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THE DAILY INDEX

Technology, AI, software, security, crypto and business

HEADLINES & LAUNCHES

TLDR AI

OPENAI RAISES $110B

OpenAI announced a $110 billion funding round at a $730 billion pre-money valuation backed by Amazon, Nvidia, and SoftBank to expand compute, distribution, and enterprise infrastructure. The company now supports 900 million weekly active users, 50 million consumer subscribers, 9 million paying business users, and 1.6 million weekly Codex developers, extending AI use deep into workflows across business functions. This capital and strategic cloud partnerships aim to shift frontier AI from research to global production scale with broader enterprise and developer adoption.

"ALL LAWFUL USE": MUCH MORE THAN YOU WANTED TO KNOW

Anthropic was recently declared a supply chain risk due to its refusal to allow the Department of War to use its technology for mass surveillance and autonomous weapons. A few hours later, the Department of War announced a partnership with OpenAI. While OpenAI and the Department of War have tried to assure the public that they won't use AI for mass surveillance and autonomous weaponry, there are wide loopholes in current laws against their use. The Department of War is also able to change many of the rules that currently exist at any time.

WHY XML TAGS ARE SO FUNDAMENTAL TO CLAUDE

Structuring prompts with XML can be a transformative experience in Claude. The AI's framework specifically incorporates XML tags as key elements. The repurposing of XML technology may be a core aspect of what makes Claude distinctive. It gives Claude the ability to distinguish between the transition from first-order to second-order expressions, which is a mechanism fundamentally required for information transfer between any two entities. Claude's awareness of the concept of delimiters is crucial to every processing and communication of information, and it is this capacity that makes Claude so effective at interpreting layered meaning.

90% OF EXPERT WORK CAN'T BE VERIFIED BY TODAY'S AI TRAINING METHODS

Around 90% of expert work across healthcare, legal, finance, and engineering relies on subjective judgment, making it incompatible with current RLVR-style verification. To force verifiability, teams over-specify tasks and rubrics, turning real expert reasoning into shallow instruction-following and corrupting the training signal. Verification, not data scale, is the core bottleneck, and the winners will be those who can evaluate judgment-heavy, non-deterministic work without distorting it.

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