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#datalabeling — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #datalabeling, aggregated by home.social.

  1. Wie KI Datenfirmen die Maschine füttern
    Während alle über Rechenzentren sprechen, entsteht im Schatten eine neue KI-Infrastruktur: Datenfirmen, die Arbeitskräfte und Fachwissen in Trainingsdaten verwandeln. Und genau dort fließt derzeit viel Geld.

    Der Markt wächst ra
    apfeltalk.de/magazin/news/wie-
    #Feature #KI #News #Arbeitsmarkt #DataLabeling #HandshakeAI #KI #Mercor #Rechenzentren #RLHF #ScaleAI #Startups #SurgeAI #Trainingsdaten

  2. Invisible Technologies just announced a 20× revenue jump as AI labs scramble to hire its human‑in‑the‑loop workforce. The ex‑McKinsey‑backed firm is scaling data‑labeling and AI‑training pipelines, backed by fresh venture funding. How this model reshapes machine‑learning development is worth a read. #InvisibleTechnologies #AIlabs #HumanInTheLoop #DataLabeling

    🔗 aidailypost.com/news/invisible

  3. Sources: AI training startup Mercor eyes $10B+ valuation on $450M run rate

    Mercor, a startup that connects companies like OpenAI and Meta with domain experts needed to train and refine…
    #NewsBeep #News #Entrepreneurship #Business #CA #Canada #datalabeling #FelicisVentures #Mercor #SPV
    newsbeep.com/ca/139372/

  4. Sources: AI training startup Mercor eyes $10B+ valuation on $450M run rate

    Mercor, a startup that connects companies like OpenAI and Meta with domain experts needed to train and refine…
    #NewsBeep #News #Entrepreneurship #AU #Australia #Business #datalabeling #FelicisVentures #Mercor #SPV
    newsbeep.com/au/138450/

  5. "Scale AI is basically a data annotation hub that does essential grunt work for the AI industry. To train an AI model, you need quality data. And for that data to mean anything, an AI model needs to know what it's looking at. Annotators manually go in and add that context.

    As is the means du jour in corporate America, Scale AI built its business model on an army of egregiously underpaid gig workers, many of them overseas. The conditions have been described as "digital sweatshops," and many workers have accused Scale AI of wage theft.

    It turns out this was not an environment for fostering high-quality work.

    According to internal documents obtained by Inc, Scale AI's "Bulba Experts" program to train Google's AI systems was supposed to be staffed with authorities across relevant fields. But instead, during a chaotic 11 months between March 2023 and April 2024, its dubious "contributors" inundated the program with "spam," which was described as "writing gibberish, writing incorrect information, GPT-generated thought processes."

    In many cases, the spammers, who were independent contractors who worked through Scale AI-owned platforms like Remotasks and Outlier, still got paid for submitting complete nonsense, according to former Scale contractors, since it became almost impossible to catch them all. And even if they did get caught, some would come back by simply using a VPN.

    "People made so much money," a former contributor told Inc. "They just hired everybody who could breathe.""

    futurism.com/scale-ai-zuckerbe

    #AI #GenerativeAI #Meta #ScaleAI #DataAnnotation #DataLabeling #GigWork

  6. "The production of artificial intelligence (AI) requires human labour, with tasks ranging from well-paid engineering work to often-outsourced data work. This commentary explores the economic and policy implications of improving working conditions for AI data workers, specifically focusing on the impact of clearer task instructions and increased pay for data annotators. It contrasts rule-based and standard-based approaches to task instructions, revealing evidence-based practices for increasing accuracy in annotation and lowering task difficulty for annotators. AI developers have an economic incentive to invest in these areas as better annotation can lead to higher quality AI systems. The findings have broader implications for AI policy beyond the fairness of labour standards in the AI economy. Testing the design of annotation instructions is crucial for the development of annotation standards as a prerequisite for scientific review and effective human oversight of AI systems in protection of ethical values and fundamental rights."

    journals.sagepub.com/doi/10.11

    #AI #GenerativeAI #DataWork #DataLabour #AIPolicy #PoliticalEconomy #DataLabeling #AIEthics #DataAnnotation

  7. According to Reuters, a major shift is underway as Google plans to cut ties with Scale AI, its largest data-labeling partner, following Meta's acquisition of a 49% stake in Scale. This strategic move aims to protect proprietary interests amid rising competitive threats. As Google explores alternatives for AI services, this could significantly impact Scale's revenue and open doors for new competitors. Read more about the implications [here](cnbc.com/2025/06/14/google-sca). Kudos to Reuters for the insightful coverage! #Google #ScaleAI #Meta #AI #DataLabeling #MachineLearning #BusinessStrategy #Technology #Competitors

  8. TechXplore: Third-party data annotators often fail to accurately read the emotions of others, study finds. “Machine learning algorithms and large language models (LLMs), such as the model underpinning the functioning of the platform ChatGPT, have proved to be effective in tackling a wide range of tasks. These models are trained on various types of data (e.g., texts, images, videos, and/or […]

    https://rbfirehose.com/2025/05/22/techxplore-third-party-data-annotators-often-fail-to-accurately-read-the-emotions-of-others-study-finds/

  9. Fascinating how people use AI to generate cute images while businesses waste hours on manual data extraction. (Un)Perplexed Spready lets you connect directly to AI models through Ollama to extract, categorize, and analyze data right in your spreadsheet.
    matasoft.hr/qtrendcontrol/inde

    #PracticalAI #DataManagement #AI #Spreadsheets #DataExtraction #DataLabeling #DataAnotation #DataCategorization #DataClassification #SmartData #AItools #ProductComparison #SmartSpreadsheets #DataStandardization #BI #MDM