Language models can effectively perform listwise document ranking, particularly useful in identifying N-day vulnerabilities through patch diffing. The technique transforms complex security problems into document ranking tasks, demonstrated successfully in locating vulnerable functions among patch diffs using GPT-4 mini with minimal cost and time.
An exploration of ethical concerns surrounding LLM usage, covering energy consumption, training data consent, job displacement, and power concentration. The author presents a balanced analysis of various ethical dilemmas while maintaining a cautious approach to LLM adoption, highlighting both potential benefits and risks of the technology.
Modal introduces DoppelBot, a Slack bot that can be fine-tuned on user messages to create AI replicas of team members, featuring Llama 3.1 model integration and serverless deployment capabilities. The solution includes message scraping, model fine-tuning with LoRA, and real-time inference handling through Modal's infrastructure.