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THE DAILY INDEX

Technology, AI, software, security, crypto and business

HEADLINES & LAUNCHES

TLDR AI

USING LLMS FOR EVALUATION

As large language models become more capable, evaluating them accurately remains challenging due to their diverse tasks. While human evaluation is the gold standard, it's costly and slow. Using LLMs themselves as evaluators offers a scalable, cost-effective alternative, despite potential biases such as positional and verbosity bias, which can be mitigated through techniques like randomizing output positions and using multiple evidence calibrations.

THREE ARCHETYPES OF AI APPLICATION STARTUPS

AI applications are evolving into three common archetypes: AI Copilots that assist with tasks, AI Colleagues that autonomously manage specific tasks alongside human workers, and AI-Native Services which offer end-to-end services that integrate AI with human input. GitHub Copilot and Devin exemplify AI Copilots and Colleagues, aiding in coding and engineering, respectively. AI-Native Services, such as Pilot for bookkeeping, compete with traditional service firms by offering automated solutions in areas like law and accounting.

INSIDE THE FIGHT OVER CALIFORNIA'S NEW AI BILL

California state Senator Scott Wiener's Safe and Secure Innovation for Frontier Artificial Intelligence Models bill requires companies training 'frontier models' that cost more than $100 million to do safety testing and be able to shut off their models in the event of a safety incident. The bill has received heavy criticism from the tech industry. It will affect everyone who does business in California, not just companies that develop their models in California. This article contains an interview with Wiener about the bill and its critics.

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