Interracial emojis have been approved by Unicode in response to a Tinder petition. Emojis are getting more inclusive. In response to the more than 52,000 people who signed an online petition posted by the Tinder dating app last year, Unicode, the global organization responsible for emoji standards, released the artwork for emoji that represent interracial couples. Tinder wrote that, "While emojis for people of color and emojis for same-sex couples both became a reality in 2015, one group of people is still excluded from emoji representation: interracial couples. Isn't it time all love was represented?"

TechRepublic's James Sanders spoke with Oblong Industries John Underkoffler about how smart assistant technologies from data-driven companies like Google and Amazon are leading the market, while Siri and Cortana are falling behind. The following is an edited transcript of the interview. James Sanders: Apple's Siri and Microsoft's Cortana are really closer to the back of the pack for smart voice assistants, while data driven companies like Google and Amazon are leading the race. What does the future hold for smart assistants and how they integrate into people's lives? John Underkoffler: I think we're at a pivotal moment for the larger field let's say, that smart assistants might be one example of, and then a set of enabling technologies like machine learning, I refuse to say AI, that tend to power them.

According to a Forbes Survey from last year, 70 percent of buying decisions are influenced by how clients feel they are being treated; therefore, a superior personalized customer experience can go a long way towards increasing sales. Personalization requires the right product or service to be offered to the customer at the right moment and at the right price. With a plethora of product and service suites available, customers often defer to the expertise of the business to recommend the right solution for them. Businesses that can predict customer needs and supply effective solutions can ensure that their client base is always satisfied. The adage "the early bird gets the worm" has never been so true.

"Alexa, what to watch on Roku?" Streaming device Roku now has three ways to use voice control to get programming, the Google Assistant, Roku's own voice search and now Amazon Alexa. Roku makes the most popular brand of low-price streaming players to connect to TVs and bring in internet channels, and it also has a low-priced branded Roku TV from TCL that's among Amazon's best sellers in the category. Roku's chief rival is Amazon, which counts the Fire TV Stick streaming player is in its top best sellers category. The Fire TV Stick uses voice search from Alexa. More: What exactly is a'smart' device anyway?

Roku's devices aren't exactly suffering from lack of hands-free control: they already support Google Assistant and their built-in OS has its own voice AI. That list could still feel incomplete if Alexa is your virtual assistant of choice, though, which is why the company's latest update is a welcome one. The company's streaming devices and TVs are now finally compatible with Amazon's voice AI, thanks to the new Roku skill for Alexa. You can issue commands through an Alexa-powered device, such as Amazon's Echo speakers, and by adding "on Roku" as a suffix. The new feature can switch Roku TVs on or off and change channels with spoken commands.

Artificial Intelligence (AI) has witnessed an exponential rise in the adoption by various sectors. The technology has unknowingly become a part of our day to day life. From Google search results to Amazon's products recommendations and Netflix's film suggestions to bank's VRU system, there are several AI-powered tools that even non-tech-savvy individuals' use. Due to the technology's ability and efficiency to offer a personalized experience, its use is set to grow immensely during the next two years. Research firm Gartner recently released results for their study about the influence of Artificial Intelligence on businesses.

Saying thank you to Google home. LINK Talk with Marcus Nyman, Sales Director Oracle, explaining us how they went from on-premise software to a SaaS player and how AI and blockchain are helping Marketing Depts. to improve in performance #MWC19 #Oracle #futureofcommunications

This is what Latent semantic analysis (LSA) does. It is based on how frequently you see the word on the exact topic. Like, there are more tech terms in tech articles, for sure. The names of politicians are mostly found in political news, etc. Yes, we can just make clusters from all the words at the articles, but we will lose all the important connections (for example the same meaning of battery and accumulator in different documents). LSA will handle it properly, that's why its called "latent semantic".

On a good day, Android TV, Google's Android OS for TVs, allows users to display photos from their Google Photos albums as screensavers. Over the weekend, a disturbed Android TV owner took to Twitter when he realized, through the Google Home app, he could access a massive list of random accounts, as well as photos they'd added to their Google Photos albums. If someone were to click on "linked accounts" while setting your Google Photos screensaver, the Google Home bug apparently showed a giant, scrolling list of users. From there, the bug allowed limited access to users' personal images in Google Photos, which could then be displayed as Ambient Mode screensavers. That is, someone could have theoretically displayed your photos as screensavers on their Android TV without you knowing it.

Artificial intelligence and machine learning are an increasingly integral part of many industries, including marketing. But while we often talk about using or incorporating AI in marketing, what do we really mean by that? What does it look like in practice? Here are 15 examples of AI and machine learning in action in the marketing industry (P.S. remember to check out Econsultancy's Marketer's Guide to Machine Learning and AI). The practice of clustering customer behaviours to predict future behaviours began way back in 1998, with a report on'digital bookshelves' by Jussi Karlgren, a Swedish computational linguist at Columbia University. In the same year, Amazon began using "collaborative filtering" to enable recommendations for millions of customers. Fast forward to 2019, and some of the most successful digital companies have built their product offerings around the ability to provide highly relevant and personalised product or content recommendations – including Amazon, Netflix and Spotify.