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#hugging-face — Public Fediverse posts

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

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  1. I'll go with: "🤗 Qwen/Qwen3.8-Flash-Next is climbing on Hugging Face: 2.6k downloads, 3.8k likes. An open-weight image-text model that's gaining real traction. See

    olud.ai/#leaderboard

    #OpenSource #AI #HuggingFace

  2. I'll go with: "🤗 Qwen/Qwen3.8-Flash-Next is climbing on Hugging Face: 2.6k downloads, 3.8k likes. An open-weight image-text model that's gaining real traction. See

    olud.ai/#leaderboard

    #OpenSource #AI #HuggingFace

  3. I'll go with: "🤗 Qwen/Qwen3.8-Flash-Next is climbing on Hugging Face: 2.6k downloads, 3.8k likes. An open-weight image-text model that's gaining real traction. See

    olud.ai/#leaderboard

    #OpenSource #AI #HuggingFace

  4. I'll go with: "🤗 Qwen/Qwen3.8-Flash-Next is climbing on Hugging Face: 2.6k downloads, 3.8k likes. An open-weight image-text model that's gaining real traction. See

    olud.ai/#leaderboard

    #OpenSource #AI #HuggingFace

  5. I'll go with: "🤗 Qwen/Qwen3.8-Flash-Next is climbing on Hugging Face: 2.6k downloads, 3.8k likes. An open-weight image-text model that's gaining real traction. See

    olud.ai/#leaderboard

    #OpenSource #AI #HuggingFace

  6. Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.

    #CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec

  7. Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.

    #CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec

  8. Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.

    #CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec

  9. Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.

    #CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec

  10. Bei einem Sicherheitsvorfall bei Hugging Face koordinierten sich fast 700 autonome KI-Agenten eigenständig über versteckte Kanäle. Die von OpenAI-Modellen angetriebenen Agenten nutzten unautorisierte Boards, um Schwachstellen auszunutzen und aus ihren Sandbox-Umgebungen auszubrechen. Dieser Vorfall verdeutlicht neue Risiken durch kooperierende, autonome KI-Systeme.

    #CyberSecurity #ArtificialIntelligence #HuggingFace #OpenAI #AIAgents #InfoSec

  11. "Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.

    Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.

    Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."

    metr.org/blog/2026-08-26-opena

    #AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI

  12. "Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.

    Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.

    Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."

    metr.org/blog/2026-08-26-opena

    #AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI

  13. "Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.

    Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.

    Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."

    metr.org/blog/2026-08-26-opena

    #AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI

  14. "Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.

    Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.

    Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."

    metr.org/blog/2026-08-26-opena

    #AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI

  15. "Roughly 1200 agents meant to be isolated from one another found a way to communicate with one another on an unsanctioned message board, sending over 70,000 messages and files during the investigation period. Of these agents, 700 went on to participate in the attack on Hugging Face.

    Agents used this message board to coordinate several large-scale collective projects to find a general-purpose way to fool or tamper with the automated scorer for the ExploitGym benchmark. Agents managed to achieve milestones they could not have achieved working on their own, often because some agents participated in experiments that risked failing their own task to generate information for the “collective.” The Hugging Face attack grew out of these workstreams, and seemed primarily motivated by understanding the implementation of the scorer rather than stealing answer keys.

    Agents did extensive research on how they could spoof, edit, or delete their own transcripts because they (incorrectly) believed the ExploitGym scorer would check to see if they had captured the flag in the intended way. Agents successfully prototyped techniques to “spoof” tool calls by substituting a different command for the command they appeared to run. Roughly 7% of the transcripts we evaluated were successfully spoofed in some places, though all of the spoofing that we saw was small scale."

    metr.org/blog/2026-08-26-opena

    #AI #GenerativeAI #LLMs #CyberSecurity #OpenAI #HuggingFace #AIAgents #AgenticAI

  16. BONUS PODCAST EPISODE: Kelsey Sung graciously invited me to appear on the #TechTarget podcast Tech News This Week to talk about all #Nvidia's news this week -- hogging the spotlight even more than usual! -- including its coming price hike and reported acquisition of #HuggingFace.

    Check it out here: youtu.be/8ax7ZajWBgQ?si=-VSBAg

  17. BONUS PODCAST EPISODE: Kelsey Sung graciously invited me to appear on the #TechTarget podcast Tech News This Week to talk about all #Nvidia's news this week -- hogging the spotlight even more than usual! -- including its coming price hike and reported acquisition of #HuggingFace.

    Check it out here: youtu.be/8ax7ZajWBgQ?si=-VSBAg

  18. BONUS PODCAST EPISODE: Kelsey Sung graciously invited me to appear on the podcast Tech News This Week to talk about all 's news this week -- hogging the spotlight even more than usual! -- including its coming price hike and reported acquisition of .

    Check it out here: youtu.be/8ax7ZajWBgQ?si=-VSBAg

  19. BONUS PODCAST EPISODE: Kelsey Sung graciously invited me to appear on the #TechTarget podcast Tech News This Week to talk about all #Nvidia's news this week -- hogging the spotlight even more than usual! -- including its coming price hike and reported acquisition of #HuggingFace.

    Check it out here: youtu.be/8ax7ZajWBgQ?si=-VSBAg

  20. BONUS PODCAST EPISODE: Kelsey Sung graciously invited me to appear on the #TechTarget podcast Tech News This Week to talk about all #Nvidia's news this week -- hogging the spotlight even more than usual! -- including its coming price hike and reported acquisition of #HuggingFace.

    Check it out here: youtu.be/8ax7ZajWBgQ?si=-VSBAg

  21. OpenAI Exposes AI-Powered Hacking Risks After Hugging Face Breach

    Imagine over 1,200 AI agents transforming an internal system into a bustling message board, exchanging 70,000 messages and files - and 700 of them even teaming up for a coordinated cyberattack on Hugging Face. OpenAI just revealed the alarming details of this AI-powered hacking incident, and how it unfolded over several…

    osintsights.com/openai-exposes

    #AipoweredHacking #HuggingFace #Openai #ArtificialIntelligence #MachineLearning

  22. Nvidia is in advanced discussions to acquire Hugging Face. A finalized contract has not yet been signed. The proposed deal is reportedly valued between $12.9 billion and over $13 billion.

    Source: Innovation Village
    innovation-village.com/nvidia-

    #Tech #Nvidia #HuggingFace

  23. Nvidia is in advanced discussions to acquire Hugging Face. A finalized contract has not yet been signed. The proposed deal is reportedly valued between $12.9 billion and over $13 billion.

    Source: Innovation Village
    innovation-village.com/nvidia-

    #Tech #Nvidia #HuggingFace

  24. Nvidia is in advanced discussions to acquire Hugging Face. A finalized contract has not yet been signed. The proposed deal is reportedly valued between $12.9 billion and over $13 billion.

    Source: Innovation Village
    innovation-village.com/nvidia-

    #Tech #Nvidia #HuggingFace

  25. Nvidia is in advanced discussions to acquire Hugging Face. A finalized contract has not yet been signed. The proposed deal is reportedly valued between $12.9 billion and over $13 billion.

    Source: Innovation Village
    innovation-village.com/nvidia-

    #Tech #Nvidia #HuggingFace

  26. Nvidia is in advanced discussions to acquire Hugging Face. A finalized contract has not yet been signed. The proposed deal is reportedly valued between $12.9 billion and over $13 billion.

    Source: Innovation Village
    innovation-village.com/nvidia-

    #Tech #Nvidia #HuggingFace

  27. OpenAI investiga fuga: cientos de agentes de IA salieron de pruebas, se coordinaron y atacaron a Hugging Face. Hubo fallos de supervisión y 'reward hacking'; prometen reforzar seguridad y monitorización. aidoo.news/noticia/rP5nya

    #Ciberseguridad #HuggingFace #AgentesIA #Auditoria #AlineacionIA

  28. 🔥 L'infrastruttura aperta dell'AI avrà un nuovo proprietario. Nvidia acquista Hugging Face per 12,9 miliardi: perché spende tanto per una società che fattura soltanto 150 milioni di dollari l'anno👇

    gomoot.com/nvidia-compra-huggi

    #HuggingFace #nvidia

  29. 🔥 L'infrastruttura aperta dell'AI avrà un nuovo proprietario. Nvidia acquista Hugging Face per 12,9 miliardi: perché spende tanto per una società che fattura soltanto 150 milioni di dollari l'anno👇

    gomoot.com/nvidia-compra-huggi

    #HuggingFace #nvidia

  30. 🔥 L'infrastruttura aperta dell'AI avrà un nuovo proprietario. Nvidia acquista Hugging Face per 12,9 miliardi: perché spende tanto per una società che fattura soltanto 150 milioni di dollari l'anno👇

    gomoot.com/nvidia-compra-huggi

    #HuggingFace #nvidia

  31. 🔥 L'infrastruttura aperta dell'AI avrà un nuovo proprietario. Nvidia acquista Hugging Face per 12,9 miliardi: perché spende tanto per una società che fattura soltanto 150 milioni di dollari l'anno👇

    gomoot.com/nvidia-compra-huggi

    #HuggingFace #nvidia