Those who find Alexa's default voice too cold can have the digital assistant mimic celebs. Though, in the past, the only A-list impression the AI could do was everyone's fave badass Samuel L. Jackson. Turns out, people liked the idea of ordering a weather report from a superstar, because Amazon is adding two more famous voices to Alexa's toolkit. The new options include four-time NBA champ Shaquille O'Neal and Oscar-nominated actor Melissa McCarthy. Amazon says the SLJ skill, introduced for a limited price of $0.99, became one of its top-selling digital purchases upon launch.

First unveiled in 2018 at CES, LG is finally bringing its futuristic, rollable LG Signature OLED R 65-inch 4K TV to the US for the hefty sum of $100,000. According to LG's website, the television has an OLED screen, a Dolby Atmos and Sound Pro sound system and has both Google Assistant and Amazon's Alexa for built-in voice control. The 65-inch screen, which is described as a'revolutionary new experience,' gets tucked into aluminum housing unit when not in use, either for watching movies or playing video games. It has an OLED screen, a Dolby Atmos and Sound Pro sound system and both Google Assistant and Amazon's Alexa for built-in voice control The cabinet also has a Dolby Atmos sound system of its own. Manufactured in LG's Gumi facility, each TV is painstakingly assembled'with craftsman-like skill with attention to every detail', LG said last year.

It has been over a year since international travel as we knew it ground to a halt. When the COVID-19 pandemic hit, air travel in the US dropped by 95% – from around two million travellers per day to fewer than 100,000. Until recently, flights in and out of Australia have been limited to those trying to get home, reuniting with their loved ones, or fleeing places that were no longer safe. Slowly, vaccination is making the possibility of taking to the skies again seem within reach. But what might have changed?

Microsoft is planning to bring Clippy, its Office 97 assistant that looks like a paperclip, back to Windows. The software giant tweeted a photo of Clippy saying that, if the post received 20,000 likes, it would replace the paperclip emoji in Microsoft Office with Clippy. At time of writing, the tweet has nearly 134,000 likes. Clippy infamously offered support in Microsoft Word and other programs, such as Microsoft Publisher, but by 2008 the assistant was killed. Windows 10, Microsoft's current operating system, uses Cortana as its virtual assistant – a name taken from the Halo game franchise.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A woman was allegedly held captive in a California home for three days by a man she met on Tinder. "On July 12th, 2021 at approximately 16:59, Oakland Police Officers were dispatched to the 5400 Block of Fleming Avenue to investigate a report of a kidnapping," the Oakland Police Department said in a statement of the incident. "A preliminary investigation revealed that an adult female (Non-Oakland resident) was falsely imprisoned and sexually assaulted by her male partner."

Sony's latest top-of-the-range noise-cancelling earbuds are a cut above the previous generation and the competition. They are the successors to the WF-1000XM3, which were great but huge. Sony has significantly shrunk the case and earbuds for the mark four model without sacrificing performance. The earbuds are fairly heavy, weighing 7.3g each, compared with the 5.4g AirPods Pro, but they don't feel so in the ear, and they are comfortable for hours of listening without a break. They don't have stalks but protrude further than some slimmer rivals.

Sequential recommender systems (SRS) have become a research hotspot due to its power in modeling user dynamic interests and sequential behavioral patterns. To maximize model expressive ability, a default choice is to apply a larger and deeper network architecture, which, however, often brings high network latency when generating online recommendations. Naturally, we argue that compressing the heavy recommendation models into middle- or light- weight neural networks is of great importance for practical production systems. To realize such a goal, we propose AdaRec, a knowledge distillation (KD) framework which compresses knowledge of a teacher model into a student model adaptively according to its recommendation scene by using differentiable Neural Architecture Search (NAS). Specifically, we introduce a target-oriented distillation loss to guide the structure search process for finding the student network architecture, and a cost-sensitive loss as constraints for model size, which achieves a superior trade-off between recommendation effectiveness and efficiency. In addition, we leverage Earth Mover's Distance (EMD) to realize many-to-many layer mapping during knowledge distillation, which enables each intermediate student layer to learn from other intermediate teacher layers adaptively. Extensive experiments on real-world recommendation datasets demonstrate that our model achieves competitive or better accuracy with notable inference speedup comparing to strong counterparts, while discovering diverse neural architectures for sequential recommender models under different recommendation scenes.

In this paper, we propose a simple yet effective solution to build practical teacher recommender systems for online one-on-one classes. Our system consists of (1) a pseudo matching score module that provides reliable training labels; (2) a ranking model that scores every candidate teacher; (3) a novelty boosting module that gives additional opportunities to new teachers; and (4) a diversity metric that guardrails the recommended results to reduce the chance of collision. Offline experimental results show that our approach outperforms a wide range of baselines. Furthermore, we show that our approach is able to reduce the number of student-teacher matching attempts from 7.22 to 3.09 in a five-month observation on a third-party online education platform.

We propose a method to easily modify existing offline Recommender Systems to run online using Transfer Learning. Online Learning for Recommender Systems has two main advantages: quality and scale. Like many Machine Learning algorithms in production if not regularly retrained will suffer from Concept Drift. A policy that is updated frequently online can adapt to drift faster than a batch system. This is especially true for user-interaction systems like recommenders where the underlying distribution can shift drastically to follow user behaviour. As a platform grows rapidly like Grubhub, the cost of running batch training jobs becomes material. A shift from stateless batch learning offline to stateful incremental learning online can recover, for example, at Grubhub, up to a 45x cost savings and a +20% metrics increase. There are a few challenges to overcome with the transition to online stateful learning, namely convergence, non-stationary embeddings and off-policy evaluation, which we explore from our experiences running this system in production.

Join executive leaders at the Conversational AI & Intelligent AI Assistants Summit, presented by Five9. During the pandemic, enterprises turned to automation to scale up their operations while freeing customer service reps to handle increasingly challenging workloads. According to Canam Research, 78% of contact centers in the U.S. now intend to deploy AI in the next 3 years. And research from The Harris Poll indicates that 46% of customer interactions are already automated, with the number expected to reach 59% by 2023. The panel touched on how AI assistants can coexist with humans and help them to perform their jobs, while at the same time respecting existing customer service guardrails. "We're talking about a spectrum of technologies," Schebella said of automation broadly.