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Machine Learning Market to Hit $419.94 Billion by 2030: Grand View Research, Inc.

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SAN FRANCISCO, July 17, 2023 /PRNewswire/ — The global machine learning market size is anticipated to reach USD 419.94 billion by 2030, according to a new report by Grand View Research, Inc. The market is expected to expand at a CAGR of 34.8% from 2023 to 2030. The market is experiencing continuous growth, driven by the increasing demand for AI-driven solutions across industries. It is expected to expand further as more organizations recognize the potential of machine learning and invest in its applications. The growing deployment of Edge AI is responsible for market growth. Edge AI reduces the reliance on cloud computing and provides faster response times, improved privacy, and bandwidth efficiency.

Key Industry Insights & Findings from the report:

  • The emergence of connected AI is anticipated to make it possible for ML algorithms to learn based on newly available information continuously. These developments are expected to propel the market expansion in the upcoming years. As these technologies continue to advance and mature, they are expected to have a transformative impact on various industries, shaping the way businesses operate, make decisions, and deliver value to customers.
  • The advertising & media segment dominated the market with a revenue share of 20.0% in 2022. The advertising and media sector accounted for the largest share in 2022 owing to capabilities such as buyer’s optimization, data processing, and analysis provided by the technology.
  • Factors such as advancements in computing power, increased data generation, and the need for automated decision-making drive the demand for machine learning solutions across various industries.
  • The Asia Pacific region is expected to grow at the fastest CAGR of 43.5% from 2023 to 2030. The region’s large population, diverse industries, and growing investment in technological infrastructure all contribute to market growth.

Read full market research report, “Machine Learning Market Size, Share & Trends Analysis Report By Component (Hardware, Software, Services), By Enterprise Size, By End-use (Advertising & Media, Healthcare, Retail), By Region, And Segment Forecasts, 2023 – 2030“, published by Grand View Research. 

Machine Learning Market Growth & Trends

Numerous companies are using machine learning (ML) in various industries to boost productivity, streamline processes, and facilitate decision-making. ML is used for personalized product recommendations, demand forecasting, fraud detection, inventory management, and pricing optimization. For instance, Netflix, Inc., a U.S.-based media-streaming and video-rental company, uses machine learning to enhance the customer experience. The company has long been using machine learning algorithms to personalize its viewer recommendations. E-commerce firms like Amazon.com, Inc, a U.S.-based multinational technology company, also uses ML for recommendation to boost sales.

Developments such as fine-tuned personalization, hyper-targeting, search engine optimization (SEO), no-code environments, self-learning bots, and others are expected to impact the machine-learning landscape significantly. These developments are responsible for the continuous evolution of machine learning applications, driven by the demand for personalized experiences, improved website rankings, efficient marketing strategies, accessibility, and intelligent automation.

For instance, Google LLC has significantly advanced machine learning, specifically in computer vision. Google’s research division, Google Research, has developed and deployed machine learning models such as the Inception series and the EfficientDet object detection model. These models have significantly enhanced the accuracy and performance of computer vision tasks, including image classification, object detection, and image segmentation.

Many industries in North America have adopted machine learning to gain insights from massive data and improve business operations. Machine learning is used in various sectors such as finance, healthcare, retail, manufacturing, and technology to perform tasks such as fraud detection, personalized marketing, predictive maintenance, and automated customer service. The growing adoption of cloud-based machine learning services in North America propels the market’s growth. The rise of cloud computing platforms, such as Amazon Web Services, Microsoft Azure, and Google Cloud, has made it easier for businesses to access and deploy machine learning tools and infrastructure.

Machine Learning Market Report Scope      

Report Attribute

Details

Market size value in 2023

USD 52.02 billion

Revenue forecast in 2030

USD 419.94 billion

Growth rate

CAGR of 34.8% from 2023 to 2030

Base year for estimation

2022

Historical data

2017 – 2021

Forecast period

2023 – 2030

 

Machine Learning Market Segmentation

Grand View Research has segmented the global machine learning market based on component, enterprise size, end-use, and region:

Machine Learning Market – Component Outlook (Revenue, USD Billion, 2017 – 2030)

  • Hardware
  • Software
  • Services

Machine Learning Market – Enterprise Size Outlook (Revenue, USD Billion, 2017 – 2030)

  • SMEs
  • Large Enterprises

Machine Learning Market – End-use Outlook (Revenue, USD Billion, 2017 – 2030)

  • Healthcare
  • BFSI
  • Law
  • Retail
  • Advertising & Media
  • Automotive & Transportation
  • Agriculture
  • Manufacturing
  • Others

Machine Learning Market – Regional Outlook (Revenue, USD Billion, 2017 – 2030)

  • North America
    • U.S.
    • Canada
  • Europe
    • Germany
    • UK
    • France
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
  • Latin America
    • Brazil
    • Mexico
  • Middle East and Africa
    • Kingdom of Saudi Arabia (KSA)
    • UAE
    • South Africa

List of Key Players in the Machine Learning Market

  • Amazon Web Services, Inc.
  • Baidu Inc.
  • H2O.ai.
  • Hewlett Packard Enterprise Development LP
  • Intel Corporation
  • Google LLC
  • International Business Machines Corporation
  • Microsoft Corporation
  • SAS Institute Inc.
  • SAP SE

Check out more related studies published by Grand View Research:

  • Artificial Intelligence Market – The global artificial intelligence market size is expected to reach USD 1,811.75 billion by 2030, expanding at a CAGR of 37.3% from 2023 to 2030, according to a new report by Grand View Research, Inc. Artificial Intelligence (AI) denotes the concept and development of computing systems capable of performing tasks customarily requiring human assistance, such as decision-making, speech recognition, visual perception, and language translation. AI uses algorithms to understand human speech, visually recognize objects, and process information.
  • Deep Learning Market – The global deep learning market size is expected to reach USD 526.7 billion by 2030, expanding at a CAGR of 33.5% from 2023 to 2030, according to a new report by Grand View Research, Inc. Deep learning is expected to gain sustainable momentum in the coming years owing to its high computational ability and improved complex data-driven applications. The growing emphasis on big data analytics and the adoption of Artificial Intelligence (AI) in customer-centric services is expected to propel the growth of the deep learning industry over the forecast period.
  • Natural Language Processing Market – The global natural language processing market size is estimated to reach USD 439.85 billion by 2030, expanding at a CAGR of 40.4% from 2023 to 2030, according to a new study by Grand View Research, Inc. Machine learning is predicted to play a critical role in natural language processing (NLP) techniques, mostly in text analytics, as AI advances. In the future, unsupervised and supervised learning will enable machine-learning engines to undertake more in-depth assessments. According to their ongoing evolution, social media platforms are expected to play a superior role in business decisions. A company, for instance, can rely on several NLP tools to track customer evaluations, feedback, and comments about their business on social media platforms and in the news around the time of a quarterly report.

Browse through Grand View Research’s Next Generation Technologies Research Reports.

About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research Helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

Contact:

Sherry James
Corporate Sales Specialist, USA
Grand View Research, Inc.
Phone: 1-415-349-0058
Toll Free: 1-888-202-9519
Email: [email protected]
Web: https://www.grandviewresearch.com
Grand View Compass | Market Trend Reports
Follow Us: LinkedIn | Twitter

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DTCC partners with Chainlink and JPMorgan to pilot blockchain integration for fund data

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As headlines spotlight spot Bitcoin (BTC) exchange-traded fund (ETF) flows and institutions revealing their exposure to BTC ETFs, financial service infrastructure providers are quietly integrating blockchain technology into their systems.

According to a recent report from the Depository Trust & Clearing Corporation (DTCC), the firm conducted a pilot program named Smart NAV in collaboration with Chainlink (LINK). This initiative aimed to extend the capabilities of DTCC’s Mutual Fund Profile Service I (MFPS I), the industry standard for transmitting ‘Price and Rate’ data, also known as ‘NAV data.’

DTCC’s Mutual Fund Services business currently operates MFPS I, offering fund companies an automated solution to deliver prices and daily distribution rates to numerous clients for tens of thousands of mutual fund securities. Traditionally, DTCC collects price and rate data from funds/service providers and distributors, then aggregates and disseminates it at regular intervals through its message queue (MQ) and file-based methods.

The Smart NAV Pilot served as a digital extension of the existing MFPS I service, aiming to broaden and complement its current capabilities. DTCC recognized the growing interest in mutual fund tokenization and saw an opportunity for on-chain price and rate data to facilitate new initiatives. Taking a ‘chain-agnostic’ approach, meaning the ability to disseminate NAV data across virtually any blockchain, was crucial for enabling other use cases to build upon Smart NAV’s foundations.

Ten market participants, including major names like American Century Investments, BNY Mellon, and JP Morgan, collaborated with DTCC and Chainlink on the pilot. They evaluated the feasibility and industry value of implementing a distributed ledger technology (DLT)-based price and rate dissemination solution to unlock new benefits and support experimentation in the asset management space.

The pilot results demonstrated that delivering structured data on-chain and establishing standard roles and processes enabled foundational data to be integrated into various on-chain use cases, such as tokenized funds and bulk consumer smart contracts. This capability can fuel future industry exploration and empower numerous downstream use cases, including brokerage portfolio applications.

The simplest application of Smart NAV is to provide trusted, verifiable data on virtually any blockchain network to support its use in business workflows. During the pilot, DTCC acted as both the provider and governor of the on-chain data solution, while Chainlink’s CCIP served as the interoperability layer. The core capability explored is adaptable across a wide range of use cases, potentially enhancing operational efficiency and streamlining processes.

Based on the positive findings, DTCC sees an opportunity to expand the scope of the pilot to explore broader use cases beyond price and rate data dissemination and across more blockchains.

Source: kitco.com

The post DTCC partners with Chainlink and JPMorgan to pilot blockchain integration for fund data appeared first on HIPTHER Alerts.

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Blockchain

Is Donald Trump’s Recent Crypto-Friendly Stance Genuine Or Opportunistic? Experts Weigh In

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Presidential candidate Donald Trump recently made a surprising endorsement of crypto, suggesting that he would ease hostility towards cryptocurrencies in the US if re-elected.

Trump stated, “If we’re going to embrace it, we have to let them be,” and urged crypto supporters to vote for him. This marks a significant shift from his previous criticisms of Bitcoin and other cryptocurrencies in 2019, where he labeled them as “not money” due to their volatility and lack of intrinsic value, expressing concerns about their potential use in illegal activities like drug trafficking.

Crypto’s Impact on Voter Preferences
With approximately 20% of American adults reportedly holding crypto, candidates are taking notice. Markus Levin of XYO Network sees embracing crypto and implementing solid regulation as a strategic move in elections and sound policy overall. He believes Trump’s apparent positive stance towards the industry will sway some voters in his favor.

Jonathan Thomas of Blueberry suggests that Trump’s crypto-friendly rhetoric may attract voters who prioritize crypto as a single-issue matter.

Skepticism Surrounding Trump’s Crypto Support
However, not everyone is convinced by Trump’s newfound endorsement of crypto. NFT enthusiast Thorne Melcher views it as “flimsy” and warns against the potential for conservative politics to restrict crypto due to its use in areas such as trans hormone replacement therapy and abortions.

While some may see Trump’s support for crypto as a reason to vote for him, others like Stephanie Vaughan of Veda caution against assuming substantial benefits from this endorsement alone. Vaughan highlights the Biden Administration’s hardline stance on crypto regulation by enforcement, which she believes is unworkable and could push voters towards Trump.

Trump’s Strategy to Attract Crypto Voters
Trump’s pivot from crypto skeptic to NFT enthusiast reflects a strategic move to appeal to voters interested in crypto. Vaughan suggests that many crypto-focused voters may have supported Biden in the last election, but Trump is actively courting them by recognizing the industry’s significance.

By acknowledging crypto’s growing influence on voters, Trump aims to draw support away from Biden, positioning himself as the candidate more aligned with the interests of the crypto community.

Source: cryptonews.com

The post Is Donald Trump’s Recent Crypto-Friendly Stance Genuine Or Opportunistic? Experts Weigh In appeared first on HIPTHER Alerts.

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droppGroup Unveils Platform with AI-Blockchain Integration

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droppGroup, a trailblazer in amalgamating blockchain and artificial intelligence, has unveiled droppLink, an innovative service platform poised to potentially revolutionize AI management and development across various blockchains. The architecture of droppLink empowers users with control over data contributions, abstracts computational requirements, and streamlines micropayments.

Stakeholders, dubbed Computational Resource Patrons (CRPs), contribute to the infrastructure costs and share profits from the facilitated AI operations.

As a web3 development firm, droppGroup specializes in deploying patented innovations in AI, machine learning (ML), object recognition, streaming, crypto, augmented reality (AR), virtual reality (VR), and mixed reality (MR). droppGroup is now advancing multi-modal AI systems with droppLink.

Gurps Rai, co-founder and CEO of droppGroup, explains that droppLink tokenizes each stage in an AI model’s lifecycle across multiple blockchains, such as Solana, Polygon, Ethereum, Base, and Hyperledger Fabric 2.5, ensuring unparalleled data integrity and expediting AI development.

Rai added, “This process upholds data ownership rights while establishing a transparent, immutable usage record via our Proof of Gen and Data Genesis protocols.”

Christopher J. Kelly, co-founder and president of droppGroup, underscores the company’s commitment to pushing the boundaries of multi-modal AI systems at the convergence of physical and digital realms, introducing cutting-edge solutions to the market.

Scheduled to speak on the monitoring and evaluation panel at the AWS Summit on May 22, Kelly will address topics like data integrity in AI and its alignment with the company’s mission.

With the AI market projected to reach $297 billion by 2027, ethical considerations such as data provenance, intellectual property protection, and fair compensation are paramount.

Accessible through droppPhygital, droppLink leverages multi-chain integration and robust tokenization to bolster data integrity. By melding blockchain technology with artificial intelligence, droppLink establishes an ethical management layer, aiming to reshape the AI landscape by fostering trust, transparency, and innovation.

Source: cryptotimes.io

The post droppGroup Unveils Platform with AI-Blockchain Integration appeared first on HIPTHER Alerts.

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