LLM-based agents are moving into long-running and production workflows, from multi-hour coding sessions to trading, gaming, e-commerce, and onboard spacecraft decisions. The main challenge is reliable orchestration and runtime behavior rather than single-shot capability.
A self-hosted user describes asking a local LLM to change vLLM settings to cut idle power draw with CUDA_DISABLE_PERF_BOOST=1. The moment highlights both the promise and risk of operational automation: real energy savings, but also the need for guard...
AstroForge will give its next Autonomy-1 space probe a small transformer-based model responsible for onboard decisions. Local inference becomes unavoidable without connectivity and under severe physical constraints. The shift from deterministic softw...
Shopify describes a continual learning loop built on PyTorch and vLLM: production failures become model weight updates. The GraphQL agent surpasses frontier-model quality and cuts serving costs by 96%, from an estimated $27 million to about $1 millio...
An experiment with a 27 billion parameter LLM in 4-bit quantization on an RTX 3090, for 63 hours, does not solve Riemann but shows the endurance of self-hosted agentic pipelines. The value is not the theorem: it is process stability, memory managemen...
A framework autonomously revises the textual policy of an LLM trading agent using decision traces and portfolio feedback, keeping the model fixed. Tests frequently show improved Sharpe Ratio and cumulative return, with analyses linking allocation cha...
A report suggests an enthusiast used a bot built on GPT-6 Astra and Python to repeatedly beat Balatro's highest difficulty, Gold Stake with the Black Deck. Technical details are scarce, but the case prompts reflection on LLM numerical reasoning limit...
