5,467 karma · joined August 31, 2013
System prompts aren't safeguards.
A step in the right direction is auto-review, available in claude-code, codex, and Cursor products. This is not foolproof either.
This is why remote calls should be gated through an MCP or other API gateway. The MCP can restrict calls even when the provider lacks scoped privileges for their integration keys.
It is indisputable that there have been successful socialized housing schemes. It is also indisputable there are successful free-market housing systems; for example, Minneapolis.
There are many Indians and Pakistanis who do consider themselves white. I'm unaware of a prominent white identity movement within China, but I don't have total certainty.
https://en.wikipedia.org/wiki/People%27s_Liberation_Army#Eng...
But I agree that adding the whiteness status of the men doesn't add to the story. The distinguishing characteristics of the men were they were rich and powerful. There are many people in the United States who despite their whiteness, suffer injustice, lived in poverty, and are oppressed by powerful interests.
The above does not erase the fact that systemic racism impacts Black and Hispanic Americans significantly to this day, and work to mitigate this should continue.
I wonder if Vietnam, Philippines, Republic of Korea, India, and Japan are acting against their own interests by aligning themselves closer to the USA than China. Maybe you can educate their governments and populations.
I don't even necessarily disagree with your assessment of this spokesperson. But you must admit how inconsistent you're being.
The economic viability of Anthropic and OpenAI rely on their being able to charge more for model access than their R&D and inference costs. If the market price for SOTA model access drops below that level, then these businesses will have to decide whether to continue to lose money or to reduce spending on R&D.
Moonshot's papers [1] claim that their training load was primarily from synthetic data and model self-teaching rather than RLHF and therefore keep their costs low. If Moonshot genuinely does not rely on human-led training, they will surpass US closed-source model providers. The United States government considers US supremacy in "AI" as a national security consideration.
This announcement is noteworthy because it implies that Moonshot's success is in fact due to distillation. It's in the interest of US frontier labs to place barriers to this if they find themselves in the position of subsidizing rival labs' research.
1. Kimi K2, https://arxiv.org/html/2507.20534v1
The reason why the United States government is weighing in is because it's in the national interest of the US to have supremacy in "AI".
Legality or lack thereof is one of many data points about whether a thing is noteworthy.
Moonshot performing distillation is rational from their point of view. Reducing costs is in the interest of businesses. It's also rational for frontier labs and the US government to add obstacles to this process.
As consumers this is probably a positive development.
It's also true that Moonshot and other labs distill from Claude. This has been reported on extensively. I don't think there's any alpha for Anthropic distilling from this model. I do not mean to discount the tremendous amount of innovation regarding MoE and quantization that Moonshot has accomplished. But its training with synthetic data is in large part from distillation from frontier labs.
Even during the pre-Snowden heyday of US cyber supremacy, these capabilities were barely part of the thought process of White House officials.
counterparty uses rhetoric in response
"Hey! No fair!"