morry040

There’s quite a difference between rapid prototyping on software/hardware versus the human body.
Musk’s approach to developing engineering advances has worked well in the software, aerospace, and vehicular industries. Development on inorganic things is much more predictable, we can isolate variables, and it is easier to understand cause & effect. If you screw up some software on an inorganic system, your program might crash, your rocket might explode, or your car won’t start. These risks can be anticipated and costed fairly well, therefore rapid prototyping has an acceptable risk/reward ratio in that environment.

The human body, on the other hand, is an extremely complex system that we still don’t fully understand. Each person is a unique variation on the model and that changes over time depending on upbringing, diet, exercise, and life experiences. Applying the same engineering approaches from inorganic industries has a much higher risk once you cross into the medical realm. If you have errors in a medical situation, you risk sickening, injuring, or even killing a person. The risk/reward ratio is skewed towards ensuring that human life is protected at all costs.

Using SpaceX as an example, the first three launches failed spectacularly and a fourth failure would have ended the business but fortunately the fourth test was a success. If you’re suggesting that we apply the same risk-taking to Neuralink, are you suggesting that it’s acceptable for the first three patients to die, as long as the fourth is a success?

It’s estimated that Tidal pays $0.013 per stream, Spotify pays $0.003 - $0.005, and Apple pays $0.01 per stream.
https://dittomusic.com/en/blog/how-much-does-tidal-pay-per-stream/

The number of reported issues seems to be about the same with WinRAR: https://www.cvedetails.com/vulnerability-list/vendor_id-1914/product_id-3768/Rarlab-Winrar.html

I’m not sure that they ever had any data because the data would probably suggest that management had the lowest productivity out of any employee. Middle management is filled with too many meetings, they’re all promoted to a level of incompetency, and have delusions that they contribute more towards the success of the business than the skilled people below them.

I’m more interested in learning about who is paying the 25 WLD, how they have funded that, and how they plan to generate a return on the investment. There is already an upfront investment involved in developing the token, the “orb”, and the uses of the data, so what is the business model that generates revenue for them?

Agreed. As soon as a web service decides to prioritise revenue growth above the user experience, it’s over. This is usually in the form of an IPO, so if you happen to be a fan of a particular service, as soon as they start talking about going public, start looking for a free / open-source alternative.

Love it. AI incest is the perfect term for it haha.

There are plenty of alternatives (e.g. Vietnam or Mexico), but China still offers enough advantages to make it the preferred option. This article explains it well: https://www.china-briefing.com/news/reshoring-from-china-to-mexico-how-prevalent-is-it-really/

If you look at various economic indicators, it seems likely that we have reached the peak of China’s production.
Exports peaked in Dec '21: https://www.ceicdata.com/en/indicator/china/total-exports
Population - declining: https://www.ceicdata.com/en/indicator/china/population
Labour force participation rate - declining: https://www.ceicdata.com/en/indicator/china/labour-force-participation-rate
Employed persons - declining: https://www.ceicdata.com/en/indicator/china/employed-persons
Manufacturing wages - doubled in the past 10 years: https://tradingeconomics.com/china/wages-in-manufacturing

A lot of the tech companies were slammed by investors over the last two years for missing their earnings and many of them are still struggling to go back to 2021 optimistic growth rates. The layoffs last year have also cost them a lot of their best talent, so the quality of innovation, decision making, and execution has suffered. You are now left with a bunch of older executives who never really understood that it was their younger talent that was the core of their company’s success, so they fall back on older methods like increasing prices and cutting costs to try and lead the board / shareholders into thinking that their ridiculous executive salary packages are somehow justified.

Stephen Wolfram’s article on how ChatGPT works was enlightening: https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/

Like you said, it’s just text prediction, using online content as the training ground.