import random

    learning_rate = 0.1
    EPOCHS = 50
    NUM_INPUTS = 3

    weights = [random.uniform(-1, 1) for _ in range(NUM_INPUTS)]
    bias = random.uniform(-1, 1)

    data = []
    for _ in range(100):
        inputs = [random.uniform(-1, 1) for _ in range(NUM_INPUTS)]
        result = sum(inputs) > 0
        data.append((inputs, result))

    for epoch in range(EPOCHS):
        for inputs, result in data:
            weighted_sum = bias
            for i in range(NUM_INPUTS):
                weighted_sum += inputs[i] * weights[i]
            
            prediction = weighted_sum > 0
            
            if prediction != result:
                error = int(result) - int(prediction)
                for i in range(NUM_INPUTS):
                    weights[i] += learning_rate * error * inputs[i]
                bias += learning_rate * error

    print(f"Final weights: {[round(w, 3) for w in weights]}")
    print(f"Final bias: {round(bias, 3)}")

But I will concede this: Due to the opaque nature of the Chinese economy to public scrutiny, we might never know.

I am sure, however that substantial use of Chinese inference (not their models per se, but on their servers) is, in aggregate, presents a substantial national security risk for the West. Heck, AI all by itself, without even considering other nations, is a national security threat of the near future, where national security is broadly construed as any threat against its people's welfare, no matter the actor.

Second, I do not think anyone is claiming that microplastic pollution is not ubiquitous, because that is obvious. That microplastics get consumed is also probably not that controversial. The extent to which microplastics get consumed but do not exit the other end of the pipe is an empirical question that has methodological challenges.

Third: I think there are some subtleties here involving the size of plastic particles. Microplastics is a catch-all term these days, but a more formal definition puts microplastics at plastic particles that range from 5 mm to 1 μm (micrometer), while nanoplasticsare 1 μm down to 1 nm (nanometer). micro- and nano- plastics can require different techniques to detect.

"The Zhejiang Provincial State-owned Assets Supervision and Administration Commission (SASAC) is the provincial government agency in Zhejiang, China, responsible for managing, regulating, and overseeing the state-owned assets and enterprises owned by the provincial government." [2]

What does this imply? A state-owned company in China invested a ton of money into DeepSeek. aka State subsidization.

[1] https://www.americansecurityproject.org/wp-content/uploads/2... [2] https://www.fitchratings.com/research/corporate-finance/zhej...

[1]: ubiquitous flame retardants, which in America they put in every couch, carpet, and mattress

[2]: ubiquitous microplastics pollution,

[3]: joint effect of Obesity and Ultra-Processed Foods

[1] https://scholar.google.com/scholar?as_ylo=2022&q=flame+retar... [2] https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&as_ylo... [3] https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&as_ylo...

[1] https://chinaselectcommittee.house.gov/sites/evo-subsites/se... [2] https://ai.americansecurityproject.org/news/ai-imperative-20...

and more.

Of course, you can choose to ignore America-biased sources, but since it aligns with the obvious.

2. It should be determined whether the fraud was just the display image (imagine a sales manager making a bad call when images are not available) or involved the underlying research (more systemic and worrying).

3. It would be interesting to examine occurrence of faked images along with apparent unreliability/irreproducibility of research that has used those products.

[1] https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Stee...