Summary: A major problem with chatbots is that they can only provide information from what’s in their knowledge base. Here’s a new approach that makes your chatbot smarter with every question it can’t answer, making it a self-learning lifelong learner.
If you’ve been keeping up with the…Continue
Summary: This is the second in our “Off the Beaten Path” series looking at innovators in machine learning who have elected strategies and methods outside of the mainstream. In this article we look at Numenta’s unique approach to scalar prediction and anomaly detection based on their own brain research.
Added by William Vorhies on February 20, 2018 at 8:30am — No Comments
The world is rapidly changing thanks to digital technologies.
Business are transforming along wit it.
Join Ronald van Loon on his journey through the intelligent world, and have a deeper look into technological development that are shaping a world and transforming business.
Added by Ronald van Loon on February 6, 2018 at 9:30pm — No Comments
Summary: Advanced analytic platform developers, cloud providers, and the popular press are promoting the idea that everything we do in data science is AI. That may be good for messaging but it’s misleading to the folks who are asking us for AI solutions and makes our life all the more difficult.
Summary: Where do we look to see the most advanced chatbots and the most complete application of AI? Chatbots designed as ‘artificially intelligent psychological counseling chatbots’, ‘therapeutic assistants’ for short.
The role of Artificial Intelligence (AI) devices in augmenting humans and in achieving tasks that were previously considered unachievable is just amazing. With the world progressing towards an age of unlimited innovations and unhindered progress, we can expect that AI will have a greater role in actually serving us for the…Continue
Added by Ronald van Loon on December 31, 2017 at 10:30pm — No Comments
Summary: Here are our 6 predictions for data science, machine learning, and AI for 2018. Some are fast track and potentially disruptive, some take the hype off over blown claims and set realistic expectations for the coming year.
Natural language conversation is one of the most challenging artificial intelligence problems, which involves language understanding, reasoning, and the utilization of common sense knowledge. Previous works in this direction mainly focus on either rule-based or learning-based methods. These types of methods often rely on manual effort in designing rules or automatic training of model with a particular learning algorithm and a small amount of data, which…Continue
Added by Harpreet Sethi on December 1, 2017 at 8:00am — No Comments
Summary: There’s a three way technology race to bring faster, easier, cheaper, and smarter AI. High Performance Computing is available today but so are new commercial versions of actual Quantum computers and Neuromorphic Spiking Neural Nets. These two new entrants are going to revolutionize AI and deep learning starting now.Continue
The technology revolution promises to deliver a lot of rewards for organizations that take it by the horns and implement it. The spread of the Internet across every facet of society has meant that the traditional approach to watching videos has changed. Research shows that the average American is still fond of watching videos on the traditional television. The interest in watching TV results in around…Continue
Added by Ronald van Loon on October 17, 2017 at 5:30am — No Comments
Summary: With only slight tongue in cheek about the road ahead we report on the just passed House of Representative’s new “Federal Automated Vehicle Policy” as well as similar policy just emerging in Germany. As a model of regulation on emerging AI technology we think they got this just about right.
Added by William Vorhies on September 12, 2017 at 9:35am — No Comments
"Artificial intelligence has been brain-dead since the 1970s." This rather ostentatious remark made by Marvin Minsky co-founder of the world-famous MIT Artificial Intelligence Laboratory, was referring to the fact that researchers have been primarily concerned on small facets of machine intelligence as opposed to looking at the problem as a whole. This article examines the contemporary issues of artificial…Continue
Added by Venkatesan M on July 4, 2017 at 1:30am — No Comments
Summary: Quantum computing is already being used in deep learning and promises dramatic reductions in processing time and resource utilization to train even the most complex models. Here are a few things you need to know.
Added by William Vorhies on June 13, 2017 at 8:00am — No Comments
Summary: Just where are we in the Age of AI, where are we going, and what happens when we get there?
When things are changing fast, sometimes it’s necessary to take a step back and see where you are. It’s very easy to get caught up in the excitement over the details. The individual data science technologies that underlie AI are all moving forward on different paths at different speeds, but all of those speeds are fast. So before you change careers or…Continue
Summary: We are swept up by the rapid advances in AI and deep learning, and tend to laugh off AI’s failures as good fodder for YouTube videos. But those failures are starting to add up. It’s time to take a hard look at the weaknesses in AI and where that’s leading us.
Added by William Vorhies on April 18, 2017 at 8:04am — No Comments
Summary: The argument in the popular press about robots taking our jobs fails in the most fundamental way to differentiate between robots and AI. Here we try to identify how each contributes to job loss and what the future of AI Enhanced Robots means for employment.
There’s been a lot of contradictory opinion in the press…Continue
Summary: Whether you are a startup person or data science-minded executive in a larger organization what logic can you apply to spot the most compelling opportunities for AI in your organization.
Added by William Vorhies on March 12, 2017 at 9:00am — No Comments
Summary: For those of you traditional data scientist who are interested in AI but still haven’t given it a deep dive, here’s a high level overview of the data science technologies that combine into what the popular press calls artificial intelligence (AI).
Added by William Vorhies on February 7, 2017 at 7:02am — No Comments
Summary: What comes next after Deep Learning? How do we get to Artificial General Intelligence? Adversarial Machine Learning is an emerging space that points to that direction and shows that AGI is closer than we think.
Deep Learning, Convolutional Neural Nets (CNNs) have given us dramatic improvements in image, speech, and text recognition over the last two years. They suffer from the flaw however that…Continue
Summary: At the core of modern AI, particularly robotics, and sequential tasks is Reinforcement Learning. Although RL has been around for many years it has become the third leg of the Machine Learning stool and increasingly important for Data Scientist to know when and how to implement.
If you poled a group of data scientist just a few years back about how many machine learning problem types there are you would almost certainly have gotten a…Continue