• 9 Posts
  • 216 Comments
Joined 3 年前
cake
Cake day: 2023年6月12日

help-circle

  • Reno Police officer R. Jager, described in the filings as a rookie officer, arrived on scene and reviewed Killinger’s documentation. Killinger provided his driver’s license, a UPS payslip, and his vehicle registration. All documents matched his name and appearance.

    Despite this, Jager accused Killinger of using fraudulent identification and suggested he had a connection inside the DMV to fabricate documents. In his police report, Jager claimed Killinger had “conflicting identification” and said he “lacked satisfactory evidence” to confirm his identity.

    I think this cop has watched too many CBS police dramas. And I think this cop is stupid.


  • The Treasury could have bought up mortgage notes instead, at pennies on the dollar, and started collecting interest on the debt just like the private banks had. Then they could have renegotiated mortgages of underwater homes at lower interest rates, while the private sector lenders filed for bankruptcy. That would have drastically reduced the foreclosure rate and dumped the material cost of the financial crisis on stock and bond holders of these private companies.

    I’m curious how this action would have changed the last 20 years of politics? Those in power during that time did a shit job of really explaining why the banks got the money and not the homeowner. I think this really exposed who the federal politicians were representing, and it wasn’t the everyday voters. I think that anger and sense of betrayal that the American people were told to “kick rocks.” while the actual criminals got a bailout of our money still sits in with of most of the population.

















  • The thing is the West and China are not really using AI in the same way so saying we are in a race with them is incorrect and using old Cold War tactics to scare the West into spending more money on this technology.

    Example of the differences:

    The US and China are taking very different paths in the development and deployment of artificial intelligence. In the US, innovation has largely focused on large language models (LLMs) and the virtual world, resulting in chatbots, image generators, and digital assistants like ChatGPT and Copilot. These tools have captured the imagination of both consumers and investors, but questions are now emerging about their real economic value. A recent MIT study, The GenAI Divide: State of AI in Business 2025, found that while more than 80% of organizations are experimenting with generative AI, only about 5% of pilots are delivering measurable value. Most remain stuck in early phases, hindered by fragile workflows, poor integration, and a lack of systemic readiness. Meanwhile, informal ‘shadow AI’ usage, that is employees using tools outside official channels, has exploded, thereby creating a mismatch between official adoption and actual productivity gains.

    By contrast, China’s approach to AI is more grounded in real-world applications. As Chinese economist Andy Xie recently explained on Tegenlicht, AI development in China is focused on practical domains such as mining, electric vehicles, and industrial efficiency. Unlike the high-cost, high-hype American model, China’s AI strategy emphasizes low-cost, scalable technology that delivers tangible utility. This makes it particularly attractive to the Global South, where cost and accessibility often outweigh cutting-edge innovation. A striking example is DeepSeek, a Chinese open-source chatbot that was developed with limited funding and no ties to elite academic institutions. Despite this, it is 10× more energy-efficient than OpenAI’s models and is already being integrated into consumer products like cars.

    https://freedomlab.com/posts/the-ai-narrative-divide-between-the-us-and-china