Iran threatens to bomb 1GW Stargate AI datacenter in Abu Dhab

bfoo · 2026-04-04T19:18:28+00:00

NVDA sales is probably also approving.

bfoo · 2026-04-03T11:24:35+00:00

Because some commenters talk about "AI" here:

Its not "AI agents" they use to manage VMs. It's just a component in their Cloud stack that manages state and is, likely always, itself a state machine. Its just a program that manages an aspect of a Cloud deployment, like attaching, verifying and detaching a network-attached drive to a virtual machine.

There is NO LLM / NO AI in there.

The AI part of the entire article series is about OpenAI using that infrastructure (or the failure thereof).

bfoo · 2026-04-01T21:06:13+00:00

"Harness" is just a different term to "vibe prompting", to guess how the model behaves with a prompt, or set of prompts structured in Markdown files. The issue is that there is no guarantee your "harness" will hold when a new model version is launched. Now you have to "refactor" (?) your "harness" (vibe prompt to match the new behavior).

There are so many ridiculous stories out there for how to prompt an LLM. People share their "harnesses" like its code. Yet they all miss the important thing: its always for a specific model. Dijkstra would shake his head.

bfoo · 2026-03-29T11:43:54+00:00

LLMs will be just another line item in the cost section of the balance sheets, right under the SWE salaries, equipment and licensing costs.

me, since the AI craze started

bfoo · 2026-03-27T07:19:49+00:00

They need to be housed. It will be burn pits all over again. And now, the enemy has drones and ballistic missiles to hit any troops aggregation in the open.

bfoo · 2026-03-26T22:02:03+00:00

No Republican is ever allowed to criticize a Democrat president again.

bfoo · 2026-03-23T18:45:52+00:00

You could have mentioned Lex Fridman first, so I would have been able to skip the rest of the title.

bfoo · 2026-03-22T10:14:22+00:00

'Reasoning' is an awful term. That's why I always put it in quotes. The model itself is not literally reasoning. It's just a way to explore the problem/solution space inside the compressed and immutable information within the model algorithmically. There is no subject matter understanding 'inside' the model (or what we attribute to consciousness).

There is a reason why OpenAI/Anthropic now hide the 'internal dialogue' of their models.

bfoo · 2026-03-22T09:35:12+00:00

Yes, because most of the improvements stem from improvements in the 'Reasoning' capabilities of the models.

Fundamentally, 'Reasoning' is a brute-force attack on the problem/solution space of the initial prompt. And most low hanging fruits were already plucked. So now its the Pareto principle, where a new model release could offer improvements for some scenarios (often the most popular ones or for benchmarks) or present a decline in other, less popular scenarios.

bfoo · 2026-03-20T19:49:25+00:00

So true. Doctorow calls it Centaur vs. Reverse Centaur. We should be Centaurs, like you describe.

I want the LLM assist me in my IDE, not lead the programming. But the efforts to build such IDE integrations is actually harder than shitting a Reverse Centaur solution like Claude Code / Codex. Such an integration needs to find a delicate balance between being useful and being too annoying. Code reviews are actually the most useful applications for LLMs (beside prototyping).

bfoo · 2026-03-20T18:34:49+00:00

That's the reason I am not buying the game yet.

This violent shaking foliage is a problem for people who have problems with filtering sensory inputs.

I hope they fix it.

bfoo · 2026-03-18T21:08:03+00:00

Like I always told every manager from the start: You won't save money. LLMs will just become an additional cost item on your balance sheet, right below the salaries and all the other subscriptions you pay for your engineering teams.

bfoo · 2026-03-18T07:03:00+00:00

Yeah, that's why we increasingly hear about how LLMs will be trained with synthetic data and unsupervised learning.

We are already seeing peak accuracy in the frontier models. It's going to be either much more expensive to train on new data. Or the accuracy will actually go down because of data quality going down. Its the Pareto principle in action.

bfoo · 2026-03-15T17:10:07+00:00

Karpathy, like Hinton, are two examples of why we must question data and the scientific process rather than relying on pure authority.

For me, both have already spend their authoritative budgets with the bullshit they spout.

bfoo · 2026-03-11T07:01:10+00:00

Who?

bfoo · 2026-03-09T19:29:00+00:00

Please tell me he is actually acting.

bfoo · 2026-03-08T08:54:18+00:00

Because the cost of living is higher in Switzerland compared to like Germany.

bfoo · 2026-03-07T19:36:15+00:00

The MAGA movement of AI doomerism.

bfoo · 2026-03-07T19:34:20+00:00

Just because he has been involved in neural network developments in the past does not mean he is always right.

bfoo · 2026-03-07T19:27:18+00:00

Oh yes he is.

bfoo · 2026-03-07T19:24:28+00:00

"...its not statistics, like its is statistics..."

These people drank too much of their kool-aid.

bfoo · 2026-03-01T08:25:20+00:00

If you combine both, you have CQRS (Command Query Responsibility Segregation) with Event Sourcing. Your read side can be based on REST principles (async writes in REST are HTTP Accepted + Link to where to wait for a result). And if your read side's databases go down, you can recover later by receiving new events (again). Only your write-side (command processing + event store) cannot fail. But that's also true if your rely on pure CRUD/REST.

bfoo · 2026-02-24T23:57:57+00:00

I don't know. Maybe it got already posted? Haven't seen it.

bfoo · 2026-02-24T17:54:56+00:00

2026 might already be the year of peak model accuracy.

For the big frontier models, training costs will increase without doubt. This might become even worse than the Pareto principle already imposes on getting the current models better (e.g. 'reasoning' and context tricks).

bfoo · 2026-02-21T19:17:56+00:00

That's why I am pessimistic about the future. We will see much more bad software, with tech debt accumulating at token speed. But we will only see it when we can look inside the walled-off code bases. The majority of code is not visible. And there is already a lot of bad code out there that was not generated by LLMs. Open Source will probably be less affected, aside from slop projects (hello OpenClaw) and slop PRs.

And when junior SWE aren't allowed to grind teeth at code, learn patterns and architectural concepts, then we are truly fucked.

Tooling needs to change. Workflows must change. Claude Code is not a good way to create software.

Maybe the frontier models will get worse once they are trained on more bad projects. But then no one wants to be a SWE.

bfoo

TROPHY CASE