Steve Jackman

MrBeast explains why the education system is completely broken “Why are students today being taught the same way their parents were? Look at how much everything else has advanced. When I was in school the teacher would just stand there, read out of a book and write on a whiteboard” "Now look at Mark Rober’s videos. You can learn complex topics in 20 minutes in a way that’s engaging, fun and you retain it. Just because our parents were taught one way doesn’t mean we need to keep teaching that same way. It makes no sense to me, I think education should be reformed dramatically” “Students spend so much time in school. If we had real courses made through videos, made learning more hands on and optimised everything with modern technology, kids could probably learn more in 5 hours than they currently do in 8 hours"

So far “telling a satisfying and well-written medium-length story” has proved far harder for LLMs than mathematical proofs, music generation, research reports, code, and many other forms of work. The technical reasons are pretty clear, but they are supposed to be language models

Why is the time 10:10 in AI land? The 10:10 bias and how to understand it applies to countless subjects in AI. — When artificial intelligence (AI) is tasked with generating images of analog watches, one fascinating and predictable outcome is that the watch hands often default to the 10:10 position. This phenomenon is not a mere coincidence but a direct result of the training data AI models are exposed to. Most AI models, particularly those used for image generation or recognition, are trained on vast datasets of images sourced from the internet, advertisements, and other visual media. Because watch companies have historically standardized on the 10:10 time in their marketing materials, this bias is naturally inherited by AI systems. Why Watch Companies Use 10:10 The 10:10 time is a nearly universal standard for analog watch advertisements. There are several reasons for its adoption: 1. Aesthetic Balance - When set to 10:10, the watch hands create a symmetrical "V" or "smile" shape on the watch face. This symmetry is visually appealing and draws attention to the design of the watch. - The placement avoids overlap with other key elements on the watch face, such as the manufacturer’s logo (usually at 12 o’clock) and other complications like date windows or chronometers (often at 3, 6, or 9 o’clock). 2. Positive Connotations - The upward-pointing hands resemble a smile, which subconsciously conveys positivity and happiness to viewers. Marketing psychology often leverages subtle cues like this to create an emotional connection with potential buyers. 3. Brand and Logo Visibility - Many watchmakers place their logos or brand names at the 12 o’clock position. The 10:10 hand placement frames the logo without obscuring it. - Additional features like subdials or text at 6 o’clock are also unobstructed. 4. Historical Tradition - The 10:10 convention has been used for decades, creating an industry-wide norm. While smaller deviations exist (e.g., 10:08 or 10:09 in some ads), they are rare. The tradition has become so entrenched that deviating from it might make a watch ad look unusual or less professional. Interestingly, some brands experimented with other hand positions in the past. For example, Bulova once used the 8:20 position in its advertisements. However, the downward-facing hands were seen as creating a "frown" and evoking a negative emotional response, leading most brands to settle on 10:10. How AI Inherits the 10:10 Bias AI models trained on large datasets learn patterns and associations from the images they process. When it comes to watches, these datasets overwhelmingly consist of marketing materials and product images from the internet. Because the vast majority of these images feature watches set to 10:10, AI systems internalize this as a default state for analog watch faces. The 10:10 Bias in AI When prompted to generate images of watches Image AI default to 10:10 hand positions unless explicitly instructed otherwise, it will try to comply but the concept of an analog watch face degrades. Additionally AI models used for image recognition usually incorrectly classify a watch with a non-10:10 hand position as "unusual" or "anomalous" because it deviates from the pattern seen in the training data. The 10:10 Bias and You The 10:10 bias shows we must be aware of biases inherent in training data. While the 10:10 bias in watch images is relatively harmless, it highlights a broader issue: AI models will replicate and amplify the patterns they are exposed to, even if those patterns are culturally or industry-specific. An example is AI systems have been trained on the bias of human interactions as seen on Reddit and Facebook. This bias builds an inaccurate portal of what human communications are really about. It is one reason I use training data that is not from these source and usually from before the internet era. Knowing these issues also afford a power over AI few can imagine.