Mobile apps like Facebook, Twitter, Snapchat and Instagram are touted as the next great opportunity for advertisers, publishers and businesses of all types. But what if a simple conversation tool had the ability to turn prospects into customers far better than any of those hot platforms? Chatbots are software programs that use messaging platforms as the interface to perform a wide variety of tasks--everything from scheduling a meeting to reporting the weather, to helping a customer buy a sweater. Because texting is the heart of the mobile experience for smartphone users, chatbots are a natural way to turn something users are very familiar with into a rewarding service or marketing opportunity. And when you consider that the top 4 messaging apps reach over 3 billion global users (MORE than the top 4 social networks), you can see that the opportunity is huge.

A few weeks ago I posted a map of the Artificial Intelligence landscape in Ireland. The map is a visual representation of resident Irish companies in the A.I. space. I decided to go a step further and put together an overview of the Irish Artificial Intelligence industry. I used the companies on the map to form the basis of the findings covered in this blog. I use the phrase'Artificial Intelligence' as an umbrella term to categorise the industry.

One approach to building conversational (dialog) chatbots is to use an unsupervised sequence-to-sequence recurrent neural network (seq2seq RNN) deep learning framework. About a year ago, researchers (Vinyals-Le) at Google published an ICML paper "A Neural Conversational Model" that describes one such framework; a review can be found here. The Vinyals-Le paper (and associated framework) is instructive in understanding some of the parameters of such seq2seq chatbot models. We assume that Vinyals-Le used Tensorflow, though this is not explicitly stated in the paper. Note that seq2seq may not be the best way to build a truly conversational chatbot; the Vinyals-Le chatbot is more of a Q/A system that originated in machine translation.

Last week, we talked about some changes we're bringing to our blog. Our goal is to create a forum where Artificial Intelligence (AI) can be examined and explored fairly without being oversimplified or overhyped. With Natural Language Generation (NLG), one of the most common storylines we see discussed in the media is how writing jobs will be impacted. Some argue that AI software will replace creative writers and journalists. This could not be further from the truth.

A group of researchers from the University College London (UCL), University of Sheffield, and University of Pennsylvania, created an Artificial Intelligence system to judge 584 human rights cases and had released its findings recently. The cases analyzed by the AI method were previously heard at the European Court of Human Rights (ECHR) and were equally divided into violation and non-violation cases to prevent bias. European Court of Human Rights in Strasbourg, France (Image Credit: ECHR) So how did the AI judge perform? Basing its judgment on the case text, the AI judge managed to predict the decisions on the cases with 79% accuracy. That means, it concurred with the decisions of human judges 8 out of 10 times.

Every company is now a data company, capable of using machine learning in the cloud to deploy intelligent apps at scale, thanks to three machine learning trends: data flywheels, the algorithm economy, and cloud-hosted intelligence. That was the takeaway from the inaugural Machine Learning / Artificial Intelligence Summit, hosted by Madrona Venture Group* last month in Seattle, where more than 100 experts, researchers, and journalists converged to discuss the future of artificial intelligence, trends in machine learning, and how to build smarter applications. With hosted machine learning models, companies can now quickly analyze large, complex data, and deliver faster, more accurate insights without the high cost of deploying and maintaining machine learning systems. "Every successful new application built today will be an intelligent application," Soma Somasegar said, venture partner at Madrona Venture Group. "Intelligent building blocks and learning services will be the brains behind apps."

Google's neural network is learning to encrypt its own messages Higher education for the AI age: Let's think about it before the machines do it for us Karbonn's Fashion Eye uses artificial intelligence to boost e-commerce Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Higher education for the AI age: Let's think about it before the machines do it for us Karbonn's Fashion Eye uses artificial intelligence to boost e-commerce Sure, A.I. Is Powerful--But Can We Make It Accountable? I Just Had A Conversation With An AI Lawyer... Stay up-to-date on the topics you care about. We'll send you an email alert whenever a news article matches your alert term. It's free, and you can add new alerts at any time.

Artificial intelligence has become one of the hottest trends in Big Law, with a number of major U.S. and international law firms starting to use machine… YOUR COMPLIMENTARY 15-DAY LAW.COM TRIAL HAS ENDED. To continue reading, upgrade and become a Law.com Get 2 MONTHS FREE when you sign up for a 12 month subscription.

Scientists have found why amputees feel the sensation of phantom limb pain. It is due to this reorganization pain occurs in the amputated limbs of a vast majority of amputees. The researchers also found a proposed way of treating the affliction through the use of artificial intelligence techniques. The researchers used a brain-machine interface to come up with this conclusion. They trained a group of ten amputees so they could control a robotic arm from their brain. The research team found learning to control the prosthetic through the amputated arm resulted in pain.