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#mythos — Public Fediverse posts

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

  1. Non, les agents IA d’OpenAI et Anthropic ne menacent pas vraiment la cybersécurité

    Non, les agents IA d’OpenAI et Anthropic ne menacent pas vraiment la cybersécurité

    Un nombre croissant de professionnels de la cybersécurité déplorent la façon « IApocalyptique » qu’ont OpenAI, Anthropic et de nombreuses entreprises des Big Tech’ de présenter les capacités des agents IA en matière de cyberattaques.

    (pas en accès libre, dommage, ça serait utile à certains qui tombent encore trop facilement dans le panneau)

  2. 👻 #Mythos zum #Frühstück: 😱

    „Ich habe ein Recht auf einen #Parkplatz

    Öffentlicher #Parkraum ist ein knappes Gut. Die #Verkehrswende und #Klimaanpassungsmaßnahmen erfordern Veränderungen in der #Stadtplanung. Sobald der Platz für Fuß- und #Radverkehr verbessert werden soll, formiert sich Widerstand. Doch was ist rechtlich erlaubt und welche Ansprüche bestehen?

    oekologisch-unterwegs.de/elekt

    #Autoverkehr #Mobilitätswende #Radverkehr #ÖffentlicherRaum #Faktencheck

  3. 👻 #Mythos zum #Frühstück: 😱

    „Ich habe ein Recht auf einen #Parkplatz

    Öffentlicher #Parkraum ist ein knappes Gut. Die #Verkehrswende und #Klimaanpassungsmaßnahmen erfordern Veränderungen in der #Stadtplanung. Sobald der Platz für Fuß- und #Radverkehr verbessert werden soll, formiert sich Widerstand. Doch was ist rechtlich erlaubt und welche Ansprüche bestehen?

    oekologisch-unterwegs.de/elekt

    #Autoverkehr #Mobilitätswende #Radverkehr #ÖffentlicherRaum #Faktencheck

  4. 👻 #Mythos zum #Frühstück: 😱

    „Ich habe ein Recht auf einen #Parkplatz

    Öffentlicher #Parkraum ist ein knappes Gut. Die #Verkehrswende und #Klimaanpassungsmaßnahmen erfordern Veränderungen in der #Stadtplanung. Sobald der Platz für Fuß- und #Radverkehr verbessert werden soll, formiert sich Widerstand. Doch was ist rechtlich erlaubt und welche Ansprüche bestehen?

    oekologisch-unterwegs.de/elekt

    #Autoverkehr #Mobilitätswende #Radverkehr #ÖffentlicherRaum #Faktencheck

  5. 👻 #Mythos zum #Frühstück: 😱

    „Ich habe ein Recht auf einen #Parkplatz

    Öffentlicher #Parkraum ist ein knappes Gut. Die #Verkehrswende und #Klimaanpassungsmaßnahmen erfordern Veränderungen in der #Stadtplanung. Sobald der Platz für Fuß- und #Radverkehr verbessert werden soll, formiert sich Widerstand. Doch was ist rechtlich erlaubt und welche Ansprüche bestehen?

    oekologisch-unterwegs.de/elekt

    #Autoverkehr #Mobilitätswende #Radverkehr #ÖffentlicherRaum #Faktencheck

  6. 👻 #Mythos zum #Frühstück: 😱

    „Ich habe ein Recht auf einen #Parkplatz

    Öffentlicher #Parkraum ist ein knappes Gut. Die #Verkehrswende und #Klimaanpassungsmaßnahmen erfordern Veränderungen in der #Stadtplanung. Sobald der Platz für Fuß- und #Radverkehr verbessert werden soll, formiert sich Widerstand. Doch was ist rechtlich erlaubt und welche Ansprüche bestehen?

    oekologisch-unterwegs.de/elekt

    #Autoverkehr #Mobilitätswende #Radverkehr #ÖffentlicherRaum #Faktencheck

  7. "You may not have heard of Aisle, an AI-native vulnerability-management startup, but some of the best open-source maintainers know it well and really like it. Why? Because Aisle finds real bugs that other, far better-known AI coding programs, such as Anthropic’s Mythos and OpenAI’s Codex, don’t.

    For example, Aisle recently said its security analysis system uncovered six previously unknown vulnerabilities in Curl that the open-source project’s maintainers accepted and assigned Common Vulnerabilities and Exposures (CVE) numbers. The findings arrived shortly after Curl founder Daniel Stenberg wrote on Mastodon that Mythos, OpenAI Codex Security, and ZeroPath had found no additional vulnerabilities in the widely deployed, open-source networking file-transfer project. Aisle, meanwhile, found 29.

    Aisle achieves this success not because it uses expensive frontier models, but because, the company states, “even small models can recognize a vulnerability when handed the right snippet of code with leading context.” We “tested whether cheap models with enough throughput can surface real bugs without that hand-holding. The answer was yes: adequately intelligent models, deployed systematically across an entire codebase, can surface real bugs without hand-scoped snippets.”"

    zdnet.com/innovation/aisle-ai-

    #AI #CyberSecurity #Mythos #Codex #SLMs #Curl #SoftwareBugs

  8. "You may not have heard of Aisle, an AI-native vulnerability-management startup, but some of the best open-source maintainers know it well and really like it. Why? Because Aisle finds real bugs that other, far better-known AI coding programs, such as Anthropic’s Mythos and OpenAI’s Codex, don’t.

    For example, Aisle recently said its security analysis system uncovered six previously unknown vulnerabilities in Curl that the open-source project’s maintainers accepted and assigned Common Vulnerabilities and Exposures (CVE) numbers. The findings arrived shortly after Curl founder Daniel Stenberg wrote on Mastodon that Mythos, OpenAI Codex Security, and ZeroPath had found no additional vulnerabilities in the widely deployed, open-source networking file-transfer project. Aisle, meanwhile, found 29.

    Aisle achieves this success not because it uses expensive frontier models, but because, the company states, “even small models can recognize a vulnerability when handed the right snippet of code with leading context.” We “tested whether cheap models with enough throughput can surface real bugs without that hand-holding. The answer was yes: adequately intelligent models, deployed systematically across an entire codebase, can surface real bugs without hand-scoped snippets.”"

    zdnet.com/innovation/aisle-ai-

    #AI #CyberSecurity #Mythos #Codex #SLMs #Curl #SoftwareBugs

  9. "You may not have heard of Aisle, an AI-native vulnerability-management startup, but some of the best open-source maintainers know it well and really like it. Why? Because Aisle finds real bugs that other, far better-known AI coding programs, such as Anthropic’s Mythos and OpenAI’s Codex, don’t.

    For example, Aisle recently said its security analysis system uncovered six previously unknown vulnerabilities in Curl that the open-source project’s maintainers accepted and assigned Common Vulnerabilities and Exposures (CVE) numbers. The findings arrived shortly after Curl founder Daniel Stenberg wrote on Mastodon that Mythos, OpenAI Codex Security, and ZeroPath had found no additional vulnerabilities in the widely deployed, open-source networking file-transfer project. Aisle, meanwhile, found 29.

    Aisle achieves this success not because it uses expensive frontier models, but because, the company states, “even small models can recognize a vulnerability when handed the right snippet of code with leading context.” We “tested whether cheap models with enough throughput can surface real bugs without that hand-holding. The answer was yes: adequately intelligent models, deployed systematically across an entire codebase, can surface real bugs without hand-scoped snippets.”"

    zdnet.com/innovation/aisle-ai-

    #AI #CyberSecurity #Mythos #Codex #SLMs #Curl #SoftwareBugs

  10. "You may not have heard of Aisle, an AI-native vulnerability-management startup, but some of the best open-source maintainers know it well and really like it. Why? Because Aisle finds real bugs that other, far better-known AI coding programs, such as Anthropic’s Mythos and OpenAI’s Codex, don’t.

    For example, Aisle recently said its security analysis system uncovered six previously unknown vulnerabilities in Curl that the open-source project’s maintainers accepted and assigned Common Vulnerabilities and Exposures (CVE) numbers. The findings arrived shortly after Curl founder Daniel Stenberg wrote on Mastodon that Mythos, OpenAI Codex Security, and ZeroPath had found no additional vulnerabilities in the widely deployed, open-source networking file-transfer project. Aisle, meanwhile, found 29.

    Aisle achieves this success not because it uses expensive frontier models, but because, the company states, “even small models can recognize a vulnerability when handed the right snippet of code with leading context.” We “tested whether cheap models with enough throughput can surface real bugs without that hand-holding. The answer was yes: adequately intelligent models, deployed systematically across an entire codebase, can surface real bugs without hand-scoped snippets.”"

    zdnet.com/innovation/aisle-ai-

    #AI #CyberSecurity #Mythos #Codex #SLMs #Curl #SoftwareBugs

  11. "You may not have heard of Aisle, an AI-native vulnerability-management startup, but some of the best open-source maintainers know it well and really like it. Why? Because Aisle finds real bugs that other, far better-known AI coding programs, such as Anthropic’s Mythos and OpenAI’s Codex, don’t.

    For example, Aisle recently said its security analysis system uncovered six previously unknown vulnerabilities in Curl that the open-source project’s maintainers accepted and assigned Common Vulnerabilities and Exposures (CVE) numbers. The findings arrived shortly after Curl founder Daniel Stenberg wrote on Mastodon that Mythos, OpenAI Codex Security, and ZeroPath had found no additional vulnerabilities in the widely deployed, open-source networking file-transfer project. Aisle, meanwhile, found 29.

    Aisle achieves this success not because it uses expensive frontier models, but because, the company states, “even small models can recognize a vulnerability when handed the right snippet of code with leading context.” We “tested whether cheap models with enough throughput can surface real bugs without that hand-holding. The answer was yes: adequately intelligent models, deployed systematically across an entire codebase, can surface real bugs without hand-scoped snippets.”"

    zdnet.com/innovation/aisle-ai-

    #AI #CyberSecurity #Mythos #Codex #SLMs #Curl #SoftwareBugs

  12. 👻 #Mythos zum #Frühstück: 😱

    „#Rotorblätter von #Windrädern haben fast 1400 Tonnen Abrieb pro Jahr“.

    #Rotorblätter unterliegen einer gewissen #Erosion. Sie verlieren kleine Partikel, zu denen auch #Mikroplastik zählt. Wie hoch ist der tatsächliche jährliche Abrieb und welche Studiendaten liegen dazu vor?

    oekologisch-unterwegs.de/energ

    #Windenergie #Umweltschutz #Kunststoffe #Faktencheck

  13. 👻 #Mythos zum #Frühstück: 😱

    „Windräder schreddern eine riesige Anzahl an Vögeln“.

    #Windräder können #Vogelschlag verursachen. #Windkraftgegner sprechen vom „Vogelschreddern“ und versuchen mit geschützen Arten den Bau von #Windkraftanlagen zu verhindern. Wie hoch sind die Opferzahlen wirklich und welche Maßnahmen existieren, um #Vogelkollisionen zu verhindern?

    oekologisch-unterwegs.de/energ

    #Windenergie #Vogelschutz #Energiewende #Naturschutz #Faktencheck