The models H71 and K71 are available exclusively on Flipkart, starting at an appealing price of INR 49,999 and INR 25,499, respectively. Additionally, the first 250 customers will give 1 year Sony Liv subscription for free, along with some special banking offer from Flipkart. Some of the common features that both models come equipped with include hands-free voice control. With far-field voice control, users can control TV, set reminders, and much more totally hands-free – Just say "Hey Google", or "Ok Google". Another common feature is micro dimming, which is designed to dim particular parts of the screen while leaving the rest in a brighter tone for an enhanced and optimized LED viewing.

Amazon's Echo Flex plug-in smart speaker should now be much more useful in the kitchen. The Verge reports that Amazon has unveiled an official, Third Reality-made Smart Clock add-on for the Flex that brings connected timekeeping to the Alexa device. The USB accessory will show the current time, of course, but it's most helpful for timers. Ask Alexa to set a timer and you'll see it count down, so you won't have to ask for an update (or use an Echo with a built-in display) just to see how soon your cooking will be ready. You can also use Alexa to switch between 12- and 24-hour formats, or manually adjust the brightness when the automatic settings aren't enough.

Of the 7,117 living languages currently known, Apple's Siri supports 21, Amazon Alexa eight, and Google Home 13. Our learned ability to use words to construct sentences that convey information, ideas, and emotions in an organized way makes us unique among animals. However, language has significance beyond communication. It is an expression of cultural identity, a demonstration of the existence of communities of peoples. According to Ethnologue: Languages of the World, there are currently 7,117 known living languages.

Billion-dollar investments in AI are booming. What does this mean for startups looking to AI for their innovative and competitive edge? The strategy seems simple: take one of humanity's perennial problems and fix it with machine learning. Google, Facebook, Netflix, and Uber did it. It can often seem like the obvious question is why not use AI?

Anything'for the first time' will certainly have plenty of predictions made and discussions on how it would be taken over in the future. Earlier when the computers got invented or when the idea of'Machine Learning' was born it was all the same through predictions and foresight. However, reality overtook all the fear and concern as the technology got even smarter than anticipated. Machine Learning in daily life is getting successfully applied in all aspects right from speech recognition apps in smartphones to YouTube recommendations and more. We literally teach machines on what we like and wish through our smart devices on a daily basis.

Although for many organizations artificial intelligence may be a work in progress, its rapid spread across the enterprise has led Gartner to predict that by 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence (AI). This in turn will drive an increase in streaming data and analytics infrastructures by up to 500%. It is likely that the current health crisis has sped up the rate of deployment. During the pandemic and with millions working from home, AI techniques such as machine learning (ML), optimization and natural language processing (NLP) have been able to provide insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures. It has also enabled many organizations to continue doing business where they might otherwise have had to slow down or even shut down.

The future of work is remote-- at this point, this assertion could easily double as the proverbial war cry of tech's most prolific armchair experts. Undoubtedly, there's ample evidence to support their claims. Over the past decade, growth in remote work careers has ballooned to the tune of 91 percent, with nearly 5 million Americans engaging in business from the comfort of their couches. Even still, there are numerous barriers preventing this lifestyle from becoming the norm, with geographically-dispersed workforces facing seemingly insurmountable challenges of fragmentation, isolation, and miscommunication. But fear not, office dwellers-- artificial intelligence, the most buzzworthy technology trend of modern computing, offers a number of capabilities that may soon serve as the most critical infrastructure in the remote work revolution.

In a fast-moving world, customers require efficiency and promptness when talking to any company. Here is where chatbots and Intelligent Virtual Assistants (IVAs) come into play. Thanks to their ability to engage into more advanced conversations, unlike rule-based chatbots, AI-powered systems are equipped with a multitude of features to assist and even entertain the users in their day-to-day activities. In addition to their customizable features, their self-learning ability and scalability have lead virtual assistants to gain popularity across various global enterprises. According to Grand View Research, the global intelligent virtual assistant market size was valued at USD 3.7 billion in 2019, growing at a Compound Annual Growth Rate (CAGR) of 34.0% over the forecast period.

Amazon is working on a new feature for its Alexa voice assistant that will let the software launch Android and iOS apps using voice commands, a first for Amazon's assistant and a bold expansion of its strategy to position Alexa as a platform-agnostic alternative to Apple's Siri and Google Assistant. Called Alexa for Apps, the new feature is launching today in preview form, meaning Amazon is working with select developers on how they'd like to make use of it. For instance, Amazon imagines users on either an iPhone or an Android device asking Alexa to open Twitter and search for a hashtag, and the app would then let the companion Alexa skill do the work of launching the app and inputting the search term. The results would then show up on the phone instead of being read aloud. Another example Amazon gives is using a voice request to launch TikTok and start a hands-free video recording (in the event you're filming yourself). It's a new type of interaction Amazon is hoping could catch on and help better position Alexa as a viable competitor to digital assistants from Apple and Google, both of which are deeply baked into their respective operating systems and have richer access to apps and system-level features as a result.

Using data science in the banking industry is more than a trend, it has become a necessity to keep up with the competition. Banks have to realize that big data technologies can help them focus their resources efficiently, make smarter decisions, and improve performance. Here is a list of data science use cases in banking area which we have combined to give you an idea how can you work with your significant amounts of data and how to use it effectively. Machine learning is crucial for effective detection and prevention of fraud involving credit cards, accounting, insurance, and more. Proactive fraud detection in banking is essential for providing security to customers and employees.