Artificial Intelligence
Insights on the Federated Learning Global Market to 2028 – Enhanced Data Privacy in Numerous Applications is Driving Growth
Dublin, Nov. 22, 2022 (GLOBE NEWSWIRE) — The “Global Federated Learning Market Size, Share & Industry Trends Analysis Report By Application, By Vertical, By Regional Outlook and Forecast, 2022 – 2028” report has been added to ResearchAndMarkets.com’s offering.
The Global Federated Learning Market size is expected to reach $198.7 Million by 2028, rising at a market growth of 11.1% CAGR during the forecast period.
Federated learning can be described as a machine learning approach that distributes an algorithm among a number of decentralized end devices or servers that each have local data samples. This strategy differs from standard centralized machine learning methods, which store all local datasets on a single server. Additionally, this technique ensures that the local data samples are disseminated to the server in the same way.
Federated learning can be utilized to build consumer behavior models from the data pool of smartphones without revealing personal information, like for next-word prediction, voice recognition, facial identification, and other applications. Federated learning enables various vendors to develop a shared machine learning algorithm without sharing data, allowing crucial issues like data access rights, data privacy and security, and the capacity to access heterogeneous data to be addressed. Defense, telecommunications, and medicines are among the businesses that can leverage federated learning to optimize their operations.
The growing need for improved data protection and privacy, as well as the increasing requirement to adapt data in real-time to optimize conversions automatically are driving the advancement of the federated learning solutions market. Moreover, by retaining data on devices, these solutions assist organizations in leveraging machine learning models, boosting the federated learning market forward.
Furthermore, the ability to provide predictive features on the latest smart devices without compromising the consumer experience or divulging private information is providing lucrative opportunities for the federated learning market to develop throughout the coming years.
COVID-19 Impact Analysis
COVID-19 is an unprecedented global public health crisis that has impacted practically every business, and its long-term repercussions significantly impacted various markets in numerous countries all over the world. In addition, governments across the world imposed lockdown in their countries in order to regulate the diffusion of the hazardous COVID-19 infection.
These lockdowns caused major disruptions in the worldwide supply chain of all the products and services due to travel restrictions. The infection was rapidly spreading all over the world, creating economic stagnation and compelling thousands of employees to work from home. However, artificial intelligence, as well as machine learning, were majorly used to forecast and investigate the spread of potential data alarms in several countries all over the world.
Market Growth Factors
Enhanced data privacy in numerous applications
Due to federated learning, the manner in which ML approaches are offered is evolving. Companies are increasing their efforts on performing a thorough investigation of federated learning. Using federated learning, companies may reinforce their existing algorithms and improve their AI applications.
The demand for improved learning is increasing among both gadgets and companies. In the healthcare field, federated learning could help healthcare personnel deliver high-quality outcomes while also accelerating drug development. For example, FADNet, a new peer-to-peer technique, is a remedy for centralized learning inadequacies.
Enables collaborative learning among various users
Federated learning, rather than keeping data on a single computer or data mart, stores data on original sources, like smartphones, manufacturing detection equipment, other end devices, and machine learning machines are trained on the go. This aids in decision-making before being sent back to a centralized computer. For example, federated learning is widely used in the finance sector for debt risk assessments.
Typically, banks use whitelisting processes to keep customers out of the Federal Reserve System based on their credit card information. Risk assessment variables, like taxation and reputation, may be employed by working with other financial institutions and eCommerce businesses.
Market Restraining Factors
Scarcity of skilled technical professionals
Many businesses encounter a significant impediment when integrating machine learning into existing workflows due to a scarcity of trained people, particularly IT specialists. Because federated learning systems are a new concept, it is difficult for personnel to grasp and execute them.
Recruiting and maintaining technical skills became a major concern for several firms due to a scarcity of skilled candidates to incorporate federated learning projects that include difficult methodologies, such as machine learning. As an organization, they must develop a growing range of talents and job titles. Organizations, for example, require experts that can administer and comprehend the current federated learning architecture connected with the installation and maintenance of machine learning algorithms.
| Report Attribute | Details |
| No. of Pages | 244 |
| Forecast Period | 2021 – 2028 |
| Estimated Market Value (USD) in 2021 | $98 Million |
| Forecasted Market Value (USD) by 2028 | $199 Million |
| Compound Annual Growth Rate | 11.1% |
| Regions Covered | Global |
Key Topics Covered:
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis – Global
3.1 KBV Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.3.2 Key Strategic Move: (Product Launches and Product Expansions : 2018, Dec – 2021, Dec) Leading Players
Chapter 4. Global Federated Learning Market by Application
4.1 Global Drug Discovery Market by Region
4.2 Global Risk Management Market by Region
4.3 Global Online Visual Object Detection Market by Region
4.4 Global Data Privacy & Security Management Market by Region
4.5 Global Industrial Internet of Things Market by Region
4.6 Global Augmented Reality/Virtual Reality Market by Region
4.7 Global Shopping Experience Personalization Market by Region
4.8 Global Other Application Market by Region
Chapter 5. Global Federated Learning Market by Vertical
5.1 Global Healthcare & Life Sciences Market by Region
5.2 Global BFSI Market by Region
5.3 Global IT & Telecommunication Market by Region
5.4 Global Energy & Utilities Market by Region
5.5 Global Manufacturing Market by Region
5.6 Global Automotive & Transportation Market by Region
5.7 Global Retail & Ecommerce Market by Region
5.8 Global Others Market by Region
Chapter 6. Global Federated Learning Market by Region
Chapter 7. Company Profiles
7.1 IBM Corporation
7.1.1 Company Overview
7.1.2 Financial Analysis
7.1.3 Regional & Segmental Analysis
7.1.4 Research & Development Expenses
7.1.5 Recent Strategies and Developments
7.1.5.1 Product Launches and Product Expansions:
7.2 Microsoft Corporation
7.2.1 Company Overview
7.2.2 Financial Analysis
7.2.3 Segmental and Regional Analysis
7.2.4 Research & Development Expenses
7.2.5 Recent Strategies and Developments
7.2.5.1 Product Launches and Product Expansions:
7.2.5.2 Acquisitions and Mergers:
7.3 Intel Corporation
7.3.1 Company Overview
7.3.2 Financial Analysis
7.3.3 Segmental and Regional Analysis
7.3.4 Research & Development Expenses
7.3.5 Recent strategies and developments:
7.3.5.1 Partnerships, Collaborations and Agreement:
7.4 Google LLC
7.4.1 Company Overview
7.4.2 Financial Analysis
7.4.3 Segmental and Regional Analysis
7.4.4 Research & Development Expense
7.4.5 Recent Strategies and Developments
7.4.5.1 Product Launches and Product Expansions:
7.5.5 Recent strategies and developments:
7.5.5.1 Partnerships, Collaborations and Agreements:
7.6 NVIDIA Corporation
7.6.1 Company Overview
7.6.2 Financial Analysis
7.6.3 Segmental and Regional Analysis
7.6.4 Research & Development Expense
7.6.5 Recent strategies and developments:
7.6.5.1 Partnerships, Collaborations and Agreements:
7.6.6 SWOT Analysis
7.7 Edge Delta, Inc.
7.7.1 Company Overview
7.7.2 Recent strategies and developments:
7.7.2.1 Product Launches and Product Expansions:
7.8 DataFleets Ltd. (LiveRamp Holdings, Inc.)
7.8.1 Company Overview
7.9 Enveil
7.9.1 Company Overview
7.9.2 Recent strategies and developments:
7.9.2.1 Product Launches and Product Expansions:
7.10. Secure AI Labs, Inc.
7.10.1 Company Overview
For more information about this report visit https://www.researchandmarkets.com/r/3xkp8q
Attachment
WESTBOROUGH, Mass., April 16, 2024 /PRNewswire/ — The Channel Company, a global provider of news, insights, strategy, events, and marketing services for the information technology industry, announced today that Wayne Silverman has joined the executive team as Chief Revenue Officer. Silverman will lead all aspects of The Channel Company’s worldwide revenue growth initiatives, sales strategy innovation, and customer engagement.
Silverman joins The Channel Company most recently from Spiceworks Ziff Davis (SWZD), where he served as Chief Revenue Officer. He also brings more than 25 years of digital media, technology, SaaS, and big data experience within global roles. Silverman has driven revenue innovation and growth across prominent companies including CBS, Dun & Bradstreet, International Data Group (IDG), CNET, and Business.com where he held senior leadership positions.
“We are thrilled to welcome Wayne to the team,” said Matthew Yorke, CEO of The Channel Company. “His global expertise within the technology and digital media industries alongside his unwavering dedication to customer experience will continue to elevate how we deliver for our clients and drive expanded opportunities for our organization.”
“It’s a privilege to step into the role of CRO at The Channel Company during such a pivotal period for the company,” Silverman stated. “As we look ahead, the tech sector is poised for a transformation with artificial intelligence taking center stage. The Channel Company, with its esteemed media outlets, signature events, and expert marketing and consulting offerings, will be instrumental for our partners, clients, and the entire tech community. I am eager to collaborate with the talented team here at The Channel Company to deliver innovative, outcome-driven services to our clients as this market evolves.”
About The Channel Company
The Channel Company, Inc. is the global leader in data-driven growth acceleration solutions and services for the IT channel. With 40+ years of channel expertise and a premier portfolio of editorial brands, marketing and event services, and strategic consulting, we help technology vendors, solution providers, and IT decision-makers worldwide unlock better business outcomes. The Channel Company is a portfolio company of investment funds managed by EagleTree Capital, a New York City-based private equity firm. For more information, visit thechannelco.com.
About EagleTree Capital:
EagleTree Capital is a leading New York-based middle-market private equity firm, with over $5.6 billion of assets under management, that has completed over 40 private equity investments and over 95 add-on transactions over the past 20+ years. EagleTree primarily invests in North America in the following sectors: media and business services, consumer, and water and specialty industrial. For more information, visit www.eagletree.com or find EagleTree on LinkedIn.
Media contact: Corporate Communications, [email protected]
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Artificial Intelligence
vLex Launches Vastly Expanded Vincent Legal GenAI Toolset, and AI-Focused Co-Development Lab
Global Legal Intelligence Innovator Adds Litigation and Transactional GenAI Tools, and vLex Labs, an AI-Focused Co-Development Unit
MIAMI, April 16, 2024 /PRNewswire/ — Today legal intelligence innovator vLex launched a powerful suite of generative AI-backed document analysis tools for litigation and transactional practitioners to the Vincent AI platform. Vincent AI Document Analyze augments lawyers’ responses to legal documents, drawing from the world’s most comprehensive global library of legal information.
In addition, vLex now offers vLex Labs to select Vincent customers – enabling them to create proprietary AI-powered workflows with the help of a dedicated team.
These developments underscore vLex’s commitment to developing innovative legal research solutions that go beyond retrieval to revolutionize how legal professionals work.
“With Vincent AI, you no longer have to choose between innovative technology and comprehensive content,” said vLex CEO Lluís Faus. “Our platform offers a seamless integration of both, setting a new standard in efficiency, customization, and effectiveness across all legal practices.”
Vincent AI Document Analyze
Vincent AI Document Analyze offers customizable GenAI-backed workflows that enable legal professionals to interrogate legal documents and use Vincent’s legal analysis abilities to begin drafting strategic responses. Benefits include:
Rapid Analysis: Vincent summarizes documents, and compares law across jurisdictions, replacing hours of non-billable time in minutes.Rapid Response: Vincent analyzes claims, generates defenses, and anticipates counterarguments.Streamlined Contract Analysis: Vincent instantly carries out tasks such as identifying problematic clauses, and providing mitigation steps.All insights are linked to primary and secondary law materials in vLex’s global repository, enabling verification with one click.
The new document analysis feature can be used with documents from any region. Vincent AI’s research workflows are available to legal professionals in the US, the UK, Ireland, Spain, the EU, Singapore, Mexico, Chile, and Colombia, with New Zealand launching in May 2024.
vLex Labs
vLex also launched vLex Labs – an exclusive in-house service that provides Enterprise customers access to leading experts on legal AI, uniting industry leaders such as Fastcase, Docket Alarm, Justis, and NextChapter.
Leading the team will be Dan Hoadley, who recently joined vLex as Head of R&D. The team will have a global scope, and work with firms to co-develop custom workflows, prepare data, and more.
About vLex
vLex is a global legal intelligence platform that provides legal professionals with access to the most extensive collection of legal and regulatory information worldwide, all on one award-winning, AI-powered, platform. vLex includes the Fastcase, Docket Alarm and NextChapter brands, and is trusted by more than two million lawyers, researchers, government departments, and law schools in more than 200 jurisdictions. The 2023 merger with Fastcase furthered vLex’s commitment to developing AI-driven solutions for the world’s legal industry and delivering the world’s largest global law library of over one billion legal documents on a single platform. Get updates at https://vlex.com/press and on Twitter @vlex.
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Artificial Intelligence
Atomicwork Launches New Digital Workplace Experience Solution Powered by Cohere’s Enterprise AI Platform
SAN FRANCISCO, April 16, 2024 /PRNewswire/ — Atomicwork, the leading provider of AI-powered IT service management for modern enterprises, has announced the launch of its new digital workplace experience solution in collaboration with Cohere, the leading enterprise AI platform, to help businesses accelerate their workspace productivity and IT support automation.
Atom AI, Atomicwork’s digital assistant, delivers intelligent and contextual solutions to employee support questions to enhance workplace support experience and boost IT teams’ productivity. The solution eliminates the need for end users to switch between different business applications to find information, and enables them to get instant help on modern collaboration tools like Microsoft Teams or Slack, fostering efficient and proactive support.
Key highlights of the launch include:
Advanced AI Automation: Built-in Atom AI skills that autonomously solve end to end IT support issues by understanding end users’ work context, delivering true self-service for employees while accelerating efficiency for IT teams.Enhanced Employee Productivity: Advanced enterprise knowledge and search capabilities across a host of business applications and internal knowledge bases, delivered in the flow of an employee’s work, to help them find the right information quickly, boosting employee productivity and experience.Seamless Enterprise IT Integration: Embedded iPaas in the Atomicwork platform enabling IT teams to seamlessly integrate business applications and internal services to deliver modern enterprise service management use cases while reducing IT integration complexity.Atomicwork’s launch of the digital workspace experience solution is powered by Cohere, and their most advanced and scalable large language model, Command R+. Purpose-built for real-world enterprise use cases, Command R+ along with Cohere’s Rerank model, enables Atomicwork to deliver Atom AI with high accuracy and performance.
Commenting on the launch of a digital workplace experience solution and the collaboration with Cohere, Vijay Rayapati, Atomicwork’s CEO, stated, “We want to empower IT leaders to transform their digital experience journey with our new solution. This strategic collaboration of Atomicwork with Cohere enables us to deliver advanced and secure enterprise AI capabilities for our clients to streamline business workflow automations.”
“We’re excited Atomicwork is using Cohere’s industry-leading Command R model family to power their new digital workplace experience solution. Atomicwork’s software has the potential to significantly boost productivity for enterprise IT teams. We look forward to seeing the real-world benefits leaders like Atomicwork develop with our technology to help transform the global IT sector with AI,” said Abhishek Sinha, VP of Product at Cohere.
“Cohere’s new Command-R+ model delivers state-of-the-art accuracy, while offering a remarkable 50% reduction in latency when compared to more expensive models. This powerful combination of performance and efficiency empowers our AI-first approach to unlock new possibilities and provide exceptional experiences for our customers,” said Kiran Darisi, CTO, Atomicwork.
About Atomicwork
Atomicwork is a digital workplace experience platform that aims to deliver modern service management to enterprises. The platform empowers businesses to deliver fast and scalable internal support for their employees and end users, thereby enhancing employee experience with enterprise efficiency. Seamlessly integrating with existing enterprise applications and internal IT systems, Atomicwork connects employees, internal processes, and business systems, enhancing efficiency in workplace support, service, and operations.
About Cohere
Cohere is the leading AI platform for enterprise. Its world-class AI is uniquely suited to the needs of business, unlocking unprecedented ease-of-use, accessibility, and data privacy. Cohere’s platform is cloud-agnostic, accessible through API as a managed service, and can be deployed on virtual private cloud (VPC) or even on-site to meet companies where their data is, offering the highest levels of flexibility and control. Founded by Google Brain alumni and a co-author of the seminal Transformer research paper, Cohere is on a mission to transform enterprises and their products with AI that unlocks a more intuitive way to generate, search, and summarize information than ever before.
Press contact
Sairam [email protected]
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