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AI in Genomics Market to Worth US$ 16,272 Million by 2031 | Growth Plus Reports

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Newark, New Castle, USA, May 08, 2023 (GLOBE NEWSWIRE) — According to a new Growth Plus Reports study, the AI In Genomics Market is estimated to hit US$ 16,272 million by 2031, with a revenue CAGR of 49.70%. The study analyzes the important strategies, drivers, competition, market dynamics, size, and important investment regions.

Key Takeaways:

  • The increasing demand for novel and personalized medicine will drive market revenue growth.
  • Increasing funding for genomics research will drive demand for AI in Genomics.
  • North America dominates the global AI in Genomics market. 

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                                               AI in Genomics Market Scope

Report Attribute Details
Market Size Value in 2022 US$ 446.84 Million
Revenue Forecast in 2031 US$ 16,272 Million
CAGR 49.10%
Base Year for Estimation 2022
Forecast Period 2023 to 2031
Historical Year 2021
Segments Covered Component, Technology, Functionality, Application, End User, and Region
Regional Scope North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa

Market Drivers

The increased demand for personalized medicine will drive the revenue growth of AI in Genomics market. Furthermore, advancements in machine learning and increased adoption of AI in Genomics are expected to boost the market revenue growth rate. Additionally, increased funding for genomics research is expected to support the market’s revenue growth.

Market Segmentation
Growth Plus Reports has analyzed global AI in Genomics market from six perspectives: Component, Technology, Functionality, Application, End User, and Region.

Component Segmentation: Based on the component, the AI in Genomics market is segmented into hardware, software, and services. The software segment dominates the market with the largest revenue share because of the rising usage of AI-based software for genomics by healthcare companies, R&D centers, and patients.

Technology Segmentation: Based on the technology, the AI in Genomics market is segmented into computer vision and machine learning. The machine learning segment dominates the market because machine learning techniques allow computers to learn from data and make predictions or choices.

Functionality Segmentation: Based on the functionality, the global AI in Genomics market is segmented into genome sequencing, gene editing, and others. The genome sequencing segment dominates the market because AI algorithms extract valuable insights from the massive volumes of data generated by genome sequencing.

Application Segmentation: Based on the application, the AI in Genomics market is segmented into drug discovery & development, precision medicine, diagnostics, and others. The drug discovery & development segment dominates the market because of the increased demand for pharmaceuticals and the high usage of AI algorithms in drug research and development to create new therapies based on genetic data.

End User Segmentation: Based on the end user, the AI in Genomics market is segmented into pharmaceutical and biotech companies, healthcare providers, research centers, and others. The pharmaceutical and biotech companies segment dominates the market because they employ AI algorithms extensively to analyze genetic data and produce novel medications and cures.

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Regional Growth Dynamics
Based on the region, the global AI in Genomics market is segmented into North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa.

North America dominates the AI in Genomics market with the largest revenue share. The presence of prosperous research institutes and biotechnology companies and increased investment in developing new and innovative technologies are the responsible for North America’s lrevenue share in the global market.  

Competitive Landscape

The key players in the global AI in Genomics market are:

· IBM
· Microsoft Corporation
· NVIDIA Corporation
· Data4Cure, Inc.
· Thermo Fisher Scientific
· SOPHiA GENETICS
· FDNA INC.
· Engine Biosciences Pte. Ltd.
· Fabric Genomics
· Verge Genomics
· Lifebit Biotech Ltd.
The market for AI in Genomics is moderately competitive, with several multinational companies. Major competitors engage in technological advancements, R&D, and mergers and acquisitions to enhance their market position.

Recent developments:

  • Zurich researchers developed a new tool in February 2023 that uses artificial intelligence to predict the effectiveness of various genome-editing repair methods. Unintentional errors in the repair of genetic illness DNA mutations can therefore be avoided.
  • WhiteLab Genomics, a Y-Combinator-backed AI-powered predictive software simulation platform for researching gene and cell therapies, received $10 million in funding in September 2022.

Table of Content

  1. INTRODUCTION
    1. Market Ecosystem
    2. Timeline Under Consideration
      1. Historical Years – 2021
      2. Base Year – 2022
      3. Forecast Years – 2023 to 2031
    3. Currency Used in the Report
  2. RESEARCH METHODOLOGY 
    1. Research Approach
    2. Data Collection Methodology
    3. Data Sources
      1. Secondary Sources 
      2. Primary Sources 
    4. Market Estimation Approach
      1. Bottom Up 
      2. Top Down 
    5. Market Forecasting Model
    6. Limitations and Assumptions
  3. PREMIUM INSIGHTS
    1. Current Market Trends (COVID-19 Perspective)
    2. Key Players & Competitive Positioning (2022) 
  4. MARKET DYNAMICS
    1. Drivers
    2. Restraints/Challenges
    3. Opportunities
  5. GLOBAL AI IN GENOMICS MARKET – ANALYSIS & FORECAST, BY COMPONENT
    1. Hardware
    2. Software
    3. Services
  6. GLOBAL AI IN GENOMICS MARKET – ANALYSIS & FORECAST, BY TECHNOLOGY
    1. Machine Learning     
      1. Supervised Learning
      2. Unsupervised Learning
      3. Deep Learning
      4. Others
    2. Computer Vision
  7. GLOBAL AI IN GENOMICS MARKET – ANALYSIS & FORECAST, BY FUNCTIONALITY
    1. Genome Sequencing
    2. Gene Editing
    3. Others
  8. GLOBAL AI IN GENOMICS MARKET – ANALYSIS & FORECAST, BY APPLICATION
    1. Drug Discovery & Development
    2. Precision Medicine
    3. Diagnostics
    4. Others

AI IN GENOMICS MARKET TOC

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VALUE PROPOSITIONS RELATED TO THE REPORT:

  • Powered with Complimentary Analyst Hours and Expert Interviews with Each Report
  • Comprehensive quantitative and qualitative insights at segment and sub-segment level
  • Covid 19 impact trends and perspective
  • Granular insights at global/regional/country level
  • Deep-rooted insights on market dynamics (drivers, restraints, opportunities) and business environment
  • Blanket coverage on competitive landscape
  • Winning imperatives
  • Exhaustive coverage on ‘Strategic Developments’ registered by leading players of the market

CUSTOMIZATION OPTIONS:

  • Distributor Landscape Assessment
  • Pricing Intelligence
  • Customer Base Assessment
  • Investment & Initiatives Analysis
  • ‘Business Profile’ of Key Players

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About Us:

Growth Plus Reports is part of GRG Health, a global healthcare knowledge service company. We are proud members of EPhMRA (European Pharmaceutical Marketing Research Association).

Growth Plus portfolio of services draws on our core capabilities of secondary & primary research, market modelling & forecasting, benchmarking, analysis and strategy formulation to help clients create scalable, ground-breaking solutions that prepare them for future growth and success.

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Artificial Intelligence

PolyU research finds improving AI large language models helps better align with human brain activity

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HONG KONG, May 27, 2024 /PRNewswire/ — With generative artificial intelligence (GenAI) transforming the social interaction landscape in recent years, large language models (LLMs), which use deep-learning algorithms to train GenAI platforms to process language, have been put in the spotlight. A recent study by The Hong Kong Polytechnic University (PolyU) found that LLMs perform more like the human brain when being trained in more similar ways as humans process language, which has brought important insights to brain studies and the development of AI models.

Current large language models (LLMs) mostly rely on a single type of pretraining – contextual word prediction. This simple learning strategy has achieved surprising success when combined with massive training data and model parameters, as shown by popular LLMs such as ChatGPT. Recent studies also suggest that word prediction in LLMs can serve as a plausible model for how humans process language. However, humans do not simply predict the next word but also integrate high-level information in natural language comprehension. 
A research team led by Prof. Li Ping, Dean of the Faculty of Humanities and Sin Wai Kin Foundation Professor in Humanities and Technology at PolyU, has investigated the next sentence prediction (NSP) task, which simulates one central process of discourse-level comprehension in the human brain to evaluate if a pair of sentences is coherent, into model pretraining and examined the correlation between the model’s data and brain activation. The study has been recently published in the academic journal Sciences Advances.
The research team trained two models, one with NSP enhancement and the other without, both also learned word prediction. Functional magnetic resonance imaging (fMRI) data were collected from people reading connected sentences or disconnected sentences. The research team examined how closely the patterns from each model matched up with the brain patterns from the fMRI brain data.
It was clear that training with NSP provided benefits. The model with NSP matched human brain activity in multiple areas much better than the model trained only on word prediction. Its mechanism also nicely maps onto established neural models of human discourse comprehension. The results gave new insights into how our brains process full discourse such as conversations. For example, parts of the right side of the brain, not just the left, helped understand longer discourse. The model trained with NSP could also better predict how fast someone read – showing that simulating discourse comprehension through NSP helped AI understand humans better.
Recent LLMs, including ChatGPT, have relied on vastly increasing the training data and model size to achieve better performance. Prof. Li Ping said, “There are limitations in just relying on such scaling. Advances should also be aimed at making the models more efficient, relying on less rather than more data. Our findings suggest that diverse learning tasks such as NSP can improve LLMs to be more human-like and potentially closer to human intelligence.”
He added, “More importantly, the findings show how neurocognitive researchers can leverage LLMs to study higher-level language mechanisms of our brain. They also promote interaction and collaboration between researchers in the fields of AI and neurocognition, which will lead to future studies on AI-informed brain studies as well as brain-inspired AI.”
Media ContactMs Annie WongSenior Manager, Public AffairsTel: +852 3400 3853Email: [email protected] 

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Artificial Intelligence

VivaTech 2024: a record-breaking event

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PARIS, May 27, 2024 /PRNewswire/ — VivaTech 2024 broke records with more than 165,000 visitors over four days, a 10% increase over 2023. The event welcomed 13,500 start-ups, a 20% increase over the previous year.

A BUSINESS AND FINANCE ACCELERATOR
VivaTech has established itself as a key business event, generating more than 400,000 online business connections this year. Startups forged business relationships with companies from 25 sectors and met over 2,000 investors.
VIVA TECHNOLOGY CONFIRMS ITS INTERNATIONAL APPEAL
The event attracted representatives from more than 120 countries and 40 national pavilions. Japan, the country of the year, showcased its ecosystem with a ministerial delegation and more than 40 startups. Africa was also in the spotlight with the Africa Tech Lab and the AfricaTech Awards, honouring innovative startups such as Schoolz, Rology and Inclusivity Solutions.
AI AND SUSTAINABLE TECH AT THE HEART OF THE PROGRAMME
VivaTech 2024 showcased the latest advances in artificial intelligence, with nearly 40% of exhibitors dedicated to this technology. Sustainable tech was also in the spotlight, especially through the Impact Bridge, a space dedicated to initiatives for a sustainable future. VivaTech’s environmental efforts were rewarded with ISO 20-121 certification.
DIVERSITY MORE THAN EVER IN VIVATECH’S DNA 
Diversity took centre stage where over 40% of speakers were women. Among the most notable initiatives, the Female Founder Challenge rewarded Albane Dersy from Inbolt. At the same time, Femtech France took advantage of the event to launch its second Femtech industry barometer.
THE MEETING PLACE FOR REVEALS, EXCLUSIVITIES AND INNOVATIONS
For four days, VivaTech was the scene of numerous revelations, with some fifty worldwide or European exclusives unveiled. Among these, Tesla’s Cybertruck made its first appearance in France, marking a highlight of the event.
INTERNATIONAL SPEAKERS
VivaTech 2024 consolidated its position as the must-attend technology event with over 400 international speakers sharing their visions on AI and sustainable tech. Speakers included Elon Musk, John Kerry, Eric Schmidt, Arthur Mensch, Robin Li, Linda Yaccarino and Serena and Venus Williams. Institutional figures such as Fumio Kishida, Bruno Le Maire and Thierry Breton also took an active part in the debates.
WE LOOK FORWARD TO SEEING YOU FROM 11 TO 14 JUNE 2025 AT PARIS PORTE DE VERSAILLES!
Contact: [email protected]
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Artificial Intelligence

Only Much Louder’s AI-powered influencer marketing tech, Hypothesis, expands globally, to empower brands to connect with international creators

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OML Entertainment’s Hypothesis is targeting the Asia–Pacific Region, Middle East, Africa, and USA by 2025.Hypothesis will open borders for brands and agencies, facilitating a region-agnostic global platformMUMBAI, India, May 27, 2024 /PRNewswire/ — Only Much Louder’s AI-powered influencer marketing tech, Hypothesis, expands its global footprint, after revolutionizing the Indian influencer market. In the first phase, Hypothesis will be available in the Asia–Pacific region (Singapore, Australia, Malaysia, Philippines, Vietnam, Thailand), Middle Eastern countries (Abu Dhabi, GCC nations, Egypt, Lebanon, Saudi Arabia, Kuwait, Qatar) as well as in Africa (Kenya, Nigeria, South Africa) and the USA.

Himani Agrawal, Senior Vice President, Hypothesis-OML, said, “At Hypothesis, we’re proud to offer a comprehensive kit for creator evaluation using 100+ data points. We provide the ultimate tool for your marketing arsenal. This is made even more convenient with our self-serve mode, empowering brands to initiate impactful influencer campaigns independently.”
Hypothesis streamlines data-driven influencer marketing globally, after recognising a critical disconnect between creator technology and services. Hypothesis was created with an inherent potential to serve a global audience, by empowering brands and agencies to transcend geographical limitations and unite discovery, outreach, and analytics in a single, user-friendly platform. This will accelerate the growth of the creator economy, creating opportunities for creators and brands.
Gunjan Arya, CEO of OML Entertainment, said, “We will be closely monitoring the milestones of Hypothesis to infiltrate the markets at the rate of 5–10% in the first year. We will also keep an eye on the acquisition rate, which is aimed to rise by 15–20%. Besides, we seek to derive over 35% of revenue from our global expansion efforts.”
With Hypothesis, OML is strategizing to expand into markets like Australia, the Asia–Pacific, the Middle East, and Africa, due to the region’s influencer marketing industry, which stands at 33.4% CAGR. Regions like the USA and the MENA have emerged as key players that are driven by advanced technologies and demand for data analytics.
Leveraging OML’s successful presence in Southeast Asia, the Middle East, Africa, and Eastern Europe, Hypothesis is set for a smooth rollout. OML’s established network, combined with their in-house expertise, will provide a strong foundation for this endeavor.
For details, visit hyp.io
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