greenmilk

> If surgery is recommended, I would try and talk to someone who has undergone the surgery. I did not do this and regret it.

This applies to all surgery.

The medical system uses coarse statistics, like "did the condition go away" and "did the patient survive".

"The patient went through a devastatingly painful 9 months and slowly recovered over the course of years to work towards a small improvement in the original symptom" may be classified as a success.

And don't forget that many actors in the system are financially incentivized to recommend interventions.

What happens when you factor in the downstream effects of carbon emissions (based on whatever the best projects are right now)?

Is it surprising that people who get most of their information from algorithms tailored by the industry they are protesting are ill-informed about the actual problems those companies are creating?

People can feel the misalignment, but they don't understand it. That's the future we are accelerating towards

a maliciously engineered dichotomy

I guess the fact that Paul Graham felt the urge to write and publish this in 2020 is indicative of the toxic relationship that was developing between silicon valley and the rest of the world.

Unfortunately, this essay exhibits the hallmark lack of empathy and self-awareness that perpetuate the toxic dynamic.

Sure, there are "haters", but the mirror effect is equal: powerful people often end up inside of bubbles that shield them from negative criticism, and often become blind to the legitimate criticisms people have of them.

These decisionmakers often have to make difficult decisions with powerful tradeoffs. It's more comfortable to cast those with values differences or who are on the wrong end of that decisionmaker's tradeoffs as "haters".

The Chinese gov't and also the rest of humanity...

I'm not sure how everyone in the US forgot that monopolies are bad

We have an entire generation of technologists convinced that you need a monopoly for a business to be viable, so every tech company is either trying to subsidize its way into a monopoly or running a deadweight loss.

Unsurprisingly, the resulting economy in aggregate is non-competitive, as it relies entirely on supply chains from competitive marketplaces.

> The state of the art models are going to get better and more expensive and smaller models are going to get cheaper.

Why do you think this will be true?

Right now I see the major US labs betting on gaining an advantage from having way more compute, and I see Chinese labs competing with one another in a resource-scarce environment, so they place much more emphasis on compute-efficiency.

But the supply chains that feed into the massive data center growth in the US are strained; there are energy, memory, and logistical bottlenecks to name a few.

In the medium-long run, compute capacity will not grow exponentially forever. Somehow it has for decades, but there can be no infinite exponential growth, and that point may be when the planet really starts to cook itself.

Maybe the US labs will become more compute-constrained, and then have to compete on efficiency.

Or maybe things change fundamentally in some other way I'm not thinking of.

I believe this is the process that defines Julia Evans' writing (and cartooning)!

Is there any country where it is?

I've got news for you there. The Biden administration tried to take the first real antitrust action in decades and then suddenly a bunch of tech oligarchs switched from supporting Democrats to supporting a convicted felon

To me the biggest (but not only) issue is that blindly connecting sensitive tools to 3rd party services has been normalized. Every time I hear the word "claw" I cringe...

They could be VC-backed and selling at a loss to grow market share

Are any inference providers currently making profit (on inference, I know google makes money)?