People panic about ownership and borrowing in Rust, like it's impossible to learn. But that's actually the simple part. The real problem? Generic function signatures that look like keyboard spam: impl<T: Clone + Send + 'static> Future<Output = Result<Box<dyn Trait>, Arc<Mutex<Error>>>> See what I mean?

Introducing MLX-Audio Studio 🚀 An open-source UI for audio gen. This new UI will allow you to easily generate and transcribe audio locally using MLX-Audio, Transformers or any other backend you prefer (i.e. OpenAI). We will be adding more tasks soon, stay tuned! Get started on our GH: github.com/Blaizzy/mlx-audio

We’re excited to announce the open sourcing of tokio-quiche, our async QUIC library built on quiche and tokio. cfl.re/4oicNwE

ML research is an engineering discipline, not a philosophy seminar. You build, you test, you learn. Untested ideas are just speculation.

Mainmatter is looking for an experienced Rust developer to join one of our projects as a freelancer. We're migrating a database from C to Rust. The project is complex and performance-sensitive. That's what makes it fun! If you're interested, send an email to the address in the screenshot.

Hottest paper on AlphaXiv 📈 Language Models are Injective and Hence Invertible Every prompt maps to a unique hidden state and can be exactly reconstructed with this paper’s algorithm SIPIT. This means the model’s internal activations are the full prompt in disguise!!

cool idea from Meta What if we augment CoT + RL’s token space thinking into a “latent space”? This research proposes “The Free Transformer”, with a way to let LLMs make global decisions within a latent space (via VAE encoder) that could later simplify autoregressive sampling

Stanford just published a huge 470-page study 📕 "The Principles of Diffusion Models" Explains how diffusion models turn noise into data and ties their main ideas together. It starts from a forward process that adds noise over time, then learns the exact reverse. The reverse uses a time dependent velocity field that tells how to move a sample at each step. Sampling becomes solving a time based equation that carries noise to data along a trajectory. There are 3 views of this idea, variational, score-based, and flow-based, and they describe the same thing. There are also 4 training targets, noise, clean data, score, and velocity, and these are equivalent. Shows how guidance can steer outputs using a prompt or label without extra classifiers. Reviews fast solvers that cut steps while keeping quality stable. Explains distillation methods that shrink many sampling steps into a few by mimicking a teacher model. Introduces flow map models that learn direct jumps between times for fast generation from scratch.

Holy shit… Meta might’ve just solved self-improving AI 🤯 Their new paper SPICE (Self-Play in Corpus Environments) basically turns a language model into its own teacher no humans, no labels, no datasets just the internet as its training ground. Here’s the twist: one copy of the model becomes a Challenger that digs through real documents to create hard, fact-grounded reasoning problems. Another copy becomes the Reasoner, trying to solve them without access to the source. They compete, learn, and evolve together an automatic curriculum with real-world grounding so it never collapses into hallucinations. The results are nuts: +9.1% on reasoning benchmarks with Qwen3-4B +11.9% with OctoThinker-8B and it beats every prior self-play method like R-Zero and Absolute Zero. This flips the script on AI self-improvement. Instead of looping on synthetic junk, SPICE grows by mining real knowledge a closed-loop system with open-world intelligence. If this scales, we might be staring at the blueprint for autonomous, self-evolving reasoning models.

Lutter pour une société inclusive, c’est lutter pour la paix et la justice. SINGA en a fait la preuve, et moi, je continue à faire tout ce que je peux pour la soutenir. fr.ulule.com/defendons-singa… #ulule #crowdfunding

Tired of chasing references across dozens of papers? This monograph distills it all: the principles, intuition, and math behind diffusion models. Thrilled to share!

🧩 Are you one of over 240 million subscribers of Amazon’s Prime Video service? - If so,you might be surprised to learn that much of the infrastructure behind Prime Video is built using Rust - Using Leptos for the UI of their streaming app for smart TVs corrode.dev/podcast/s05e01-p…

Rig 0.23.0 is now officially available! The leading AI framework in Rust grows yet again, and with even more features to boot. Want a feature rundown? Check out the thread below 🧵👇

Book signings hit different when it’s an author like @rasbt. At @PyTorch Conf, fans lined up for signatures and selfies — proof that his reach goes way beyond social. Get your copy of Build a Large Language Model (From Scratch): hubs.la/Q03Q55Pn0 Drop your selfies below ↓

There’s no “idea owners” in this game. Any idea you have, someone else in the world most likely already had the same idea. And if you don’t see anywhere else, someone probably tried and failed because there’s no market. Ideas worth nothing without shipping.

reminder that i'm doing a talk on the 4th of november at rust manchester about bridging rig to JS through wasm - no detail will be missed here make sure you grab a slot because this talk probably won't be recorded get your seat: meetup.com/rust-manchester/e…

After doing OOP for quite some time - both in my daily job and for hacking in projects - taking time to now explore the depths of category theory using rust , especially these series of blog posts are specially useful : kurtlawrence.info/blog/categ…

We used DeepSeek OCR to extract every dataset from tables/charts across 500k+ AI arXiv papers for $1000 🚀 See which benchmarks are trending and discover datasets you didn't know existed Doing the same task with Mistral OCR would've cost $7500 👀

Joining @vercel is an embarrassing admission of being morally desolate. Like a permanent emblem of willingly arming a ww2 concentration camp, fully aware of what’s inside.

Bullshit