California's lengthy and uncertain approval process cost it a $3.2B defense shipyard project and 10,000 jobs. Texas won the deal by providing a "clear expedited approval process" and tax incentives. This demonstrates that for large industrial investments, regulatory speed and certainty can be a more powerful competitive advantage than a state's existing economic base.
The argument that Disney's market cap is less than its acquisition costs presents a flawed picture of value creation. This analysis fails to account for the approximately $70 billion returned to shareholders via dividends and buybacks over the same period. A true assessment of an M&A strategy's success must include capital returned, not just final enterprise value.
New open-weight models like Inkling are not entirely 'pure'; they use 'distillation light' from other open models (e.g., Kimi). Since those models may be distilled from closed-source giants like OpenAI, it creates a multi-layered dependency chain where traits and biases are passed down, blurring the lines between truly independent and derivative models.
The release of a powerful, US-based open-source model like Inkling is particularly well-timed. As Beijing considers curbing overseas access to its top AI models, a void is created for a trusted, "Western open source" alternative. This positions Thinking Machines to capture businesses wary of geopolitical risks or potential lock-outs associated with using Chinese models.
The battle against AI model distillation is not a niche issue. Anthropic is shutting down millions of accounts per week attempting to distill their models, revealing a highly organized and distributed effort by competitors. This frames the problem as a major cybersecurity and national security challenge, not just a terms-of-service violation.
The latest AI models appear more creative in design tasks not by learning new skills, but by being explicitly trained to avoid generic outputs that signal AI generation, like "bento box" layouts. This strategy of identifying and eliminating "bad AI smell" is a novel approach to improving the perceived quality and sophistication of generative models.