By Michael Sartori and Matthew Avery (March 2, 2022, 6:27 PM EST) -- Artificial intelligence has seeped into so many areas, and the chemical industry is no exception. The increasing number of patents being sought for AI-based chemical inventions reflects the innovations in the field. This article discusses the increase in the patenting of AI-based inventions related to the chemical industry and provides insights for the industry into how to navigate this new course. Patenting of AI-Based Chemical Inventions According to Andrew Moore at NC State University's College of Natural Resources, the chemical industry has used AI "to increase operational efficiency, reduce costs and improve customer satisfaction."[1]

This article is Part 3 of a 3 Part Series on Spatial Audio and Well-being. In the first article, Spatial Audio Trend Sparks New Opportunities In Digital Health, we explored some of the history, nomenclature and evolving trends behind spatial audio. In Part 2, 3 Ways Spatial Audio Can Transform The Future Of Digital Health, we dove deeper into the potential health and wellness implications of spatial audio on the human brain and our physiology. We looked at some of the latest research, the key drivers behind the trends, and the potential impact on future audio content and products. In Part 3, Spatial, Music & Hearables: The Next Frontier In Health And Wellness, we explore how the integration of immersive audio, personalized sound, and the Hearables Revolution is redefining the future of music as precision medicine. What might this "musical" New World Order mean to you? Imagine yourself wearing your brand-new pair of fashionable Ear Buddies comfortably tucked away as you go about your day.

If you're interested in obscure things, there are two reasons why your searches for items and products are likely to be less related to your interests than those of your'mainstream' peers; either you're a monetization'edge case' whose interests will only be catered to if you're also in the upper categories of economic purchasing power (for example, products and services related to'wealth management'); or the search algorithms that you're using are leveraging collaborative filtering (CF), which favors the interests of the majority. Since collaborative filtering is cheaper and more established than other potentially more capable algorithms and frameworks, it's possible that both these cases apply. CF-based search results will prioritize items that are perceived to be popular among'people like you', as best the host framework can understand what kind of a consumer you are. If you're wary of providing data profiling information to the host system – for instance, not inclined to press the'Like' buttons in Netflix and other video content services – you're likely to be classified quite generically in your earliest interactions with the system, and the recommendations you receive will reflect the most popular trends. On a streaming platform, that could mean being recommended whatever shows and movies are currently'hot', such as reality TV and forensic murder documentaries, irrespective of your interest in these.

Last year, genealogy service MyHeritage went viral after introducing a new "deepfake" feature that allowed users to animate the faces of loved ones in still photos. TikTok users posted videos reacting to the technology, called "Deep Nostalgia," as they brought back relatives they never got to meet or those whose loss they still grieved. To date, more than 100 million photos have been animated with the feature. Now comes the next iteration. Today, MyHeritage along with technology partner D-ID is expanding upon "Deep Nostalgia," with the launch of "LiveStory," a feature that doesn't just bring the people in photos to life with movement, but actually has them speak.

Effects of Optical Character Recognition (OCR) quality on historical information retrieval have so far been studied in data-oriented scenarios regarding the effectiveness of retrieval results. Such studies have either focused on the effects of artificially degraded OCR quality (see, e.g., [1-2]) or utilized test collections containing texts based on authentic low quality OCR data (see, e.g., [3]). In this paper the effects of OCR quality are studied in a user-oriented information retrieval setting. Thirty-two users evaluated subjectively query results of six topics each (out of 30 topics) based on pre-formulated queries using a simulated work task setting. To the best of our knowledge our simulated work task experiment is the first one showing empirically that users' subjective relevance assessments of retrieved documents are affected by a change in the quality of optically read text. Users of historical newspaper collections have so far commented effects of OCR'ed data quality mainly in impressionistic ways, and controlled user environments for studying effects of OCR quality on users' relevance assessments of the retrieval results have so far been missing. To remedy this The National Library of Finland (NLF) set up an experimental query environment for the contents of one Finnish historical newspaper, Uusi Suometar 1869-1918, to be able to compare users' evaluation of search results of two different OCR qualities for digitized newspaper articles. The query interface was able to present the same underlying document for the user based on two alternatives: either based on the lower OCR quality, or based on the higher OCR quality, and the choice was randomized. The users did not know about quality differences in the article texts they evaluated. The main result of the study is that improved optical character recognition quality affects perceived usefulness of historical newspaper articles significantly. The mean average evaluation score for the improved OCR results was 7.94% higher than the mean average evaluation score of the old OCR results.

Edition: 6; Released: February 2022 Executive Pool: 133782 Companies: 202 - Players covered include ABB; Alphabet Inc. (Google Inc.); Amazon; Asustek Computer; Blue Frog Robotics; Bsh Hausgeräte; Fanuc; Hanson Robotics; Harman International Industries; IBM Corporation; Intel Corporation; Jibo; Kuka; LG; Mayfield Robotics; Microsoft Corporation; Neurala; Nvidia; Promobot; Softbank; Xilinx and Others. Coverage: All major geographies and key segments Segments: Component (Software, Hardware); Robot Type (Service, Industrial); Application (Military & Defense, Law Enforcement, Personal Assistance & Caregiving, Public Relations, Education & Entertainment, Industrial, Stock Management, Other Applications) Geographies: World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World. Complimentary Project Preview - This is an ongoing global program. Preview our research program before you make a purchase decision. We are offering a complimentary access to qualified executives driving strategy, business development, sales & marketing, and product management roles at featured companies.

(2022) A model of speech recognition for hearing-impaired listeners based on deep learning. The Journal of the Acoustical Society of America.

The machine-learning algorithm has analyzed more than 115,000 orders, collecting approximately 260,000 individual data points and that data was then …

Wipro's hiring hackathon – sustainability machine learning challenge – concluded on February 14, 2022.

Google has unveiled technology that can read people's body movements to let devices'understand the social context around them' and make decisions. Developed by Google's Advanced Technology and Products division (ATAP) in San Francisco, the technology consists of chips built into TVs, phones and computers. But rather than using cameras, the tech uses radar – radio waves that are reflected to determine the distance or angle of objects in the vicinity. If built into future devices, the technology could turn down the TV if you nod off or automatically pause Netflix when you leave the sofa. Assisted by machine learning algorithms, it would also generally allow devices to know that someone is approaching or entering their'personal space'. Google has unveiled technology that can read people's body movements to let devices'understand the social context around them' and make decisions, such as flashing up information when you walk by or turning down volume on Radar is an acronym, which stands for Radio detection and ranging.