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#ai-training — Public Fediverse posts

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

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  1. 🐢 Oh, joy! #Perforce has graced us with their AI-narrated "training" videos for a mere $500! Because nothing says value like paying a small fortune to hear a robot explain—well, who knows what, since it's just perpetually "Loading." 🙄
    training.perforce.com/learn/co #AItraining #TechHumor #OverpricedTech #AutomationFails #HackerNews #ngated

  2. 🐢 Oh, joy! #Perforce has graced us with their AI-narrated "training" videos for a mere $500! Because nothing says value like paying a small fortune to hear a robot explain—well, who knows what, since it's just perpetually "Loading." 🙄
    training.perforce.com/learn/co #AItraining #TechHumor #OverpricedTech #AutomationFails #HackerNews #ngated

  3. 🐢 Oh, joy! #Perforce has graced us with their AI-narrated "training" videos for a mere $500! Because nothing says value like paying a small fortune to hear a robot explain—well, who knows what, since it's just perpetually "Loading." 🙄
    training.perforce.com/learn/co #AItraining #TechHumor #OverpricedTech #AutomationFails #HackerNews #ngated

  4. 🐢 Oh, joy! #Perforce has graced us with their AI-narrated "training" videos for a mere $500! Because nothing says value like paying a small fortune to hear a robot explain—well, who knows what, since it's just perpetually "Loading." 🙄
    training.perforce.com/learn/co #AItraining #TechHumor #OverpricedTech #AutomationFails #HackerNews #ngated

  5. 🐢 Oh, joy! #Perforce has graced us with their AI-narrated "training" videos for a mere $500! Because nothing says value like paying a small fortune to hear a robot explain—well, who knows what, since it's just perpetually "Loading." 🙄
    training.perforce.com/learn/co #AItraining #TechHumor #OverpricedTech #AutomationFails #HackerNews #ngated

  6. Did you miss a previous AI webinar? Would you like to review previous lessons in our AI series? Visit our Learn AI page to  access lessons, practice exercises, and additional AI resources. freedomscientific.com/training

    #AITraining #VisperoTraining

  7. Did you miss a previous AI webinar? Would you like to review previous lessons in our AI series? Visit our Learn AI page to  access lessons, practice exercises, and additional AI resources. freedomscientific.com/training

    #AITraining #VisperoTraining

  8. Did you miss a previous AI webinar? Would you like to review previous lessons in our AI series? Visit our Learn AI page to  access lessons, practice exercises, and additional AI resources. freedomscientific.com/training

    #AITraining #VisperoTraining

  9. Did you miss a previous AI webinar? Would you like to review previous lessons in our AI series? Visit our Learn AI page to  access lessons, practice exercises, and additional AI resources. freedomscientific.com/training

    #AITraining #VisperoTraining

  10. Did you miss a previous AI webinar? Would you like to review previous lessons in our AI series? Visit our Learn AI page to  access lessons, practice exercises, and additional AI resources. freedomscientific.com/training

    #AITraining #VisperoTraining

  11. Engadget: A hacker accessed Suno source code that reportedly details how the company scraped millions of songs . “Suno — an app that vomits out soulless audio in the form of AI-generated ‘music’ — has been hacked. According to 404 Media, the hacker accessed data related to Suno’s training practices, as well as details on its customers.”

    https://rbfirehose.com/2026/07/16/engadget-a-hacker-accessed-suno-source-code-that-reportedly-details-how-the-company-scraped-millions-of-songs/
  12. Engadget: A hacker accessed Suno source code that reportedly details how the company scraped millions of songs . “Suno — an app that vomits out soulless audio in the form of AI-generated ‘music’ — has been hacked. According to 404 Media, the hacker accessed data related to Suno’s training practices, as well as details on its customers.”

    https://rbfirehose.com/2026/07/16/engadget-a-hacker-accessed-suno-source-code-that-reportedly-details-how-the-company-scraped-millions-of-songs/
  13. Engadget: A hacker accessed Suno source code that reportedly details how the company scraped millions of songs . “Suno — an app that vomits out soulless audio in the form of AI-generated ‘music’ — has been hacked. According to 404 Media, the hacker accessed data related to Suno’s training practices, as well as details on its customers.”

    https://rbfirehose.com/2026/07/16/engadget-a-hacker-accessed-suno-source-code-that-reportedly-details-how-the-company-scraped-millions-of-songs/
  14. Engadget: A hacker accessed Suno source code that reportedly details how the company scraped millions of songs . “Suno — an app that vomits out soulless audio in the form of AI-generated ‘music’ — has been hacked. According to 404 Media, the hacker accessed data related to Suno’s training practices, as well as details on its customers.”

    https://rbfirehose.com/2026/07/16/engadget-a-hacker-accessed-suno-source-code-that-reportedly-details-how-the-company-scraped-millions-of-songs/
  15. Engadget: A hacker accessed Suno source code that reportedly details how the company scraped millions of songs . “Suno — an app that vomits out soulless audio in the form of AI-generated ‘music’ — has been hacked. According to 404 Media, the hacker accessed data related to Suno’s training practices, as well as details on its customers.”

    https://rbfirehose.com/2026/07/16/engadget-a-hacker-accessed-suno-source-code-that-reportedly-details-how-the-company-scraped-millions-of-songs/
  16. PetaPixel: Patreon Blocks AI Crawlers From Copying Content: ‘Creators Deserve Compenstion’. “Patreon has announced a new update that blocks AI crawlers from hoovering up content on the platform for training purposes.”

    https://rbfirehose.com/2026/07/16/patreon-blocks-ai-crawlers-from-copying-content-creators-deserve-compenstion-petapixel/
  17. PetaPixel: Patreon Blocks AI Crawlers From Copying Content: ‘Creators Deserve Compenstion’. “Patreon has announced a new update that blocks AI crawlers from hoovering up content on the platform for training purposes.”

    https://rbfirehose.com/2026/07/16/patreon-blocks-ai-crawlers-from-copying-content-creators-deserve-compenstion-petapixel/
  18. PetaPixel: Patreon Blocks AI Crawlers From Copying Content: ‘Creators Deserve Compenstion’. “Patreon has announced a new update that blocks AI crawlers from hoovering up content on the platform for training purposes.”

    https://rbfirehose.com/2026/07/16/patreon-blocks-ai-crawlers-from-copying-content-creators-deserve-compenstion-petapixel/
  19. PetaPixel: Patreon Blocks AI Crawlers From Copying Content: ‘Creators Deserve Compenstion’. “Patreon has announced a new update that blocks AI crawlers from hoovering up content on the platform for training purposes.”

    https://rbfirehose.com/2026/07/16/patreon-blocks-ai-crawlers-from-copying-content-creators-deserve-compenstion-petapixel/
  20. PetaPixel: Patreon Blocks AI Crawlers From Copying Content: ‘Creators Deserve Compenstion’. “Patreon has announced a new update that blocks AI crawlers from hoovering up content on the platform for training purposes.”

    https://rbfirehose.com/2026/07/16/patreon-blocks-ai-crawlers-from-copying-content-creators-deserve-compenstion-petapixel/
  21. 9to5 Google: Samsung Health won’t delete all of your data if you opt out of AI training after all [U]. “In a statement to 9to5Google, Samsung says that it won’t delete all of your data if you opt-out of AI training. Rather, it will only delete ‘data collected for AI development.’ In other words, it sounds like it is deleting data from Samsung’s end rather than the user’s.”

    https://rbfirehose.com/2026/07/16/9to5-google-samsung-health-wont-delete-all-of-your-data-if-you-opt-out-of-ai-training-after-all-u/
  22. 9to5 Google: Samsung Health won’t delete all of your data if you opt out of AI training after all [U]. “In a statement to 9to5Google, Samsung says that it won’t delete all of your data if you opt-out of AI training. Rather, it will only delete ‘data collected for AI development.’ In other words, it sounds like it is deleting data from Samsung’s end rather than the user’s.”

    https://rbfirehose.com/2026/07/16/9to5-google-samsung-health-wont-delete-all-of-your-data-if-you-opt-out-of-ai-training-after-all-u/
  23. 9to5 Google: Samsung Health won’t delete all of your data if you opt out of AI training after all [U]. “In a statement to 9to5Google, Samsung says that it won’t delete all of your data if you opt-out of AI training. Rather, it will only delete ‘data collected for AI development.’ In other words, it sounds like it is deleting data from Samsung’s end rather than the user’s.”

    https://rbfirehose.com/2026/07/16/9to5-google-samsung-health-wont-delete-all-of-your-data-if-you-opt-out-of-ai-training-after-all-u/
  24. 9to5 Google: Samsung Health won’t delete all of your data if you opt out of AI training after all [U]. “In a statement to 9to5Google, Samsung says that it won’t delete all of your data if you opt-out of AI training. Rather, it will only delete ‘data collected for AI development.’ In other words, it sounds like it is deleting data from Samsung’s end rather than the user’s.”

    https://rbfirehose.com/2026/07/16/9to5-google-samsung-health-wont-delete-all-of-your-data-if-you-opt-out-of-ai-training-after-all-u/
  25. 9to5 Google: Samsung Health won’t delete all of your data if you opt out of AI training after all [U]. “In a statement to 9to5Google, Samsung says that it won’t delete all of your data if you opt-out of AI training. Rather, it will only delete ‘data collected for AI development.’ In other words, it sounds like it is deleting data from Samsung’s end rather than the user’s.”

    https://rbfirehose.com/2026/07/16/9to5-google-samsung-health-wont-delete-all-of-your-data-if-you-opt-out-of-ai-training-after-all-u/
  26. Enterprise AI training vs. #AIInference: two fundamentally different workloads.

    #AITraining: intensive GPU compute over days/weeks
    Inference: fast, continuous production responses

    Conflate them and you overpay for infrastructure, choose the wrong hardware, and you miss compliance. Both introduce distinct security risks.

    The solution?
    Private, sovereign AI infrastructure = full data control + compliance.

    amazee.ai/blog/ai-training-vs-

  27. Enterprise AI training vs. #AIInference: two fundamentally different workloads.

    #AITraining: intensive GPU compute over days/weeks
    Inference: fast, continuous production responses

    Conflate them and you overpay for infrastructure, choose the wrong hardware, and you miss compliance. Both introduce distinct security risks.

    The solution?
    Private, sovereign AI infrastructure = full data control + compliance.

    amazee.ai/blog/ai-training-vs-

  28. "The hacked data is a rare look at exactly how AI models and tools are built. Suno is one of the largest AI music generation tools on the internet, and has been the subject of several major lawsuits from the record industry, which accused the company of training on millions of copyrighted songs. As part of these legal proceedings, Suno previously admitted that it was trained on “essentially all music files of reasonable quality that are accessible on the open internet,” which included a total of “tens of millions of recordings.” Suno has been making the argument that it is allowed to train on copyrighted works as fair use in those cases, one of which has been settled.

    The lawsuits have made clear that Suno did train on huge amounts of copyrighted works, but the hacked data shared with 404 Media sheds more light on how Suno scraped songs from the internet and where it took them from. The Recording Industry Association of America accused Suno of ripping songs directly from YouTube; the hacked data seen by 404 Media confirms this.

    The hacked material includes source code that appears to be from 2023 and 2024 that includes scraping instructions and details about the scope of at least some of the scraping. For example, the comments in one file note that they will pull from “genius_hq, youtube_music, freesound, jamendo, imp, deezer, ytm_tagged,” and that “non-music will be filtered out.” A file called “youtube_music” notes that at the time the file was last updated, it had ingested “2,013,545 music clips.” Another file contains comments about different datasets Suno had created, which included “113,879 hours of youtube_music,” “17,615 hours of genius_hq,” “410 hours of free sound,” “19,514 hours of imslp,” “3,726 hours of jamendo,” “62,117 hours of pond5_music,” “12,287 hours of deezer,” “152,162 hours of ytm_tagged,” and “103 hours of musescore_lyrics.”"

    404media.co/hack-reveals-suno-

    #AI #GenerativeAI #Suno #AITraining #CyberSecurity #Copyright #IP

  29. "The hacked data is a rare look at exactly how AI models and tools are built. Suno is one of the largest AI music generation tools on the internet, and has been the subject of several major lawsuits from the record industry, which accused the company of training on millions of copyrighted songs. As part of these legal proceedings, Suno previously admitted that it was trained on “essentially all music files of reasonable quality that are accessible on the open internet,” which included a total of “tens of millions of recordings.” Suno has been making the argument that it is allowed to train on copyrighted works as fair use in those cases, one of which has been settled.

    The lawsuits have made clear that Suno did train on huge amounts of copyrighted works, but the hacked data shared with 404 Media sheds more light on how Suno scraped songs from the internet and where it took them from. The Recording Industry Association of America accused Suno of ripping songs directly from YouTube; the hacked data seen by 404 Media confirms this.

    The hacked material includes source code that appears to be from 2023 and 2024 that includes scraping instructions and details about the scope of at least some of the scraping. For example, the comments in one file note that they will pull from “genius_hq, youtube_music, freesound, jamendo, imp, deezer, ytm_tagged,” and that “non-music will be filtered out.” A file called “youtube_music” notes that at the time the file was last updated, it had ingested “2,013,545 music clips.” Another file contains comments about different datasets Suno had created, which included “113,879 hours of youtube_music,” “17,615 hours of genius_hq,” “410 hours of free sound,” “19,514 hours of imslp,” “3,726 hours of jamendo,” “62,117 hours of pond5_music,” “12,287 hours of deezer,” “152,162 hours of ytm_tagged,” and “103 hours of musescore_lyrics.”"

    404media.co/hack-reveals-suno-

    #AI #GenerativeAI #Suno #AITraining #CyberSecurity #Copyright #IP

  30. "The hacked data is a rare look at exactly how AI models and tools are built. Suno is one of the largest AI music generation tools on the internet, and has been the subject of several major lawsuits from the record industry, which accused the company of training on millions of copyrighted songs. As part of these legal proceedings, Suno previously admitted that it was trained on “essentially all music files of reasonable quality that are accessible on the open internet,” which included a total of “tens of millions of recordings.” Suno has been making the argument that it is allowed to train on copyrighted works as fair use in those cases, one of which has been settled.

    The lawsuits have made clear that Suno did train on huge amounts of copyrighted works, but the hacked data shared with 404 Media sheds more light on how Suno scraped songs from the internet and where it took them from. The Recording Industry Association of America accused Suno of ripping songs directly from YouTube; the hacked data seen by 404 Media confirms this.

    The hacked material includes source code that appears to be from 2023 and 2024 that includes scraping instructions and details about the scope of at least some of the scraping. For example, the comments in one file note that they will pull from “genius_hq, youtube_music, freesound, jamendo, imp, deezer, ytm_tagged,” and that “non-music will be filtered out.” A file called “youtube_music” notes that at the time the file was last updated, it had ingested “2,013,545 music clips.” Another file contains comments about different datasets Suno had created, which included “113,879 hours of youtube_music,” “17,615 hours of genius_hq,” “410 hours of free sound,” “19,514 hours of imslp,” “3,726 hours of jamendo,” “62,117 hours of pond5_music,” “12,287 hours of deezer,” “152,162 hours of ytm_tagged,” and “103 hours of musescore_lyrics.”"

    404media.co/hack-reveals-suno-

    #AI #GenerativeAI #Suno #AITraining #CyberSecurity #Copyright #IP

  31. "The hacked data is a rare look at exactly how AI models and tools are built. Suno is one of the largest AI music generation tools on the internet, and has been the subject of several major lawsuits from the record industry, which accused the company of training on millions of copyrighted songs. As part of these legal proceedings, Suno previously admitted that it was trained on “essentially all music files of reasonable quality that are accessible on the open internet,” which included a total of “tens of millions of recordings.” Suno has been making the argument that it is allowed to train on copyrighted works as fair use in those cases, one of which has been settled.

    The lawsuits have made clear that Suno did train on huge amounts of copyrighted works, but the hacked data shared with 404 Media sheds more light on how Suno scraped songs from the internet and where it took them from. The Recording Industry Association of America accused Suno of ripping songs directly from YouTube; the hacked data seen by 404 Media confirms this.

    The hacked material includes source code that appears to be from 2023 and 2024 that includes scraping instructions and details about the scope of at least some of the scraping. For example, the comments in one file note that they will pull from “genius_hq, youtube_music, freesound, jamendo, imp, deezer, ytm_tagged,” and that “non-music will be filtered out.” A file called “youtube_music” notes that at the time the file was last updated, it had ingested “2,013,545 music clips.” Another file contains comments about different datasets Suno had created, which included “113,879 hours of youtube_music,” “17,615 hours of genius_hq,” “410 hours of free sound,” “19,514 hours of imslp,” “3,726 hours of jamendo,” “62,117 hours of pond5_music,” “12,287 hours of deezer,” “152,162 hours of ytm_tagged,” and “103 hours of musescore_lyrics.”"

    404media.co/hack-reveals-suno-

    #AI #GenerativeAI #Suno #AITraining #CyberSecurity #Copyright #IP

  32. "The hacked data is a rare look at exactly how AI models and tools are built. Suno is one of the largest AI music generation tools on the internet, and has been the subject of several major lawsuits from the record industry, which accused the company of training on millions of copyrighted songs. As part of these legal proceedings, Suno previously admitted that it was trained on “essentially all music files of reasonable quality that are accessible on the open internet,” which included a total of “tens of millions of recordings.” Suno has been making the argument that it is allowed to train on copyrighted works as fair use in those cases, one of which has been settled.

    The lawsuits have made clear that Suno did train on huge amounts of copyrighted works, but the hacked data shared with 404 Media sheds more light on how Suno scraped songs from the internet and where it took them from. The Recording Industry Association of America accused Suno of ripping songs directly from YouTube; the hacked data seen by 404 Media confirms this.

    The hacked material includes source code that appears to be from 2023 and 2024 that includes scraping instructions and details about the scope of at least some of the scraping. For example, the comments in one file note that they will pull from “genius_hq, youtube_music, freesound, jamendo, imp, deezer, ytm_tagged,” and that “non-music will be filtered out.” A file called “youtube_music” notes that at the time the file was last updated, it had ingested “2,013,545 music clips.” Another file contains comments about different datasets Suno had created, which included “113,879 hours of youtube_music,” “17,615 hours of genius_hq,” “410 hours of free sound,” “19,514 hours of imslp,” “3,726 hours of jamendo,” “62,117 hours of pond5_music,” “12,287 hours of deezer,” “152,162 hours of ytm_tagged,” and “103 hours of musescore_lyrics.”"

    404media.co/hack-reveals-suno-

    #AI #GenerativeAI #Suno #AITraining #CyberSecurity #Copyright #IP