I think it’s more about the web visitor cost. Handling traffic and API calls becomes a financial problem when there are a growing number of companies using bots to scrape data. Larger companies are moving their content behind paywalls, which acts as a bot filter, and have also identified that they can generate a revenue stream from subscriptions and API connections. Old content on the web is not deemed to have much business value, so it’s a decision of either charging for it or scrapping it.

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

The article by Wait But Why has always been my favourite reference guide for explaining the future of AI to friends and family: https://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.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.

Great article, thanks! The last few sections really make it seem like a dumpster fire.

So, in simple terms, the value proposition is that the retinal scan will generate a unique ID of a person in the system and ensure that a person cannot be registered more than once. This will then allow the system to be used for tasks like authentication or ensuring fair distribution of tokens. Another potential use case mentioned is something like the administration of Universal Basic Income (UBI), whereby the system would verify that people receive UBI and cannot claim duplicate payments. You could also extend that idea to things like government ID.

The privacy concerns would probably prevent a roll-out in most Western markets, so it will be interesting to see if they can generate enough business in other markets.

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.

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.