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    AI Systems Are Learning From Players' Imperfect Gaming Skills●The Next Evolution of AI Is Learning From Your Dodgy Gaming Skills https://www.wired.com/story/the-next-evolution-of-ai-MmastodonCultureGaming35 d ago

    Wired reports on a new wave of AI research that trains models on how real people play video games, including their mistakes and sloppy habits, rather than only on expert or scripted play. The idea is that human error contains useful data for teaching AI systems to behave more naturally. The piece is being shared and discussed in tech and gaming circles.

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    An open-source model for medical video AI is being credited with speeding up global progress in the field. Reports say making the model freely available allows researchers and health developers worldwide to build diagnostic and analysis tools faster, without starting from scratch. The move is seen as lowering barriers to advanced medical imaging technology, particularly for hospitals and research teams with limited resources.

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    AI model Jev beats Pokémon Red in under a week●Developer says AI decision model Jev beat Pokémon Red in under a week — non-LLM engine succeeds where traditional chatbots stalled for months, but Claude Opus 5 coached the model through its dead ends✉newsTechnologyAI5 d ago

    A developer says Jev, a non-LLM AI decision model, has completed Pokémon Red in under a week, a feat that reportedly stalled traditional chatbot-based attempts for months. According to the report, Claude Opus 5 acted as a coach, helping Jev work through dead ends during the run. The result is being discussed as evidence that specialized decision engines can outperform large language models on structured, long-horizon tasks like game completion.

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    British startup trains AI on video game player inputs●📰 The Next Evolution of AI Is Learning From Your Dodgy Gaming Skills A British startup is shaping video game inputs intoMmastodonTechnologyAI15 d ago

    A British startup is turning video game controller inputs into training data for AI models designed to navigate the physical world. The idea is that human gameplay, including mistakes and clumsy manoeuvring, offers rich examples of how people learn to control complex systems, which could help robots and other embodied AI improve. The approach is drawing attention as a cheaper alternative to real-world data collection.

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    A new AI model called Griffin is drawing attention for its ability to hold natural, real-time voice conversations, including interrupting people the way a human would. The company behind it says the system is already fooling people on video calls into believing they are speaking with a person. The development is fueling fresh debate about how quickly AI is crossing the line into convincingly human-like interaction.

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    Greg Kroah-Hartman on security in the LLM age●Greg Kroah-Hartman – Security in the LLM Age [video] Article URL: https://www. youtube.com/watch?v=NnV_cWeoo5Q CommentsMmastodonTechnologyCybersecurity33 h ago

    Kernel developer Greg Kroah-Hartman, the maintainer of the Linux kernel stable branches, has given a talk on what large language models mean for software security. The presentation examines how AI-generated code affects vulnerability handling and maintenance work in large open source projects. The talk is circulating among developers and technology commentators, with early responses still limited but interest growing in how core infrastructure maintainers view LLM-driven risks.

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    Python script paces multi-shot AI video generations●AI video models now let you cut between several shots inside one generation. That's great, until you... # python # ai #MmastodonTechnologyAI32 d ago

    AI video models can now generate several distinct shots within a single generation, letting creators cut between angles without stitching separate clips. A developer has shared a small Python script that helps pace a 15-second multi-shot AI video, timing each cut. The technique highlights how AI video tools are becoming more production-ready, though quality and consistency across shots remain a concern.

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    MoneyPrinterTurbo, an open-source Python project by developer harry0703, automates the creation of high-definition short videos. Users enter a topic or keyword and the tool uses large AI models and an automated workflow to produce a finished clip. The project is gaining attention among developers and content creators interested in AI-powered video generation.

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    Greg Kroah-Hartman on security in the LLM age▼Greg Kroah-Hartman – Security in the LLM Age [video]YhnTechnologyAI24511 min ago

    Greg Kroah-Hartman, the longtime maintainer of the Linux kernel's stable branch, has released a talk on what large language models mean for software security. He is one of the most influential figures in open-source kernel development, so his views on how AI-generated code affects vulnerability review and maintenance carry weight. The talk is drawing discussion among developers weighing the security risks and benefits of LLM-assisted programming.

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    AI video company Tavus has introduced Griffin, a conversational video model it says is realistic enough to pass a video Turing test. The announcement is drawing attention to how closely AI-generated humans now resemble real people on camera, and to what that means for trust in video, digital identity and online deception.

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    Runway unveils Praxis-1 world action model for robotics▼Runway introduces Praxis-1 world action model for robotics✉newsTechnologyRobotics21 min ago

    Runway, the AI company best known for generative video, has introduced Praxis-1, a world action model aimed at robotics. The model is designed to help robots understand and act in physical environments, extending Runway's work beyond media generation. Details on capabilities and partners remain limited, but the move signals growing competition among AI firms to bring foundation models into real-world robotics applications.

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    Tavus's Griffin AI model fools humans in nearly half of video call tests▼US startup Tavus unveils Griffin model — 48% of test subjects mistook video call partner for a real human✉newsBusinessStartups35 min ago

    US startup Tavus has unveiled Griffin, a conversational video model so lifelike that 48% of test subjects mistook their video call partner for a real person. The result highlights how quickly AI-generated human avatars are approaching the point where viewers can no longer reliably tell them apart from real people on live calls.

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    NVIDIA's Physis-Lang Pushes Cosmos 3 Past Veo 3.1 on Physics●NVIDIA Researchers Introduce Physis-Lang: Self-Evolving Physical Language That Lifts Cosmos 3 Past Veo 3.1 on Physics Benchmarks✉newsSciencePhysics2 d ago

    NVIDIA researchers have introduced Physis-Lang, a self-evolving physical language designed to improve how AI models understand and simulate physical dynamics. According to reports, the technique lifted NVIDIA's Cosmos 3 video generation model past Google's Veo 3.1 on physics benchmarks, suggesting stronger real-world motion and interaction fidelity in generated video.

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    Peking University, Tsinghua and Alibaba open-source SparkDiffusion video AI accelerator●Peking University, Tsinghua and Alibaba have open-sourced SparkDiffusion, an AI video generation accelerator. The framewMmastodonTechnology13 d ago

    Peking University, Tsinghua University and Alibaba have released SparkDiffusion as an open-source framework that dramatically speeds up AI video generation. The tool cuts Wan 2.1 video generation time by a factor of 265, reducing it from 4,769 seconds to 18 seconds on an Nvidia RTX 5090 GPU. Code and model weights are freely available on GitHub and Hugging Face, letting developers adopt the accelerator immediately.

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    Running Xiaomi's MiMo Qwen 9B Distill on a 16GB MacBook Pro●This is the third video already in the series I started this month. I am trying to share my... # ai # programming # tutoMmastodonTechnologySoftware33 d ago

    A developer is demonstrating Xiaomi's MiMo V2.6 Qwen 9B distill model running locally on a 16GB MacBook Pro, the third installment in a tutorial series launched this month. The series covers AI, programming and agents, with an emphasis on inclusive, community-oriented learning. Interest centres on whether mid-range laptops without high-end GPUs can now run capable open-weight language models.

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