Rob High: The future of AI-powered chatbots

 

Rob High IBM Watson CTO

Rob High, Chief Technology Officer at IBM Watson

Since their first appearance decades ago, chatbots have come a long way thanks to leaps in natural language processing and generation (NLP/NLG), the branches of artificial intelligence that enable us to interact with computers in a conversational manner. Today AI-powered chatbots have established a prominent role in various fields, including customer service, healthcare, banking and more.

Meanwhile, the technologies that power chatbot assistants are growing smarter and more efficient. I had a chance to talk with Rob High, Chief Technology Officer at IBM Watson, on the evolution of chatbots and where the trend is leading to. He shared some very interesting insights on the prospects and challenges that lie ahead. Continue reading

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Why is edge AI important?

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.

Imagine having to run to your local library and flip through the pages of an encyclopedia every time you saw a dog or cat in the street and wanted to know what its species is. That is pretty much how artificial applications function currently.

Artificial intelligence can predict stocks, diagnose patients, hire job applicants, play the games of chess and go, and do many more tasks on par or better than humans. Humans still have an advantage however: They have intelligence at the edge. Continue reading

What is the future of artificial intelligence?

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.

Where will humans fit in a world where robots outsmart them? This is the focus of a heated debate between thought leaders and tech billionaires.

Some believe we’re steadily meandering toward an AI apocalypse, where humans are either obliterated or enslaved by robots, and we must act quickly to prevent it. Others will tell you that artificial intelligence will always be the subservient best friend of mankind, even when it outwits its creators, and we should move ahead with developing AI at full speed. Continue reading

Do you want AI to solve a marketing, business or operational challenge?

By Matt Jones, Tessella

Most articles about artificial intelligence start with big claims. ‘AI will change the world’; ‘Here are some exciting examples of AI’.

These are all legitimate starting points, but fewer words are spent understanding what contemporary AI really is, and who can benefit from it. An uninformed observer could be forgiven for thinking AI is a new technology that you can buy as part of a platform and simply plug into your business and become the next digital company of the future.

Most technology is quite complicated. And AI is ‘quite complicated’ multiplied. If a business wants to really take advantage of AI, they need to stop worrying about what the latest, cool AI gadget or platform will be and start thinking about what an AI toolset can do for the specific problems facing their enterprise. Continue reading

How artificial intelligence will find its way into brick-and-mortar retail

It’s fair to say that artificial intelligence has helped online shopping take huge leaps and leave brick-and-mortar retail behind in terms of innovation and efficiency. There are no in-store equivalents for the personalized features that you find in e-commerce platforms.

The main hurdle to putting AI to use in retail is data, the new gold, and the reason companies such as Google and Facebook are offering you their services for free. Online shopping platforms provide a direct interface to the customer. This is useful to gather tons of information about every user, including the products they view, their search queries, items they add to or remove from their shopping carts, points where they abandon a purchase, and even the items they pause or hovered on. Continue reading

How the semantic web revolution is starting from a blog post

By Andrea Volpini, WordLift

Search engines are evolving. They went from simple keyword matching to natural language processing. Those search engines got better at interpreting long tail queries. Yet they are still error-prone. Let’s put this into context: Google itself claimed that it started to use machine learning to cope with the 15 percent of searches done by users, on a daily basis, that have never been seen before. These are roughly 500 million new searches every day where Google doesn’t have a clue.

Semantic web is making those computational search engines taking a giant leap forward in three ways. Continue reading

How Amazon’s acquisition of Whole Foods affects the data battleground

Why would Amazon, one of the biggest tech companies in the world, spend $13.4 billion to acquire Whole Foods, a grocery chain?

Some analysts believe this is Bezos’ response to Walmart’s inroads into online retail. But I think the bigger picture is about data, the new oil, the new gold, the subject of a not-so-secret battle between the leading tech companies (Apple, Google, Facebook, Microsoft and Amazon). Continue reading