🎉 Big news: RxInfer.jl is now a @NumFOCUS Affiliated Project! Born from PhD research on reactive message passing, it’s now an open-source tool for fast, scalable Bayesian inference — and part of a world-class ecosystem #JuliaLang #BayesianInference #NumFOCUS #OpenSource

This is a cool Julia version of my Jax library for Bayesian Structural Time Series modeling (github.com/probml/sts-jax) from the folks at @ReactiveBayes. It can easily handle non-linear and non-conjugate likelihoods (eg Poisson distribution for integer count observations). For inference, it uses a very fast variational message passing algorithm (combined with data augmentation and local MC approximations for non-conjugate messages). In this example, they infer the latent states of the SSM as well as the model parameters (representing how the continuous latent demand evolves over time). But their RxInfer.jl library also supports inference in many other kinds of graphical model (see examples.rxinfer.com/).

New Bayesian Structured Time Series example: predicting taco demand during #NeurIPS 2025 ⚡️ Learnable Dynamics 🔢 Non-Conjugacies 🏎️ Blazing Speed examples.rxinfer.com/categor… #JuliaLang #BayesianInference #DataScience

🏆 Best Technical Paper at @iwai_ws! Recasting EFE planning as Variational Inference → sample-efficient Active Inference agents that actually run. Built in RxInfer. Won by @wouterwln. Paper: arxiv.org/abs/2508.02197 Code: github.com/biaslab/EFEasVFE #IWAI2025 #RxInfer #Bayesian

🚀 We’re open-sourcing Gears.jl — a Julia package for precise task scheduling in simulation environments! ⚙️ Run timed, event-based, or ASAP jobs with flexible schedulers, multiple clocks, and multi-threading. 🔗 github.com/lazydynamics/Gear… #JuliaLang #OpenSource #Agents

We've been seeing some cool examples of fast Bayesian inference LLMs - from trust/reliability to LLMs participating in inference (even learning to derive variational rules!). Check out the examples: examples.rxinfer.com/

We’re on Discord! 🎧🚀 Moving beyond GitHub discussions—join the new RxInfer server (by @LazyDynamics ) to chat, ask Qs, get updates, and plan hackathons. Jump in: discord.gg/UvMhrbQh #RxInfer #BayesianInference #ProbabilisticProgramming

We’re on Discord! You asked for better community engagement around RxInfer & RxInfer Pro—so here it is. Join us for Q&A, updates, hackathons & more. It’s quiet now, but let’s build it together. 📷 discord.gg/UvMhrbQh #RxInfer #BayesianInference #ProbabilisticProgramming

In Active Inference, a lot of time is spent on computing Expected Free Energy. What if we could tweak the generative model such that EFE can be minimised with traditional variational inference methods?

🧠 We hooked LLMs into Bayesian inference in 30 minutes ChatGPT as a native node in message-passing. Working sentiment clustering with uncertainty quantification. 📖 Notebook: examples.rxinfer.com/categor… #BayesianInference #LLM

rxinfer.com can be powerful for robotics - but requires deep probabilistic programming knowledge. What if there was a simpler way? LLM → RxInfer → Robotics = 𝗖𝘂𝗿𝘀𝗼𝗿 𝗳𝗼𝗿 𝗿𝗼𝗯𝗼𝘁𝗶𝗰𝘀? #RxInfer #Robotics #LLM #CursorForRobotics #AIRobotics

Check out our DeepWiki page - it looks pretty accurate! deepwiki.com/ReactiveBayes/R… Thanks to @cognition_labs!

🎯 New Contextual Multi-Armed Bandits example in RxInferExamples.jl! Fresh take using message passing inference. No MCMC, no hyperparameters - just principled decision making. examples.rxinfer.com/categor… #BayesianML #JuliaLang #RxInfer

100%.

🚀Behind the scenes at Lazy Dynamics: We are working on Cortex, our future reactive message-passing backend for RxInfer! Designed for fast, reliable, and asynchronous probabilistic inference on edge devices. Ideal for robotics, audio processing, and more. github.com/ReactiveBayes/Cor…

That is 🤯

Probabilistic modeling in Julia just got smoother. With RxInfer GraphPPL, you write models like regular code — loops, functions, submodels — and it handles the inference under the hood. From simple regressions to massive hierarchies. Check it out 👇 examples.rxinfer.com/

LLMs were a leap — but the next gen of AI won’t just generate. It will adapt in real-time. At Lazy Dynamics, we’re building reactive AI with RxInfer: real-time Bayesian inference for uncertain, dynamic environments. The future of AI is reactive. #EdgeAI #Bayesian #RxInfer #AI

Thanks to @LazyDynamics for open-sourcing latent vector autoregressive model for RxInfer! Handles 20 5th-order AR processes, 2000 noisy obs, and 50-step predictions in 3s. 🔗examples.rxinfer.com/categor… #ProbabilisticProgramming #OpenSource #RxInfer

New paper alert! Active Inference (AIF) agents score policy candidates using a cost function called the Expected Free Energy (EFE), which has many desirable features, such as a parameter-free balance between information-seeking and goal-driven behavior. (1/4)