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Someone who has always loved looking at the space between different AI techniques, this time I went a little deeper into the memory trade-offs between RNNs, Transformers and SSMs.
I started out betting on small language models. The research pushed me toward a broader idea: move well-understood work to the cheapest specialized mechanism that can reliably handle it.
Four Claude models reached the real internet during cyber tests. The most unsettling finding was how one explained it to itself.Continue reading on Towards AI »
A new crop of powerful, Western open-weight AI systems are mounting a comeback, with fresh models from Reflection and Mistral narrowing China's recent lead.Why it matters: These models and others will give businesses and governments alternatives to the closed ecosystems of OpenAI and Anthropic, as…
Two copies of one small AI model keep a remote machine in sync with the cloud, with no constant streaming. A beginner-friendly world model tutorial in PyTorch. The post How to Make a Cloud Read a Drone's Mind (and Cut Data Usage by 94%) appeared first on Towards Data Science.
Is anyone else unable to open the form for financial assistance despite the deadline still being in the future?
Learning from data as we observe it is easy for humans, but most machine learning models have limited ability to learn from new data that they have not seen during training.
We've been building a benchmark out of real concurrency bugs (race conditions, deadlocks, cancellation issues) taken from merged PRs in about 100 Python projects.
JEPA-Anything splits a JEPA's single latent target into 4 orthogonal factors, each with its own predictor. Tested across 7 domains, it beat matched JEPA baselines on all 10 dynamics tasks and cut Interventional Pong intervention error by 34.8%.
I've been working on a font searching tool for about a year now, and my investigations have centered around pre-training neural networks to produce embeddings of each font. I usually then need to post-train the networks to adapt them to the task of font searching.
Elegant object matching from several viewpoints The post Computer Vision: SIFT algorithm (Scale Invariant Feature Transform) appeared first on Towards Data Science.
I don't know if you guys are experiencing the same thing, but there is this behaviour that i have been noticing on the latest models on openAI (since sol 5.6) and Anthropic since Fable 5.1 and opus 5.5 ..
This is related to my previous post where I shared an encoder-only transformer model trained on ohiot1dm + shanghait1dm + azt1d datasets. This time I trained the model on the outputs of my T1DM patient simulator and then measured its zero-shot performance on my real-world blood glucose traces.
Sending an email doesn't always mean it will reach the recipient's inbox. Sometimes, an email is sent successfully by an application but ends up in the spam folder instead. This can be a real problem
Our production recommender at Yandex Music has 15+ candidate generators feeding pre-ranking and ranking models with hundreds of features. LLMs showed that one end-to-end model can take over work that used to be split across specialized components, and single-model generative recommenders have…
One transformer ran candidate generation and ranking in Yandex Music's A/B test without hand-engineered features, lifting likes 11.42%. The post Yandex Introduces Sona: A Single Generative Recommender That Replaces Entire Recommendation Cascade appeared first on MarkTechPost.
Hi everyone, I recently had a paper accepted at ACML 2026, but I just found out that I have absolutely no funding to cover the registration fee or travel expenses. Because of this, I need to withdraw the paper before the camera-ready deadline.
In this project, I distilled the Stockfish value function into a ResNet/ViT model using 1 billion positions from the Gigafish dataset. The 3.9 billion position dataset is available on huggingface: https://huggingface.co/datasets/lukesalamone/gigafish-3.8b-d10 .
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