March 13 (Reuters) - Ukraine's defense ministry on Saturday began using Clearview AI's facial recognition technology, the company's chief executive told Reuters, after the U.S. startup offered to uncover Russian assailants, combat misinformation and identify the dead. Ukraine is receiving free access to Clearview AI's powerful search engine for faces, letting authorities potentially vet people of interest at checkpoints, among other uses, added Lee Wolosky, an adviser to Clearview and former diplomat under U.S. presidents Barack Obama and Joe Biden. The plans started forming after Russia invaded Ukraine and Clearview Chief Executive Hoan Ton-That sent a letter to Kyiv offering assistance, according to a copy seen by Reuters. Clearview said it had not offered the technology to Russia, which calls its actions in Ukraine a "special operation." Ukraine's Ministry of Defense did not reply to requests for comment.

Ukraine's defense ministry on Saturday began using Clearview AI's facial recognition technology, the company's chief executive told Reuters, after the U.S. startup offered to uncover Russian assailants, combat misinformation and identify the dead. Ukraine is receiving free access to Clearview AI's powerful search engine for faces, letting authorities potentially vet people of interest at checkpoints, among other uses, added Lee Wolosky, an adviser to Clearview and former diplomat under U.S. Presidents Barack Obama and Joe Biden. The plans started forming after Russia invaded Ukraine and Clearview Chief Executive Hoan Ton-That sent a letter to Kyiv offering assistance, according to a copy seen by Reuters. Clearview said it had not offered the technology to Russia, which calls its actions in Ukraine a "special operation." Ukraine's Ministry of Defense did not reply to requests for comment.

Training neural networks takes a lot of time, even with the fastest and costliest accelerators on the market. It's maybe no surprise then that a number of startups are looking at how to speed up the process at the software level and remove some of the current bottlenecks in the training process. For Strong Compute, a Sydney, Australia-based startup that was recently accepted into Y Combinator's Winter '22 class, it's all about removing these inefficiencies in the training process. By doing so, the team argues that it can speed up the training process by 100x or more. "PyTorch is beautiful and so is TensorFlow. These toolkits are amazing, but the simplicity they have -- and the ease of implementation they have -- comes at the cost of things being inefficient under the hood," said Strong Compute CEO and founder Ben Sand, who previously co-founded AR company Meta (before Facebook used that name).

We propose VALSE (Vision And Language Structured Evaluation), a novel benchmark designed for testing general-purpose pretrained vision and language (V&L) models for their visio-linguistic grounding capabilities on specific linguistic phenomena. VALSE offers a suite of six tests covering various linguistic constructs. Solving these requires models to ground linguistic phenomena in the visual modality, allowing more fine-grained evaluations than hitherto possible. We build VALSE using methods that support the construction of valid foils, and report results from evaluating five widely-used V&L models. Our experiments suggest that current models have considerable difficulty addressing most phenomena. Hence, we expect VALSE to serve as an important benchmark to measure future progress of pretrained V&L models from a linguistic perspective, complementing the canonical task-centred V&L evaluations.

Marine debris is a problem both for the health of marine environments and for the human health since tiny pieces of plastic called "microplastics" resulting from the debris decomposition over the time are entering the food chain at any levels. For marine debris detection and removal, autonomous underwater vehicles (AUVs) are a potential solution. In this letter, we focus on the efficiency of AUV vision for real-time and low-light object detection. First, we improved the efficiency of a class of state-of-the-art object detectors, namely EfficientDets, by 1.5% AP on D0, 2.6% AP on D1, 1.2% AP on D2 and 1.3% AP on D3 without increasing the GPU latency. Subsequently, we created and made publicly available a dataset for the detection of in-water plastic bags and bottles and trained our improved EfficientDets on this and another dataset for marine debris detection. Finally, we investigated how the detector performance is affected by low-light conditions and compared two low-light underwater image enhancement strategies both in terms of accuracy and latency. Source code and dataset are publicly available.

Global Artificial Intelligence market report provides an in-depth overview of Product Specification, technology, product type and production analysis considering major factors such as Revenue, Cost, Gross and Gross Margin. The current trends will determine what options will be for strategical investment. The Artificial Intelligence Market report also provides an in-depth survey of key players in the market which is based on the various objectives of an organization such as profiling, the product outline, the quantity of production, required raw material, and the financial health of the organization. This Artificial Intelligence market Report cover strategic profiling of key players in the market, comprehensively analyzing their core competencies, and drawing a competitive landscape for the market. At present, the market is developing its presence and some of the Global Artificial Intelligence Market key players Involved in the study are Advanced Micro Devices, Inc., Aicure, LLC, Arm, Ltd., Atomwise, Inc., AYASDI AI LLC, Baidu Inc., ClariFI, Inc., Cyrcadia Health, Enlitic, Inc., H2O.ai, Research study is to define Market Sizes of various segments & countries in previous years and to forecast the values to the next 5-8 years.

Greg Kruger pauses for what seems like an eternity during his presentation, but it actually just lasts six seconds. The senior agronomist for BASF's xarvio digital farming division did it to prove a point about BASF's Smart Farming joint collaboration with Bosch that includes precision spraying technology the firms call Smart Spraying. The strategy teams machine-learning algorithms with computer vision to enable "green-on-green" spraying that distinguishes between weeds and crops in-season. Kruger's presentation was part of a BASF media briefing held before this week's Commodity Classic in New Orleans. "In the six seconds that I paused, we've taken 1,000 images [with Smart Spraying] on the boom," says Kruger.

Cognitec Systems has announced it is joining the SALTO Group. SALTO selected Cognitec to meet market requests for adding face recognition and artificial intelligence technologies to the company's electronic access control and ticketing solutions. "Working with Cognitec gives SALTO the opportunity to integrate emerging biometric and AI technologies into our Group products and platforms to create new solutions and services that benefit all of our clients," said SALTO's Chief Technology and Innovation Officer Marc Handels. Cognitec will continue focusing on all business relations with its government and commercial clients worldwide. The current office locations and experienced teams remain in Germany, the United States, and Australia.

Edition: 7; Released: February 2022 Executive Pool: 18336 Companies: 46 - Players covered include AdhereTech Inc.; Capsule Technologies, Inc.; Cerner Corporation; GE Healthcare; Honeywell International Inc.; Koninklijke Philips N.V.; McKesson Corporation; Medtronic plc; SAP SE; Siemens AG; STANLEY Healthcare and Others. Coverage: All major geographies and key segments Segments: Component (Services, Hardware, Systems & Software); Application (Remote Medicine Management, Electronic Health Record & Clinical Workflow, Medical Assistance, Outpatient Vigilance, Medical Connected Imaging) Geographies: World; USA; Canada; Japan; China; Europe; France; Germany; Italy; UK; 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.

Italy's data privacy watchdog said it will fine the controversial facial recognition firm Clearview AI for breaching EU law. An investigation by Garante, Italy's data protection authority, found that the company's database of 10 billion images of faces includes those of Italians and residents in Italy. The New York City-based firm is being fined €20 million, and will also have to delete any facial biometrics it holds of Italian nationals. This isn't the first time that the beleaguered facial recognition tech company is facing legal consequences. The UK data protection authority last November fined the company £17 million after finding its practices--which include collecting selfies of people without their consent from security camera footage or mugshots--violate the nation's data protection laws.