Oracle Magazine, Jan/Feb 2018
The increase in access to data over the last decade means that machine learning has more to learn from so it can be more accurate and more deterministic Suhas Uliyar Vice President of Mobile Bot and AI Strategy and Product Management Oracle ORACLE MAGAZINE JANUARY FEBRUARY 2018 39 strategy and product management at Oracle He explains that there are three trends toward message based conversation First messaging channels such as Facebook Messenger and WhatsApp are familiar to users so users dont need to download and learn new apps Next users can engage using the language of their choice And finally a well programmed chatbot can respond instantly For enterprises to scale with the volume of interactions that comes with such messaging channels AI is critical for processing these natural language conversations and returning the appropriate response This doesnt mean that the technology is simple says Uliyar It takes a lot of processing power as well as a lot of data to compute the sophisticated AI algorithms behind text recognition including determining context retrieving information and of course formulating the best reply all in a fraction of a second The challenge is compounded when a user sends the chatbot informal language slang tones emotions or misspellings Still the development of powerful cloud services with impressive computational ability as well as huge quantities of and improvements in text algorithms has brought the industry to the tipping point of making chatbots ready for pervasive deployment says Uliyar The compute power has increased enough to handle the sophistication of the machine learning algorithms behind AI technologies he says and the increase in access to data over the last decade means that machine learning has more to learn from so it can be more accurate and more deterministic Thats why responsive chatbots are ready for prime time With a chatbot you can apply things like your customer service use cases to it
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