NK

Token costs are becoming one of the hottest topics for any enterprise I talk with right now. It’s very bullish for AI in general because it means these systems are being used at a scale that wasn’t contemplated before. It also gives way to another form of differentiation that will emerge for the applied AI layer, which is model routing. As tokens take on a significant amount of the cost of any given workflow, then companies will inevitably want to ensure that their dollars go into the most efficient use of tokens for the particular job at hand. Frontier intelligence will always be relevant at the high end of tasks, like coding, legal and financial analysis, healthcare, and more. And dollars spent here will only go up over time. But, equally, you can peel off individual tasks to lower cost models (whether they’re from open weights vendors or the major labs) and deliver a more efficient end outcome. To do this effectively, the applied AI layer needs to understand the workflows in their domain better than anyone else, and be able to mix and match models to different jobs. If you’re doing document extraction, you need to know which models perform better or worse for any given document type. If you’re legal analysis, you want to know which models perform various types of tasks best. And so on. This will become one of the bigger differentiation points over time. The companies with the best evals, the best ability to route the workloads, and those that have business models directly aligned to customers financial goals, will be in a great position.

BREAKING: The US economy adds 172,000 jobs in May, crushing expectations of 85,000. The unemployment rate was 4.3%, in-line with expectations of 4.3%. April's jobs number was also revised UP by +64,000 jobs. This marks the second strongest US jobs report in 13 months.

As a large commercial real estate holder I want to 🚩this as near certainty fraud. I have never bought a $2 million property that I successfully rented out for $2.4 million a year. This is the type of fraud you announce, when you just don’t give a fck because its pensions set to lose everything and government to bail them out. $15 Billion / Year - Anthropic $11 Billion / Year - $GOOG $26 Billion / Year Deals xAI raised $35 Billion for Operations and Capex Hardware cited at 60% capital raise $21 Billion Hardware Bought and Rented at $26 Billion a year to Google and Anthrophic.

BREAKING: Trump administration is discussing a possible government stake in OpenAI, per CNBC

Today, Anthropic engineers on average ship 8x as much code per quarter as they did compared to 2021-2025.