training

An announcement for the upcoming release of Linux Kernel Exploitation, with discounted reservation spots available.

The author provides an update on building a small 2B parameter AI model with an Engram component, trained on 15m tokens from Wikipedia to achieve surprising coherence, with plans for an Apache 2.0 open-source release.

The article refutes the idea that AI development is slowing down, highlighting that Grok4.8, a 2.5T parameter model, has finished training and that major tech companies are still actively training AI models.

An astronaut recounts the thrill of landing the Space Shuttle Atlantis, detailing the rigorous training and precision required for the dead-stick descent from Mach 1 to touchdown.

ZGCM-1 is a fully open 7B LLM trained from scratch with FP8, MDP mid-training, and AI4AI, achieving performance comparable to Qwen3-235B on math and agentic search tasks.

Elon Musk announces that Grok 4.8, a 2.5 trillion parameter AI model trained with a new C++ software stack, will finish training and start reinforcement learning this week, while @kentcdodds comments on Musk's tendency to discuss future developments early.

This paper decomposes transformer representation updates into parallel and perpendicular components to study evolution geometry, linking it to editing robustness, compression diagnosis, and training improvements.

Tahuna is an open-source AI training infrastructure designed for small teams to train models, run inference, orchestrate GPUs, and experiment with autonomous research, featuring reproducible runs and tools like Hillclimb.

A developer has created a dense 9.4B parameter AI model with technical enhancements like Engram tables and AttnRes modeling, aiming for open-source release and seeking community interest for further training and deployment.

This paper introduces techniques to manage memory peaks in training large Mixture-of-Experts models with long context lengths, including Pipelined LLEP, Ring-DTP, SCO, and OffloadStreamAdamW, which enable fixed GPU working sets and improve throughput up to 10.4x.

The article reveals that OpenAI's terms allow it to use paid users' interactions for training despite opt-out options, due to a loophole with reasoning tokens not being classified as user-owned output.

Google Search's AI features can help runners prepare for races by offering personalized training plans, custom playlists, and gear recommendations.

The article reflects on the historical lack of knowledge sharing and training in Digital Forensics and Incident Response (DF/IR), highlighting personal experiences and efforts to improve processes through automation and documentation.

The author is experimenting with an adaptive memory governor for PyTorch to prevent CUDA OOM errors on 8GB GPUs, sharing code and seeking community feedback.

An experiment where two segmentation models were trained using GPT-6 Astra Ultra as an orchestrator without human labels, with lazy prompts due to time constraints, showing predictions on held-out videos.

4000 NVIDIA GB200 GPUs arrived in Texas for the Horizon TACC cluster, forming the largest academic supercomputer, with plans to train open AI models.

A lightweight TTS implementation, replicating Audio8's training with 2000 hours of data, achieving a SIM metric of 0.72 in under 10 hours of training on H200.

This is a massively revised Machine Learning Engineering open book, updated with the latest hardware specifications and examples, providing practical guidance for training and fine-tuning large language models and multi-modal models.

This blog post introduces how to train and finetune multi-vector embedding models using the Sentence Transformers library, showcasing its v6.0 update with a new MultiVectorEncoder type and demonstrating superior performance on medical retrieval tasks.

This paper proposes a unified dynamical framework for training, learning, and inference in neural systems.