One goal of AI work in natural language is to enable communication between people and computers without resorting to memorization of complex commands and procedures. Automatic translation – enabling scientists, business people and just plain folks to interact easily with people around the world – is another goal. Both are just part of the broad field of AI and natural language, along with the cognitive science aspect of using computers to study how humans understand language.
The world around us is changing rapidly. With the arrival of industrial revolution 4.0, businesses of all sizes and types are increasingly capitalizing on advanced, intelligent technologies. They are taking advantage of automation to reduce time-consuming, tedious tasks, especially automating assembly line work. However, as such intelligent technologies are better performing than humans, it is necessary businesses must think of knowledge management for their employees. Knowledge is significantly a crucial aspect in achieving high-quality performance for employees.
Artificial intelligence is one of the most revolutionary technologies of our time, which is advancing as each day goes by. AI labs contribute to these advancements by housing scientists and researchers under one roof to study this disruptive technology for further developments. While there are quite a few AI labs across the globe, artificial intelligence researchers go perplexed when people ask them to rate the top labs in the world. And rightfully so, because they're all unique in the way they work. While every lab focuses on different domains of artificial intelligence, commercial AI labs like Google, Facebook, Amazon, Apple, and Microsoft, the U.S Big Tech, have set up dedicated AI labs too.
By Nikhil Bedi & Vivek Bhamodkar With evolving business models, increased use of tech and a changing regulatory landscape, fraud management is fraught with newer and more complex challenges. These are further exacerbated during cross-border investigations, where varied levels of standardisation, languages, local laws and regulations, along with specific cultural attributes, bring additional complexities--mandating an investigation methodology standardisation and requiring tools for quick insights. Emerging technology and artificial intelligence (AI) can help make investigations efficient, generate insights, and/or aid reviews. Optimal use of AI demands the knowledge of'possibilities and limitations' of such techniques, either in the form of'special purpose software' or the ability to combine various methods. As significant a role as these tools and technologies may play in the fight against fraud, use of AI, NLP and other technologies come with their own set of challenges.
To understand the "clicks" sperm whales make to talk (stringing together a series of statements called "codas"), researchers have launched a five-year-long quest called Protect CETI. It'll be the most comprehensive attempt at interspecies communication ever, the team believes. CETI (Cetacean Translation Initiative) begins with the capturing and cataloging of millions of morse-code-like whale vocalizations. Video and audio tools will be used, and the data will be fed to an AI that uses natural language processing (the tech that brought us Siri and Alexa) to decode it. Cues from captured video will provide context to the conversations and, if all works according to plan, will bring researchers closer to a breakthrough than ever before.
Like Google, Bing has long graduated from being a simple search engine. Yes, you can use it exclusively for searching the web, but it's also a place to read the news, learn about history and more. And on Android, Microsoft has updated the Bing Search app to better reflect that complexity (via Windows Central). The most notable new feature is the addition of a personalized homepage. Here you'll find shortcuts to topics you might search frequently such as the current weather forecast or what's nearby.
Now that every adult in the US is eligible for a COVID-19 vaccine, Amazon wants to make it as simple as possible to get your shots. Alexa now helps you find vaccination sites just by saying "where can I get a COVID vaccine?" to your smart speaker or other supporting device. You can specify a city if you want more than nearby results, and you can call a given site if you have questions about appointments. Alexa is also useful for learning about vaccine availability and eligibility in over 85 countries, and you can find COVID-19 testing locations much like you would vaccinations. There's a good chance you'll use a mapping app first, but there's no doubt this is convenient -- you can ask about those potentially life-saving vaccine doses while you're busy making breakfast.
Spoken dialogue is the most natural way for people to interact with complex autonomous agents such as robots. Future Army operational environments will require technology that allows artificial intelligent agents to understand and carry out commands and interact with them as teammates. Researchers from the U.S. Army Combat Capabilities Development Command, known as DEVCOM, Army Research Laboratory and the University of Southern California's Institute for Creative Technologies, a Department of Defense-sponsored University Affiliated Research Center, created an approach to flexibly interpret and respond to Soldier intent derived from spoken dialogue with autonomous systems. This technology is currently the primary component for dialogue processing for the lab's Joint Understanding and Dialogue Interface, or JUDI, system, a prototype that enables bi-directional conversational interactions between Soldiers and autonomous systems. "We employed a statistical classification technique for enabling conversational AI using state-of-the-art natural language understanding and dialogue management technologies," said Army researcher Dr. Felix Gervits. "The statistical language classifier enables autonomous systems to interpret the intent of a Soldier by recognizing the purpose of the communication and performing actions to realize the underlying intent."
Translation tools from Google and other companies could be contributing to significant misunderstanding of legal terms with conflicting meanings such as "enjoin," according to research due to be presented at an academic workshop. Google's translation software turns an English sentence about a court enjoining violence, or banning it, into one in the Indian language of Kannada that implies the court ordered violence, according to the new study. "Enjoin" can refer to either promoting or restraining an action. Mistranslations also arise with other contronyms, or words with contradictory meanings depending on context, including "all over," "eventual" and "garnish," the paper said. Google said machine translation is "is still just a complement to specialized professional translation" and that it is "continually researching improvements, from better handling ambiguous language, to mitigating bias, to making large quality gains for under-resourced languages."
Ever wish you could easily export all your Facebook posts and notes onto a completely different platform? On Monday, Facebook announced a few new data portability options that allow you to seamlessly transition the content you've written on the social network onto platforms made for writing. Specifically, Facebook has built in an option to transfer your posts and notes into Google Docs as well as two popular blogging platforms, WordPress.com To give people more control and choice over their data, today we're announcing that Facebook posts and notes can be directly transferred to @GoogleDocs, @Blogger and @WordPress via our Transfer Your Information tool:https://t.co/ksHO0oeYq5 Facebook already offers options to export your data to your local hard drive.
Whatever business a company may be in, software plays an increasingly vital role, from managing inventory to interfacing with customers. Software developers, as a result, are in greater demand than ever, and that's driving the push to automate some of the easier tasks that take up their time. Productivity tools like Eclipse and Visual Studio suggest snippets of code that developers can easily drop into their work as they write. These automated features are powered by sophisticated language models that have learned to read and write computer code after absorbing thousands of examples. But like other deep learning models trained on big datasets without explicit instructions, language models designed for code-processing have baked-in vulnerabilities.