If online dating has gotten stale, here's an app that may change that with this one element.

Businesses and consumers are experiencing a gap in perception when it comes to the use of AI. While almost two-thirds (63%) of businesses believe that chatbots and virtual assistants make it easier for customers to get their issues resolved, only one-third (33%) of consumers agree, according to a customer experience benchmark report from NICE inContact. There is an even bigger gap when it comes to businesses believing that customers would like to use their virtual assistants (such as Amazon Alexa/ECHO or Google Home) to interact with them. While 68% of businesses carry this perception – and despite ownership of such devices continuing to increase in the US – only 30% of customers actually want to interact with businesses using them. Even so, businesses are continuing to look to the future when it comes to voice ordering.

We describe a method for selecting relevant new training data for the LSTM-based domain selection component of our personal assistant system. Adding more annotated training data for any ML system typically improves accuracy, but only if it provides examples not already adequately covered in the existing data. However, obtaining, selecting, and labeling relevant data is expensive. This work presents a simple technique that automatically identifies new helpful examples suitable for human annotation. Our experimental results show that the proposed method, compared with random-selection and entropy-based methods, leads to higher accuracy improvements given a fixed annotation budget. Although developed and tested in the setting of a commercial intelligent assistant, the technique is of wider applicability.

Apple said it is now, by default, opting customers out of a program that listens to audio snippets scraped up by its voice-assistant, Siri. The company announced the decision in a blog post this week and marks the most significant step since it decided to suspend the program earlier this summer. Apple has been identified as one of many companies that was harvesting audio snippets from users in an effort to improve the accuracy of its voice-assistant. Unbeknownst to most, those snippets were then reviewed by human contractors. 'As a result of our review, we realize we haven't been fully living up to our high ideals, and for that we apologize,' wrote Apple. According to the company, it will will resume its program later this fall with several major changes.

SAN FRANCISCO – Apple is apologizing for allowing outsiders to listen to snippets of people's recorded conversations with its digital assistant Siri, a practice that undermined its attempts to position itself as a trusted steward of privacy. As part of the apology posted Wednesday, Apple reiterated an earlier pledge to stop keeping audio recorded through Siri unless consumers give their permission. When permission is granted, Apple said only its own employees will be allowed to review audio to help improve the service. Previously, the company hired contractors to listen to some recordings. "We realize haven't been fully living up to our high ideals, and for that we apologize," Apple conceded. It's not yet clear how Apple will seek permission, though in the past, Apple has typically requested permissions through prompts during software update installations.

Apple says it will no longer retain audio recordings of your interactions with Siri by default and has issued an apology for having done so previously. "We realize we haven't been fully living up to our high ideals, and for that we apologize," Apple stated on its website. Apple had taken a lot of heat for the practice recently following a report by the Guardian that contractors "regularly hear confidential medical information, drug deals, and recordings of couples having sex, as part of their job providing quality control, or grading'" Siri. "We know customers have been concerned … We heard their concerns," the company wrote. Apple had previously announced that it halted the grading practice, which, following software updates and other changes, will resume in the fall.

Be honest – how many times have you used the'Recommended for you' section on Amazon? Ever since I found out a few years back that machine learning powers this section – I have been hooked. I keep an eye on that section each time I log into Amazon. There's a reason companies like Netflix, Google, Amazon, Flipkart, etc. spend millions perfecting their recommendation engine. It is a powerful acquisition channel and enhances the customer's experience. Let me use a recent example to showcase their power.

The BBC is launching its own voice assistant, appropriately called'Beeb' (though the efficacy of that wake word is completely suspect in a world where people might talk about Justin Bieber, just saying). Upon hearing this news, you might be tempted to think, "Ugh, why? The Beeb assistant might be a boondoggle, a waste of British taxpayer money, and a classic example of the BBC making a tech thing without a super clear reason or need just because it can. In fact, I would put even money on it being all three of those things, but I'm still rooting for it anyway. Command Line is our daily newsletter about personal tech.

Quite unlike what you may be inclined to believe, artificial intelligence has been around for quite a while. It's just that it is only over the past few years that the world has found d increasingly mainstream applications for it. Its adoption has multiplied in the recent past that you'd be hard-pressed to think of things where either artificial intelligence is not already being used or where its integration isn't being considered or worked upon. Think about it -- what do you think drives virtual assistants like Alexa, Google Now, Siri, and more? The point is that it isn't surprising to see that artificial intelligence also makes its way into e-commerce, which has firmly established itself as a leading way to shop today.

"Today, people are frustrated when a digital assistant says, 'Sorry, I couldn't understand that,'" said Mr. Chapman, who was named CEO of the venture-capital-backed startup this week after about five years as director of engineering for Amazon.com Quantum computers "could alleviate those problems," he said. That's because quantum computers have the potential to sort through a vast number of possibilities within a fraction of a second to come up with a probable solution. A Rubik's Cube, in an analogy to illustrate the power of quantum computers, could be solved instantaneously because the technology can process different combinations at once. A classical computer, by contrast, would need to search through the possibilities sequentially, which could take days, months or even longer, IonQ executives said.