AI News Today

<!-- SC_OFF --><div class="md"><p>Hi everyone,</p> <p>I wanted to share an open-source repo collecting 20 exploratory studies focused on Next-Concept Modeling (NCM), mechanistic interpretability (like IOI in GPT-2), and model controls.</p> <p>Link: <a href="https://github.com/Quantix-eng/ncm-experiment-notes">https://github.com/Quantix-eng/ncm-experiment-notes</a></p> <p>This is an independent project documenting empirical experiments on how transformers process and edit internal features. No pe

<!-- SC_OFF --><div class="md"><p><strong>TL;DR:</strong> AI written reviews, and AI-writing in papers</p> <p>I was going to give this a title "An Obituary of the Review Process", but in the interest of not sounding too defeatist, I will just say "Critical Condition" because of AI writing, both on the author side and the reviewer side.</p> <p>I am a reviewer for AAAI 2027 and ICLR 2027. Since Phase 1 and Phase 2 was completed, I can now see other reviews. I can bet good money that about half of

<!-- SC_OFF --><div class="md"><p>I’ve uploaded a minimal, self-contained implementation of manual autograd for a transformer-based classifier in PyTorch. It can help build intuition for what autograd is doing under the hood and is a useful hands-on reference for low-level differentiation in Transformer models, such as writing custom backward passes and tracing how gradients flow through attention blocks.</p> <p>🐙 GitHub:</p> <p><a href="https://github.com/ifiaposto/transformer_custom_autograd/

<!-- SC_OFF --><div class="md"><p>Self-distillation methods usually rely on an Exponential Moving Average (EMA) teachers to get synced and stable critics. However, this doesn't scale well for large models since holding both teacher and student (trained) on GPU increases latency, zero3 communication, etc.</p> <p>We can mitigate this with LoRA finetuning: the backbone is shared & frozen, and we need to maintain two light adapters: one for the student (trained) and one for the teacher (EMA of the s

<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1xgzbik/i_built_this_feedback_welcome_p/"> <img src="https://preview.redd.it/n2c2qke6r1yh1.png?width=140&height=119&auto=webp&s=10ddab5ed96fd3d275973ac2438e51787a4a09e1" alt="I built this, feedback welcome [P]" title="I built this, feedback welcome [P]" /> </a> </td><td> <!-- SC_OFF --><div class="md"><p>It's a 50 hour course for beginners in AI/ML (obviously it's fully free). Starts out with linear algebra, derivatives,

<!-- SC_OFF --><div class="md"><p>Hey! We published a set of 6-step LoRAs, one without the upsampling step: <a href="https://huggingface.co/PrunaAI/P-Q-Image-2.1">https://huggingface.co/PrunaAI/P-Q-Image-2.1</a></p> <p>- Generate or edit images in just 6 steps instead of 40. Use 6-steps for preserving inputs when editing and 6-steps-upsampled for improved visual quality and shorter end-to-end generation.<br/> - 6-step distillation provides improved quality with few generation steps. 6-steps-upsa

This article is brought to you by VicOne . A mobile robot slows for someone in a hallway. A collaborative arm eases its movement as a worker approaches. A humanoid pauses to let a person pass. Each response depends on information about the robot or its surroundings: a distance reading, a position estimate, or a stop signal. But what happens when one of those inputs is wrong, and the robot still responds exactly as designed? The mobile robot reads the hallway as clear while someone is still there

<!-- SC_OFF --><div class="md"><p>For my master’s thesis I built an accelerator for diffusion-based action generation in robotics policies. Offline, it looks great: the median absolute deviation between the accelerated output and the original model’s output is extremely small, so I concluded it reproduces the model’s behavior faithfully.</p> <p>When I deployed it on a real robot for a task (picking up a book and placing it on a shelf), it did not work as well as the original model. The offline n

There are 57 million people worldwide living with dementia today. For the researchers working to help them, the obstacle isn’t a lack of effort — it’s too much data, too few experts to synthesize it and a pace of discovery that can’t keep up with the disease. The Consortium for Biomedical Research and AI in […]

Science has a spam problem. And the spam filter is getting clogged up. According to all reports, academic publishing is drowning in what has come to be called AI slop: low-quality, mass-produced content generated with AI. By 2025, an estimated 57 percent of all published academic articles exhibited detectable evidence of large language model (LLM) influence, a massive jump from 12 percent in 2023. What’s more, over 12 percent of Nature Communications reviews were found to be completely AI-genera

Mirendil released Fern 0.1, its first model, pretrained from scratch with a 10M-token context window. It targets agentic AI R&D work, scores 100% on RULER single needle at 10M, but trails frontier models on agentic coding. The post Mirendil Launches Fern 0.1, Its First Model, With 10M-Token Context appeared first on MarkTechPost .

<!-- SC_OFF --><div class="md"><p>Hey, I've been working on a PyTorch optimizer called ApexW and figured I'd share it here to get some feedback from people who know more about this stuff than I do.</p> <p>The main goal is to reduce optimizer-state memory usage and see how much faster I can make optimizer steps on larger GPU workloads. I've been experimenting with compact optimizer states and a Triton-based execution path.</p> <p>In my current tests, the Triton + compact-state path was around 1.5

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Will the real Anthropic please stand up? After weeks of frenzied speculation, Anthropic has filed its IPO prospectus. The 335-page document (100 pages or so are focused on risks) lays out…

<!-- SC_OFF --><div class="md"><p>Papers with Code is now open-source with an Apache 2.0-license. </p> <p>The goal is to collaboratively create the best paper interface with the community! </p> <p>Over the past couple of months, I've been working with my buddies Claude and Codex on creating a website that tracks trending AI research, benchmarks and state-of-the-art (SOTA). It's a revival of the original Papers with Code website, which Meta acquired and later shut down. </p> <p>The website is pre

Transformers are a crucial but nearly invisible part of our grid. The devices help efficiently move power across long distances, but they’re complicated and in short supply. And given that their basic design hasn’t changed much for about a century, they could use an upgrade. As the world races to meet rising electricity demand from…

<!-- SC_OFF --><div class="md"><p>I'm working through a free series on GPU kernel engineering (my own channel; I posted the roadmap here earlier: <a href="https://www.reddit.com/r/MachineLearning/comments/1xa4h2g/open_gpu_kernel_engineering_series_naive_gemm_to/">https://www.reddit.com/r/MachineLearning/comments/1xa4h2g/open_gpu_kernel_engineering_series_naive_gemm_to/</a> ) . Session 1 is a setup session. While preparing it I collected a few things that cost me time and that I rarely see in one

OpenAI released GPT-6.1 Terra, a fast computer-use and vision model priced at $1/$5 per million tokens. It matches GPT-6 Astra’s medium-effort Agents’ Last Exam score at $0.29 per task versus $4.82. The post OpenAI Launches GPT-6.1 Terra, Halving GPT-6.1 Sol’s API Price for Agent Work appeared first on MarkTechPost .