johnbarron

>> Those differ from Dan’s essay, which engages with the literal text of Ed’s numerous predictions during 2024 and 2025 which are demonstrably invalidated by their measurable outcomes.

Dan Luu did not engage on anything more, than a disorganized wall of text, ranted like a teenager using toxic personal attacks, while obsessing over calendar errors and a placeholder in a spreadsheet. If this is what passes here for a smart engineer...Lets analyze his post in a more logical and analytical way:

- His entire argument is based on the naive logic that because LLM execution speeds or benchmarks marginally improved over the last 24 months, the entire trillion dollar investment cycle is justified. A short window of venture subsidized chip buying...tells you absolutely nothing about the multi decade debt structures, physical infrastructure depreciation, and power grid constraints that dictate whether a capital heavy business model survives.

- While he whines about Zitron numbers, fails to provide a single! macro level equation to address the real financial threat. NYU finance professor Aswath Damodaran for example, explicitly warned that the current AI build out is an asset heavy, debt funded run up backed by private capital markets. Unlike the dotcom boom which was equity funded and contained to tech shareholders today AI infrastructure burdens companies with a massive $80 billion in CapEx per gigawatt, meaning a monetization correction will trigger widespread systemic debt distress and loan defaults across the real economy.

"Aswath Damodaran: Big Tech Has No Idea How AI Pays Off" - https://news.ycombinator.com/item?id=49229981

- Luu and this HN crowd, today in a mob mood...completely ignore the highly unstable plumbing of the sector growth metrics. Patrick Boyle is a quantitative finance professor and former hedge fund manager, and has meticulously mapped out the mutual dependence the entire AI boom. Big Tech companies are pouring massive venture pools into AI startups, which are then contractually bound to hand that cash right back to the hyperscalers to buy cloud compute. Analysts have identified more than $800 billion in these arrangements:

"Why Wall Street is ignoring big tech's debt" - https://news.ycombinator.com/item?id=49230630

- The worst of Luu logical failure, is ignoring ( on purpose? ) were Zitron numbers come from! They come from some very disciplined institutions, which Luu completely ignores. Citigroup quantitative analysts project cumulative global AI CapEx hitting $9 Trillion through 2030, with maximum global AI revenues ( not profit...) covering less than 30% of that expenditure.

- To break even on the physical infrastructure currently under construction, the AI sector needs to generate over $2 Trillion in annual end user revenue by 2030. Total actual revenue generated across the ENTIRE global AI sector today sits at a fraction, around $150 billion.

- Anthropic in a hysterical push, to make it to public markets, before the bubble bursts, recently claimed their addressable market is 30 trillion... the whole of US economy. Are we getting a post from Luu on that? This of course this ignores that MIT Professor and Nobel Laureate, Daron Acemoglu, mathematically proved that while 20% of all labor tasks are exposed to AI, only about 5% can be automated profitably due to upfront enterprise systems integration and the high financial burden of constant human in the loop verification.

"A new look at the economics of AI" - https://mitsloan.mit.edu/ideas-made-to-matter/a-new-look-eco...

- Dismissing the AI bubble thesis, because you found a spreadsheet typo in a newsletter, and ignoring the other voices who are aligned with Zitron core premise, means you are also dismissing the research of a Nobel Laureate in economics, the Dean of Valuation, veteran hedge fund managers, Barclays, S&P Global, and Citigroup. Arguing that "the models are hitting benchmarks" while ignoring that the physical balance sheets and enterprise budgets cannot support a multi trillion dollar infrastructure build out, is exactly the type of Dunning Kruger this corner excels at....

Ed Zitron is correct, despite the clumsiness or unpleasantness of his message delivery, and this community reaction, will be an historical record of the AI bubble crowd madness.

It took years to take down Maddoff, and more to take down Bear Stearns. It will take maybe 5 - 10 years of "Ed Zitron is wrong posts here" until Anthropic and OpenAI have to be bailed out by the US government, but the day of reckoning will come. The end of this universe is all tax payers will own a piece of AI and will pay for it with increased interest rates for the next 25 years...

You will see, they will change both laws and expectations, to say its normal for software to always have terrible bugs. You can always solve a problem by lowering your expectations. :-)

It does not work because the errors compound and also are most times correlated.

"Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panels" - https://arxiv.org/abs/2605.29800

"From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration" - https://arxiv.org/abs/2605.29800

"Large Language Models Cannot Self-Correct Reasoning Yet" - https://arxiv.org/abs/2310.01798

"Correlated Errors in Large Language Models" - https://proceedings.mlr.press/v267/kim25e.html

"Partially Correlated Verifier Cascades in LLM Harnesses: Concave Log-Odds, Polynomial Reliability, and Blind-Spot Ceilings" - https://arxiv.org/abs/2607.13918

"Cross-Context Verification: Hierarchical Detection of Benchmark Contamination through Session-Isolated Analysis" - https://arxiv.org/abs/2603.21454

That has been proven not to work and a variation of the "make no mistakes" meme. What about the lawyer doing the actual work, he/she is being paid for?

An AI does not need bonus to keep up with a trophy wife...

If you spent your whole career inside one corporate ecosystem...do not confuse your rank in that hierarchy, with your rank in the profession. By looking at the some comments here, many are doing that.

https://www.youtube.com/shorts/FXPh2_BAZD8

I am also Sovereign. Will do it for half the price this one is asking for.

I love Hereditary Dentists....

It does matter. His airplane has to make more and zigzags, to avoid any airspace where he can be arrested. And he is only one mechanical fault away from landing in a place who will extradite him to The Hague...

"Sentient Being - Measure of a Man" - https://youtu.be/EFNbTnFHruI

Meaning you can switch in seconds. Stripe just has too much money...

Who is that someone? And unnamed employee that told somebody else?

They make less than 140 million in revenue, what today is like 5 signing bonus for OpenAI :-) They are not profitable and see through less than 2 billion in revenue.

These are easy to check so...

They might be popular for indie developers, but nobody doing serious AI or in a corporate environment is using them.

And if they are, their compliance team is about to strike them down. The VCs forcing this acquisition do know this.

- Why would you add a penalty of 50 ms at a minimum? And that is not the p95... Just run LiteLLM in house and you dont even really need that.

- Their capacity pools are shared across the whole user base, a massive batch processing by another of their customers and think what that means for your response time...

- So instead of negotiating corporate rates with OpenAI or Anthropic, you would be using an intermediary and topping up the corporate credit card... for a 5% markdown ? Really?

- They can see all your critical corporate data on the in and out

- They present some pink SOC 2 promises but then wash their hands and defer to you and the providers. Its just the Bolt and Uber model the drivers are not our employees....

- They are a man in the middle proxy that is a massive security liability for your corporation

- They have no support for private cloud points

- No geofencing guarantees

- No intellectual property legal indemnification unlike what AWS or Microsoft or Google offers

- Its a provider roulette inconsistent with hosts providing different quantization levels causing random shifts in response quality

- Support via a Discord server...

The only reason they were not shutdown yet by Anthropic or OpenAI is because they have the same VCs, as those two. That would mean said VCs investment would go to zero. Oh and those are the same VCs that own Stripe...

Just setup a private proxy tier using something like LiteLLM, even if you really dont need it. Just code your enterprise apps to have have fallback loops on the core hyperscaler providers like AWS Bedrock or Azure Foundry...

Did you meant this for LinkedIn?

"An engineer checked progress twice a day and reviewed every proposed change. Simpler instructions worked better than a more elaborate setup."

Oh dear, poor Asana customers...

This year is not over yet....

>> choice of where hosted,

You dont understand Bedrock fundamental use case.