Linked media – Linked media
An older voice assistant like Siri, which reacts to a database of commands and questions that it was programmed to understand, would fail unless you used specific words, including “What’s the weather in New York?” and “What should I pack for a trip to New York?”
The former conversation sounds more fluid, like the way people talk to each other.
A major reason people gave up on voice assistants like Siri and Alexa was that the computers couldn’t understand so much of what they were asked — and it was difficult to learn what questions worked.
Dimitra Vergyri, the director of speech technology at SRI, the research lab behind the initial version of Siri before it was acquired by Apple, said generative A.I. addressed many of the problems that researchers had struggled with for years. The technology makes voice assistants capable of understanding spontaneous speech and responding with helpful answers, she said.
John Burkey, a former Apple engineer who worked on Siri in 2014 and has been an outspoken critic of the assistant, said he believed that because generative A.I. made it easier for people to get help from computers, more of us were likely to be talking to assistants soon — and that when enough of us started doing it, that could become the norm.
“Siri was limited in size — it knew only so many words,” he said. “You’ve got better tools now.”
But it could be years before the new wave of A.I. assistants become widely adopted because they introduce new problems. Chatbots including ChatGPT, Google’s Gemini and Meta AI are prone to “hallucinations,” which is when they make things up because they can’t figure out the correct answers. They have goofed up at basic tasks like counting and summarizing information from the web.
Linked media – Associated media
