Browsing: Training

AI chatbots are preferred to colleagues and managers for work-related matters, according to a survey of 2,000 UK workers, with under a quarter (24%) bothering to confirm the results or directions from an AI-generated solution.

What usually stops PyTorch training from scaling out to a cluster is the container, not the model code. Every container needs the same CUDA runtime, a PyTorch build compiled against it, NCCL (NVIDIA Collective Communications Library), the Elastic Fabric Adapter (EFA) userspace libraries, the AWS OFI NCCL plugin that connects NCCL to EFA, and a…

An AI agent can sound convincing and still fail at the job it was hired to do. Teaching it to select the right tool, follow a company’s workflow and recognize a successful outcome requires more than access to a capable model. For teams customizing models themselves, it can also mean managing the expensive computing infrastructure…

As physical AI moves into factories, warehouses, homes, and other real-world environments, engineering teams need to understand how AI, edge computing, and functional safety integrate to support safe deployment.

Most large language models (LLMs) use transformer architectures with softmax attention. During inference, their key-value (KV) cache grows with the conversation or document context. This can reduce concurrency, increase serving cost, and force agentic applications to discard useful history.

Apollo Research, an AI safety evaluation organization, says it has caught a frontier open-weight model reasoning about something no model has been documented doing before: how its own answers today might shape the training of its future self. The model is GLM-5.3, built by the Chinese AI lab Z.ai, and the finding landed in an…

When implementing an EEG machine-learning pipeline, there are many samples obtained from a small number of subjects. One recording can be divided into multiple windows, which then can be randomly split into train and test splits. This produces a sample size that might seem very big. Yet, if the same subject’s windows are present in…

OpenAI said it has paused training of its latest artificial intelligence models as reports of AI agents going rogue mount.

Reinforcement learning (RL) post-training is becoming a standard step in building capable language model agents. Models learn to reason and act across sequences of steps by generating trajectories, receiving rewards, and updating their policy based on outcomes. Running this at scale, across multiple nodes with hundreds of GPU-hours of rollouts per training run, requires persistent…

In their 2024 International Conference on Machine Learning paper, Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews, Weixin Liang, Zachary Izzo, and their coauthors built a statistical method for estimating how much text in a large collection had been substantially written or rewritten by a…