{"id":11426,"date":"2024-04-08T17:45:24","date_gmt":"2024-04-08T17:45:24","guid":{"rendered":"https:\/\/dailyai.com\/?p=11426"},"modified":"2024-04-09T08:28:17","modified_gmt":"2024-04-09T08:28:17","slug":"inside-big-techs-tussle-over-ai-training-data","status":"publish","type":"post","link":"https:\/\/dailyai.com\/de\/2024\/04\/inside-big-techs-tussle-over-ai-training-data\/","title":{"rendered":"Einblicke in das Gerangel um KI-Trainingsdaten bei Big Tech"},"content":{"rendered":"

Auf der Jagd nach KI-Trainingsdaten haben die Tech-Giganten OpenAI, Google und Meta Berichten zufolge Unternehmensrichtlinien umgangen, ihre Regeln ge\u00e4ndert und die Umgehung von Urheberrechtsgesetzen diskutiert.\u00a0<\/b><\/p>\n

A <\/span>Untersuchung der New York Times<\/span><\/a> zeigt, wie weit diese Unternehmen gehen, um Online-Informationen f\u00fcr ihre datenhungrigen KI-Systeme zu sammeln.<\/span><\/p>\n

Ende 2021 entwickelten OpenAI-Forscher ein Spracherkennungstool namens Whisper, um YouTube-Videos zu transkribieren, wenn es an seri\u00f6sen englischsprachigen Textdaten mangelt.\u00a0<\/span><\/p>\n

Trotz interner Diskussionen \u00fcber einen m\u00f6glichen Versto\u00df gegen die YouTube-Regeln, die die Nutzung der Videos f\u00fcr \"unabh\u00e4ngige\" Anwendungen untersagen,\u00a0<\/span><\/p>\n

Die NYT fand heraus, dass OpenAI letztendlich \u00fcber eine Million Stunden an YouTube-Inhalten transkribiert hat. Greg Brockman, der Pr\u00e4sident von OpenAI, hat pers\u00f6nlich beim Sammeln der Videos geholfen. Der transkribierte Text wurde dann in GPT-4 eingespeist.<\/span><\/p>\n

Google soll auch YouTube-Videos transkribiert haben, um Text f\u00fcr seine KI-Modelle zu sammeln, was m\u00f6glicherweise gegen die Urheberrechte der Videoautoren verst\u00f6\u00dft. <\/span><\/p>\n

Dies geschieht wenige Tage nachdem der CEO von YouTube erkl\u00e4rt hat, dass solche Aktivit\u00e4ten gegen die <\/span>Gesch\u00e4ftsbedingungen des Unternehmens<\/span><\/a> und untergraben die Sch\u00f6pfer.\u00a0<\/span><\/p>\n

Im Juni 2023 beantragte die Rechtsabteilung von Google \u00c4nderungen an den Datenschutzrichtlinien des Unternehmens, um \u00f6ffentlich zug\u00e4ngliche Inhalte aus Google Text & Tabellen und anderen Google-Anwendungen f\u00fcr eine breitere Palette von KI-Produkten zu erm\u00f6glichen.\u00a0<\/span><\/p>\n

Meta hat angesichts seiner eigenen Datenknappheit verschiedene M\u00f6glichkeiten in Betracht gezogen, um mehr Trainingsdaten zu erhalten.\u00a0<\/span><\/p>\n

Die F\u00fchrungskr\u00e4fte diskutierten dar\u00fcber, f\u00fcr Buchlizenzen zu zahlen, den Verlag Simon & Schuster zu kaufen und sogar urheberrechtlich gesch\u00fctztes Material ohne Erlaubnis aus dem Internet zu holen und damit m\u00f6gliche Klagen zu riskieren.\u00a0<\/span><\/p>\n

Die Anw\u00e4lte von Meta argumentierten, dass die Verwendung von Daten zum Trainieren von KI-Systemen unter die \"faire Nutzung\" fallen sollte und beriefen sich dabei auf ein Gerichtsurteil aus dem Jahr 2015, in dem es um Googles Buchscan-Projekt ging.<\/span><\/p>\n

Ethische Bedenken und die Zukunft der KI-Trainingsdaten<\/h2>\n

Die kollektiven Ma\u00dfnahmen dieser Technologieunternehmen unterstreichen die entscheidende Bedeutung von Online-Daten f\u00fcr die boomende KI-Branche.<\/span><\/p>\n

Diese Praktiken haben Bedenken hinsichtlich der Verletzung von Urheberrechten und der gerechten Entsch\u00e4digung von Urhebern aufgeworfen.\u00a0<\/span><\/p>\n

Die Filmemacherin und Autorin Justine Bateman hat dem Copyright Office mitgeteilt, dass KI-Modelle Inhalte - einschlie\u00dflich ihrer Texte und Filme - ohne Erlaubnis oder Bezahlung \u00fcbernehmen. <\/span><\/p>\n

\"Dies ist der gr\u00f6\u00dfte Diebstahl in den Vereinigten Staaten, Punkt\", sagte sie in einem Interview.<\/span><\/p>\n

In der bildenden Kunst wurden MidJourney und andere Bildmodelle <\/span>nachweislich Urheberrechte erzeugen<\/span><\/a> Inhalte, wie Szenen aus Marvel-Filmen.\u00a0<\/span><\/p>\n

Da einige Experten vorhersagen, dass hochwertige Online-Daten bis 2026 ersch\u00f6pft sein k\u00f6nnten, erforschen Unternehmen alternative Methoden, wie z. B. die Generierung synthetischer Daten mithilfe von KI-Modellen selbst.\u00a0<\/span>Synthetische Trainingsdaten sind jedoch mit eigenen Risiken und Herausforderungen verbunden und k\u00f6nnten sich nachteilig auswirken <\/span>Auswirkungen auf die Qualit\u00e4t der Modelle<\/span><\/a>.\u00a0<\/span><\/p>\n

Der CEO von OpenAI, Sam Altman, r\u00e4umte in einer Rede auf einer Technologiekonferenz im Mai 2023 selbst ein, dass die Online-Daten endlich sind: \"Das wird ausgehen\", sagte er.<\/span><\/p>\n

Sy Damle, ein Anwalt, der Andreessen Horowitz, ein Risikokapitalunternehmen aus dem Silicon Valley, vertritt, er\u00f6rterte ebenfalls die Herausforderung: \"Die einzige praktische M\u00f6glichkeit f\u00fcr diese Tools besteht darin, dass sie auf riesigen Datenmengen trainiert werden k\u00f6nnen, ohne diese Daten lizenzieren zu m\u00fcssen. Die ben\u00f6tigten Daten sind so umfangreich, dass selbst eine kollektive Lizenzierung nicht wirklich funktionieren kann\".<\/span><\/p>\n

Die NYT und OpenAI sind in einen Streit verwickelt Bittere Urheberrechtsklage<\/a>Die Times fordert Schadenersatz in Millionenh\u00f6he.<\/p>\n

OpenAI schlug zur\u00fcck und beschuldigte die Times ihre Modelle 'hacken'<\/a> um Beispiele f\u00fcr Urheberrechtsverletzungen zu finden.<\/p>\n

Mit \"hacken\" meinen sie \"jailbreaking\" oder \"red-teaming\", bei dem das Modell mit speziell formulierten Aufforderungen angegriffen wird, um die Ergebnisse zu manipulieren.<\/p>\n

Die NYT sagte, dass sie nicht auf Jailbreaking-Modelle zur\u00fcckgreifen m\u00fcssten, wenn KI-Unternehmen transparent \u00fcber die von ihnen verwendeten Daten w\u00e4ren.<\/p>\n

Zweifelsohne stellt diese interne Untersuchung den Datenraub von Big Tech als ethisch und rechtlich inakzeptabel dar.<\/p>\n

Die Rechtsstreitigkeiten h\u00e4ufen sich,<\/span>\u00a0Die rechtliche Situation im Zusammenhang mit der Nutzung von Online-Daten f\u00fcr das KI-Training ist \u00e4u\u00dferst prek\u00e4r.\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

Auf der rasanten Jagd nach KI-Trainingsdaten haben die Tech-Giganten OpenAI, Google und Meta Berichten zufolge Unternehmensrichtlinien umgangen, ihre Regeln ge\u00e4ndert und die Umgehung von Urheberrechtsgesetzen diskutiert. Eine Untersuchung der New York Times zeigt, wie weit diese Unternehmen gehen, um Online-Informationen f\u00fcr ihre datenhungrigen KI-Systeme zu sammeln. Ende 2021 entwickelten OpenAI-Forscher ein Spracherkennungs-Tool namens Whisper, um YouTube-Videos zu transkribieren, wenn ein Mangel an seri\u00f6sen englischsprachigen Textdaten bestand. Trotz interner Diskussionen \u00fcber einen m\u00f6glichen Versto\u00df gegen die YouTube-Regeln, die die Verwendung von YouTube-Videos f\u00fcr \"unabh\u00e4ngige\" Anwendungen verbieten, fand die NYT heraus, dass OpenAI letztendlich \u00fcber eine Million Stunden transkribierte<\/p>","protected":false},"author":2,"featured_media":11427,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[197],"class_list":["post-11426","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-copyright"],"yoast_head":"\nInside Big Tech\u2019s tussle over AI training data | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/de\/2024\/04\/inside-big-techs-tussle-over-ai-training-data\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Inside Big Tech\u2019s tussle over AI training data | DailyAI\" \/>\n<meta property=\"og:description\" content=\"In the frantic pursuit of AI training data, tech giants OpenAI, Google, and Meta have reportedly bypassed corporate policies, altered their rules, and discussed circumventing copyright law.\u00a0 A New York Times investigation reveals the lengths these companies have gone to harvest online information to feed their data-hungry AI systems. 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