#MachineLearning

OpenAI has partnered with Amazon, marking a major shift in the AI race with a $1.5 billion investment...

Weekly AI Roundup: The Most Important Artificial Intelligence Developments Your...

Weekly AI Roundup: The Most Important Artificial Intelligence Developments Your...

Hey r/ML, I spent the last few months building a tool that hooks into PyTorch training loops to automatically detect and localize failures (vanishing gradients, exploding gradients, data anomalies).…

I benchmarked it against PyTorch with a Wikipedia dataset. I heavily used Gemini Flash 3.5 to build out my vision https://huggingface.co/etoxin/neuronguard-wikipedia-classifier submitted by /u/Logical_Prompt_3543 [link] [comments]

My paper was recently accepted to a workshop at CVPR-2026 as non-archival acceptance. Is it mandatory for me to register to the conference as I won't be able to attend(visa issues), but my friend will be there in the conference and can present on my…

I didn't submit any but did place bids on some papers. I got assigned four papers. I have a bit of travel coming up and I don't think I will be able to do justice to as many the papers, especially in the rebuttal period.…

Ps. Not pitching anything; Just trying to understand where reality differs from the narrative. We're a couple of ML students, mostly worked on ML/software before, but over the last few months we've been playing with VLAs, robot datasets, and trying to…

I'm trying to understand the intuition behind Word2Vec training using a neural network. In Word2Vec (CBOW or Skip-gram), we often hear that the weight matrices learned during training contain the vector representations (embeddings) of words.…

In early 2022, I was deciding between PhD offers. The deal maker was a prospective supervisor telling me that through their connections with big tech, I would be able to do a PhD internship each summer, which was one of my main goals for the PhD.…

Weekly AI Roundup: The Most Important Artificial Intelligence Developments Your...

We're writing a research paper on explainable fraud detection GNN model and in the first step we're creating a basic Graph Neural Network for that.…

Vision Transformers waste 90% of their compute recalculating stationary asphalt. NeuroFlow tracks semantic surprise in embedding space, physically eliminating background tokens before the encoder.…

Dataset for fine-tuning compliance assistants. Each pair includes: - A practical SME-facing question ("Can I use pre-ticked consent boxes?") - An answer with specific UK GDPR article references, ICO guidance by name, and actionable steps - Source…

New preprint. A Mixture-of-Experts inference kernel (TritonMoE) written entirely in OpenAI Triton, targeting portability across NVIDIA and AMD without vendor-specific code.…

Profiling PyTorch training has an interesting measurement problem: the more you measure, the more you can change the behavior of the run itself. A simple example is torch.cuda.synchronize().…

[R] BEAM 100K memory benchmark: CSM vs Hindsight local artifact comparison I’m looking for feedback on a local agent-memory benchmark comparison, especially from people who care about evaluation methodology.…

Each brain is unique, and from the best generations that I save, a worm can pick random brain files to use, letting each worm be completely unique and feel alive. This is for Bonk Universe. submitted by /u/Lanse012 [link] [comments]

I am responsible for a research project that is supposed to train a GPT-like model (Transformer-decoder) with 100M, 250M and 500M model variants.…