Dartmouth College in 1956 at a conference where the leading experts in the field of computer science met. A feeling of optimism pervaded the conference at attendees were confident that within 20 years, machines would be doing all our work for us. But by the 70's humans were no closer to creating artificial intelligence and money and interest in the field dried up. It was only recently that interest in AI was renewed and it has led to the current artificial intelligence revolution that we are in the midst of. Now that the day dream about at the Dartmouth conference of 1956 is just around the corner, here are four ways businesses can be benefiting from artificial intelligence.

The field of artificial intelligence was born at Dartmouth College in 1956 at a conference where the leading experts in the field of computer science met. A feeling of optimism pervaded the conference at attendees were confident that within 20 years, machines would be doing all our work for us. But by the 70's humans were no closer to creating artificial intelligence and money and interest in the field dried up. It was only recently that interest in AI was renewed and it has led to the current artificial intelligence revolution that we are in the midst of. Now that the day dream about at the Dartmouth conference of 1956 is just around the corner, here are four ways businesses can be benefiting from artificial intelligence.

Four Ways Every Business Can Benefit from Artificial Intelligence The field of artificial intelligence was born at Dartmouth College in 1956 at a conference where the leading experts in the field of computer science met. A feeling of optimism pervaded the conference at attendees were confident that within 20 years, machines would be doing all our work for us. But by the 70's humans were no closer to creating artificial intelligence and money and interest in the field dried up. It was only recently that interest in AI was renewed and it has led to the current artificial intelligence revolution that we are in the midst of. Now that the day dream about at the Dartmouth conference of 1956 is just around the corner, here are four ways businesses can be benefiting from artificial intelligence.

The field of artificial intelligence was born at Dartmouth College in 1956 at a conference where the leading experts in the field of computer science met. A feeling of optimism pervaded the conference at attendees were confident that within 20 years, machines would be doing all our work for us. But by the 70's humans were no closer to creating artificial intelligence and money and interest in the field dried up. It was only recently that interest in AI was renewed and it has led to the current artificial intelligence revolution that we are in the midst of. Now that the day dream about at the Dartmouth conference of 1956 is just around the corner, here are four ways businesses can be benefiting from artificial intelligence.

When former Microsoft CEO Steve Ballmer handed the reins to Satya Nadella, the company had not long before undergone a complete reorganization. Ballmer knew that Microsoft needed a new face with a fresh set of eyes at the helm, that it was time to let younger blood lead the company wherever it was destined. And where exactly is that? Fast forward to today and Nadella is steering Microsoft towards an interesting future in deep learning and artificial intelligence. Lest there be any doubt, Nadella said as much during a keynote at Microsoft's Ignite conference for IT professionals in Atlanta, GA.

This is how simple neurons get smarter and perform so well for certain problems such as image recognition and playing Go. Inception: an image recognition model published by Google (From: Going deeper with convolutions, Christian Szegedy et al.) Some published examples of visualization by deep networks show how they're trained to build the hierarchy of recognized patterns, from simple edges and blobs to object parts and classes. In this article, we looked at some TensorFlow Playground demos and how they explain the mechanism and power of neural networks. As you've seen, the basics of the technology are pretty simple.

IBM Watson is a Cognitive Computer that has opened up new avenues of human - computer collaboration. IBM Watson has a lot of human language processing capabilities and extreme scale information retrieval. It has found a lot of applications in the areas of Healthcare, Banking, Consumer Retail and Lifestyle, thanks to the ability to understand complex information architectures and human life scenarios. Its ability to make continuous inferences based on repeated question - answering problems is amazing. It is a continuously learning machine with cognitive information processing abilities.

We are happy to announce one of the first new contributions driven by our AI Lab in Graz, Austria: adding a feature that provides semantic segmentations for a select number of object categories. In this blog post we will discuss what this is all about and why we think that this development will be useful for our members and customers. With over 20M Mapillary photos processed so far, we see this advancement as the beginning of our quest to apply broader object recognition globally to all Mapillary photos. Semantic segmentation is a long-studied problem in computer vision and one of the grand challenges to be solved when it comes to automatically understanding the world we live in. Essentially, semantic segmentation allows us to assign a categorical tag (also called a label) to each pixel in an image.