aurareturn

If you have more efficient models, you can reduce price and grab market share or keep price and increase your margins.

Over time, this compounds. More profits means more investments. More market share means more control.

I think the point here is that it takes the same hardware to inference an open source model as OpenAI/Anthropic inference their models.

IE, a lower param OpenAI/Anthropic model can compete with a higher param open source model.

So even if you are an American company who downloaded Chinese models in hopes of saving in cost, you still have to beat OpenAI and Anthropic in $/task which is very tough to do over the long run.

Cost of electricity isn’t a long term advantage in my opinion. Private companies will figure it out.

What matters most is $/completed task. It does seem like OpenAI and Anthropic are winning here even with worse electricity rates. Perhaps it is made up by the efficiency of Nvidia and Broadcom chips, which China can’t get in mass.

I do think that OpenAI and Anthropic are moving up in stickiness. My company has rallied around Claude. We are customizing Claude Code, adding knowledge bases for non technical people, writing skills for them, using Claude features company wide. It’s hard to move.

Meanwhile, I personally use ChatGPT outside of work. The memory, ease of use, habit keeps my subscribed.

I've been hearing about the 777x for so long that I just assumed it was flying already. It's just crazy that nearly 7 years later, it's still not ready.

It's good that Boeing is taking its time instead of rushing out a flawed product. But between the 777x, the 737 Max, the quality issues of 787, and the embarrassment that is the Starliner against SpaceX Dragon, Boeing's engineering is rotten to the core it seems.

I don't think ASICs is the long term answer here at the local LLM level. I think GPUs will still be.

If you can have only one AI processor in your laptop (because they're big and expensive), it's going to be a GPU. This AI processor needs to inference LLMs, audio processing, image generation, video generation, etc. This is on top of normal graphics processing requirements such as video games, playing videos, decoding, encoding, etc.

At the enterprise level, I can see some ASICs working once the market fully matures and improvements in architectures slow down drastically while demand for inference increases drastically. How far are we from this world? Maybe 5-10 years? It seems like model architectures are still changing rapidly and labs want fast experimentation that programmable GPUs offer.

GPUs will still dominate in general - just like how CPUs still dominate despite ASICs.

Big tech employee counts are still nearly 2x higher now than 2019.

I’ve been staggeringly productive with Fable. Opus 4.8 fails a lot more for me.

Fable often just “knows” what I want with vague instructions. It also is able to autonomously perform work that lasts an hour long from my experience. I haven’t tested further.

Without Fable included in subscriptions, I would have moved my entire team over to Codex 5.6.

News flash: most of software engineering is already automated. When was the last time you wrote code?

They did not claim there is no human involved.

Show me where Anthropic claims you don't need any humans anymore to build working, production ready software.

I think everyone assumes most, if not all of the code written in a piece of new software is done by AI.

What hypocrisy? Anthropic never said you don't need a human anymore.

  the ROI just isn't there. they aren't making these capital investments back in the next decade even.

People say LLMs are scholastic parrots, but people who say this stuff have almost certainly not done the homework themselves and are just repeating what others say without verifying.

I don't think LLM labs ever claimed that their LLMs are intelligent the way we believe animals are.

It's a combination of Covid over hiring, CapEx for AI hardware, AND you don't need as many software developers anymore per product.

I said "generally". It's declined sharply over the last few months.

The goal posts have moved. People generally stopped saying this stuff now.

Even if you go to the ultimate anti-AI subreddit r/betteroffline, they've changed from "AI is useless" to "AI is good but the AI bubble will collapse soon" over the last 6 months.

They had a human oversee the bun rewrite, didn't they?

I knew this was going to be the first reply.

The answer is because you still need at least one human to develop and test any tool, integration, feature.

  Moore's law is the observation that the number of transistors in an integrated circuit (IC) doubles about every two years, with minimal increase in cost.

Is Claude Code bottlenecked by performance?

I think a JS runtime is fine because the ecosystem of tools is very large and plugins are easy.

Cartel behavior? You mean supply and demand?

Besides the AI shortage, Moore’s Law has ended which means in order to get faster chips, you have to use bigger dies, fancier packaging, more cooling, more power. This increases costs.

A PS6 really doesn’t increase much over the PS5 even without the AI shortage. You’re probably getting doubled the performance at best, which barely makes a noticeable difference in gaming when PS1 to PS2 had 180x better GPU.

I think the next leap has to come from mostly software and I think we will move towards a world in which most/all of the rendering is done by an AI. See Google’s Genie3.

Not entirely true anymore because Apple also targets the bottom of the mid end. Watch SE, Neo, iPad, iPhone SE.

I’m inclined to believe the Macrumors story because Apple did have a great cycle with the 17 and high memory prices affect brands with less pricing power more.

Anthropic just made a profit. So it does seem to be enough.

Most of them were outside of the traditional San Francisco/Silicon Valley tech companies.

Most of these were in Asia, New York, 2nd/3rd world countries, etc.

I think any association between cryptocurrencies and AI is a lazy one.

The actual money is coming from big tech profits, debt, and rapidly growing AI revenue (Anthropic growing from $9b ARR to $60b+ ARR in a few months). A very small percentage is coming from Nvidia.

And before someone tells me AI demand is fake and circular, my company is spending thousands on Anthropic a month, up from $0 in 2025. And no, we're not getting scammed by Anthropic or tokenmaxxing for no reason. We are getting value. At minimum, my company is not part of this circular thing.

But we're seeing Anthropic add $15b ARR every month. They're adding 0.34 Salesforce every single month! In 3 months, they add one Salesforce business.

How are we still saying there is no outside money flowing in? Demand is so great that no one has any extra capacity.

And clearly, the more compute we have, the better the results. AI intelligence has not hit a ceiling yet. More compute means more training, more inference, more thinking, more verification, more multi-agent work.

I don't think the tech industry embraced cryptocurrency.

There are a few outliers like Meta's basket of currency crypto attempt and Sam Altman's World Coin.

Meanwhile, the entire tech industry has embraced LLMs one way or another.

  - you fund a new company and sign long terms contracts with it - this new company uses the money you gave it and a lot of debt (backed by long term contracts) to build datacenters and buy a lot of GPU - your figures look great

If their business model thinks they can make a profit doing it this way, why stop them?

The core problem here seems to be that people think your supplier having an equity stake in your company is wrong or risky.