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AI Training Dataset Market worth $9.58 billion by 2029 – Exclusive Report by MarketsandMarkets™

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DELRAY BEACH, Fla., Oct. 24, 2024 /PRNewswire/ — The AI Training Dataset Market is slated to expand from USD 2.82 billion in 2024 to USD 9.58 billion by the year 2029 at a robust CAGR of 27.7% over the forecast period, according to a new report by MarketsandMarkets™.

Browse in-depth TOC on “AI Training Dataset Market”

487 – Tables
66 – Figures
446 – Pages

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Scope of the Report

Report Metrics

Details

Market size available for years

2019–2029

Base year considered

2023

Forecast period

2024–2029

Forecast units

USD (Billion)

Segments covered

Offering, Dataset Creation, Dataset Selling, Type, Data Modality, Annotation Type, End User, and Region

Geographies covered

North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

Companies covered

Google (US), IBM (US), AWS (US), Microsoft (US), NVIDIA (US), Snorkel (US), Gretel (US), Shaip (US), Clickworker (US), Appen (Australia), Nexdata (US), Bitext (US), AIMLEAP (US), Deep Vision Data (US), Cogito Tech (US), Sama (US), Scale AI (US), Lionbridge Technologies (US), Alegion (US), TELUS International (Canada), iMerit (US), Labelbox (US), V7Labs (UK), Defined.ai (US), SuperAnnotate (US), LXT (Canada), Toloka AI (Netherlands), Innodata (US), Kili (France), HumanSignal (US), Superb AI (US), Hugging Face (US), CloudFactory (UK), FileMarket (Hong Kong), TagX (UAE), Roboflow (US), Supervise.ly (Estonia), Encord (UK), TransPerfect (US), Keylabs (Israel), and data.world (US).

The market for AI training datasets has gained substantial traction, with the major catalyst being the need for fair and unbiased datasets. Enterprises are gradually realizing the implications of bias within the dataset. Such bias was highlighted in the case of the Apple Card, where women were given lower credit limits than men due to biased training data embedded in the credit disbursal algorithms. Large language models have also been criticized for making negative stereotypes, such as when OpenAI’s GPT-3 unintentionally linked objectionable words to certain ethnic groups. These cases stress the need for curating well-balanced training datasets that adequately capture real life scenarios; and are inclusive as well. Other factors helping the market growth include the rise of synthetic data to address privacy concerns and scarcity issues, allowing industries like healthcare and autonomous vehicles to simulate rare scenarios. Other pivotal market trends include the progressively increasing use of multimodal datasets, to power virtual assistants and smart gadgets that require the simultaneous processing of text, images and audio.

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By offering, dataset creation segment will account for largest market share in 2024 owing to high demand for accurately labelled datasets.

The market for data labeling & annotation software is expected to hold major market share in 2024, spurred along by the rising need for accurate and precisely labelled data. One of the main factors for growth is the rising demand for context-specific annotations that go beyond basic labeling. Companies like Tempus Labs are using intricately labeled genomic and clinical data to develop precision medicine AI tools, requiring highly detailed and specialized annotations from medical experts. Furthermore, with the introduction of AI-powered annotation automation tools such as SuperAnnotate, the AI annotation is combined with human annotators, creating a human-in-the-loop (HITL) system that enhances workflow efficiency. This has become a popular trend as organizations want to reduce the amount of manual work while maintaining good standards. For example, Aptiv is leveraging such HITL datasets for training advanced driver-assistance systems (ADAS). Another major factor is the progressive increase in the adoption of multimodal data, which require highly accurate and robustly annotated dataset across various modalities.

Rising consumption of high-quality datasets to develop domain-specific AI models will push software & technology providers as the fastest growing end user segment during the forecast period

The software and technology providers segment is experiencing the fastest growth in the AI Training Dataset Market, driven by increasing demand for scalable and high-quality dataset creation solutions. These providers, especially cloud hyperscalers like AWS and Google Cloud, are leveraging massive datasets to enhance AI offerings like voice recognition, computer vision, and natural language processing. Microsoft Azure, for instance, has launched several services like Azure Machine Learning that take advantage of large amounts of data to train advanced AI models. Foundation models providers, such as Cohere and Anthropic, are also investing a lot of resources into the procurement of datasets in order to train and custom design LLMs. Furthermore, IT services companies are developing end-to-end data pipelines for their customers, allowing them to scale AI applications with ethically sourced and unbiased training datasets. The segment’s robust expansion is also aided by the growing use of industry specific datasets for niche applications like AI in cyber security and supply chain analytics.

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North America is set to hold the largest market share in 2024, fueled by a strong regulatory environment and increasing investments in responsible AI deployment

North America has emerged as the largest regional market for AI training dataset, owing to hefty R&D investments being poured into AI. As reported in the 2022 US budget, the federal AI spending of the US government was greater than USD 3.3 billion dollars, which created a demand for quality training datasets. The region’s strong focus on advancing large-scale AI models like GPT-4 by OpenAI and DeepMind’s AlphaFold also showcases the requirement for multimodal and high-quality training datasets to develop such models. Also, the existence of cloud hyperscalers like AWS, Microsoft Azure, and Google Cloud has sped up the provision of scalable AI solutions, including data annotation and management, as part of their cloud services. In Canada, companies like Element AI (acquired by ServiceNow) are creating sophisticated AI models for sectors like finance and logistics, driving the need for reliable datasets to ensure precision and effectiveness.

This trend is also assisted by the North American regulatory landscape, which favors responsible artificial intelligence practices, increasing the market demand for data sets that are both transparent and free from bias. A similar trend is reflected in California’s Automated Decision Systems Accountability Act (AB-13) which seeks to ensure that AI systems are fair and accountable.

Top Key Companies in AI Training Dataset Market:

The major players in the AI Training Dataset Market include Scale AI (US), Appen (Australia), Lionbridge Technologies (US), AWS (US), and Sama (US), along with SMEs and startups such as Snorkel AI (US), V7 Labs (UK), Alegion (US), Toloka AI (US), and iMerit (US).

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Karma Automotive Announces Eximius, the Bespoke Vehicle Program for Elite Clients Seeking Singular Expressions of Extreme Performance and Bold Craftsmanship

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The First Eximius Creation, “Eximius 1,” is a Menacing Four-Seater Built for the Track which Makes its World Premiere at the 2026 Concours at Wynn Las Vegas

LAS VEGAS, Oct. 31, 2026 /PRNewswire/ — Karma Automotive builds vehicles in the hundreds rather than the thousands, attracting a highly individualistic clientele seeking a unique statement. For those who wish to go further still, and explore new possibilities beyond the extensive options for personalization available through the Studio program, Karma has created the Eximius bespoke vehicle program. Eximius clients may modify the vehicle’s body, performance and powertrain, collaborating with Karma’s design and engineering teams to build a One-of-One statement which will never be repeated.

Karma Eximius clients may modify the vehicle’s body, performance and powertrain to build a One-of-One statement

The first vehicle from Karma Eximius debuts today at the 2026 Concours at Wynn Las Vegas. A menacing four-seater purpose-built for the track, “Eximius 1” is in ongoing development with its commissioning client, who is not revealed at this time. Upon delivery in 2027, “Eximius 1” will be fitted with an extreme-performance Plug-in Series Hybrid utilizing a 6.2 Liter V8 producing nearly 1200hp (550hp ICE, 645hp battery), delivering acceleration from 0-60mph in 2.7 seconds and a top speed in excess of 200mph (estimated). As these parameters would demand, “Eximius 1” will be equipped with carbon-ceramic brakes and two-piece slotted brake rotors, and Ohlins semi-active suspension.

“‘Eximius 1’ began as a conversation with an elite client who loves their Karma Revero, but wanted something more extreme and unexpected, which was music to our ears,” says Marques McCammon, President and Chief Executive, Karma Automotive. “The Eximius program effectively deletes the word ‘no’ from conversations about what’s possible,” he continues, “and as a four-seat track weapon packing what’ll be the most powerful Plug-in Series Hybrid powertrain and vehicle ever developed, ‘Eximius 1’ shatters expectations and further establishes Karma as a manufacturer of exotic, uniquely American vehicles.” 

Exterior Design
“Eximius 1” is an imposing vehicle to behold, exhibiting the muscularity and eyepopping strength of a superhero. Every panel – excluding the body surface outer – is constructed of pre-impregnated carbon fiber, and the vehicle is 50mm wider due to its wheel arch extensions. The front doors and hood have a unique technical fade from glossy, exposed regular carbon fiber to signature Borealis Blue paint.

The front carbon splitter sets an aggressive tone and is flanked by massive side air intakes incorporating Karma’s Target Acquisition Lighting, rotated 45º to create a distinctive ‘><‘ DRL graphic identity. On the hood, the dramatic arc of the Comet Line – which is inspired by Halley’s Comet is it streaks across the evening sky – widens from its apex towards the base of the windshield; vents above the front fenders release air pressure from the wheel housings and add further visual intrigue. Moving to the side of the vehicle, the front fenders aft of the wheels feature Karma’s signature “Backslash” bearing the number “5,” which is of particular significance to the commissioning client. 21″ Magnesium wheels with center-locks reduce rotating and unsprung mass, and are finished in satin black. Aft of the driver’s side front wheel, twin exhaust tips announce the fearsome new powertrain.

The full-width rear GT wing maximizes stability and downforce at high speeds, and continues the distinctive ‘><‘ DRL graphic identity established at the front of “Eximius 1.” The rear fascia also boasts large side air intakes which are connected by a dominant diffuser to manage underbody airflow.

Interior Design
An aura of intensity continues to the interior of “Eximius 1.” In concert with the exterior, blue-tinted carbon-fiber adorns the seats, flat-bottom steering wheel and doors; for aesthetics and weight-savings, all four doors are manufactured in exposed carbon fiber with one purposeful arm pad on each door. The seats, which are Recaro carbon fiber buckets up front, are trimmed with blue Alcantara and blue Italian leather with Moondust Alcantara upper sections, creating an articulated, form-fitted feel. To support high-speed driving and intense braking force, the accelerator, brake pedal and dead pedal are billet machined aluminum.

The instrument panel is reimagined in glossy carbon fiber and incorporates anodized billet aluminum HVAC vents. The carbon fiber center console is simplified to include the essentials only: the PRND gear selector, window switches, key fob holder, and Emergency kill switch. This console extends through to the rear compartment, to which the client’s custom-fitted carbon fiber racing helmet is held in place by a center-latched strap matching the blue seat belts.

About Karma Automotive
Karma Automotive is America’s only full-line ultra-luxury vehicle manufacturer, and a pioneer of Plug-in Series Hybrid vehicles which it manufactures at its Karma Innovation and Customization Center (KICC) in Moreno Valley, CA. Its Executive, Product Development, and Design headquarters are located in nearby Irvine, CA. The Karma portfolio embodies California’s spirit of innovation and entrepreneurial boldness, reflected by the signature Comet Line which is the central hallmark of Karma’s new design language. The Gyesera Grand Coupe, a Plug-in Series Hybrid four-seater, arrives at dealerships in December 2026; and the Amaris GT 2-Door Plug-in Series Hybrid arrives in Q4 2027. The Karma Kaveya Super Coupe, with over 1,000HP and butterfly-doors, will arrive in Q1 2028, to be followed by the Karma Ivara GT-UV: both EVs will incorporate SDVA (Software-Defined Vehicle Architecture) developed with leading technology partners. For more information, visit www.karmaautomotive.com) 

Media Contact:

Joe Richardson, (917) 716-6617
Joe@BeautifulNoisePR.com 

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ModelBest and OpenBMB Open-Source MiniCPM-OCR Series, Delivering High-Performance Document Parsing and AI-Powered Quality Control

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BEIJING, Oct. 31, 2026 /PRNewswire/ — ModelBest and OpenBMB jointly announced the release and open-source availability of the MiniCPM-OCR series, a family of models for efficient document parsing and parsing-quality assessment. The launch includes two models: MiniCPM-OCR 1.0 (1.3B) and MiniCPM-OCR Jev (2B).

As the first OCR-focused model in the MiniCPM family, MiniCPM-OCR 1.0 brings top-tier parsing accuracy to a compact 1.3-billion-parameter architecture optimized for edge deployment, pushing forward the balance between efficiency and performance for open-source OCR models. Built for real-world conditions, it accurately parses scanned, photographed, curved, tilted and screen-captured documents without cumbersome image pre-correction, lowering the barrier to large-scale document digitization.

The model handles dense bilingual Chinese-English content, complex mathematical formulas, and multi-level or borderless tables, consistently performing at a leading level across a broad range of mainstream industry evaluations. Beyond full-page reconstruction, it supports key information extraction (KIE), pulling specified fields from invoices, IDs and financial statements according to business instructions.

Powered by DSpark decoding acceleration, MiniCPM-OCR 1.0 significantly increases end-to-end throughput while lowering per-page latency. For enterprises processing millions of pages—such as financial contract archives, academic libraries and government records—this means processing far more documents with the same hardware and time budget, at a substantially lower computing cost.

To address the long-standing need for page-by-page manual review, ModelBest and OpenBMB also introduced MiniCPM-OCR Jev, the first OCR result decision model that acts as an “AI quality inspector.” Rather than performing OCR itself, Jev compares the source image with OCR output and rapidly assigns confidence scores to text, LaTeX formulas and tables, detecting missing characters, errors and formatting misalignments. Despite its compact 2B-parameter size, Jev delivers judgment accuracy typically associated with far larger models.

Jev supports cross-model deployment and can be integrated into existing OCR workflows without replacing the underlying OCR engine. It can automatically identify reliable results for direct processing, flag potentially inaccurate outputs for human review and select the best result from multiple OCR systems. This enables enterprises to move from full manual inspection toward risk-based, automated quality control.

The MiniCPM-OCR series is available on GitHub, Hugging Face and ModelScope, and supports vLLM, SGLang, llama.cpp and Ollama, along with SDKs, APIs, Agent Skill plugins and open-source fine-tuning code. Day-0 hardware adaptation covers AMD, Arm, Houmo AI, Intel and NVIDIA. Through the FlagOS software stack, it also has Day-0 support for AI and edge chips from CIX Technology, Huawei Ascend, Hygon, Iluvatar CoreX, Kunlunxin, MetaX, Moore Threads, Sunrise, T-Head, TsingMicro, NVIDIA and Apple Mac (Arm).

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SOURCE ModelBest

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Wulcea Elevates Consumer Trust in Heated Apparel Through Multi-National Safety Certifications and Rigorous Technical Testing

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NEW YORK, Oct. 31, 2026 /PRNewswire/ — As smart heated clothing gains broader adoption, consumers are paying closer attention to the safety and reliability of the technology behind these products. Wulcea, a brand specializing in graphene-powered heated apparel, combines its flexible GrapheneNano™ heating technology with documented safety compliance and durability testing for its heating components and battery systems.

“Trust in smart heated apparel goes beyond warmth—it comes down to confidence in battery safety and heating element reliability,” said John C, Founder of Wulcea. “Our goal is to give users peace of mind through certified technical standards.”

Advanced Graphene Heating Elements Supported by Global Standards

At the core of Wulcea’s thermal architecture is its GrapheneNano™ heating technology. Engineered to eliminate garment stiffness, Wulcea integrates flexible graphene elements that deliver balanced warmth across key upper-body zones while preserving natural garment drape and full freedom of movement.

Wulcea supports its heating components with applicable compliance documentation for major markets. These include CE and FCC compliance documentation addressing relevant electrical and electromagnetic compatibility requirements, as well as PSE compliance for applicable products in Japan. RoHS compliance further addresses restrictions on specified hazardous substances in applicable electrical and electronic components.

Multi-Certified Battery System for Dependable Power

To power its heating elements, Wulcea pairs its heated apparel with rechargeable battery systems designed for convenient everyday use. Featuring a compact design and housed in dedicated interior pockets, the batteries provide portable power while maintaining a streamlined garment profile and comfortable fit.

Wulcea backs its battery options with comprehensive third-party accreditations. UL certification demonstrates that the battery system has been evaluated against recognized power bank safety requirements, covering key areas such as overcharge protection, short-circuit protection, and thermal safety. The battery systems are also supported by applicable CE and FCC compliance documentation, addressing relevant regulatory requirements for electrical and electromagnetic compatibility.

For daily handling and travel, RoHS compliance validates that the battery system meets stringent global standards for material safety. The battery models have also undergone applicable UN 38.3 testing, supporting compliance with international requirements for lithium battery transportation.

Real-World Durability and Practical Usability

Component compliance forms Wulcea’s foundation, but reliability is defined by real-world performance. Built for high-flex endurance, Wulcea’s flexible graphene heating elements are tested through 10,000 active flexing cycles to maintain steady thermal output through repeated bending and everyday body movement.

Everyday convenience is equally essential. Built for hassle-free care, Wulcea’s heating elements withstand 100 machine-wash cycles under standard care guidelines, maintaining internal conductivity and structural stability under repeated laundering.

Integrated NTC temperature sensors provide thermal monitoring and are designed to stop heating if temperatures exceed 131°F (55°C). Combined with runtime of up to 10 hours on the low setting and a discreet interior control button, these features support practical everyday use in cold-weather conditions.

Aligning Technical Standards with Everyday Warmth

By combining graphene-based heating technology with documented battery safety compliance and durability testing, Wulcea continues to focus on the technical foundations of dependable heated apparel. This approach reflects the brand’s emphasis on bringing together safety considerations, practical functionality, and everyday comfort for cold-weather use.

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