On Twitter yesterday, @RJoads asked me how I got good at styling (CSS).
I replied: “Raw hours. I’m obsessed with how things look and feel—probably more than the median engineer. Mind you, this has not always been a positive. I’ve been wildly distracted for hours and hours on the smallest items, things that truly do not matter to the business. But that’s how I’ve gotten better.”
If you want to get really good at something, forget about shortcuts. You simply have to inject a ton of raw hours.
“Work smarter, not harder” is a common refrain these days—particularly in sophisticated circles. The thing is, for most people I think it’s bad advice. My experience learning to code has suggested you have to work hard before you know how to work smart. No substitute for raw hours.
It’s similar to what Brian Armstrong says: “If you’re pre-product/market fit, the best advice that I have from that period is: action produces information. Just keep doing stuff.”
People with limited experience are similar to startups pre-product/market fit. Of course you should aim to work smarter! The catch is that you have to work extremely hard in order to know HOW to work smart. You must first go down dozens of dead-end paths to know where the smarter paths lie.
The second catch is that in order to be able to inject a ton of raw hours in a natural, sustainable way, oftentimes you need to be OBSESSED. Otherwise – you’ll be banging your head against the wall year after year. Some people are so dogged they’re able to do it. But this is exceedingly rare and probably not worth aspiring to.
“It’s hard to do a really good job on anything you don’t think about in the shower.” – Paul Graham
Braindump is an attempt to imagine what game creation could be like in the brave new world of LLMs and generative AI to give you an entire AI game studio, complete with coders, artists, and so on, to help you create your dream game.
CEO total compensation has outpaced US median annual income by 16,638%, on average.
US median annual income increased by just 4% on average ($2,108/year).
CEO total compensation had an average annual increase of 7% ($676,153/year
Since 1974, CEO compensation has grown 940% while the average worker’s compensation has risen just 12%. Meanwhile, the purchasing power of the dollar over that same period has decreased an average of 3% a year from inflation. As a result, the average worker can afford significantly less goods and services today than they could 50 years ago, including housing, clothes and food. The average worker is losing big time.
And for those who would argue the high cost of social welfare, corporate welfare will cost taxpayers almost $400 billion this year alone, which is 25,000% higher than the $1.6 billion that will be spent on social welfare.
Spectral sensitivity of eye is influenced by light intensity. And the light intensity determines the level of activity of cones cell and rod cell. This is the main characteristic of human vision. Sensitivity to individual colors, in other words, wavelengths of the light spectrum, is explained by the RGB (red-green-blue) theory. This theory assumed that there are three kinds of cones. It’s selectively sensitive to red (700-630 nm), green (560-500 nm), and blue (490-450 nm) light. And their mutual interaction allow to perceive all colors of the spectrum.
The dynamic range is a ratio between the maximum and minimum values of a physical measurement. Its definition depends on what the dynamic range refers to.
For a scene: Dynamic range is the ratio between the brightest and darkest parts of the scene.
For a camera: Dynamic range is the ratio of saturation to noise. More specifically, the ratio of the intensity that just saturates the camera to the intensity that just lifts the camera response one standard deviation above camera noise.
For a display: Dynamic range is the ratio between the maximum and minimum intensities emitted from the screen.
The Dynamic Range of real-world scenes can be quite high — ratios of 100,000:1 are common in the natural world. An HDR (High Dynamic Range) image stores pixel values that span the whole tonal range of real-world scenes. Therefore, an HDR image is encoded in a format that allows the largest range of values, e.g. floating-point values stored with 32 bits per color channel. Another characteristics of an HDR image is that it stores linear values. This means that the value of a pixel from an HDR image is proportional to the amount of light measured by the camera.
For TVs HDR is great, but it’s not the only new TV feature worth discussing.
