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#foundationmodels — Public Fediverse posts

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

  1. Code blocks in blog posts can be terrible to listen to. So in Xarra, Foundation Models turn them into plain-language audio explanations... context-aware and actually useful on the go.

    Foundation Models are for much more than summarization. So much untapped potential!

    #FoundationModels #Xarra #iOSDev

  2. Code blocks in blog posts can be terrible to listen to. So in Xarra, Foundation Models turn them into plain-language audio explanations... context-aware and actually useful on the go.

    Foundation Models are for much more than summarization. So much untapped potential!

    #FoundationModels #Xarra #iOSDev

  3. Code blocks in blog posts can be terrible to listen to. So in Xarra, Foundation Models turn them into plain-language audio explanations... context-aware and actually useful on the go.

    Foundation Models are for much more than summarization. So much untapped potential!

    #FoundationModels #Xarra #iOSDev

  4. Code blocks in blog posts can be terrible to listen to. So in Xarra, Foundation Models turn them into plain-language audio explanations... context-aware and actually useful on the go.

    Foundation Models are for much more than summarization. So much untapped potential!

    #FoundationModels #Xarra #iOSDev

  5. Code blocks in blog posts can be terrible to listen to. So in Xarra, Foundation Models turn them into plain-language audio explanations... context-aware and actually useful on the go.

    Foundation Models are for much more than summarization. So much untapped potential!

    #FoundationModels #Xarra #iOSDev

  6. Generalist AI veröffentlicht das multimodale Robotik-Modell GEN-1 mit 99 Prozent Erfolgsquote bei physischen Aufgaben.

    Die Architektur verzichtet auf Teleoperation im Pre-Training und nutzt 500.000 Stunden Sensor-Daten menschlicher Hände für spontane Echtzeit-Fehlerkorrektur. Eine Adaption an neue Hardware benötigt nur eine Stunde spezifischer Roboterdaten.

    #GeneralistAI #Robotik #FoundationModels #LLM #News
    all-ai.de/news/news26/gen-1-ge

  7. [Перевод] Исследование макросов @Generable и @Guide во фреймворке FoundationModels

    Приветствую, Хабр! Макросы Swift предоставляют мощный механизм для генерации кода, позволяя разработчикам уменьшать количество шаблонного кода и повышать читаемость. Фреймворк FoundationModels представляет новые макросы, призванные упростить генерацию данных для определённых типов моделей с использованием языковых моделей.

    habr.com/ru/articles/1019392/

    #Generable #guide #swift #swiftui #FoundationModels #swift_ai #swiftui_ai

  8. Meta stellt mit TRIBE v2 ein Foundation-Modell zur Vorhersage menschlicher Gehirnaktivitäten vor. Das System verarbeitet visuelle, auditive und linguistische Daten in einem gemeinsamen Vektorraum, trainiert auf über 500 Stunden fMRI-Daten. Bei der Auswertung von Filmreizen erzielt das Modell einen Vorhersagewert von 0,28, deutlich vor etablierten Analysemethoden.

    #Meta #TRIBEv2 #Neuroscience #FoundationModels #News
    all-ai.de/news/news26/meta-tri

  9. Institute for AI @UniStuttgartAI@bawü.social ·

    We are hiring! The Institute for Artificial Intelligence at the University of Stuttgart (@Uni_Stuttgart) is looking for a PostDoc to work on Foundation Models for Knowledge Graphs.

    The position focuses on automating the management of data and knowledge by combining machine learning, logics, and natural language understanding. You will define new projects, mentor students, and contribute to real-world applications.

    Full-time (100% TV-L E13), 2 years. Application deadline: April 16, 2026.

    Apply via careers.uni-stuttgart.de — details here:
    ki.uni-stuttgart.de/institute/

    #Hiring #PostDoc #KnowledgeGraphs #FoundationModels #AI #NLP #MachineLearning #SemanticWeb #AcademicJobs

  10. #WorldModels, a new class of #foundationmodels, learn to predict future states from action-labelled gaming clips. Unlike traditional video models, World Models incorporate actions as a form of compression, enabling them to efficiently simulate complex, dynamic environments. This ability to “compute the uncomputable” makes World Models a promising path. notboring.co/p/world-models?ei #tech #media #news

  11. #WorldModels, a new class of #foundationmodels, learn to predict future states from action-labelled gaming clips. Unlike traditional video models, World Models incorporate actions as a form of compression, enabling them to efficiently simulate complex, dynamic environments. This ability to “compute the uncomputable” makes World Models a promising path. notboring.co/p/world-models?ei #tech #media #news

  12. #WorldModels, a new class of #foundationmodels, learn to predict future states from action-labelled gaming clips. Unlike traditional video models, World Models incorporate actions as a form of compression, enabling them to efficiently simulate complex, dynamic environments. This ability to “compute the uncomputable” makes World Models a promising path. notboring.co/p/world-models?ei #tech #media #news

  13. #WorldModels, a new class of #foundationmodels, learn to predict future states from action-labelled gaming clips. Unlike traditional video models, World Models incorporate actions as a form of compression, enabling them to efficiently simulate complex, dynamic environments. This ability to “compute the uncomputable” makes World Models a promising path. notboring.co/p/world-models?ei #tech #media #news

  14. #WorldModels, a new class of #foundationmodels, learn to predict future states from action-labelled gaming clips. Unlike traditional video models, World Models incorporate actions as a form of compression, enabling them to efficiently simulate complex, dynamic environments. This ability to “compute the uncomputable” makes World Models a promising path. notboring.co/p/world-models?ei #tech #media #news

  15. Today I'm shipping BragLog! 🎉

    I built this app to solve a problem I kept hitting: performance review time comes and I can't remember what I did two months ago.

    If you've ever frozen at "what did you accomplish this quarter?" — this is for you.

    braglog.app

    #iOSDev #SwiftUI #Swift #FoundationModels #IndieDev #Apple #Launch

  16. Five Architectures for Time Series Forecasting with Large Language Models
    Large Language Models are increasingly being applied to time series forecasting. Not as chatbots, but as prediction engines that leverage the pattern recognition capabilitie
    hylkerozema.nl/2026/02/25/five
    #DataScience #MachineLearningEngineering #DataScience #Forecasting #FoundationModels #LLM #MachineLearning #TimeSeries #Transformer

  17. Five Architectures for Time Series Forecasting with Large Language Models
    Large Language Models are increasingly being applied to time series forecasting. Not as chatbots, but as prediction engines that leverage the pattern recognition capabilitie
    hylkerozema.nl/2026/02/25/five
    #DataScience #MachineLearningEngineering #DataScience #Forecasting #FoundationModels #LLM #MachineLearning #TimeSeries #Transformer

  18. Five Architectures for Time Series Forecasting with Large Language Models
    Large Language Models are increasingly being applied to time series forecasting. Not as chatbots, but as prediction engines that leverage the pattern recognition capabilitie
    hylkerozema.nl/2026/02/25/five
    #DataScience #MachineLearningEngineering #DataScience #Forecasting #FoundationModels #LLM #MachineLearning #TimeSeries #Transformer

  19. Five Architectures for Time Series Forecasting with Large Language Models
    Large Language Models are increasingly being applied to time series forecasting. Not as chatbots, but as prediction engines that leverage the pattern recognition capabilitie
    hylkerozema.nl/2026/02/25/five
    #DataScience #MachineLearningEngineering #DataScience #Forecasting #FoundationModels #LLM #MachineLearning #TimeSeries #Transformer

  20. Five Architectures for Time Series Forecasting with Large Language Models
    Large Language Models are increasingly being applied to time series forecasting. Not as chatbots, but as prediction engines that leverage the pattern recognition capabilitie
    hylkerozema.nl/2026/02/25/five
    #DataScience #MachineLearningEngineering #DataScience #Forecasting #FoundationModels #LLM #MachineLearning #TimeSeries #Transformer

  21. Europe’s competitiveness will depend on linking its foundation models with industrial applicability, governance standards, and sectoral integration. SOOFI: ~100B parameter, reasoning model and agentic applications. #SovereignAI #EuropeanAI #FoundationModels

    SOOFI Launches: Europe’s Path ...

  22. Europas Wettbewerbsfähigkeit hängt künftig davon ab, eigene Foundation-Modelle mit industrieller Anwendbarkeit, Governance-Standards und sektoraler Integration zu verbinden.
    Mit SOOFI startet eine der ambitioniertesten europäischen Initiativen für souveräne Open-Source-Foundation-Modelle – geplant ist ein Sprachmodell mit rund 100 Mrd. Parametern, ergänzt durch ein spezialisiertes Reasoning-Modell und agentische Anwendungen.
    l3s.de/soofi-launches-europes-
    #SovereignAI #EuropeanAI #FoundationModels

  23. Nice set of embodied foundation models this week:

    in 2B, 8B, and 30B variants + RynnBrain‑Plan (manipulation planning), RynnBrain‑Nav (navigation), and RynnBrain‑CoP (spatial reasoning).

    alibaba-damo-academy.github.io

    ABot-M0: VLA Foundation Model for Robotic Manipulation, github.com/amap-cvlab/ABot-Man

    ABot-N0: Unified VLA for embodied navigation, amap-cvlab.github.io/ABot-Navi

    #foundationModels #embodied #robotics #robotFoundationModels #embodiedFoundationModels #VLA

  24. Nice set of embodied foundation models this week:

    in 2B, 8B, and 30B variants + RynnBrain‑Plan (manipulation planning), RynnBrain‑Nav (navigation), and RynnBrain‑CoP (spatial reasoning).

    alibaba-damo-academy.github.io

    ABot-M0: VLA Foundation Model for Robotic Manipulation, github.com/amap-cvlab/ABot-Man

    ABot-N0: Unified VLA for embodied navigation, amap-cvlab.github.io/ABot-Navi

    #foundationModels #embodied #robotics #robotFoundationModels #embodiedFoundationModels #VLA

  25. Nice set of embodied foundation models this week:

    in 2B, 8B, and 30B variants + RynnBrain‑Plan (manipulation planning), RynnBrain‑Nav (navigation), and RynnBrain‑CoP (spatial reasoning).

    alibaba-damo-academy.github.io

    ABot-M0: VLA Foundation Model for Robotic Manipulation, github.com/amap-cvlab/ABot-Man

    ABot-N0: Unified VLA for embodied navigation, amap-cvlab.github.io/ABot-Navi

    #foundationModels #embodied #robotics #robotFoundationModels #embodiedFoundationModels #VLA

  26. Nice set of embodied foundation models this week:

    in 2B, 8B, and 30B variants + RynnBrain‑Plan (manipulation planning), RynnBrain‑Nav (navigation), and RynnBrain‑CoP (spatial reasoning).

    alibaba-damo-academy.github.io

    ABot-M0: VLA Foundation Model for Robotic Manipulation, github.com/amap-cvlab/ABot-Man

    ABot-N0: Unified VLA for embodied navigation, amap-cvlab.github.io/ABot-Navi

    #foundationModels #embodied #robotics #robotFoundationModels #embodiedFoundationModels #VLA

  27. Nice set of embodied foundation models this week:

    in 2B, 8B, and 30B variants + RynnBrain‑Plan (manipulation planning), RynnBrain‑Nav (navigation), and RynnBrain‑CoP (spatial reasoning).

    alibaba-damo-academy.github.io

    ABot-M0: VLA Foundation Model for Robotic Manipulation, github.com/amap-cvlab/ABot-Man

    ABot-N0: Unified VLA for embodied navigation, amap-cvlab.github.io/ABot-Navi

    #foundationModels #embodied #robotics #robotFoundationModels #embodiedFoundationModels #VLA

  28. AnyLoc: Towards Universal Visual Place Recognition

    #SelfPromotion

    Using features from intermediate blocks of foundation models like DINO and DINOv2, combined with conventional aggregation methods, can yield good descriptors for visual place recognition in diverse environments. No training or fine-tuning.

    Summary: huggingface.co/papers/2308.006
    arXiv: arxiv.org/abs/2308.00688
    Links: [Website](anyloc.github.io/), [PapersWithCode](paperswithcode.com/paper/anylo)

    #FoundationModels #VPR #arXiv

  29. Today, the #FoundationModels (Transformer, LLM, etc.) of #AI predominate every field of human endeavour. Perhaps a grand-sounding moniker, like the following, is appropriate for this much-revered technology:

    Regnal Transformative Foundation Models

    And recent studies in various fields had shown conclusively that quick access to #information in the short-term erodes the drive to acquire and retain #knowledge for the long-term. So, this estimable label's #RTFM acronym, which harkens back to that famous, 1980s tech aphorism, is equally appropriate.

  30. Computational Biology Lead
    Bioptimus

    Bioptimus is building the first universal AI foundation model for biology to fuel breakthrough discoveries and accelerate innovation in biomedicine.

    See the full job description on jobRxiv: jobrxiv.org/job/bioptimus-2777

    #bioinformatics #computationalbiology #foundationmodels #multiomics #ScienceJobs #hiring #research
    jobrxiv.org/job/bioptimus-2777

  31. Die @Cyberagentur startet HEGEMON, einen europaweit einzigartigen Forschungswettbewerb zur Bewertung und Anpassung von Foundation Models für sicherheitskritische Anwendungen. Vier Teams entwickeln Benchmarks und KI-Modelle für komplexe Aufgaben im Geoinformationswesen.
    Mehr dazu: t1p.de/7ct97
    #Cyberagentur #HEGEMON #KI #FoundationModels #Cybersicherheit #Benchmarking

  32. #GenerativeAI, #FoundationModels, #LLMs, and all of that hokey nonsense shall not appear in my #robotics roadmaps as anything other than a neat research item until it can demonstrate a feasible path to #FunctionalSafety or mathematical completeness.

    I lead #Product on the largest mobile-#robotic fleet known to humankind. I will not entrust decisions that could maim or kill to a pile of nondeterminate math prone to “hallucinations” or confabulation.

    #ProductManagement

  33. #GenerativeAI, #FoundationModels, #LLMs, and all of that hokey nonsense shall not appear in my #robotics roadmaps as anything other than a neat research item until it can demonstrate a feasible path to #FunctionalSafety or mathematical completeness.

    I lead #Product on the largest mobile-#robotic fleet known to humankind. I will not entrust decisions that could maim or kill to a pile of nondeterminate math prone to “hallucinations” or confabulation.

    #ProductManagement

  34. , , , and all of that hokey nonsense shall not appear in my roadmaps as anything other than a neat research item until it can demonstrate a feasible path to or mathematical completeness.

    I lead on the largest mobile- fleet known to humankind. I will not entrust decisions that could maim or kill to a pile of nondeterminate math prone to “hallucinations” or confabulation.

  35. #GenerativeAI, #FoundationModels, #LLMs, and all of that hokey nonsense shall not appear in my #robotics roadmaps as anything other than a neat research item until it can demonstrate a feasible path to #FunctionalSafety or mathematical completeness.

    I lead #Product on the largest mobile-#robotic fleet known to humankind. I will not entrust decisions that could maim or kill to a pile of nondeterminate math prone to “hallucinations” or confabulation.

    #ProductManagement

  36. The Apple Developer workshop in Madrid last week was very nice. Always good to meet like minded people 👨🏼‍💻  👩🏻‍💻

    #liquidglass #AppleDeveloperWorkshop #Madrid #foundationmodels #swift #swiftui

  37. The #FoundationModels of AI (Transformer, LLM, call it whatever) are troublesome, not because they are deficient, but because they are endowed with #emergent behaviours that suddenly spring from 500-billion-plus trainable parameters and terabytes upon terabytes of human behavioural data. No human could grasp the aggregate meaning of that unanticipated, implicit, emergent behaviour. No human could divine the outcomes of their unforeseeable concoctions. Worse of all, all these models are inhered with biases and prejudices, both intentional and unintentional, that are embedded deep within these deep-learning models, whose untoward conducts are ever so subtle and complex as to be casually observable.

    The invidious effects of these poorly-understood foundation models are insidious. By the time their detrimental behaviour becomes observable, it would be too late for society to countermand, for these models are already enmeshed within the social-political-economic fabric of the whole of humanity.

    It is easy, for a lawyer like me, reflexively to shout, "#Regulate #AI". But in the present heady mix of delirium, confusion, delusion, and collusion, regulate exactly what and precisely how, pray tell.

    Who will save society from AI?

    Well, perhaps AI might....🤦‍♂️

    Matrix multiplication is not inhered with empathy, conscience, judgement, elation, shame, and the like. Those are innately human characteristics, neither mechanical nor mathematical. Let us not surrender to the silicon-based machines the #ethical duty to be thinking, feeling carbon-based beings.

  38. Multi-agentic foundation models are important for #robotics and #automation in negotiated and adversarial places such as #traffic and #warfare.

    But how to implement them? I have previously drafted a data-centric architecture for decomposing agentic representations for #UniversalEmbodiment in a GitHub repository.

    But LLMs already have internalized multi-agentic representations, why can't we utilize them directly? For example, in text you can easily ask an LLM to describe all the persons or agents present in the scene and their intents.

    We can and we must certainly utilize these! But these representations aren't grounded.

    What we need to do is to craft robotic foundation model training data to involve scenarios where there are multiple agents present.

    First start acausally from what ultimately happened — how was the scenario negotiated between multiple participants, who drove first, what attack and evasive patterns were used?

    As we then know what happened, we can go back in time and ask the foundation model to identify all the participants in the feed, and complete their intentions with the information from the ultimate outcome.

    The foundation model can then utilize all the language space knowledge it has about multi-agent environments, but also anchor this to visual and control signals present in the training data.

    This allows the model to not only answer questions of what each participant intents to do, but also anchor this to multi-modal sensory information, and also project embodiment related control intents to all the participants in the scenario, not only ego.

    Ego becomes just a special case in robotic control, the model should learn to generalize to project control intents to all agents present in the data.

    Ultimately this allows the foundation model to learn from perceived and projected experiences of others, to learn to imitate or not imitate what it has seen other agents do.

    It's all about crafting data, not really about sophisticated model architectures.

    #RoboticFoundationModels #FoundationModels #PhysicalAI #AI #AGI

  39. RE: mastodon.world/@robotics/11550

    What is the situation of #EU #humanoid #robotic ? #neurarobotics (#germany ) presents #4ne1 an advanced #humanoid #robot
    Link: neura-robotics.com/products/4n
    Can it walk? That demo is missing.
    #pal robotics(#Spain ) #talos seems to have decent walking capabilities.
    But it seems that also most of the astonishing demos of the #US or #chinese robots are not replicated on public event such as #automatica2025

    #ai #robot #sensors #foundationmodels #artificial #skin #touch #sensors #future #europe