"Lies are all we have."

If so, how do we distinguish between code that works and code that doesn't work? Why should we even care?

> If so, how do we distinguish between code that works and code that doesn't work?

Hilariously, not by using our brains, that's for sure. You have to have an external machine. We all understand that "testing" and "code review" are different processes, and that's why.

Good point. We choose certain tests to perform. We choose certain test results to pay attention to. We don't just keep chatting about (reviewing) the code. We do something else.

If lies are all we have, then how is this behavior possible?

LLMs can write and run tests though.

You're cherry picking my little bit of wordsmithing. Obviously we aren't always wrong. I'm saying that our thought processes stem from hallucinatory connections and are routinely wrong on first cut, just like those of an LLM.

Actually I'm going farther than that and saying that the first cut token stream out of an AI is significantly more reliable than our personal thoughts. Certainly than mine, and I like to think I'm pretty good at this stuff.

I don't think the complaint about cherry picking is quite fair. Most of your original comment consists of claims that we're bullshit machines, our internal dialog is almost 100% fantasy, we're hallucinating, etc. Those claims may be true. But I'm not carefully like curating them out of nowhere.

If a known-broken calculator claims it's broken, I more or less concur. (Chain of reasoning omitted here.)

It's disconcerting. But in 2026 it's not very surprising.

But, Doctor, the data does back that up. The US middle class is shrinking, and most of the shrinkage is on the low end. There's no mystery about this, only potential for distractions.

Rage farming with no scientific interest. Sad to see this upvoted to front page.

There is an interesting question - how can we prove paternity or other DNA based questions with identical twins (full sequencing looking for mutations?) and if we can't, how do we handle legal responsibilities in this sort of case?

There's a lot of good material to discuss here.

Can you give a few penciled numbers?

You can rent a H100 GPU for $4/hour. [1]

300k tokens for that hour.

OpenAI charges $6.

Those are pessimistic assumptions.

[1] https://lambda.ai/instances

Can you keep that GPU 100% saturated at least 16 hours per day every day of the week?

If not, you aren't breaking even.

Note this is also assuming you

(1) Rent your GPUs.

(2) Pay list price, no volume breaks.

(3) Get only 85 tokens/sec. Realistically, frontier models would attain 200+ tokens/second amortized.

Inference is extremely profitable at scale.

Assuming 80GB H100 and you inference a model that is MoE and close to the size of the 80GB VRAM, you're going to see around 10k tokens/second fully batched and saturated. An example here might be Mixtral 8x7B.

You're generating about 36 million tokens/hour. Cost of Mixtral 8x7b on Open router is $0.54/M input tokens. $0.54/M output tokens.

You're looking at potentially $38.88/hour return on that H100 GPU. This is probably the best case scenario.

In reality, inference providers will use multiple GPUs together to run bigger, smarter models for a higher price.

3.99 at 8x instances, with a minimum 2 week commitment. Good luck getting 70% usage average during that time. Useful when you're running a training round and can properly gauge demand, not so great when you're offering an API.

Is it not a good penciled number? It helps set the directional tone that at inference cost is being covered.

It says the numbers are theoretically possible. Requiring a 66% usage to break even when 100% usage will piss off customers by invoking a queue means it’s a balancing act.

“Technically correct. The best kind of correct”. So inference may technically be _capable_ of being profitable, but I have question’s about them being profitable in _practice_.

The article is professional.

Soooo many comments here cite the "overreacting" point and then go on to prove it.

Another pack of evil volunteers trying to give us free stuff. Vote with your wallet. Stop paying your $0 per month until these crooks feel the pain.

One important thing is whether the tutoring is making better students, or just gaming the test.

And after graduation they can grind leetcode, and after that they can practice social cues to get in the management class. It's gamed tests all the way down.

For people who choose that career path. Still, somewhere somebody is doing some work.

The uggos I guess

Are those independent?

That's tricky. I think it depends on what kind of gaming and what kind of test.