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SAN FRANCISCO, Sept. 2, 2021 /PRNewswire/ --LendingClub Corporation(NYSE: LC), the parent company of LendingClub Bank, America's leading digital marketplace bank, announced that its Chief Financial Officer Tom Casey and its Chief Consumer Banking Officer Ronnie Momen will participate at the JMP Securities Fintech Forum on September 10.

Momen will also join JMP analyst Devin Ryan on a panel entitled, "The Connected Financial Life" at 2:00 pm ET. The panel will explore the evolution of artificial intelligence within financial technology, improvement in data collection through aggregators, new means of offering more customized and optimized financial recommendations, and the ways in which these changes are important for companies and their end consumers.

Webcast information A live webcast of the call will be available athttps://wsw.com/webcast/jmp50/panel3/1864356. Registration is required.

ReplayAn archive of the call will be available at http://ir.lendingclub.com under the News & Market Data menu in Events & Presentations.

About LendingClubLendingClub Corporation (NYSE: LC) is the parent company of LendingClub Bank, National Association, Member FDIC. LendingClub Bank is the leading digital marketplace bank in the U.S. Members can gain access to a broad range of financial products and services through a technology-driven platform, designed to help them pay less when borrowing and earn more when saving. Since 2007, more than 3.5 million members have joined the Club to help reach their financial goals. For more information about LendingClub, visithttps://www.lendingclub.com.

Safe Harbor StatementSome of the statements made during the event, including statements regarding LendingClub's planned or projected product offerings, performance and strategy, will be "forward-looking statements." The words "anticipate," "believe," "estimate," "expect," "intend," "may," "outlook," "plan," "predict," "project," "will," "would" and similar expressions may identify forward-looking statements, although not all forward-looking statements contain these identifying words. Factors that could cause actual results to differ materially from those contemplated by these forward-looking statements include those factors set forth in the section titled "Risk Factors" in LendingClub's most recent Annual Report on Form 10-K and Quarterly Report on Form 10-Q, each as filed with the Securities and Exchange Commission, as well as in LendingClub's future filings made with the Securities and Exchange Commission. LendingClub may not actually achieve the plans, intentions or expectations disclosed in forward-looking statements, and you should not place undue reliance on forward-looking statements. Actual results or events could differ materially from the plans, intentions and expectations disclosed in forward-looking statements. LendingClub does not assume any obligation to update any forward-looking statements, whether as a result of new information, future events or otherwise, except as required by law.

CONTACT:For Investors:[emailprotected]Media Contact:[emailprotected]

SOURCE LendingClub Corporation

https://www.lendingclub.com

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LendingClub to Participate in The JMP Securities Fintech Forum: Artificial Intelligence on September 10 - PRNewswire

In a recent article inthe journal Nature Communications, an international team of researchers ledbythe British Antarctic Survey and the Alan Turing Institute describe the new artificial intelligence (AI) tool which they have named IceNet.

IceNet has the potential to fill an urgent gap in forecasting sea ice for Arctic sustainability efforts and runs thousands of times faster than traditional methods, explained study lead author Tom Andersson to Earth.com.

IceNet can predict with an accuracy of 95percentwhether sea ice will be present two months ahead.In contrast to conventional forecasting systems that attempt to model the laws of physics directly, IceNet is based on a concept called deep learning.The researchers have uploadeddecades of observational data concerning ice sea levels,together with thousands of years of climate simulation data into the AI tool. This makes IceNet a dynamic tool that keeps learning and adapting in order to extract increasingly high-level information from the available data.

Im excited to see how AI is making us rethink how we undertake environmental research, said Dr. Scott Hosking. Our new sea ice forecasting framework fuses data from satellite sensors with the output of climate models in ways traditional systems simply couldnt achieve.

Now weve demonstrated that AI can accurately forecast sea ice, our next goal is to develop a daily version of the model and have it running publicly in real-time, just like weather forecasts, said Andersson.

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New Artificial Intelligence Tool Can Predict the Future of Arctic Sea Ice - High North News

NASA Never Turns Back to Utilize AI and Machine Learning in the Best Possible Way.

Artificial intelligence and machine learning have had a profound influence on a wide range of areas and businesses, where they have paved the way for the automation and optimization of operations as well as the development of new business opportunities. However, due to quick advances, these technological innovations are being used in research and development outside of our atmosphere and into space.

Now, lets take a quick look at how NASA uses AI and Machine Learning for various space projects and earth science.

NASA is constantly progressing in AI applications for space research, such as automating image analysis for the galaxy, planet, and star classification, developing autonomous space probes that can avoid space junk without human involvement, by using AI-based radio technology to make communication networks more effective and disturbance-free. However, the creation of autonomous landers (robots) that wander the surface of other planets is one of NASAs most critical AI applications. Without explicit orders from the control room, these autonomous robots must make judgments and avoid obstacles on the uneven terrain while choosing the optimal course. Some of the most significant advances in Mars exploration have relied heavily on autonomous robots.

The Radiant Earth Foundation and NASA Earth Science Data Systems (ESDS) sponsored a workshop for professionals in January 2020 to explore the progress of machine learning (ML) methods on NASAs Earth Observation (EO) data. The event, which took place in Washington, D.C., drew 51 participants from government entities, non-profit groups, colleges, and commercial businesses. The session report (PDF) is now online, and it emphasizes the difficulties, potential solutions, and best practices for integrating EO data in machine learning processes for Earth science research and applications.

The Advancing ML Tools for Earth Science Workshop drew 51 people from government agencies, non-profits, universities, and the commercial sector. The Radiant Earth Foundation provided this image. Machine learning is a type of AI that can learn from data, recognize patterns and make choices with little or no human interaction. Because of the abundance of publicly available EO data, Earth scientific fields are particularly well suited to make use of ML.

Open data, open-source technology, community building, specialized algorithm development study, and benchmark-labeled samples are the building elements for mainstream use of ML in Earth science. To that aim, NASAs ESDS program has invested in machine learning-based technology and industry that concentrate on data-driven science and operational efficiency. There are also plans to create highly curated Earth science benchmark instructional datasets that may be utilized to speed up advanced computer algorithms and benchmarking.

However, there are also issues with applying machine learning to Earth science, such as a shortage of training datasets and transferring ML applications from development to production. Participants in the workshop explored these major issues and offered suggestions for how to best proceed.

1. Rovers on Mars

Did you believe Tesla, Google, Uber, and other companies were the first to commit substantially to self-driving cars? In reality, NASA developed autonomous driving systems for Mars Rovers over a year earlier. AutoNav, a machine learning-based navigational and mobility system for self-driving Mars rovers, was utilized in the Spirit and Opportunity rovers that arrived on Mars in 2004. Curiosity, a rover deployed in 2011, also utilizes AutoNav and is continuing investigating Mars to this day with the goal of discovering water and other elements that might make Mars viable for human travel in the future!

2. Medicine in Space

What will happen if astronauts require medical assistance when they travel farther into space outside Earths orbit? They wont be able to go back to Earth for a check-up with a physician, certainly! As a result, NASA is developing the Exploration Medical Capability, which will utilize Machine Learning to provide healthcare alternatives based on the astronauts projected future medical requirements. These healthcare choices will be developed by certified medical professionals, and they will learn and grow over time as the astronauts experiences inform them.

3. Planets Search

You already know how huge the universe is. NASA estimates that there are about 100 billion stars in the galaxy, with around 40 billion having the potential to support life. This isnt science fiction; NASA believes we may one day discover aliens! However, before NASA can find aliens, it must first uncover a growing number of new planets in other solar systems. Once these exoplanets have been identified, NASA will analyze their atmosphere spectra to see if they have the potential to support life.

4. A Robotic Astronaut

Were you under the impression that astronauts could only be human beings? Normally, youd be correct, but NASA has now produced a robotic astronaut. Science fiction is becoming a reality! The Robonaut was designed to operate alongside astronauts in space, assisting them in doing activities that would be unsafe for humans to complete. This was important because it will boost NASAs capability for space research and discovery, allowing us to understand more about the galaxy.

5. Navigation on the Moon

What would happen if you become separated from the rest of the world? Well, not much at all! You may just use GPS to get to your desired location. But what if you become separated from your companions on the Moon?! Because GPS doesnt function on the moon, youd best pray somebody finds you! Or, at the very least, it didnt until today!!! The NASA Frontier Development Laboratory is now working on a project that will allow navigation on the surface of the moon! This project seeks to offer GPS even on the moons surface, but without the need for numerous high-cost satellites!

In space research, such as charting unlabelled galaxies, stars, black holes, and investigating cosmic occurrences, as well as communications, autonomous StarCraft navigation, tracking, and control systems, AI has proved to be a game-changer in all of these. The most current use of AI may be seen in efforts to develop AI-powered, empathic robotic assistants to aid astronomers in long-distance space flight by recognizing and anticipating the crews demands, as well as interpreting astronauts emotions.

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Use of Artificial Intelligence and Machine Learning in NASA NASA Never Turns Back to Utilize AI - Analytics Insight

Oregon Health & Science University is part of a new National Science Foundation-funded institute to develop artificial intelligence systems to help people live independently as they age. (OHSU)

Oregon Health & Science University is one of five universities nationwide to form a new National Science Foundation-funded institute to design and build intelligent systems to help people age in place.

The five-year, $20 million grant will support the creation of an AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups, or AI-Caring. The institute will develop artificial intelligence systems that work for aging adults, including those diagnosed with mild cognitive impairment, and their caregivers.

Most older adults prefer to remain in their own homes. But safety concerns, medication schedule and isolation can all make it difficult for them to do so.

The work builds on a model OHSU established more than a decade ago through its Oregon Center for Aging and Technology, or ORCATECH. In this research, participants agree to permit the ORCATECH system to collect unique life data in their homes, using an array of sensors to assess changes in gait, sleep and overall activity. It also includes a MedTracker electronic pill box as well as a scale to measure weight, body fat and pulse.

Our project is focused on assisting people to age independently and in particular people who might develop cognitive impairment later in life, said OHSU site leader Jeffrey Kaye, M.D., director of the OHSU Layton Aging & Alzheimers Disease Center. ORCATECH has unique datasets that will allow the new institute to develop and create advanced artificial intelligence algorithms to help people age in place.

OHSU has developed terabytes of privacy-protected data that will be useful for the new institute.

Were very honored and pleased to be partners in this national effort, Kaye said. We look forward to collaborating with other investigators, who will help advance our home assessment platform and the artificial intelligence. The goal is to make better diagnoses and ultimately mediate disabilities in aging.

Given the staggering costs of long-term care services for people who can no longer live independently, estimated to top $1 trillion by 2050 to care for those with Alzheimers disease, Kaye said the new institute is an important step toward developing solutions.

Our goal is to create systems that help people take care of people, said Beth Mynatt, director of the Institute for People and Technology at Georgia Tech, the lead institution for the new project. Care can be a complicated task, requiring coordination and decision-making across family members managing day to day demands.

Aside from OHSU and Georgia Tech, the institute will include faculty from Carnegie Mellon University, Oregon State University and the University of Massachusetts Lowell. Amazon and Google are industry sponsors.

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OHSU is part of national institute to advance artificial intelligence in aging - OHSU News

The Army Artificial Intelligence Integration Center (AI2C) is seeking artificial intelligence research and development whitepapers and proposals in support of new technologies and translational research-based approaches that support the identification, alignment, and exploitation of basic, applied, and advanced research and technology.

The Broad Agency Announcement (BAA) includes activities involving basic research, applied research, advanced technology development, and, under certain conditions, may include activities involving advanced component development and prototypes. This Announcement is not for the acquisition of technical, engineering, and other types of support services.

As a part of this BAA, AI2C will post specific areas with strong potential for funding on its website and as an amendment to this BAA via http://www.grants.gov. These topics will generally have clear deadlines for submission and may have other specific preparation guidelines.

Ongoing Areas of Interest

Autonomous Platforms The Army is particularly interested in research in autonomous ground and air vehicles, which must operate in open, urban and cluttered environments.

Artificial Intelligence and Machine Learning Algorithms (AI/ML) The Army is interested in core algorithmic improvements such as improved methods for collecting, labeling, utilizing, managing, and tracking data and the models learned from them.

AI-Based Decision Making The Army is interested in research on AI algorithms and systems to improve decision making across all echelons

Analysis and Human-Machine Interfaces The Army is interested in AI/ML research in areas which can reduce the cognitive burden on humans and improve overall performance through human-machine teaming.

Data Visualization and Synthetic Environments The Army is interested in research that enables improved situational awareness and the visualization and navigation of large data sets to enhance operational activities and training and readiness.

Assured Position, Navigation, and Timing (PNT) The Army is interested in research involving novel PNT technologies for many capabilities including autonomous vehicles, communications, and land navigation.

Sensing The Army is interested in developing a detailed understanding of the environments and activities in the areas where it operates. Research is needed in the areas of sensors and associated processing in order to detect people, equipment, weapons, and any other object or action of interest; detect all targets even when obscured; detect based upon, physical, behavioral, cyber or other signatures; sensing methods to detect chemical, biological, radiological, nuclear, and explosive threats.

Communications & Networks It is critical the Army maintain secure, reliable communications for soldiers, vehicles, and at fixed locations even in austere environments. Research is needed in several areas including cyber protection technologies and AI-based approaches to offensive capabilities.

Internet of Things (IoT) The Army needs to better integrate a wide range of capabilities and equipment and capitalize on commercial developments in industrial and human IoT. Research is needed in areas including new machine learning techniques.

Human Performance Technologies that reduce soldiers mental or physical burden and allow them to react faster than their adversaries are needed.

Underpinning Methodologies Methodologies, frameworks, tools, facilities, techniques, and experimentation concepts, which underpin and enable advanced research and development are of interest.

Read the full BAA

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US Army Seeks Artificial Intelligence R&D Whitepapers and Proposals in Support of New Technologies Homeland Security Today - HSToday