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LONDON, May 24, 2022 (GLOBE NEWSWIRE) -- According to The Business Research Companys research report on the artificial intelligence (AI) in drug discovery market, the rising adoption of cloud-based applications and services by pharmaceutical companies will contribute to the growth of AI in the drug discovery market. Among the various end-users of cloud-based drug discovery platforms, pharmaceutical vendors are likely to be major stakeholders, holding a high-value share of the global cloud-based drug discovery platform market. An opportunity analysis of the global market reveals that leading software vendors have already adopted cloud-based drug discovery platforms to facilitate seamless research and development processes. Moreover, the cloud-based drug discovery platform revolution will witness significant growth in the coming years, thereby creating better opportunities for software vendors for growth and expansion. For example, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced in December 2021 that it is collaborating with Pfizer to develop innovative, cloud-based solutions that have the potential to improve how new medicines are developed, manufactured, and distributed for clinical trials. The companies are exploring these advances through their newly created Pfizer Amazon Collaboration Team (PACT) initiative, which applies AWS capabilities in analytics, machine learning, compute, storage, security, and cloud data warehousing to Pfizer laboratory, clinical manufacturing, and clinical supply chain efforts. Thus, the increasing adoption of cloud-based applications and services by pharmaceutical companies will contribute positively to the AI drug discovery market size.

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The global artificial intelligence in drug discovery market size is expected to grow from $0.79 billion in 2021 to $1.04 billion in 2022 at a compound annual growth rate (CAGR) of 31.6%. The growth in the market is mainly due to the companies resuming their operations and adapting to the new normal while recovering from the COVID-19 impact, which had earlier led to restrictive containment measures involving social distancing, remote working, and the closure of commercial activities that resulted in operational challenges. The AI in drug discovery market is expected to reach $2.99 billion in 2026 at a CAGR of 30.2%.

Use of AI through Machine Learning (ML) is a trend in assessing pre-clinical studies during the drug development process. Pre-clinical studies are non-clinical studies for novel drug substances to establish clinical efficacy and safety in a controlled environment before testing with a final target population. ML modelling pharmacokinetic (PK) and pharmacodynamic (PD) methodologies are applied in in-vitro and preclinical PK studies to successfully anticipate the dose concentration response relationship of pipeline assets. In addition, deep learning methodologies are employed as In-Silico methods for successfully predicting the therapeutic/pharmacological properties of novel molecules by utilizing transcriptomic data, which includes various biological systems and controlled conditions. Besides the drug discovery market, machine learning technology finds its application in the AI in medical diagnostics market as well as AI in medical imaging market.

Major players in the artificial intelligence for drug discovery and development market are IBM Corporation, Microsoft, Atomwise Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, Benevolent AI, Exscientia, Cyclica, and BIOAGE.

The global artificial intelligence in drug discovery market report is segmented by technology into deep learning, machine learning; by drug type into small molecule, large molecules; by disease type into metabolic disease, cardiovascular disease, oncology, neurodegenerative diseases, others; by end-users into pharmaceutical companies, biopharmaceutical companies, academic and research institutes, others.

In 2021, North America was the largest region in the artificial intelligence (AI) in drug discovery market. It was followed by the Asia-Pacific, Western Europe, and then the other regions. The regions covered in the AI in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, and Africa.

Artificial Intelligence (AI) In Drug Discovery Global Market Report 2022 Market Size, Trends, And Global Forecast 2022-2026 is one of a series of new reports from The Business Research Company that provide artificial intelligence (AI) in drug discovery market overviews, artificial intelligence (AI) in drug discovery market analyze and forecast market size and growth for the whole market, artificial intelligence (AI) in drug discovery market segments and geographies, artificial intelligence (AI) in drug discovery market trends, artificial intelligence (AI) in drug discovery market drivers, artificial intelligence (AI) in drug discovery market restraints, artificial intelligence (AI) in drug discovery market leading competitors revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.

The report also gives in-depth analysis of the impact of COVID-19 on the market. The reports draw on 150,000 datasets, extensive secondary research, and exclusive insights from interviews with industry leaders. A highly experienced and expert team of analysts and modelers provides market analysis and forecasts. The reports identify top countries and segments for opportunities and strategies based on market trends and leading competitors approaches.

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Artificial Intelligence (AI) In Drug Discovery Market Growth Is Driven At A 30% Rate With Increasing Adoption Of Cloud-Based Applications And Services...

Written by Suzanne Smalley May 25, 2022 | CYBERSCOOP

The U.S. militarys top expert on artificial intelligence (AI) said Wednesday that the Pentagon must up its game to ensure American supremacy in a future era where artificial intelligence will determine success on the battlefield.

China aims to dominate the world in the AI space by 2030, the Pentagons Joint Artificial Intelligence Director Lt. Gen. Michael Groen told an Atlantic Council-convened audience gathered for a discussion of AI in national security. Groen said that AI will be a $16 trillion industry by 2030, and will raise GDP significantly for both China and the U.S.

Groen said DOD must reinvent itself to meet the challenge, arguing that the Pentagon will need to do more to bring the branches together and act as a doer instead of a coordinating body. Citing Amazon founder Jeff Bezoss 2002 directive that all Amazon components must work with one organization-wide data set, Groen said that in the same way the Pentagon must lead its various components to be on more unified footing.

Its time for the Department of Defense to have a similar focus on using data to solve problems, to think about their problems through a data lens overcoming the cultural obstacles to actually become a competitive enterprise that can outfight any opponent and has the same level of productivity and efficiency that we desire for our taxpayers, Groen said. Clearly, the competition is around us.

Its time for the Department of Defense to have a similar focus on using data to solve problems, to think about their problems through a data lens overcoming the cultural obstacles to actually become a competitive enterprise that can outfight any opponent.

Acknowledging the difficulties inherent to adaptation for an agency bogged down by bureaucracy, Groen said he is focused on improving DODs efficiency as it seeks to take on the Chinese AI machine.

Implementation in the department, of course, is always a challenge as new technology meets legacy processes, legacy organizations and legacy technology, Groen said. Implementation, of course, is the key to successful transformation and implementation is extraordinarily challenging as artificial intelligence and related technologies cross cut not just service lines, but almost every procedural line or process line across the department.

Groen said China is now executing its 14th five-year plan to meet its goal for AI supremacy by 2030 while the U.S. is now building its 14th AI-based program objective memorandum (POM), which refers to how DOD allots future funding to meet its strategic objectives. Suggesting that the U.S. and China are locked in a neck at neck battle for AI dominance, Groen said, those dates, maybe uncomfortably, maybe comfortably, overlap to quite a degree.

Groens remarks were made at an event at which the Atlantic Councils Scowcroft Center for Strategy and Security unveiled a new report focused on artificial intelligence in national security and defense. The report warns that without intentional, coordinated, and immediate action, the United States risks falling behind competitors in the ability to harness game-winning technologies that will dominate the kinetic and non-kinetic battlefield of the future.

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Head of DOD artificial intelligence command warns Pentagon must improve to beat China on AI - CyberScoop

As artificial intelligence (AI) becomes increasingly embeddedinto products, services, and business decisions, state and locallawmakers have been considering and passing a range of lawsaddressing AI. These vary from laws that promote AI to moreregulatory approaches that impose obligations on AI in specificareas. In a development that parallels the evolution of privacylaws, states and localities have moved ahead with initiatives ontheir own. However, unlike in privacy, where a set of legislativeapproaches has been debated for years, approaches to dealing withAI have been far more varied and scattershot. This kind of apatchwork approach, if it continues, may create issues withmanaging regulatory compliance for many uses of AI acrossjurisdictions.

States and Localities Are Beginning to Move Forward with aPiecemeal Approach to AI

In 2021, five jurisdictions Alabama, Colorado, Illinois,Mississippi, and New York City enacted legislationspecifically directed at the use of AI. Their approaches varied,from creating bodies to study the impact of AI to regulating theuse of AI in contexts where governments have been concerned aboutincreased risk of harm to individuals.

Some of these laws have focused on promoting AI. For instance,Alabama's law establishes a council to review and advise theGovernor, the legislature, and other interested parties on the useand development of advanced technology and AI in the state. TheMississippi law implements a mandatory K-12 curriculum thatincludes instruction in AI.

Conversely, some laws are more regulatory and skeptical of AI.For example, Illinois has adopted two AI laws onethatdevelopsa task force to study the impactof emerging technologies, including AI, on the future of work andanother thatmandatesnotice, consent, and reportingobligations for employers that use AI in hiring. Under existingIllinois law, an employer that asks applicants to record videointerviews and uses an AI analysis must: (1) notify the applicantthat AI may be used to analyze the applicant's video interviewand consider the applicant's fitness for the position; (2)provide each applicant with information explaining how the AI worksand what general types of characteristics the AI uses to evaluateapplicants; and (3) obtain consent from the applicant. The law alsolimits the sharing of the videos and extends to applicants a rightto delete the videos. A 2021 amendment imposes reportingrequirements on an employer that relies solely upon an AI analysisof a video interview to determine whether an applicant will beselected for an in-person interview. The state Department ofCommerce and Economic Opportunity is required to annually analyzecertain demographic data reported and report to the Governor andGeneral Assembly whether the data discloses a racial bias in theuse of AI.

Colorado's law takes a sectoral approach,prohibitinginsurers from using anyinformation sources as well as any algorithms or predictive modelsin a way that produces unfair discrimination. Unfair discriminationincludes "the use of one or more external consumer data andinformation sources, as well as algorithms or predictive modelsusing external consumer data and information sources, that have acorrelation to race, color, national or ethnic origin, religion,sex, sexual orientation, disability, gender identity, or genderexpression, and that use results in a disproportionately negativeoutcome for such classification or classifications, which negativeoutcome exceeds the reasonable correlation to the underlyinginsurance practice, including losses and costs forunderwriting." This law comes in addition to Colorado'scomprehensive privacy law, theColorado Privacy Act, set to go into effect onJuly 1, 2023, which provides consumers with a right to opt out ofthe processing of their personal data for purposes of targetedadvertising, the sale of personal data, or automated profiling infurtherance of decisions that produce legal or similarlysignificant effects.

In late 2021, New York City notablyenacteda specific algorithmicaccountability law, becoming the first jurisdiction in the UnitedStates to require algorithms used by employers in hiring orpromotion to be audited for bias. New York City's law bars AIhiring systems that do not pass annual audits checking for race- orgender-based discrimination. The bill would require the developersof such AI tools to disclose the job qualifications andcharacteristics that will be used by the tool and would provideemployment candidates the option of choosing an alternative processfor employers to review their application. The law imposes fines onemployers or employment agencies of up to $1,500 per violation.

California's Privacy Regulations May Also TargetAI

California's California Privacy Protection Agency (CPPA), the new agency charged with rulemakingand enforcement authority over the California Privacy Rights Act(CPRA), is expected to issue regulations governing AI by 2023. Thestatute specifically addresses a consumer's right to understandand opt out of automating decision-making technologies such as AIand machine learning. In particular, the agency is charged with"[i]ssuing regulations governing access and opt-out rightswith respect to businesses' use of automated decisionmakingtechnology, including profiling and requiring businesses'response to access requests to include meaningful information aboutthe logic involved in those decisionmaking processes, as well as adescription of the likely outcome of the process with respect tothe consumer."

In September 2021, the CPPAreleasedan Invitation for PreliminaryComments on Proposed Rulemaking (Invitation) and accepted commentsthrough November 8, 2021. The Invitation to comment issued by theCPPA asked four questions regarding interpretation of theagency's automated decision-making rulemaking authority:

While the statute calls for final rules to be adopted by July2022, at a February 17 CPPA board meeting, Executive DirectorAshkan Soltani announced that draft regulations will be delayed. Aswe've previouslydiscussed, this effort in California toregulate certain automated decision-making processes may open thedoor to greater regulation of AI and should be watchedclosely.

Even as the federal governmentlooks more closelyat AI, some states andlocalities appear to be poised to jump ahead. Indeed, many otherstates continue to debate AI proposals in 2022. Companiesdeveloping and deploying AI should continue to monitor this area asthe regulatory landscape develops.

2022 Wiley Rein LLP

The content of this article is intended to provide a generalguide to the subject matter. Specialist advice should be soughtabout your specific circumstances.

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States And Localities Begin To Focus On Use Of Artificial Intelligence - New Technology - United States - Mondaq

Do you know what Artificial Intelligence is? This is a growing industry with great opportunities and a perfect place for investments. AI has appeared on the market as a working solution to make the life of people in every industry easier. Due to the massive investment plan in the sector, there are tons of teaching practices to master on the topic. You can find a lot of experts in the field who can teach you to become the leading AI specialist in the field.

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There are various sectors where AI can contribute successfully. It helps with process optimization and eases the work in general. When better effectiveness and results are needed, Artificial Intelligence comes to the fore. Hence, if you are interested in the topic and would like to be a part of the global tech sector, you need to start with thorough learning.

Where to find an online platform to help beginner learners master their skills and scale up their knowledge? This is a common question from Internet users who request AI learning courses a lot. Fortunately, theres a high-quality and well-known Sypwai company that offers one of the best learning practices for beginners on the market. Having got massive experience in the field of Artificial intelligence, the company can now help others with their beginning initiatives.

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It offers simple tasks for beginner users to help them get the main idea behind the AI work. The tasks are easy and dont take much time. You can not only learn how to use the AI algorithms but even get money for your learning practice. The website pays its users for accomplishing simple tasks on the platform.

How do you start learning how Artificial Intelligence works? You should find yourself enough time to dedicate to the Sypwai platform. It has the best reviews on the web as a learning service for beginners. You can perform easy tasks, get money for them and accomplish your dream of learning more about AI. How to register on the site and work with the tasks? Lets check what kind of registration process the platform offers.

Are you ready to start? There are a couple of steps to be done to make your first results in the field. If youre not afraid to kick start, make sure to place your account and get into the world of AI.

Why Sypwai? You may wonder why you should choose Sypwai to start managing the artificial intelligence practice. Theres a clear response to this kind of task. Sypwai company is the leading platform on the market. Being a competing service for a couple of years, the company can offer the best AI solutions today. The company visits all possible conferences to soak the relevant knowledge and share common experiences that will help in the development of new AI solutions.

The effort of the company presents the best results not long in coming. Its a highly protected service that puts its effort into the development of the IT sector in the whole world. The community has a wide range of experts following the technical tasks and paving the way to a successful AI future. If you join the team, you can attract new achievements and even become a part of the team in the future.

Read: TeamViewer brings Artificial Intelligence to the Shopfloor

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Artificial Intelligence in Today's World: What's the Tendency? - TechnoSports

Ameco Research Analysts says that the global market for artificial intelligence (AI) in aviation will reach a market size of more than US$ 6,900 Mn by 2028 rising at a CAGR of around 47% during the predicted years

Airports around the world took the brunt of the travel prohibitions and limitations imposed by the COVID-19 outbreak in a short period of time. Operations have been severely affected or fully suspended since international travel has been restricted to repatriation planes and cargo, and most airport halls are almost empty. Machine learning (ML), deep learning (DL), and other artificial intelligence (AI) approaches are beginning to influence the industry and have become fundamental methodologies in many research initiatives and new industrial advances. Machine learning becomes easier with access to vast volumes of data, allowing us to address previously inconceivable issues. The use of artificial intelligence (AI) in aviation can help with capacity, forecasting, air traffic management (ATM), delay management, the environment, connectivity, and safety.

The growing adoption of big data inArtificial Intelligence (AI) in Aviation Marketgrowth

Quick reactions to present and future market demands, better planning and tactically aligned decision making, and a clear understanding and monitoring of all important performance drivers significant to the airline industry are the ultimate benefits of big data analytics. When these advantages are correctly exploited, they contribute to lower operating costs, market-leading competitiveness, better customer service, higher profit margins, and more shareholder value.

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While a variety of variables have contributed to the expansion of AI in travel, one of the most important has been a shift in customer expectations. Because of the experiences provided by huge tech companies like Google, Amazon, Apple, and Facebook, travelers are increasingly demanding seamless and personalized experiences.

By leveraging artificial intelligence through virtual assistant technology that reads weather forecasts on demand, switches radio channels, and delivers situational information on demand, airline pilots can save time and increase efficiency. AI-based virtual assistants can manage repeated chores thanks to their capabilities. Additionally, Garmin offers AI audio panels that can be beneficial to pilots.

Artificial intelligence can also help to reduce overbooking. Based on past flyer information and historical passenger data, as well as changes in weather trends on a certain route, AI might be used to anticipate if a specific passenger will not show up or will transfer to another aircraft. The AI would then offer ground employees the most up-to-date passenger information. This technology could make it easier to remove passengers from planes that have already taken off.

Global Artificial Intelligence (AI) in Aviation Market Classification

Artificial intelligence (AI) in aviation market is divided into four categories: offering, technology, application, and regions. The offering segment can be split into hardware, software, and services. Based on offering, the software segment generated the largest revenue in 2020 while the services are likely to attain the fastest growth rate during the forecast period 2021 2028. Machine learning, context awareness computing, natural language processing, and computer vision are the categorizations of technology segments. The machine learning application acquired the most market share in 2020, whereas the natural language processing segment is expected to grow with a significant growth rate. Computer vision, a technique that utilizes cameras and machine learning algorithms to monitor complicated ground servicing activities, detect safety hazards in real-time, or sound alerts when a service takes longer than intended, is one of the emerging AI applications at airports. Gatwick Airport in London was one of the first major airports to use computer vision to speed up aircraft turnaround times and improve ground personnel safety. Based on application, the market is divided into virtual assistants, smart maintenance, manufacturing, training, surveillance, flight operations, and dynamic pricing. Among applications, the virtual assistant segment dominated the market with maximum share and is also likely to exhibit the quickest growth in the coming years.

Regional Stance

North America, Asia-Pacific, Latin America, Europe, and the Middle East & Africa (MEA) are the regional categorization of the global artificial intelligence (AI) in aviation market. North America generated the largest revenue in 2020 due to the early adoption of technologies and the presence of key players in the region. Meanwhile, the Asia-Pacific region is expected to witness the fastest growth rate in the coming years. China and Japan are the two largest contributors to AIs growth in the APAC aviation sector. The deployment of machine learning and natural language processing (NLP) technology for virtual assistance and training applications in the aviation sector is boosting AIs growth in this region. These countries have a high demand for AI technology to improve the efficiency of their aviation sectors.

Major Players

The key companies offered in the report include Airbus SE, Boeing, Garmin Ltd., Amazon, IBM Corporation, Intel Corporation, Lockheed Martin, Micron Technology, General Electric, MiSmart Maintenanceoft, Neurala, Inc. NVIDIA corporation, MINDTITAN, TAV Technologies, Samsung Electronics, Thales Group, and Xilinx.

FEW SIGNIFICANT POINTS FROM TABLE OF CONTENT:

Global Artificial Intelligence (AI) in Aviation Market Research Report 2021-2028

CHAPTER 1. Industry Overview of Artificial Intelligence (AI) in Aviation MarketCHAPTER 2. Research ApproachCHAPTER 3. Market Dynamics And Competition AnalysisCHAPTER 4. Manufacturing Plant AnalysisCHAPTER 5. Artificial Intelligence (AI) in Aviation Market By OfferingCHAPTER 6. Artificial Intelligence (AI) in Aviation Market By TechnologyCHAPTER 7. Artificial Intelligence (AI) in Aviation Market By ApplicationCHAPTER 8. North America Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 9. Europe Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 10. Asia Pacific Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 11. Latin America Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 12. Middle East & Africa Artificial Intelligence (AI) in Aviation Market By CountryCHAPTER 13. Player Analysis Of Artificial Intelligence (AI) in Aviation MarketCHAPTER 14. Company Profile

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Artificial Intelligence (AI) in Aviation Market Sales and Revenue Report 2021 2030 The Daily Vale - The Daily Vale