Chatbots Are Getting Smarter – The New York Times


To meet this challenge, mutually named AI Big Tech companies such as Microsoft, Amazon, Google and Oracle, and Kore.ai, Omilia, Rasa, Senseforth.ai, Verint and Yellow.ai.

Suppliers provide software tools that companies then customize and train on their own data.

According to a Gartner forecast, this year the job market for virtual assistants – aka chatbots – will grow 15 percent to exceed $7 billion. Some of these bots are designed to assist employees, but most are for customer service.

No company has taken a more humble and instructive journey into chatbot technology than IBM. After the Watson supercomputer triumphed over human champions On the TV game show “Jeopardy!” About a decade ago, IBM applied Watson’s natural language processing to other areas. An early focus was on the diagnosis and treatment of cancer, and IBM called healthcare the “beat of the month.”

In January, after years of struggling, IBM to sell Watson Health is transferring its business to a private equity firm. A few days later, Gartner rated IBM’s Watson Assistant as a “leader” in speech-based AI for business. Watson has moved from cancer satellites to customer service chatbots.

Today Watson Assistant is a success story for IBM among its remaining AI products, which includes software to explore data and automate business tasks. Watson Assistant has evolved over the years, constantly improved and improved. IBM learned quite quickly that a strict question-and-answer approach, while ideal for a game show, was very limited and inflexible in customer service settings.

“The real world has opened our eyes,” said Aya Soffer, vice president of artificial intelligence technologies at IBM Research.

Dr. Soffer said the starting point for improvement is to work with other companies to better understand what’s going on in their call centers, researching and analyzing the thousands of calls between customers and human representatives. In dialogues, for example, he said which questions and which follow-ups led to solving a client’s problem and what were the revealing signals of “bad conversations”.



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