DUBLIN--(BUSINESS WIRE)--The "Machine Learning: The New Driving Force for DevOps" report has been added to ResearchAndMarkets.com's offering. When they work together, software development and operations teams can advance a company's business transformation. The integration of these teams, also known as DevOps, streamlines the legacy software development process. However, with the growing emphasis on digital transformation, the pace of development and innovation has increased. Therefore, the need for optimal orchestration in DevOps is rising, which requires innovation and advanced tools and technologies.
GE Healthcare and Optellum today announced that they have signed a letter of intent to collaborate to advance precision diagnosis and treatment of lung cancer. GE Healthcare is a global leader in medical imaging solutions. Optellum is the leader in AI decision support for the early diagnosis and optimal treatment of lung cancer. This press release features multimedia. Together, the companies are seeking to address one of the largest challenges in the diagnosis of lung cancer, helping providers to determine the malignancy of a lung nodule: a suspicious lesion that may be benign or cancerous.
Modern disruptive technologies like Machine Learning (ML) and Artificial Intelligence (AI) make their presence known in today's competitive markets. Organizations continuously attempt to improve profit margins, cut down on expenses, and provide a superior customer experience. It is evident that Artificial Intelligence and Machine Learning have become buzzwords in various industries, but what is their role, and what do they mean when it comes to Supply Chain Management? Using machine learning in logistics and supply chain management may aid in the automation of various routine processes, allowing businesses to concentrate on more strategic and significant business operations. Artificial intelligence and machine learning applications can be seen in every element of the supply chain process, including production, inventory management, procurement, warehousing, shipping, and customer support.
SAN DIEGO, Nov. 16, 2021 (GLOBE NEWSWIRE) -- GBT Technologies Inc. (OTC PINK: GTCHD) ("GBT" or the "Company"), is developing machine learning based software solutions to include integrated circuit design, verification and manufacturing aspects under one platform, enabling faster design, higher performance, and silicon yield. Based on its recent patented technology, GBT has started the development of a comprehensive software solution to address advanced nanometer challenges under one design environment. The software platform (internal code name MAGIC II), will address a wide variety of IC design aspects among these are functional verification, geometric design-rules correctness, power management, reliability and design for manufacturing (DFM). The platform is targeted to support analog, digital and mixed signal designs, enabling efficient scalability and process migration. GBT's ML technology plans to be implemented to ensure fast performance; especially, with today's very large ICs in the domains of AI, IoT and data processing.
Alluxio has raised $50 million in a Series C round of funding, capital the company will use to fuel the growth of its global operations and continue building out the capabilities of its data orchestration software for managing large-scale distributed data workloads. With the additional capital Alluxio will "enlarge our bandwidth in research and development to expand product capabilities, as well as increase our go-to-market capacity in different regions," said founder and CEO Haoyuan Li in an interview with CRN. The company is particularly looking to expand its Asia-Pacific presence and just opened an office in Beijing, China. Alluxio also announced the availability of version 2.7 of its Data Orchestration Platform with improved I/O performance for machine learning and support for open table formats such as Apachi Hudi and Iceberg. Alluxio's software, a virtual distributed file system that separates compute from storage, provides a way to unify access to data scattered across widely distributed hybrid-cloud and multi-cloud environments, making all data appear local no matter where it's stored.
Enterprise machine learning development platform startup Comet ML Inc. has raised $50 million in new funding to continue to evolve how it provides data science and machine learning teams a single platform to manage and optimize their work. The Series B round was led by OpenView. Also participating in the round were Scale Venture Partners, Trilogy Equity Partners and Two Sigma Ventures. Including the new funding, Comet has raised $69.8 million to date, according to data from Crunchbase. Founded in 2017, Comet pitches itself as doing for machine learning what GitHub did for code.
Cognixion, a neural interface startup, raised $12 million in seed funding to develop AI-powered neural interfaces that unlock speech and smart home controls for the hundreds of millions of people worldwide with communication and physical disabilities. The funding will help Cognixion develop new adaptive interfaces that make the Assisted Reality technology easier to use by everyone. Prime Movers Lab led the round with co-investors Northwell Health, Amazon Alexa Fund and Volta Circle. Cognixion's patented non-invasive, wireless brain-computer interface with an integrated augmented reality display, Cognixion ONE, detects the signals from the user's brainwaves associated with visual fixation on interactive objects and enables hands-free, voice-free control of AR/XR applications in the headset. Cognixion ONE is a closed-loop device that stimulates the visual cortex within the brain and reads its activity while sending control signals back to the AR application.
Shares of iRobot (NASDAQ:IRBT) and C3.ai (NYSE:AI) have taken a beating in 2021, falling 43% and 72%, respectively, off their all-time highs. While the two experienced different causes for these drops, they don't play major roles in the long-term thesis for either company. After iRobot was hit with unexpected tariffs this year and C3.ai lost its IPO hype, both stocks have fallen drastically. But those factors might disappear in 2022, meaning that these two companies have a bright future. When you think of artificial intelligence (AI) and machine learning, iRobot might not be the first company that comes to mind, but it has the potential to have a strong AI foundation.
Artificial intelligence is quickly changing the way fintech, insurtech and 5G operate during the covid-19 crisis and beyond. Machine learning and artificial intelligence are improving Fintech by increasing the accuracy and personalization of payment, lending, and insurance services while also helping to discover new borrower pools. Since that time the Covid-19 crisis and tragedy arose. On the one hand Paul Clarke noted that UK fintech investment slumps by 40% amid Covid-19 crisis, whilst on the other Deloitte in Beyond COVID-19: New opportunities for Fintech companies note that "As the COVID-19 pandemic continues to create uncertainty, many fintechs are under stress on a number of fronts. But, as the broader economy shifts from "respond" to "recover", new opportunities may be created for some fintechs. A key question is how fintechs may leverage their unique assets and skills to seize new opportunities in the future. It could be an opportune time to think big and act boldly." Pavitra R considered the impact of Covid-19 and noted in 5 U.S. FinTech startups reimagining the healthcare industry notes that FinTech is undoubtedly shaping the face of the Health Care industry. "FinTech companies leverage powerful innovations blockchain, Artificial Intelligence, and Machine Learning to eliminate the inefficiencies and knowledge gaps endemic to most healthcare payment plans." The likes of Nigel Wilson (@nigewillson) and Brian Ahier (@ahier) have stressed the importance of applying AI to positive use cases such as preventative medicine and improved Health Care outcomes. McKinsey in an article entitled AI-bank of the future: Can banks meet the AI challenge? " The potential for value creation is one of the largest across industries, as AI can potentially unlock $1 trillion of incremental value for banks, annually (Exhibit 1)." Source for image above: AI-bank of the future: Can banks meet the AI challenge? "While for many financial services firms, the use of AI is episodic and focused on specific use cases, an increasing number of banking leaders are taking a comprehensive approach to deploying advanced AI, and embedding it across the full lifecycle, from the front- to the back-office (Exhibit 2)" Source for image above: AI-bank of the future: Can banks meet the AI challenge?