The original Chromecast that debuted in 2013 was a simple $35 dongle. But it was still notable, providing a cheap way to make any TV "smart." Things have changed a lot since then, however. Not only do a lot of TVs now come with built-in apps, Roku and Amazon developed their own streaming sticks over the years -- both of which have remote controls and visual menus for easy navigation. Google's Chromecast soon seemed outdated by comparison.

Amazon is gearing up for its latest hardware event where it's expected to announce its latest smart home gear. Based on prior years, we could see new Echo speakers, Alexa updates, Eero routers, Ring cameras, and more. But looking at Amazon's smart home lineup right now, the question isn't whether Amazon will have new hardware to show off. It's whether Amazon can convince its current customers to buy them. Look at the current slate of Echos or Eeros, for example.

It's been ten years since Nest first launched its first smart thermostat, and it's become the most popular brand in the connected home temperature control space. If you've seen one of its products, you'll recognize the distinctive puck-like shape and rotating edge controls. Now that it's ten years old, though, it's time for the thermostat to get a glow up. Google is launching the new Nest Thermostat today for $130, and it features an impressively sleek, attractive makeover that'll make the device look less like a bump on your wall and more like an elegant ornament. It's available in four colors --snow, sand, charcoal, and fog and looks significantly smaller than before.

Financial institutions such as banks are at the forefront of technological innovations, looking for ways to execute faster and serve their customers better. It may be tempting to embrace whatever technology comes on the way in striving for the latest and greatest solutions. It has led to the proliferation of chatbots that claim to reinforce call centres with automation. In reality, these bots behave like dated robots and are stubborn in how they communicate with customers, building an IVR 2.0 format that frustrates callers and does not allow banks from serving customers. Due to the pandemic and the possibility of subsequent lockdowns, this seems challenging.

If you're waiting for Amazon Prime Day to kick off tomorrow, you may want to take advantage of the deals that other retailers already have going on. Walmart has already kicked off its own "anti-Prime Day" savings event and with it comes the best price we've seen on the Lenovo Smart Clock. Right now, Walmart has the smart alarm clock for $39, which is $1 cheaper than its previous low and 50 percent off its normal price. This little gadget has gotten quite popular since its release last year. We gave it a score of 87 for its charming design, ambient light sensor, sunrise alarm feature and lack of camera.

We're in 2020 and long past the days back when we used to stand outside the school library to get the opportunity to copy two or three Encyclopedia pages, to use as a kind of reference for our school projects. With this age having grown up with the benefit of access to technology at their fingertips, the field of education has hugely changed and overturned in this digitally driven world. Artificial Intelligence in the education market was worth US$2.022 billion for the year 2019. The worldwide AI in the education market is anticipated to be valued at USD 3.68 billion by 2023, at a CAGR of 47% during the forecast period of 2018 till 2023. Artificial intelligence has already infiltrated our lives on an individual level.

Google's first smart speaker has finally got a much-needed upgrade in sound with the new Nest Audio. The speaker replaces the Google Home and costs £89.99, fitting in between the £49 Nest Mini and £299 Google Home Max. The design is completely different from the original Google Home. The outside of the Nest Audio is covered in a recycled plastic fabric – the same used on the recent Nest Mini. There is a mute switch for the microphones on the back and a port for the power plug but those are the only visible features.

In this article, Alibaba technical expert Aohai introduces the online service orchestration and architecture for a recommender system.Continue reading on Medium » Source

A new website has launched which uses algorithms to judge your face. It uses similar software to that used by major companies not only for advertising, but for collecting your data in ways you had no idea about for all sorts of uses. And, as the website says – unlike cookies, you can't delete your face. The first trait the algorithm judges is your attractiveness. The website claims that apps like Tinder use similar software to show potential matches of equal attractiveness to each other, and that companies like TicToc are known to weight promoting content in favour of attractive people.

Deep neural networks are widely used in personalized recommendation systems. Unlike regular DNN inference workloads, recommendation inference is memory-bound due to the many random memory accesses needed to lookup the embedding tables. The inference is also heavily constrained in terms of latency because producing a recommendation for a user must be done in about tens of milliseconds. In this paper, we propose MicroRec, a high-performance inference engine for recommendation systems. MicroRec accelerates recommendation inference by (1) redesigning the data structures involved in the embeddings to reduce the number of lookups needed and (2) taking advantage of the availability of High-Bandwidth Memory (HBM) in FPGA accelerators to tackle the latency by enabling parallel lookups. We have implemented the resulting design on an FPGA board including the embedding lookup step as well as the complete inference process. Compared to the optimized CPU baseline (16 vCPU, AVX2-enabled), MicroRec achieves 13.8~14.7x speedup on embedding lookup alone and 2.5$~5.4x speedup for the entire recommendation inference in terms of throughput. As for latency, CPU-based engines needs milliseconds for inferring a recommendation while MicroRec only takes microseconds, a significant advantage in real-time recommendation systems.