On August 28, China's Ministry of Commerce and Ministry of Science and Technology released the new updated version of the Catalogue of Technologies Prohibited and Restricted from Export, which imposed restrictions on the trading of sensitive technologies such as AI. The new document is released near the closing date of the ByteDance's TikTok acquisition by a US company. The updated catalogue divides technology export into three categories: "open", "restricted" and "prohibited". The restricted section now includes the computer service industry spearheaded by the emerging AI technologies, such as AI speech synthesis, AI-backed interactive interface, personalized recommendation system powered on data analysis, and more. The most valuable asset of TikTok, the internationally popular short video app, is the FYP (for you page) algorithm that recommends videos based on user interests, which suits the above definition of "personalized recommendation powered on data analysis". Its owner company ByteDance also holds a number of cutting-edge technologies in AI and other fields, including "AI-backed interactive interface".

The next time you need to fill up your car, you might pay for your gas using your voice. Amazon, ExxonMobil and payment provider Fiserv have announced that you can pay with Alexa at some pumps. The Alexa skill was announced at CES in January, and it's now available at more than 11,500 Exxon and Mobil stations across the US. When you pull up to a pump, you can simply ask the voice assistant to "pay for gas" using your phone or through your car itself if you have an Alexa-enabled vehicle or Echo Auto. Alexa will confirm the station and pump number with you, then it'll activate the pump.

The expression, "Marketers are data rich and insight poor" is more true today than ever. Marketers all over the world are working to optimize marketing operations and effectiveness using their abundance of data. Many are turning to tools and platforms powered by artificial intelligence and machine learning. AI promises to make sense of all the dark data companies are sitting on as well as structured and unstructured data online to surface insights about customer behaviors, opportunistic content and emotional triggers to inspire conversions. In an age of too many choices, increased competition for customer attention requires every advantage to optimize for reach, engagement and conversion.

Amazon's Echo Buds arrived this time last year, and we've only seen the wireless earbuds go on sale once since then. Today, in another rare sale, the price dropped to $90. That's the lowest the Echo Buds have ever been listed for, and it's a $40 savings off their regular list price of $130. Buy Amazon's Echo Buds at Amazon - $90 The Echo Buds were priced and positioned to take on Apple's AirPods and Google tech. They do offer hands-free, always-on Alexa, Bose's active noise reduction and a good deal of customization for an affordable price.

Artificial intelligence is about to trigger explosive changes in our lives, work, and leisure, but few understand what the technology can do beyond Amazon AMZN 2%'s Alexa or Apple AAPL 3.4%'s Siri. These are examples of virtual assistant or'weak AI' technology -- the most common example of AI application. But in the data-driven energy sector, sophisticated machine learning is paving the way for'strong AI' to improve efficiency, forecasting, trading, and user accessibility. Electricity is a commodity that can be bought, sold, and traded in open markets. For these markets to function efficiently, massive amounts of data -- from weather forecasting to grid demand/supply balance -- must be constantly analyzed by power sellers, buyers, and brokers.

What do you really need from an alarm clock? Smart displays can be a little extreme to sit by your bedside, but having something that syncs nicely with your phone doesn't hurt. Now Lenovo has followed last year's Google Assistant-connected Smart Clock with this few-frills Smart Clock Essential. As Cherlynn Low points out, its four-inch display doesn't just tell the time, it also shows the current weather and temperature, along with your alarms and other status indicators. Of course, it has microphones for "OK, Google" voice commands, and a three-watt speaker to make sure Mat's voice comes through clearly every morning.

Amazon released the first Echo Plus smart speaker/smart-home hub in 2017, and this second generation arrived a year later. What makes it "Plus" is simple: A built-in Zigbee radio. That eliminates the need to also have something like a Samsung SmartThings or a Hubitat Elevation on your network--at least to control other smart home devices that use Zigbee. We'll get deeper into that in a bit. The second-generation Echo Plus has one other minor new addition: An ambient temperature sensor, so you can ask Alexa what the temperature in the room is, in addition to getting a weather report that includes the current temperature outside.

The robot possesses an infrared thermal imager and a visual light camera, thereby giving them the ability to replace 24-hour manual inspection. Artificial intelligence is about to trigger explosive changes in our lives, work, and leisure, but few understand what the technology can do beyond Amazon AMZN's Alexa or Apple AAPL's Siri. These are examples of virtual assistant or'weak AI' technology -- the most common example of AI application. But in the data-driven energy sector, sophisticated machine learning is paving the way for'strong AI' to improve efficiency, forecasting, trading, and user accessibility. Electricity is a commodity that can be bought, sold, and traded in open markets.

Developments in AI are advancing at a rampant pace, with innovations improving the quality of life in different ways across disciplines. For instance, Forbes estimates that 10 million self-driving cars will hit the road in 2020, and another study reported by Business Wire projects that automotive artificial intelligence will bring in revenues of over $14 billion by 2025. Another example is Google's Deep Learning program helping pathologists detect cancer with higher accuracy. Another article from Forbes asserts how the use of big data can help prevent a heart attack every 40 seconds. Although many organizations across fields still lack the foundational practices needed to create value from AI at scale, AI is being adopted at a rapid rate by digital marketers across niches. As reported by Statista, artificial intelligence and machine learning are among the most effective digital marketing techniques used by marketers today.

Two-stage recommender systems are widely adopted in industry due to their scalability and maintainability. These systems produce recommendations in two steps: (i) multiple nominators preselect a small number of items from a large pool using cheap-to-compute item embeddings; (ii) with a richer set of features, a ranker rearranges the nominated items and serves them to the user. A key challenge of this setup is that optimal performance of each stage in isolation does not imply optimal global performance. In response to this issue, Ma et al. (2020) proposed a nominator training objective importance weighted by the ranker's probability of recommending each item. In this work, we focus on the complementary issue of exploration. Modeled as a contextual bandit problem, we find LinUCB (a near optimal exploration strategy for single-stage systems) may lead to linear regret when deployed in two-stage recommenders. We therefore propose a method of synchronising the exploration strategies between the ranker and the nominators. Our algorithm only relies on quantities already computed by standard LinUCB at each stage and can be implemented in three lines of additional code. We end by demonstrating the effectiveness of our algorithm experimentally.