DUBLIN--(BUSINESS WIRE)--The "Digital Transformation 2021: 5G, AI, Big Data Analytics, Blockchain, Cloud and Mobile Edge Computing, Connected and Wearable Devices, Cybersecurity, Digital Twins, Identity Management, IoT, Robotics, Smart Cities, Teleoperation and Virtual Reality" report has been added to ResearchAndMarkets.com's offering.

This research evaluates key technologies involved in digital transformation including 5G, AI, Big Data Analytics, Blockchain, Cloud and Mobile Edge Computing, Connected and Wearable Devices, Cybersecurity, Digital Twins and Teleoperation, IoT, Robotics, Smart Cities, and Virtual Reality solutions. These technologies will all be germane to the evolution of many areas important to enterprise and industrial organizations including internal and external processes, products and services, virtualization, OSS/BSS, and more.

This is the most comprehensive research available anywhere that evaluates each of these technologies and assesses their convergence and integration opportunities. The research provides a wide-ranging view into the ecosystem including companies, strategies, and solutions for each technical domain as well as cross-domain implementation and operations. It provides detailed forecasts by application and service, use case, and industry vertical.

The enterprise and industrial sectors are rapidly digitizing their products and services including software-controlled and virtualized infrastructure as well as leveraging next-generation connectivity, signaling, and automated decision-making algorithms. This will have a profound effect on both overall strategic positioning and day-to-day tactical operations. New technologies and tools are being rapidly integrated into production and service systems, which are facilitating the transformation of processes, creating new business opportunities, and enabling an overall smarter workplace for humans and machines alike.

Telecom infrastructure and services providers are also undergoing a massive transformation. For example, the combination of 5G and edge computing will transform wireless carrier operations and facilitate enhanced services, new applications, and completely new business models for mobile network operators. In addition, software-defined control and infrastructure virtualization are poised to transform network and service architecture thanks to improvements in technologies that offer improved performance and lower costs. As the border between cloud computing and network infrastructure continues to blur, so does the demarcation between the network as a whole and those network elements (servers, terminals, etc.) that comprise the network.

Artificial Intelligence (AI) algorithms enhance the ability of big data analytics and IoT platforms to provide value to each of these market segments. The combination of AI and the Internet of Things (IoT) has the potential to dramatically accelerate the benefits of digital transformation for consumer, enterprise, industrial, and government market segments. The author sees the Artificial Intelligence of Things (AIoT) as transformational for both technologies as AI adds value to IoT through machine learning and decision-making and IoT adds value to AI through connectivity and data exchange.

AIoT solutions dramatically accelerate the benefits of digital transformation for consumer, enterprise, industrial, and government market segments. The use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective smart city solutions in terms of decision-making. 5G provides substantial bandwidth were needed as well as significantly lower latency for next-generation applications and services such as virtual reality-controlled teleoperation and other enhanced user interfaces.

The publisher sees smart cities providing significant opportunities for technology integration in support of highly customized, yet scalable services. There will be a positive feedback loop created and sustained by leveraging the interdependent capabilities of AI, IoT, and 5G (AIoT 5G). For example, AI will work in conjunction with IoT to substantially improve smart city supply chains. Metropolitan area supply chains represent complex systems of organizations, people, activities, information, and resources involved in moving a product or service from supplier to customer.

The Industrial IoT (IIoT) market is much more than the sum of its parts, but its parts alone can be daunting, especially considering how emerging technologies such as Artificial Intelligence (AI), robotics, and modified reality are being rapidly integrated into industrial processes. AI alone is anticipated to dramatically reduce costs and improve processes as well as facilitate completely new products and services that improve production, quality, and the producer-supplier relationship.

Some of the Companies Mentioned include:

For more information about this report visit https://www.researchandmarkets.com/r/qhrslh

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Digital Transformation 2021: 5G Technology and Solutions for IoT, Artificial Intelligence in Big Data Analytics and IoT, Digital Twins Market Sizing...

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence (AI) in Drug Discovery Market: Global Industry Analysis, Trends, Market Size, and Forecasts up to 2027" report has been added to ResearchAndMarkets.com's offering.

The report predicts the global artificial intelligence (AI) in drug discovery market to grow with a CAGR of 30.2% over the forecast period from 2021-2027.

The report on the global artificial intelligence (AI) in drug discovery market provides qualitative and quantitative analysis for the period from 2019 to 2027. The study on artificial intelligence (AI) in drug discovery market covers the analysis of the leading geographies such as North America, Europe, Asia-Pacific, and RoW for the period of 2019 to 2027.

The report on artificial intelligence (AI) in drug discovery market is a comprehensive study and presentation of drivers, restraints, opportunities, demand factors, market size, forecasts, and trends in the global artificial intelligence (AI) in drug discovery market over the period of 2019 to 2027. Moreover, the report is a collective presentation of primary and secondary research findings.

Porter's five forces model in the report provides insights into the competitive rivalry, supplier and buyer positions in the market and opportunities for the new entrants in the global artificial intelligence (AI) in drug discovery market over the period of 2019 to 2027. Further, Growth Matrix gave in the report brings an insight into the investment areas that existing or new market players can consider.

Report Findings

1) Drivers

2) Restraints

3) Opportunities

Company Profiles

Key Topics Covered:

1. Preface

1.1. Report Description

1.2. Research Methods

1.3. Research Approaches

2. Executive Summary

2.1. Artificial Intelligence (AI) in Drug Discovery Market Highlights

2.2. Artificial Intelligence (AI) in Drug Discovery Market Projection

2.3. Artificial Intelligence (AI) in Drug Discovery Market Regional Highlights

3. Global Artificial Intelligence (AI) in Drug Discovery Market Overview

3.1. Introduction

3.2. Market Dynamics

3.2.1. Drivers

3.2.2. Restraints

3.2.3. Opportunities

3.3. Analysis of COVID-19 impact on the Artificial Intelligence (AI) in Drug Discovery Market

3.4. Porter's Five Forces Analysis

3.5. Growth Matrix Analysis

3.6. Value Chain Analysis of Artificial Intelligence (AI) in Drug Discovery Market

4. Artificial Intelligence (AI) in Drug Discovery Market Macro Indicator Analysis

5. Global Artificial Intelligence (AI) in Drug Discovery Market by Offering

5.1. Software

5.2. Services

6. Global Artificial Intelligence (AI) in Drug Discovery Market by Technology

6.1. Machine Learning

6.2. Natural Language Processing (NLP)

6.3. Computer Vision

6.4. Others

7. Global Artificial Intelligence (AI) in Drug Discovery Market by Application

7.1. Target Identification

7.2. Molecule Screening

7.3. Drug Design and Drug Optimization

7.4. Preclinical and Clinical Testing

7.5. Others

8. Global Artificial Intelligence (AI) in Drug Discovery Market by Indication

8.1. Oncology

8.2. Neurodegenerative Diseases

8.3. Infectious Disease

8.4. Others

9. Global Artificial Intelligence (AI) in Drug Discovery Market by End User

9.1. Pharmaceutical & BIoTechnology Companies

9.2. Contract Research Organizations

9.3. Academic & Government Research Institutes

10. Global Artificial Intelligence (AI) in Drug Discovery Market by Region 2021-2027

10.1. North America

10.1.1. North America Artificial Intelligence (AI) in Drug Discovery Market by Offering

10.1.2. North America Artificial Intelligence (AI) in Drug Discovery Market by Technology

10.1.3. North America Artificial Intelligence (AI) in Drug Discovery Market by Application

10.1.4. North America Artificial Intelligence (AI) in Drug Discovery Market by Indication

10.1.5. North America Artificial Intelligence (AI) in Drug Discovery Market by End User

10.1.6. North America Artificial Intelligence (AI) in Drug Discovery Market by Country

10.2. Europe

10.3. Asia-Pacific

10.4. RoW

11. Company Profiles and Competitive Landscape

11.1. Competitive Landscape in the Global Artificial Intelligence (AI) in Drug Discovery Market

11.2. Companies Profiles

For more information about this report visit https://www.researchandmarkets.com/r/s67gr3

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Artificial Intelligence (AI) in Drug Discovery Markets - Global Industry Analysis, Trends, Market Size, and Forecasts to 2027 - ResearchAndMarkets.com...

The Athens Roundtable on AI and the Rule of Law

The third edition of the Athens Roundtable on Artificial Intelligence and the Rule of Law will take place online on 6 and 7 December 2021.

The event is organised by the Future Society and ELONTech under the Patronage of the President of the Hellenic Republic, Katerina Sakellaropoulou and is co-hosted by UNESCO, the Council of Europe, the European Parliaments Panel on the Future of Science and Technology (STOA), h IEEE SA, the Center on Civil Justice at the NYU School of Law and the National Judicial College, among other prominent institutions.

The roundtable is designed to facilitate a participatory dialogue among key stakeholders on international AI policy developments and key AI standardisation and benchmarking initiatives in the US, Europe and beyond.

It will also address important issues at the intersection of AI, industry, government and law, including civil liability regimes, regulatory compliance, privacy and consumer protection, and judicial capacity building.

The Secretary General of the Council of Europe, Marija Pejinovi Buri, will deliver welcome remarks at the opening. The Director of Information Society Action against Crime, Jan Kleijssen, will speak in the panel EU AI Act and Beyond: Regulatory Perspectives from Europe and the United States. The Head of Information Society Department, Patrick Penninckx, will participate in the panel on AI and Human Rights.

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Council of Europe to participate in the Athens Roundtable on Artificial Intelligence and the Rule of Law - Council of Europe

Machine Learning, Artificial Intelligence and Blockchain are Revolutionizing the Legal Industry

Blockchain, machine learning, and artificial intelligence are revolutionizing the legal industry.

Digital transformation in the legal industry has been slow, but as benefits are becoming more obvious, legal firms are adopting digital technologies to improve their services.

Since privacy is of utmost importance in this field, the use of technology has not yet extensively pervaded, due to gradual and cautious implementation. However, digitization, although initially slow to catch on in the legal industry, is seeing a steady increase in its adoption. The digital transformation in the legal industry is already proving to be highly beneficial and is promising even greater benefits once fully realized. Digital technology promises not only smoother legal processes for clients and lawyers, but also improved decision-making for judges and lawmakers.

A majority of a lawyers time, while working on a case, is scouring through pages of data to find relevant information. Although the right information is necessary for succeeding in trials, spending hours just to find a line of supporting evidence or law can be highly wasteful for lawyers and legal firms, as they can be better spent preparing for cases. Digitization in the legal industry has led to the introduction of technologies like AI and machine learning, which excel at scrutinizing massive amounts of data at high speeds. Machine learning, which can be trained to make sense of unstructured data such as text from various online and offline sources, can help lawyers and paralegals find key facts and information from legal texts and historical data.Machine learning is transforming legal servicesby saving time and manual effort for lawyers, which can be invested in more vital activities.

Digitization can minimize the need for trials in minor non-criminal cases, such as vehicle parking tickets. Applications have been developed using technologies likeAI to help civilians contest parking ticketsby determining whether the parking infraction is justified or not. This application has not only saved time and money for people but has also minimized the workload on legal courts, which can spend more time contemplating challenging cases that have grave consequences. AI can also be potentially applied in chatbots that provide people legal advice on simple and straightforward matters and can also guide them through legal processes. Use of AI chatbots in clearing basic customer queries can free up more time for law professionals working in legal firms and enable law firms to utilize their skills in more productive activities.

The digital technology that can have the greatest impact on the legal industry is blockchain. Blockchains ability to record information in an immutable, highly reliable manner can help legal processes and in many cases can also eliminate the need for litigation. This can be especially helpful in preventing cases involving finance and asset management. Blockchain can not only be used to record financial transactions but also to maintain ownership records for various assets such as real estate. Having a transparent and secure database of transactions and asset ownership eliminates the possibility of illegal transfer and accumulation of wealth, preventing financial crimes. Blockchains ability to execute smart contracts can also be highly valuable for the legal industry, as it ensures that there is no room for foul play and non-compliance.

The digital transformation in the legal industry, especially through technology like blockchain can potentially bring about revolutionary changes in the field. All stakeholders in the legal industry such as civilians, law professionals and firms, and judicial bodies should actively embrace and be a part of this change, as it can make life much better for everyone.

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Machine Learning, Artificial Intelligence and Blockchain are Revolutionizing the Legal Industry - BBN Times

In the world of science fiction, beyond its stories and created artifacts, the central point of everything that at the same time manages to catch the publics attention, is that there is a certain possibility that what is raised in the story becomes real taking into account counts its scientific bases. Although it seems like a young genre for its futuristic vision, it is actually something that has been around since the beginning of cinema.

Keep reading: REVIEW | King Richard: A Winning Family | Success, sacrifice and controversy on the court

One of the most significant films in this regard is Metropolis 99% from 1927 directed by Fritz Lang, also one of the most representative of German expressionism. But in all these stories in which a future enveloped by technology is proposed, represented above all by the presence of robots, there is the moral line that carries either the protagonist or the villain. Some of the approaches in this class of stories have not emerged as such for example, flying cars as a means of daily transport but others have surprised with their proximity.

Such is the case of I, Robot 58%, one of the most popular films starring Will Smith after Men in Black 92%. This story based on a series of stories under the same name published by Isaac Asimov in 1950, had an important reception by the audience. However, these humanoids were raised as a support for the human being and, as the minutes pass, their intentions become darker in an idea of the rebellion of the machines.

In recent days, this film has become a trend on social networks, and not because they wanted to gladly remember one of Smiths greatest successes, but because that fiction is taking shape or, it is already made in its entirety in the real life. Over the course of last week, news broke that the Engineered Arts company has created a new robot that looks identical to Sonny from the movie.

Continue with: Bel-Air, reboot of The Prince of Bel-Air, presents teaser trailer

The objective of the leading company in the design and manufacture of androids is to support large businessmen by having these machines as personal assistants, information modules, or receptionists so that the clients work is more fluid, especially if it receives many people. Engineered Arts already has several assistant robot models such as Mesmer, Quinn and RoboThespian, each with special abilities such as research or even acting.

Its new product is called Ameca, and its peculiarity is that it already has human facial expressions and quite natural movements, in addition to having the ability to learn autonomously. Its certainly a breakthrough for technology, but for moviegoers who remember in detail I robot its not that good and anyone would think were close to a rebellion.

It may interest you: Will Smith admits hes responsible for his sons bad reputation

See below what is being said in networks regarding the Alex Proyas film becoming a reality.

No. Shut up for the fucking time. NOW.

This is Sunny from Yo, Robot. He will be talking about dreams in a few years.

Friendly reminder that the movie Me, Robot was set in 2025. Were doing pretty well.

Yo, Robot takes place in 2035. We have another 13 years. Will Smith will be too old and Jada will have taken the last shred of confidence from the man. Guys, were screwed.

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Yo, Robot is trending for Ameca, an android with artificial intelligence and facial expressions - Central Valley Business Journal

Artificial intelligence technologies have reached impressive levels of adoption, and are seen as a competitive differentiator. But there comes a point when technology becomes so ubiquitous that it is no longer a competitive differentiator -- think of the cloud. Going forward, those organizations succeeding with AI, then, will be those that apply human innovation and business sense to their AI foundations.

Such is the challenge identified in astudy released by RELX, which finds the use of AI technologies, at least in the United States, has reached 81% of enterprises, up 33 percentage points from 48% since a previous RELX survey in 2018. They're also bullish on AI delivering the goods -- 93% report that AI makes their business more competitive. This ubiquity may be the reason 95% are also reporting that finding the skills to build out their AI systems is a challenge. Plus, these systems could be potentially flawed: 75% worry that AI systems may potentially introduce the risk of bias in the workplace, and 65% admit their systems are biased.

So there's still much work to be done. It comes down to the people that can make AI happen, and make it as fair and accurate as possible.

"While many AI and machine learning deployments fail, in most cases, it's less of a problem with the actual technology and more about the environment around it," says Harish Doddi, CEO of Datatron. Moving to AI "requires the right skills, resources,andsystems."

It takes a well-developed understanding of AI and ML to deliver visible benefits to the business. While AI and ML have been around for many years, "we are still barely scratching the surface of uncovering their true capabilities," says Usman Shuja, general manager of connected buildings for Honeywell. "That said, there are many valuable lessons to be gleaned from others' missteps. While it's arguably true that AI can add significant value to practically any department across any business, one of the biggest mistakes a business can make is to implement AI for the sake of implementing AI, without a clear understanding of the business value they hope to achieve."

In addition, AI requires adroit change management, Shuja continues. "You can install the most cutting-edge AI solutions available, but if your employees can't or won't change their behaviors to adapt to a new way of doing things, you will see no value."

Another challenge is bias, as expressed by many executives in the RELX survey. "Algorithms can easily become biased based on the people who write them and the data they are providing, and bias can happen more with ML as it can be built in the base code," says Shuja. "While large amounts of data can ensure accuracy, it's virtually impossible to have enough data to mimic real-world use cases."

For example, he illustrates, "if I was looking into recruiting collegiate athletes for my professional lacrosse team, and I discovered that most of the players I am hearing about are Texas Longhorns, that might lead me to conclude that the best lacrosse players attend the University of Texas. However, this could just be because the algorithm has received too much data from one university, thus creating a bias."

The way the data is set up and who sets it up "can inadvertently sneak bias into the algorithms," Shuja says. "Companies that are not yet thinking through these implications need to put this to the forefront of their AI and ML technology efforts to build integrity into their solutions."

Another issue is that AI and ML models simply become outdated too soon, as many companies found out, and continue to find out as a result of Covid and supply chain issues. "Having good documentation that shows the model lifecyclehelps, butit'sstill insufficient when models become unreliable," says Doddi, "AI model governance helps bring accountability and traceability to machine learning models by having practitioners ask questions such as 'What were the previous versions like?' and 'What input variables are coming into the model?''" Governance is key. During development,Doddi explains, "MLmodels are bound by certain assumptions, rules, and expectations. Once deployed into production, the results can differ significantly from results in development environments.This is where governance is critical once a model is operationalized.There needs to be a way to keep track of various models and versions."

In some cases with AI, "less is more," says Shuja. "AI tends to be most successful when it is paired with mature, well-formatted data. This is mostly within the realm of IT/enterprise data, such as CRM, ERP, and marketing. However, when we move into areas where the data is less cohesive, such as with operational technology data, this is where achieving AI success becomes a bit more challenging. There is a tremendous need for scalable AI within an industrial environment, for example using AI to reduce energy consumption in a building or industrial plant -- an area of great potential for AI. One day soon, entire businesses -- from the factory floor to the board room -- will be connected; constantly learning and improving from the data it is processing. This will be the next major milestone for AI in the enterprise."

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Artificial intelligence: Everyone wants it, but not everyone is ready - ZDNet

138 new HD cameras installed in 2021 and 487 cameras are now in operation: 46 with AI test software

Eyes in the sky across most of High Fire-Threat Districts in Northern and Central California improve situational awareness and intelligence

SAN FRANCISCO, November 18, 2021--(BUSINESS WIRE)--During extremely dry, hot, and windy weather, being able to differentiate wildfire smoke from fog and other false indicators is invaluable to analysts in Pacific Gas and Electric Companys (PG&E) Wildfire Safety Operations Center and fire agencies. Thats why PG&E is testing artificial intelligence (AI) and machine-learning capabilities in the growing network of high-definition cameras across Northern and Central California to see how it can enhance fire-watch and response capabilities.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20211118006094/en/

HD smoke-spotting cameras on top of Mount Tamalpais are included in PG&Es artificial intelligence pilot program. (Photo: Business Wire)

This year, PG&E, in collaboration with ALERTWildfire, has installed 138 new HD cameras across High Fire-Threat Districts, in accordance with its 2021 Wildfire Mitigation Plan. Of those 138 cameras, 46 of them are included in the new AI testing program in partnership with Alchera and ALERTWildfire. A similar pilot was conducted with Pano through participation in EPRIs 2021 Incubatenergy Labs Challenge. PG&E began installing HD cameras in 2018, as part of its Community Wildfire Safety Program. As of October 31, 487 cameras are now in operation.

"Even with the two significant rainstorms in October and November, we are still in a historic drought and California, along with other western states, continue to experience an increase in wildfire risk and a longer wildfire season. We are using every new tool and technology at our disposal to improve situational awareness and intelligence to help mitigate and prevent wildfires, including this new AI capability," said Sumeet Singh, PG&E Chief Risk Officer. "Every bit of data and intelligence that comes to us could potentially save a life."

Story continues

The pilot program is already demonstrating the AIs potential to reduce fire size expansion. On August 4, 2021, PG&Es Howell Mountain 1 camera located in Placer County and equipped with Alcheras AI software, spotted smoke one minute before the actual fire dispatch and several minutes sooner than the manual movement of the camera. That smoke ended up becoming the River Fire. This is one example of many noted during both pilots confirming the value of early fire detection technology.

The expert staff in the companys Wildfire Safety Operations Center (WSOC), outside agencies and first responders use the fire-watch cameras to monitor, detect, assess for threats, and respond to wildfires. The AI test programs include PG&E determining a way to get the new data to the right people quickly and effectively. The quicker the data is received, the more rapidly first responders and PG&E can confirm fires and move the right resources to the right place.

"The software analyzes the video feed and if it thinks it sees smoke, we receive an alert via email and text, telling us it just detected smoke. Our analysts then pinpoint where the smoke is coming from and determine if its a car fire, dumpster fire, or even a vegetation fire. Based on the location, we can assess for threat to the public or PG&E facilities," said Eric Sutphin, Supervisor at PG&Es WSOC whos in charge of the camera installations. "The AI filters out a significant number of false positives, for example, ruling out dust, fog or haze."

Sutphin explained that the recent installation of the AI test software with its machine-learning capabilities means the WSOC team is getting smarter over time with more experience and more data gathered.

"We know the cameras are doing well at spotting wisps of smoke from long distances. We plan to assess our initial implementation, continue to gather the data, and develop a plan for using this leading-edge technology on a more expanded basis," he said.

The cameras provide 360-degree views with pan, tilt and zoom capabilities and can be viewed by anyone through the ALERTWildfire Network at http://www.alertwildfire.org. By the end of 2022, the company plans to have approximately 600 cameras installed, providing an ability to see in real-time more than 90% of the high fire-risk areas it serves.

About PG&E

Pacific Gas and Electric Company, a subsidiary of PG&E Corporation (NYSE:PCG), is a combined natural gas and electric utility serving more than 16 million people across 70,000 square miles in Northern and Central California. For more information, visit http://www.pge.com/ and http://www.pge.com/about/newsroom/.

View source version on businesswire.com: https://www.businesswire.com/news/home/20211118006094/en/

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PG&E Testing Artificial Intelligence Which Could Expand Wildfire Detection Capabilities to Growing Network of High-Definition Cameras - Yahoo Finance

Sanofi invests $180 million equity in Owkins artificial intelligence and federated learning to advance oncology pipeline

PARIS November 18, 2021 Sanofi announced today an equity investment of $180 million and a new strategic collaboration with Owkin comprised of discovery and development programmes in four exclusive types of cancer, witha total payment of $90 million for three years plus additional research milestone-based payments. Owkin, an artificial intelligence (AI) and precision medicine company, builds best-in-class predictive biomedical AI models and robust data sets. With the ambition to optimize clinical trial design and detect predictive biomarkers for diseases and treatment outcomes, this collaboration will support Sanofis growing oncology portfolio in core areas such as lung cancer, breast cancer and multiple myeloma.

To accelerate medical research with AI in a privacy-preserving way, Owkin has assembled a global research network powered by federated learning, which allows data scientists to securely connect to decentralized, multi-party data sets and train AI models without having to pool data. This approach will complement Sanofis emerging strength in oncology, as the companys scientists apply cutting-edge technology platforms to design potentially life-transforming medicines for cancer patients worldwide.

"Owkins unique methodology, which applies AI on patient data from partnerships with multiple academic medical centers, supports our ambition to leverage data in innovative ways in R&D, said Arnaud Robert, Executive Vice President, Chief Digital Officer, Sanofi. We are striving to advance precision medicine to the next level and to discover innovative treatment methods with the greatest benefits for patients.

Sanofi will leverage the comprehensive Owkin Platform, in order to find new biomarkers and therapeutic targets, building prognostic models, and predicting response to treatment from multimodal patient data. Sanofis investment will support Owkins development and goal to grow the worlds leading histology and genomic cancer database from top oncology centers.

Owkins mission is to improve patients lives by using our platform to discover and develop the right treatment for every patient, said Thomas Clozel, M.D., Co-Founder and CEO at Owkin. We believe that the future of precision medicine lies in technologies that can unlock insights from the vast amount of patient data in hospitals and research centers in a privacy-preserving and secure way. This landmark partnership with Sanofi will see federated learning used to create research collaborations at a truly unprecedented scale. The future of AI to transform how we develop treatments is incredibly bright, and we are proud to partner with Sanofi on this mission.

This collaboration agreement will allow Sanofi to work closely with Owkin in identifying new oncology treatments across four cancers.

We look forward to working with our colleagues at Owkin to analyze data from hundreds of thousands of patients, said John Reed, M.D., Ph.D., Global Head of Research and Development, Sanofi. Sanofi's investment in the company includes a three-year agreement that will help discover and develop new treatments for non-small cell lung cancer, triple negative breast cancer, mesothelioma and multiple myeloma. This partnership will help accelerate our ambitious oncology program as we advance a rich pipeline of medicines to address unmet patient needs.

About Owkin

Owkin is a French American startup that specializes in AI and federated learning for medical research. It was co-founded in 2016 by Dr Thomas Clozel M.D., a clinical research doctor and former assistant professor in clinical hematology, and Dr Gilles Wainrib, Ph.D., a pioneer in the field of artificial intelligence in biology. Owkin has recently published groundbreaking research at the frontier of AI and medicine in Nature Medicine, Nature Communications and Hepatology. The Owkin Platform connects life science companies with world-class academic researchers and hospitals to share deep medical insights for drug discovery and development. Using federated learning and breakthrough collaborative AI technology, Owkin enables its partners to unlock siloed datasets while protecting patient privacy and securing proprietary data. Through sharing high-value insights, the company powers unprecedented collaboration to improve patient outcomes. Owkin works with the most prominent cancer centers and pharmaceutical companies in Europe and the US. Key achievements to date include HealthChain and MELLODDY; two Owkin led federated learning consortia fuelling unprecedented collaboration in academic research and drug discovery, respectively. For more information, please visit Owkin.com and follow @OWKINscience on Twitter.

About SanofiSanofi is dedicated to supporting people through their health challenges. We are a global biopharmaceutical company focused on human health. We prevent illness with vaccines, provide innovative treatments to fight pain and ease suffering. We stand by the few who suffer from rare diseases and the millions with long-term chronic conditions. With more than 100,000 people in 100 countries, Sanofi is transforming scientific innovation into healthcare solutions around the globe.

Media Relations ContactsSally BainTel: +1 (781) 264-1091Sally.Bain@sanofi.com

Nicolas Obrist Tel: + 33 6 77 21 27 55Nicolas.Obrist@sanofi.com

Investor Relations Contacts ParisEva Schaefer-JansenArnaud DelepineNathalie Pham

Investor Relations Contacts North AmericaFelix Lauscher

Tel.: +33 (0)1 53 77 45 45investor.relations@sanofi.comhttps://www.sanofi.com/en/investors/contact

Forward-Looking StatementsThis press release contains forward-looking statements as defined in the Private Securities Litigation Reform Act of 1995, as amended. Forward-looking statements are statements that are not historical facts. These statements include projections and estimates and their underlying assumptions, statements regarding plans, objectives, intentions and expectations with respect to future financial results, events, operations, services, product development and potential, and statements regarding future performance. Forward-looking statements are generally identified by the words expects, anticipates, believes, intends, estimates, plans and similar expressions. Although Sanofis management believes that the expectations reflected in such forward-looking statements are reasonable, investors are cautioned that forward-looking information and statements are subject to various risks and uncertainties, many of which are difficult to predict and generally beyond the control of Sanofi, that could cause actual results and developments to differ materially from those expressed in, or implied or projected by, the forward-looking information and statements. These risks and uncertainties include among other things, the uncertainties inherent in research and development, future clinical data and analysis, including post marketing, decisions by regulatory authorities, such as the FDA or the EMA, regarding whether and when to approve any drug, device or biological application that may be filed for any such product candidates as well as their decisions regarding labelling and other matters that could affect the availability or commercial potential of such product candidates, the fact that product candidates if approved may not be commercially successful, the future approval and commercial success of therapeutic alternatives, Sanofis ability to benefit from external growth opportunities, to complete related transactions and/or obtain regulatory clearances, risks associated with intellectual property and any related pending or future litigation and the ultimate outcome of such litigation, trends in exchange rates and prevailing interest rates, volatile economic and market conditions, cost containment initiatives and subsequent changes thereto, and the impact that COVID-19 will have on us, our customers, suppliers, vendors, and other business partners, and the financial condition of any one of them, as well as on our employees and on the global economy as a whole. Any material effect of COVID-19 on any of the foregoing could also adversely impact us. This situation is changing rapidly and additional impacts may arise of which we are not currently aware and may exacerbate other previously identified risks. The risks and uncertainties also include the uncertainties discussed or identified in the public filings with the SEC and the AMF made by Sanofi, including those listed under Risk Factors and Cautionary Statement Regarding Forward-Looking Statements in Sanofis annual report on Form 20-F for the year ended December 31, 2020. Other than as required by applicable law, Sanofi does not undertake any obligation to update or revise any forward-looking information or statements.

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Sanofi invests $180 million equity in Owkin's artificial intelligence and federated learning to advance oncology pipeline - GlobeNewswire

From commerce, finance and agriculture to self-driving cars, personalised healthcare and social media advancements in artificial intelligence (AI) unlock countless opportunities. New applications promise to improve the quality of peoples lives throughout the world, but at the same time, raise a number of societal questions. A joint panel discussion of the German National Academy of Sciences Leopoldina and the Korean Academy of Science and Technology (KAST) explores AI technologies, their benefits and their challenges for society.

Virtual panel discussion of the German National Academy of Sciences Leopoldina and the Korean Academy of Science and TechnologyRealizing the Promises of Artificial IntelligenceThursday, 25 November 2021, 8am to 9am (CET)Online

Following opening remarks from the President of the Leopoldina, Prof (ETHZ) Dr Gerald Haug and Prof Min-Koo Han, PhD, President of the KAST, legal scholar Prof Ryan Song, PhD, Kyung Hee University, Seoul/South Korea, will provide an introduction into the topic. Subsequently, computer scientist Prof Alice Oh PhD, KAIST School of Computing, Daejeon/ South Korea, and Member of the Leopoldina Prof Dr Alexander Waibel, Karlsruhe Institute of Technology/Germany and Carnegie Mellon University, Pittsburgh/USA, will provide input statements for further discussion. The speakers will present current developments and applications of AI technologies and discuss their societal and scientific impact.

The event is open to the interested public and free of charge. It will be held in English. The panel discussion will be live-streamed via the KAST YouTube Channel. Please submit your questions prior to and during the event here: https://docs.google.com/forms/d/1A9L7JqvjljYbZH3JYX_CBGyCK91ayiJAmcPZET6O91c/edit.

Further information about the event is available here: https://www.leopoldina.org/en/events/event/event/2938/

Follow the Leopoldina on Twitter: http://www.twitter.com/leopoldina

About the German National Academy of Sciences LeopoldinaAs the German National Academy of Sciences, the Leopoldina provides independent science-based policy advice on matters relevant to society. To this end, the Academy develops interdisciplinary statements based on scientific findings. In these publications, options for action are outlined; making decisions, however, is the responsibility of democratically legitimised politicians. The experts who prepare the statements work in a voluntary and unbiased manner. The Leopoldina represents the German scientific community in the international academy dialogue. This includes advising the annual summits of Heads of State and Government of the G7 and G20 countries. With 1,600 members from more than 30 countries, the Leopoldina combines expertise from almost all research areas. Founded in 1652, it was appointed the National Academy of Sciences of Germany in 2008. The Leopoldina is committed to the common good.

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What is artificial intelligence good for? Panel discussion addresses the promises, opportunities and challenges - EurekAlert

Of all the potentially new and revolutionary technologies,artificial intelligence(AI) may be the most disruptive of all. In laymans terms, AIrefers to systems able to perform tasks that normally require human intelligence, such as visual and speech recognition, decisionmaking and, perhaps one day, thinking.

Thinking? AI has already defeated the world's best chess and Pokemon GO players.SupposeAIsurpasses the intelligence of human beings.What then?

Could AIssuper-intelligencecure cancer, enhance wellbeing, redress climate change and deal with many of the planets worst evils? Or might a super-smart AI turn on mankind as portrayed in the Terminator movies?Finally, is the potential of AI being exaggerated?

Albert Einsteindescribed the universe as finite but unbounded. That definition could fit AIs future applications.But how will we know?

Perhaps the only comparable disruptive technology wasnuclear and thermonuclear weapons. These weapons irreversibly disrupted and changed the nature, conduct and character of the politics of war. The reason: no winners, only victims and losers, would emerge after a thermonuclear holocaust eviscerated the belligerents.

What then are the common links?

Nuclear weapons provoked often-fiery debateover the moral and legal implications and when or how these weapons could or should be employed from a counterforce first strike against military targets to countervalue retaliatory roles against population and industrial centers andtactically to limit escalation or rectify conventional arms imbalances.AI has reignited debate over equally critical questions and issues about its place in society.

Nuclear weapons ultimately led to adoctrineand rules of the game to deter and prevent their spread and use partly through arms control. Will AI lead to a regulatory regime or is the technology too universal for any governing code?

Nuclear weapons are existential.Are there conditions under which AI could become as dangerous? Proliferationof these weapons led to international agreements to prevent their spread.Willthat apply to AI?

It was argued that if one side gained superiority over another, conflict or more aggressive behavior would follow.Does AI raise similar concerns?

Important differences exist.Nuclear weapons affected national security.AI most certainly will affect the broader sweep of society, as have the industrial and information revolutions with positive and negative consequences.

Second, thedestructive powerof these weapons made them so significant.AI, at this stage, needs an intermediary link to exercise its full disruptive power. However, ironically, as societies became more advanced, those two revolutions had theunintended consequenceof also creating greater vulnerabilities, weaknesses and dependencies subject to major and even catastrophic disruption.

COVID-19, massive storms, fires, droughts and cyberattacks are unmistakable symptoms of the power of the new MAD Massive Attacks of Disruption.AI is a potential multiplier by its abilityto interactwith these and other disruptors, exploiting inherent societal weaknesses and vulnerabilities and creating new ones as well as preventing their harmful effects.

Last,unlike nuclear weapons, if used properly AI will have enormous and even revolutionarybenefitsfor the human species.

The critical question is what mechanisms can identify what former Defense Secretary DonaldRumsfeldcalled the known knowns; known unknowns; and unknown unknowns regarding AI.

Anational AI commissionjust completed its effort.Commissions often can bury a tough topic.The9/11 Commissiondid stellar work. But only a portion of its most important recommendations were implemented.Forming the Department of Homeland Security and the Office of the Director of National Intelligence did not bring needed reform because those agencies ultimately expanded the layering of an already bloated government bureaucracy.

That criticism aside, instead of a new AI commission, a permanent AI oversight council with a substantial amount of research funding to examine AIs societal implications must be created.Membership should be drawn from the public and the legislative and executive branches of government.

Funding should go to the best research institutions, another parallel with nuclear weapons. During the Cold War, the Pentagon underwrote countless studies covering all aspects of the nuclear balance. The same mustapply to AIbut with wider scope.

This council must also coordinate, liaise and consult with the international community, including China, Russia, allies, friends and others to widen the intellectual aperture and as confidence building measures.

By employing lessons learned from studying the nuclear balance, not only can AIspotentially destructive consequences be mitigated.More importantly, if properly utilized, as Einstein observed about the universe, AI has nearly unbounded opportunity to advance the public good.

Harlan Ullman, Ph.D, is United Press Internationals Arnaud deBorchgrave Distinguished Columnist. His latest book, due out this year, is The Fifth Horseman and the New MAD: The Tragic History of How Massive Attacks of Disruption Endangered, Infected, Engulfed and Disunited a 51% Nation and the Rest of the World.

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