machine learning

NeurIPS 2026 Paris complimentary registration already full. Did any Top Reviewers get a spot? [D]

I was selected as a NeurIPS 2026 Top Reviewer and awarded complimentary registration.

I trained a 414k-parameter transformer to fly a boids flock, then tested whether the rules a probe can read are the ones it uses [P]

I wrote a small boid simulator (12 birds), recorded it flying, and trained a transformer to predict each bird's next move without it knowing about any boid rules.

World Action Models vs VLAs: Robotics Just Had Its GPT-2 Moment [N]

Pecision models that score every allowed label from the logits: Jebadiah v2.1 (27B, 9B), open weights and self-run benchmark results [P]

I've been building open models that treat a decision as a closed-set scoring problem rather than text generation. The input is structured context plus a typed question with a fixed set of options.

OrcaRouter Releases OrcaCyber Zero 1.5 Cybersecurity Model With 1M Context

OrcaRouter released OrcaCyber Zero 1.5, a gated cybersecurity model with a 1M-token context window. It reports 100% on Cybench and 95.8% on an evaluable CVE-Bench subset, priced at $3.00 / $7.50 per 1M tokens.

Do I need to do anything now to use an ARR August review for NAACL 2027? [D]

This is my first time ARR submission. I have a paper from the ARR 2026 August cycle with completed reviews and I understand the reviews remain valid for 6 months.

What ai is best to operate a system from screen video [p]

I have working programmatic control over a system, I can send inputs reliably and capture the screen as visual feedback. The control/feedback loop is already done.

Has machine learning research gotten more "wordy"? [D]

I feel like I am unable to digest most machine learning research these days. The primary reason is because I feel like they have gotten tremendously wordy. I find it not uncommon to find research papers consisting of 20+, 30+, 40+ pages of pure texts.

I Built a O(NlogN) attention system that retains 97% accuracy over long context (MQAR)[P]

ALHR- Adaptive learnable Hierarchical Routing is a static binary tree based system that uses learnable functions to REDUCE the amount of keys used. It takes less memory and SCALES much better VRAM with tokens submitted by /u/Alarming-Emotion-894 [link] [comments]

The Evolution of Fine-Tuning: From Retraining Everything to Rewarding Correctness

Last month I had a model, a dataset, and a GPU already warm. The old reflex said fine-tune. I didn’t. I sat there and asked whether…Continue reading on Towards AI »

Are .ipynb notebooks already outdated in the agentic era? [D]

I am a data scientist who started working in the industry before the LLM revolution. Back then, Jupyter Notebooks were a perfect fit for the classical DS pipeline: EDA -> data prep -> fit -> eval -> tune -> save model artefact and notebook.

Microsoft AI Releases Microsoft-Decision-1: A Qwen3.5-9B Decision-Scoring Model

Microsoft has released Microsoft-Decision-1, a decision model for routing, classification, verification and agent control. Microsoft-Decision-1 is a decision-scoring model that returns a calibrated probability for each fixed answer option instead of generated text.

OpenAI Decisions API Hits Public Beta With 10x Faster Typed Answers

OpenAI’s Decisions API is now in public beta on GPT-6 Luna. It returns typed probabilities, choices and scores about 10x faster than the Responses API, billing $0.10 per 1M input tokens with no output charges.

Talus: a 23M-parameter diffusion model for game terrain, evaluated against a real-vs-real noise floor, running in the browser on WebGPU [P]

Talus generates 64x64 heightmaps (4 km, up to 1,200 m) conditioned on a terrain type and any subset of five measured properties: mean elevation, relief, mean slope, water fraction and spectral slope. I trained it from scratch on one RTX 5060 (8 GB), about 4.5 hours in total across versions.

Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash

We are expanding the Clef decision model family with Clef-omni, natively processing audio, video, images, and text in a single pipeline. We’ve also lowered Clef-flash pricing and boosted Clef inference speeds by up to 2.0x.

Can TypeSafe's Jev Make AI Agents Safer Without Another LLM?

How a decision-first model can catch risky tool calls before they turn into real-world actions The post Can TypeSafe's Jev Make AI Agents Safer Without Another LLM? appeared first on Towards Data Science.

Clarification ARR Commitment [D]

Should I address the reviewer comments/suggestions (minor things) in this version already or wait for camera ready if accepted?

I built ALHR: A tree based sparse attention system that achieves sub-quadratic inference while retaining accuracy. [P]

ALHR - Adaptive Learnable Hierarchical Routing, uses static binary trees and learnable functions to minimize the amount of keys to be read.