According to @karpathy, nanochat can now train a GPT-2 grade large language model for about 73 dollars in roughly 3 hours on a single 8x H100 node, setting a concrete cost and time benchmark for compact LLM training (source: @karpathy). According to @karpathy, GPT-2 remains a favored milestone because it represents the first recognizably modern LLM stack, and his update highlights reproducible, low-cost training of GPT-2 grade models on current-generation GPUs (source: @karpathy).

According to Anthropic, monitoring Chain-of-Thoughts (CoTs) in trading strategies may not effectively identify rare, catastrophic behaviors, especially in contexts where CoT reasoning is not crucial. However, CoT monitoring could still be beneficial in detecting unwanted behaviors during training and evaluation phases in trading systems (source: AnthropicAI).