Bluware Corp, the digital innovation platform that enables the oil and gas industry to accelerate digital transformation initiatives using deep learning, is pleased to announce a new agreement with BP (NYSE: BP). Bluware's technology will help BP to improve quality and speed when delivering seismic interpretation products. "BP recognizes the significant impact advances in digital technology can bring and we are pleased to implement Bluware InteractivAI, a new and innovative deep learning technology, augmenting our geoscientists' ability to accelerate subsurface data interpretation," says Ahmed Hashmi, Upstream Chief Digital and Technology Officer at BP. Large seismic data sets are difficult to move and use in workflows and time consuming to interpret. InteractivAI, powered by Bluware Volume Data Store (VDS) cloud-native data environment, enables the acceleration of detailed interpretation tasks. With this tool geoscientists can now train and correct deep learning results interactively, significantly improving structural interpretation workflows.

Artificial intelligence (AI) is expected to play a major role in shaping global competitiveness and productivity over the next couple of decades, granting early adopters significant societal, economic, and strategic advantages. As the pace of AI innovation and development picks up--underpinned by advancements in big data and high-performance computing--the United States and China are both in the driver's seat.

MIM Software Inc., a leading global provider of medical imaging software, announced today it has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its deep learning auto-contouring software, Contour ProtégéAI . Contour ProtégéAI is an auto-contouring solution that seamlessly integrates into any department's workflow and can be rapidly implemented into virtually any environment. User feedback and a determination to continuously improve auto-segmentation were key drivers in developing the product. "Our customers are under continual pressure to improve their practices while facing escalating time constraints,'' said Andrew Nelson, Chief Executive Officer of MIM Software Inc. "Our deep learning auto-segmentation product, Contour ProtégéAI, will play a critical role in reducing the burden of contouring." Auto-contouring is an ideal use case for deep learning algorithms because it is one of the most time-consuming clinical tasks.

LEUVEN, Belgium, and SANTA CLARA, Calif., July 9, 2020 – Imec, a research and innovation hub in nanoelectronics and digital technologies, and GLOBALFOUNDRIES (GF), a specialty foundry, announced a hardware demonstration of a new artificial intelligence chip. Based on imec's Analog in Memory Computing (AiMC) architecture utilizing GF's 22FDX solution, the new chip is optimized to perform deep neural network calculations on in-memory computing hardware in the analog domain. Achieving record-high energy efficiency up to 2,900 TOPS/W, the accelerator is a key enabler for inference-on-the-edge for low-power devices. The privacy, security and latency benefits of this new technology will have an impact on AI applications in a wide range of edge devices, from smart speakers to self-driving vehicles. Since the early days of the digital computer age, the processor has been separated from the memory.

WellAI data scientists Daniel Satchkov and Sergei Polevikov will present their most recent research entitled "Reading 25 Million Studies in Seconds: Implications for Fighting COVID-19 and Managing a Portfolio" at a free webinar on August 25, 2020. The webinar will take place from 12pm to 1pm EST, and is jointly organized by the Society of Quantitative Analysts (SQA) and WellAI. Discussion will be partly based on a study "Artificial Intelligence-powered search tools and resources in the fight against COVID-19" published in the Journal of the International Federation of Clinical Chemistry and Laboratory Medicine in June 2020, and is currently available through the PubMed database of the National Institutes of Health (NIH). Sergei Polevikov, CEO of WellAI and a board director at SQA, explained: "We wanted to share our unique experience as we believe our work is relevant to both medical researchers and finance professionals. WellAI data scientists had built a free COVID-19 analytical tool for medical researchers around the world in early April 2020, to help fight the pandemic. As some of us had also had previous experience as data scientists in the finance industry, we found some interesting similarities and differences in a way one applies machine learning algorithms in healthcare versus applying those in finance. What better place to share this knowledge than the SQA – one of the most recognized organization in the United States among the quantitative investment professionals?"

Comau has created an innovative, in-line testing and quality control paradigm that optimizes the construction and assembly of batteries. MI.RA/Thermography is one of the newest solutions within Comau's cutting-edge vision systems family of Machine Inspection Recognition Archetypes, named MI.RA. Designed for industrial-scale battery manufacturing, MI.RA/Thermography uses thermal imaging and artificial intelligence to perform non-invasive automated assessment and control of welded joints, to ensure battery integrity and prevent waste. Its non-destructive testing methodology protects cycle times without changing the existing manufacturing layout. Battery packs are composed of a large number of individual battery cells that are structurally held and electrically connected by numerous welded joints.

The challenge Artificial intelligence (AI) holds the potential to vastly improve government operations and help meet the needs of citizens in new ways, ranging from traffic management to healthcare delivery to processing tax forms. But most public institutions have not yet adopted this powerful technology. While public sector officials are increasingly aware of the transformational impact of data and AI-powered solutions, the data needed for AI solutions to be developed and deployed is often neither accessible nor discoverable. Public sector officials may also lack the appropriate knowledge and expertise to make strategic buying decisions for AI-powered tools. Uncertainty about ethical considerations adds further layers of complexity. As a result, officials tend to delay buying decisions, or reduce perceived risk by concentrating their purchasing on a few known suppliers. The opportunity The World Economic Forum’s Centre for the Fourth Industrial Revolution has brought together a multistakeholder community to co-design the AI Procurement in a Box toolkit guide for governments to rethink their public procurement processes:  IntroductionGuidelines for AI procurement, presenting the general considerations to be taken when government is procuring AI-powered solutionsWorkbook for policy and procurement officials guiding them through the guidelines ChallengesPilot case studiesThis guidance aims to empower government officials to more confidently make responsible AI purchasing decisions. The tools also improve the experience for AI solutions providers by supporting the creation of transparent and innovative public procurement processes that meet their needs. Impact By co-designing these guidelines with governments, small and large businesses, civil society and academia, the intended impact is the responsible deployment of AI solutions for the public benefit of constituents. Leveraging the significant purchasing power of government in the market, the private-sector adoption of the guidelines can permeate the industry beyond the adoption by public sector organizations. Embedding the principles advocated for in the guidelines into administrative processes will also expand opportunities for new entrants and create a more competitive environment for the ethical development of AI. Further, as industry debates its own standards on these technologies, the government’s influence can help set a baseline for the harmonization of standards-setting. Project accomplishments  March–September 2019: Policy development – the World Economic Forum worked with fellows from the public and private sectors, and a multistakeholder group that also included academia and civil society organizations, to create action-orientated guidelines for government procurement of AI. October–March 2020: Pilot and Iteration – the project team validated guidelines through feedback sessions and a pilot project with the United Kingdom government, the Dubai Electricity and Water Authority and the Government of Bahrain. June 2020: Publication of the AI Procurement in a Box guide that will allow governments to effectively learn and adopt the best practices developed. Contact information For more information, contact Kay Firth-Butterfield, Head of AI and Machine Learning, World Economic Forum, at Kay.Firth-Butterfield@weforum.org.

Elliptic Labs announced today that it has signed a contract with a new smartphone OEM customer in Asia that will incorporate Elliptic's INNER BEAUTY AI Virtual Proximity Sensor into their next smartphone model. "We are excited that more smartphone OEMs see the value in our technology and appreciate the opportunities that Elliptic's AI Virtual Smart Sensor platform has to offer" said Laila Danielsen, CEO of Elliptic Labs. INNER BEAUTY is just one of several virtual smart sensors that Elliptic Labs provides OEMs that deliver greater user functionality and cleaner, sleeker phone designs. Another such example is INNER REFLECTION, a pioneering virtual presence sensor that offers sub-millimeter precision capable of detecting a person breathing. Elliptic Labs is a global AI software company and the world leader in AI virtual sensors for the smartphone, IoT, and automotive industries.

Forecasting is a technique that uses historical data and events to build estimates about future trends, potential disasters, and the overall behavior of any subject. Forecasting can be used as probabilistic support for decision analysis, to estimate expenses, revenues, and budget plans. Forecasting in business can be divided into two distinct categories: qualitative forecasting and quantitative forecasting. For more information, you can take a look at Investopedia's Financial Forecasting primer. Both types of forecasting have shown a lot of promise and managed to create business enhancements for many entities.

XAOS MOTORS, headquartered in KOREA, challenges the technological progress of autonomous driving. XAOS MOTORS, by launching XCAT LiDAR Sensor now, give OEMs to make fully self-driving cars earlier than the market expected. MEMS LiDAR Sensor XCAT was developed for self-driving cars. With the ability to scan over 300 meters, XCAT can safely cope with high-speed driving. XCAT is designed for mass production, and OEMs can adopt high-performance 3D LiDARs at a low cost.