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AUSTIN, Texas, March 4, 2020 /PRNewswire/ --CB Insights today named SparkCognition to the fourth annual AI 100 ranking, showcasing the 100 most promising private artificial intelligence companies in the world. This makes SparkCognition one of only two companies to be listed on every AI 100 List since its inauguration in 2017.

"It's been remarkable to see the success of the companies named to the Artificial Intelligence 100 over the last four years. The 2019 AI 100 saw 48 companies go on to raise $4.9B of additional financing and nine got acquired," said CB Insights CEO Anand Sanwal. "It has been gratifying to see that CB Insights' data-driven approach to identifying the top AI companies using patents, customer traction, investor quality, market sizing and more has become so effective at picking the AI winners of tomorrow. We look forward to seeing what the 2020 AI 100 companies will accomplish over the course of this year and beyond."

In addition to disrupting core sectors including healthcare, retail, and finance, the 2020 AI 100 companies are revamping the broader enterprise tech stack. These companies span the globe, from the US, UK, China, Chile, and South Africa, and are supported by more than 600 investors.

"We're very happy to be named to CB Insights' AI 100 List for the fourth time," said Amir Husain, Founder and CEO of SparkCognition. "2019 was a banner year with tremendous value delivery to our clients, a $100M funding round, significant product releases, and seminal advancements in our AI research. And we are poised for an even more fantastic 2020!"

Through an evidence-based approach, the CB Insights research team selected the AI 100 from nearly 5,000 companies based on several factors including patent activity, investor quality, news sentiment analysis, proprietary Mosaic scores, market potential, partnerships, competitive landscape, team strength, and tech novelty. The Mosaic Score, based on CB Insights' algorithm, measures the overall health and growth potential of private companies to help predict a company's momentum.

SparkCognition is a leading industrial artificial intelligence company that builds AI solutions for industrial applications, working with industries including energy, aerospace and aviation, cybersecurity, and more. With a foundation of deep AI expertise and investment in research and advancing the science of artificial intelligence, SparkCognition currently offers four main products: SparkPredict, an analytics solution, Darwin, a data science automation platform, DeepArmor, a cybersecurity platform, and DeepNLP, a natural language processing solution. In October 2019, SparkCognition announced the close of its $100M Series C funding round from investors including March Capital Partners, Temasek, Kerogen Digital Solutions, and Hearst Ventures.

Quick facts on the 2020 AI 100:

About CB InsightsCB Insights helps the world's leading companies accelerate their digital strategy and transformation efforts with data, not opinion. Our Emerging Tech Insights Platform provides companies with actionable insights and tools to discover and manage their response to emerging technology and startups. To learn more, please visit http://www.cbinsights.com.

Contact:CB Insightsawards@cbinsights.com

About SparkCognition:

With award-winning machine learning technology, a multinational footprint, and expert teams focused on defense, IIoT, and finance, SparkCognition builds artificial intelligence systems to advance the most important interests of society. Our customers are trusted with protecting and advancing lives, infrastructure, and financial systems across the globe. They turn to SparkCognition to help them analyze complex data, empower decision-making, and transform human and industrial productivity. SparkCognition offers four main products:DarwinTM, DeepArmor, SparkPredict, and DeepNLPTM. With our leading-edge artificial intelligence platforms, our clients can adapt to a rapidly changing digital landscape and accelerate their business strategies. Learn more about SparkCognition's AI applications and why we've been featured in CNBC's 2017 Disruptor 50, and recognized three years in a row on CB Insights AI 100, by visiting http://www.sparkcognition.com.

Contact:Cara SchwartzkopfSparkCognitioncschwartzkopf@sparkcognition.com512-956-5491

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SparkCognition Named to the 2020 CB Insights AI 100 List of Most Innovative Artificial Intelligence Startups - Star Local Media

- Researchers will utilize Iktos generative modeling AI technology with SRIs SynFini synthetic chemistry platform to discover new compounds against multiple viruses, including the Wuhan coronavirus (COVID-19) -

Iktos, a company specialized in artificial intelligence (AI) for novel drug design and SRI International (SRI), a research center headquartered in Menlo Park, California, today announced that the companies have entered into a collaboration agreement designed to accelerate discovery and development of novel anti-viral therapies. Under the collaboration, Iktos generative modeling technology will be combined with SRIs SynFini, a fully automated end-to-end synthetic chemistry system, to design novel, optimized compounds and accelerate the identification of drug candidates to treat multiple viruses, including influenza and the Wuhan coronavirus (COVID-19).

Iktos AI technology, based on deep generative models, helps bring speed and efficiency to the drug discovery process by automatically designing virtual novel molecules that have all of the desirable characteristics of a novel drug candidate. This tackles one of the key challenges in drug design: rapid and iterative identification of molecules which simultaneously validate multiple bioactive attributes and drug-like criteria for clinical testing.

"Iktos generative AI technology has proven its value and potential to accelerate drug discovery programs in multiple collaborations with renowned pharmaceutical companies. We are eager to apply it to SRIs endonuclease program, and hope our collaboration with SRI can make a difference and speed up the identification of promising new therapeutic option for the treatment of COVID-19," said Yann Gaston-Math, co-founder and CEO of Iktos. "We are excited at the prospect of combining our automated compound design technology with SRIs SynFini platform and the potential this has to further accelerate drug discovery."

SRIs SynFini platform is designed to accelerate chemical discovery and development, and thereby bring new drugs to the clinic more quickly and affordably. The closed loop SynFini platform automates the design, reaction screening and optimization (RSO), and production of target molecules. SynFini comprises three components that work seamlessly together: a software platform (SynRoute), a reaction screening platform (SynJet), and a multi-step flow chemistry automation and development platform (AutoSyn).

SRI has an ongoing program focused on discovering drugs to block endonuclease enzymes that are common to many viruses. These enzymes are involved in viral replication and blocking of host resistance to infection. Sequence analysis of COVID-19 indicates that this virus has an endonuclease that it is genetically about 97 percent similar to the SARS virus. Recent studies show that blocking the SARS virus endonuclease inhibits the infections pathogenesis, leading to a 100 percent survival rate in preclinical models. This suggests that the COVID-19 endonuclease is a good therapeutic target.

"The SynFini system has the potential to dramatically expedite small molecule drug discovery," said Nathan Collins, Ph.D., Chief Strategy Officer of SRIs Biosciences Division and Head of the SynFini program. "We look forward to exploring how the integration of Iktos AI-driven generative molecule combined with SynFini supports the rapid and efficient discovery of new drugs to treat emerging infectious diseases."

By combining platforms for the accelerated molecular design and automated production of target molecules with established high-throughput biology, Iktos and SRI hope to demonstrate a new paradigm in extremely rapid drug discovery against high-value pharmaceutical targets.

About Iktos

Incorporated in October 2016, Iktos is a French start-up company specialized in the development of artificial intelligence solutions applied to chemical research, more specifically medicinal chemistry and new drug design. Iktos is developing a proprietary and innovative solution based on deep learning generative models, which enables, using existing data, to design molecules that are optimized in silico to meet all the success criteria of a small molecule discovery project. The use of Iktos technology enables major productivity gains in upstream pharmaceutical R&D. Iktos offers its technology both as professional services and as a SaaS software platform, Makya. Iktos is also developing Spaya, a synthesis planning software based upon Iktoss proprietary AI technology for retrosynthesis.

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About SRI International

SRI International, a non-profit research institute founded in 1946 and headquartered in Menlo Park, California, creates world-changing solutions to make people safer, healthier, and more productive. SRI Biosciences, a division of SRI International, integrates basic biomedical research with drug and diagnostics discovery, and preclinical and clinical development. SRI Biosciences has produced several marketed drugs and advanced more than 100 drugs to clinical trials. The division is focused on novel platforms and programs in a variety of therapeutic areas targeting high unmet medical needs. SRI Biosciences collaborates with a broad range of partners from small and virtual biotechnology companies to top 10 pharmaceutical companies and other leading industry partners. More information is available at http://www.sri.com.

View source version on businesswire.com: https://www.businesswire.com/news/home/20200303005770/en/

Contacts

For Iktos Yann Gaston-Math, CEOcontact@iktos.com +33 6 30 07 99 26

For SRI Melissa Wagner, Business Developmentmelissa.wagner@sri.com +1 650 859 3505

Michele Parisi, Mediamparisi@forwardhealthinc.com +1 925 864 5028

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Iktos and SRI International Announce Collaboration to Combine Artificial Intelligence and Novel Automated Discovery Platform for Accelerated...

By Louise Lamatsch, Policy Assistant, EPHA

Artificial Intelligence (AI) and other emerging digital technologies have the potential to build up public health capacity to deliver equitable solutions by improving screening, diagnosis, and treatments across many medical disciplines. In addition, AI can generate productivity gains and improve operational efficiency by providing more precise and complete information, better workflow management and refine continuity of care. However, these technologies are still in their infancy. Their increased use within society and the healthcare sector require sufficient safeguards and guidelines to minimize the risk of harm these technologies may cause to individuals.

Future research will need to set the focus even more on the vulnerability and liability gaps in AI as well as on the adjustments that need to be made in the already existing EU legislation, such as the Product Liability Directive. Concerning already existing liability regimes regarding digital technologies, the law of tort of EU Member states is largely non- harmonised, except for the Product Liability Law under Directive 85/374/ EC, liability for infringing Data Protection Law under Article 82 of the General Data Protection Regulation (GDPR) and liability for infringing Competition Law under the directive 2014/ 104/ EU. Thus on National level, it can be observed that laws of the Member States do not contain liability rules specifically applicable to damage resulting from the use of emerging digital technologies such as Artificial Intelligence. Adequate and complete liability regimes in the development of technological challenges are crucially important for society to ensure that damage or harm caused by emerging digital technologies do not lead to victims ending up totally or partially uncompensated.

As discussed at the recent workshop on Civil Liability Regime for Artificial Intelligence in the European Parliament, organized by the S&D group and hosted by MEP Tiemo Wlken (Germany), the following key suggestions (among many others) could be included in future discussions and research regarding the adjustments that need to be made on existing EU liability regimes:

AI is a difficult and complex system, which needs better understanding, building up health literacy, and research. Most importantly, the existing liability laws do not necessarily have to be reinvented but they will require modification and adjustment. . The EU should, therefore, try to find a balanced solution based on a harmonized and human-centred approach on AI to ensure civil protection and a fair and safe environment. In the health sector existing laws should be specifically adapted in the field of health and safety at workplace. AI may not only affect the employment area and wages but also the way workers approach their work and this could have an impact on their well-being such as job satisfaction, stress and health in a variety of ways. AI is therefore not only related to potential physical harm but also mental harm. The integration of Big Data and AI technologies into health systems must be accompanied by appropriate legislation, rules and standards that protect the fundamental rights of individuals and address new ethical challenges. Emerging technologies is an area, which still needs much discussion and research before we have a well-performing digital and AI- friendly European Union.

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Why we need to adapt existing EU laws to Artificial Intelligence - European Public Health Alliance

To the untrained eye, zebras in Kenya probably all look alike. But each animals black and white markings are like a fingerprint, distinct and invaluable for scientists who need to track the animals and information about them, including their births, deaths, health and migration patterns.

Traditionally, getting this kind of information has been an invasive and labor-intensive process. But breakthroughs in artificial intelligence (AI) and crowdsourcing of photos of individual animals are beginning to change the conservation game.

Portland, Oregon-based nonprofit Wild Me has developed AI to pick out identifying markers the stripes on a zebra, the spots on a giraffe, the contours of a sperm whales fin and catalog animals much faster than a human can. Photo surveys are increasingly used as the backbone for population estimates, and Wild Mes Wildbooks, which catalog various species, are giving conservation groups, governments and citizen scientists a faster way to monitor animals around the world.

We can use this information to track diseases and poaching threats, look at manifestations of diseases, said Michael Brown, a conservation science fellow at the Giraffe Conservation Foundation and the Smithsonian Conservation Biology Institute, who has been working with Wild Me for the past few years. It lets us piece together an understanding of how these threats to giraffes are spatially situated (and) how the giraffes are utilizing different landscapes over time.

Founder Jason Holmberg launched the first iteration of Wild Me in 2003 after swimming with whale sharks off the coast of Djibouti. He wanted to find a different way to track the animals other than invasive tagging, so he teamed up with a biologist and a NASA astronomer, adapting the algorithm for the Hubble telescope to match the sharks spot patterns.

For years, Holmbergs endeavors were a side project he didnt leave his full-time job in tech until recently. Wild Mes work gradually expanded, then it really kicked into gear with a 2018 grant from Microsofts AI for Earth. Today, Wild Me has a team of six full-time staffers, with plans to add more soon.

Wild Mes process of creating and training algorithms takes serious time. Thousands of photos of the species must be manually annotated so that the algorithm learns what a given animal is, what the distinguishing characteristics are and whats just background noise.

The model relies largely on photographs taken by scientists or everyday people who upload their photos to the corresponding Wildbook. It uses AI to find things in the picture and then hand it to algorithms or machine learning to suggest IDs which whale, which giraffe, etc., Holmberg said.

Christin Khan conducts aerial surveys of North Atlantic right whales for the National Oceanic and Atmospheric Administration and had sought an AI-based solution for years. She said she watched Facebook implement facial recognition and wanted to use similar technology to help identify whales within the endangered species (there are only about 400 North Atlantic right whales left).

We needed a really simple, user-friendly web-based interface where a biologist who knows nothing about AI could upload a photograph and get a result back, she said. Eventually we realized the developers at Wild Me had already done a lot of what we needed, and it wouldnt require us to reinvent the wheel.

The Wildbook for whales, called Flukebook, encourages collaboration, which is particularly useful for whales that travel long distances because it can be difficult for one research group to effectively monitor one area.

The more people on the water, the more photos, the more its decentralized, (the better), said Shane Gero, who founded and runs the Dominica Sperm Whale Project. By doing the matching themselves, by contributing their own data, not only do they get to know the animals, but it creates a locally motivated community of people that can react when conservation actions come up.

Before the introduction of AI, Gero said it would take about a month to process a months worth of photos.

(Now), we have our numbers of individuals sighted and population estimates faster, so we can report (almost) in real time, he said.

That means his group is able to provide the government of Dominica with more up-to-date information and offer better advice on how to shape conservation efforts.

One of Wild Mes more recent innovations is an AI-driven feature that datamines YouTube videos of whale sharks and sea turtles, using user-generated videos (often taken by tourists) to get a better sense of the populations. This has been a great way to increase the amount of photos coming in and provide researchers with more data. But it also creates even more work for people on the ground, who have to manually check the AIs suggestions and accept the results.

Were flooding the whale shark community with more data than it can handle, said Holmberg.

So Wild Me is now building the capacity to automate the identification process and scaling the tech that combs social media for relevant videos.

The nonprofit recently received a two-year grant from the Gordon and Betty Moore Foundation to develop the new algorithm that will make the animal IDs on its own.

Its focusing the initial work on zebras because it already has an incredibly rich dataset. Every two years since 2016, the Great Grvys Rally in Kenya has used hundreds of citizen scientists spread out over thousands of kilometers to photograph Grvys zebras over two days. Wild Mes AI analyzes the zebra markings on all the photos to come up with a total population, which the Kenyan government treats as the official census for Grvys zebras.

This type of work is a huge upgrade from the traditional capture-mark-recapture process, which is both invasive and time consuming, with studies done every five to 10 years.

You can only make very coarse-grained conservation decisions, Holmberg said. The point of going to a fully automated system is to shorten that cycle so we can take all of the data over the past week or two weeks and have a continuous prediction of population size. Its fine-grained, which helps researchers understand and lobby for better conservation activities.

For Khan, meanwhile, the existing technology is still in its early days. The algorithm for North Atlantic right whales became operational in November 2019, and she said theyre still working out the kinks and figuring out how best to use it. But, she said, she sees the incredible potential that it holds.

My dream is that we get to the point where the worlds oceans will be trolled by satellite photos and we can understand the worlds whale population, she said. Combining AI with satellite imagery and drones we have the potential to exponentially understand the worlds oceans thats just not possible with manned aircraft.

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How a Portland nonprofit is using artificial intelligence to help save whales, giraffes, zebras - Seattle Times

With AI and the resultant technology up-gradation in industry, organizations need to plan for the tech-driven future.

To take optimum advantage of the disruptive technologies that AI brings in, a few businesses may need to make dramatic adjustments in their company culture and the way they work. Right now, for some businesses, AI and big data are merely perceived as something that can cut operational expenses, instead of it being a crucial methodology for creating increased profit, output, and improved assurance of business success. The C-suite cannot overlook AI and big data convergence as it is needed to consolidate the business ability and critical insights.

Data Centers Embarking On the Cloud Migration Journey

The rapid progress of data platforms has seen advanced analytical models being used to display complex business scenarios for operations, planning, investment, and innovation. While technological capabilities are readily available everywhere, what makes the real impact is how they are deployed to make progress.

The increasing demand for cloud and data analytics capacities encourages experimentation. It helps in ad hoc utilization to deliver quick outcomes knowing the abilities and associated dangers of having individuals with experience and knowledge. For pivotal business assignments, AI may not be granted decision-making capabilities. But, its capacity to give reliable, accurate data is as of now prompting compelling insights that change business operations entirely.

AIs automation abilities imply it to be progressively utilized to streamline unremarkable tasks, freeing up resources to focus on high-level activities. This can add to process efficiencies by improving profitability and bringing down operating expenses.

As AI gets enriched from new data inputs, it will turn out to be progressively ground-breaking and ready to simplify complex tasks and algorithms. It will further create growth opportunities for collaboration and increased efficiency. ML is helping AI applications to comprehend a more extensive scope of guidelines better, clarify the context by understanding the need better.

While the pace of technological change is uncertain, one thing is sure. It will continue to gather pace, driving innovative systems, new processes and efficiencies, delivering new solutions and products. The ability to recognize and fuse the best solution for business growth, and at the right time to increase advantage, is a significant challenge.

Firms must guarantee a well-structured architecture framework that empowers CIOs to respond with the required flexibility to join the new and replace the old. As AI applications are becoming progressively intricate and more ingrained in daily life, there will be an increased requirement for people to clarify the discoveries and decisions by a machine.

5G Enterprise Adoption- Security is Still a Major Concern

Supervision of AI applications will be crucial to ensure that undesirable results, for instance, discrimination, are recognized and prevented. Regardless of how perfect AI becomes, it will always require human intelligence and guidance to discover innovative solutions to satisfy its intended function.

Even though AI offers immense opportunities for improvement and innovation, it cant achieve its full potential on its own. A community future will see engineers, programmers, data scientists, workers, and everyday consumers completely integrating AI into their daily lives.

Read more from the original source:
Artificial Intelligence Infused with Big Data Creating a Tech-driven World - EnterpriseTalk