Ray Kurzweil’s Ambition and Musings on The Future of Virtual Agent Technology

Digital BrainSingularity Hub did an interview with Ray Kurzweil back in January, during which Kurzweil talked about his vision for an artificial intelligence that will act as a trusted personal assistant to humans. Kurzweil had only just started his stint at Google when the interview took place. He briefly shared his vision of constructing an artificially intelligent software system that mimics the hierarchical architecture of the human brain. It remains to be seen how successful Kurzweil and the team at Google will be in their endeavor. Whatever the outcome, the race to produce smarter and smarter digital entities is definitely underway. As Gary Marcus points out in his review of Kurzweil’s book on building a brain, there are many different machine learning techniques and cognitive systems that are being researched today in the public and private sector. Whether Kurzweil’s hierarchical approach pans out or not is really irrelevant. Advanced AI that can understand human intent and provide answers to human questions will happen. The progress made in this field is bound to influence commercially available virtual agent technologies, both in the mobile personal assistant and in the enterprise and customer support virtual agent domains.

Older conversational agent technologies will most likely be superseded by new ones. The work that Ray Kurzweil, the DeepQA team, and many other artificial intelligence researchers are engaged in today is producing techniques that far outpace the rudimentary pattern matching technology deployed in most simple chatbots. In the hands of dedicated and savvy bot masters, chatbot scripting languages such as AIML can be used to create impressive question answering agents. But unless it is combined with natural language processing, search, and machine learning algorithms, AIML by itself can’t produce a truly effective virtual agent.  It’s sporty to make any predictions when it comes to the future of artificial intelligence, but one pretty safe prediction would seem to be this: the intelligent virtual agent that one day passes the Turing Test won’t have been created using basic AIML pattern matching technology.

For commercially viable virtual agents in the field of customer support, incorporating strong search capabilities would seem to be a must. Search can be combined with pattern matching against a broad database of known frequently asked questions to provide web or mobile users with basic self serve information. Text and/or speech recognition and natural language processing would also seem to be non-negotiable skills for a virtual customer service agent. User profiling and targeted recommendations are capabilities that advanced virtual agents should also have in their toolkit. We could go even farther and list attributes such as a sense of humor, the ability to detect human emotion, and empathy. All of these would be desirable qualities in a customer-facing virtual agent.

Perhaps as Kurzweil / Google and others work towards recreating the human brain in digital form, advancements in cognitive computing, speech recognition, natural language processing, and other interrelated fields will be the outcome. It will be hugely interesting to see how software vendors in the virtual agent and personal digital assistant space capitalize on these breakthroughs to improve and reshape their commercial offerings.

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