Amazon’s Echo has made tangible the promise of an artificially intelligent personal virtual assistant in every home.
“And he had power to give life unto the image of the beast, that the image of the beast should both speak, and cause that as many as would not worship the image of the beast should be killed.” Revelation 13:15 (KJV)
“But thou, O Daniel, shut up the words, and seal the book, even to the time of the end: many shall run to and fro, and knowledge shall be increased.” Daniel 12:4 (KJV)
EDITOR’S NOTE: It is amazing to me that, right here and now, we are living during the time of the greatest explosion of knowledge and technological advancement in human history. Revelation tells us that, in the time of Jacob’s trouble, the False Prophet makes an image of the Beast and it comes alive. So right now what we are seeing is the entire civilized world being groomed to talk with ‘virtual assistants’ like Alexa from Amazon, Cortana from Microsoft, Siri from Apple, and the list goes on and on. The future is happening now, exactly like King James Bible said it would be.
Those who own the voice-activated gadget, known colloquially as Alexa, after its female interlocutor, are prone to proselytizing “her” charms, applauding Alexa’s ability to call an Uber, order pizza or check a 10th-grader’s math homework. The company says more than 5,000 people a day profess their love for Alexa.
On the other hand, Alexa devotees also know that unless you speak to her very clearly . . . and . . . slowly, she’s likely to say: Sorry, I don’t have the answer to that question. “I love her. I hate her, I love her,” one customer wrote on Amazon’s website, while still awarding Alexa five stars. “You will very quickly learn how to talk to her in a way that she will understand and it’s not unlike speaking to a small frustrating toddler.”
Voice recognition has come a long way in the past few years. But it’s still not good enough to popularize the technology for everyday use and usher in a new era of human-machine interaction, allowing us to talk with all our gadgets—cars, washing machines, televisions. Despite advances in speech recognition, most people continue to swipe, tap and click. And probably will for the foreseeable future.
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What’s holding back progress? Partly the artificial intelligence that powers the technology has room to improve. There’s also a serious deficit of data—specifically audio of human voices, speaking in multiple languages, accents and dialects in often noisy circumstances that can defeat the code.
So Amazon, Apple, Microsoft and China’s Baidu have embarked on a world-wide hunt for terabytes of human speech. Microsoft has set up mock apartments in cities around the globe to record volunteers speaking in a home setting. Every hour, Amazon uploads Alexa queries to a vast digital warehouse. Baidu is busily collecting every dialect in China. Then they take all that data and use it to teach their computers how to parse, understand and respond to commands and queries.
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The challenge is finding a way to capture natural, real-world conversations. Even 95 percent accuracy isn’t enough, says Adam Coates, who runs Baidu’s artificial intelligence lab in Sunnyvale, California. “Our goal is to push the error rate down to 1 percent,” he says. “That’s where you can really trust the device to understand what you’re saying, and that will be transformative.”
Not so long ago, voice recognition was comically rudimentary. An early version of Microsoft’s technology running in Windows transcribed “mom” as “aunt” during a 2006 demo before an auditorium of analysts and investors. When Apple debuted Siri five years back, the personal assistant’s gaffes were widely mocked because it, too, routinely spat out incorrect results or didn’t hear the question correctly. When asked if Gillian Anderson is British, Siri provided a list of English restaurants. Now Microsoft says its speech engine makes the same number or fewer errors than professional transcribers, Siri is winning grudging respect, and Alexa has given us a tantalizing glimpse of the future.
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Much of that progress owes a debt to the magic of neural networks, a form of artificial intelligence based loosely on the architecture of the human brain. Neural networks learn without being explicitly programmed but generally require an enormous breadth and diversity of data. The more a speech recognition engine consumes, the better it gets at understanding different voices and the closer it gets to the eventual goal of having a natural conversation in many languages and situations.
Hence the global scramble to capture a multitude of voices. “The more data we shove in our systems the better it performs,” says Andrew Ng, Baidu’s chief scientist. “This is why speech is such a capital-intensive exercise; not a lot of organizations have this much data.”
When the industry began working seriously on voice recognition in the 1990s, companies like Microsoft relied on publicly available data from research institutes such as the Linguistics Data Consortium, a storehouse of voice and text data founded in 1992 with backing from the U.S. government and located at the University of Pennsylvania. Then tech companies started collecting their own voice data, some of it garnered from volunteers who came in to read and be recorded. Now, with the popularity of speech-controlled software gaining ground, they harvest much of the data from their own products and services.
When you tell your phone to search for something, play a song or guide you to a destination, chances are a company is recording it. (Apple, Google, Microsoft and Amazon emphasize that they anonymize user data to protect customer privacy.) When you ask Alexa what the weather is or the latest football score, the gadget uses the queries to improve its understanding of natural language (although “she” isn’t listening to your conversations unless you say her name). “By design, Alexa gets smarter as you use her,” says Nikko Strom, senior principal scientist for the program. source