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themgt

8,873 karmajoined 15 lat temu
ongoing side projects/brainstorming:

https://z3kv.dev https://attoclaw.dev https://501api.org https://quidities.com

Submissions

Amazon and the White House Ended Anthropic's Fable

axios.com
12 points·by themgt·27 dni temu·1 comments

Mythos and Engels' Pause

fabricatedknowledge.com
3 points·by themgt·28 dni temu·0 comments

My AI Opinions

astralcodexten.com
6 points·by themgt·29 dni temu·0 comments

[untitled]

1 points·by themgt·w zeszłym miesiącu·0 comments

// The hope is that Claude Code will be unusable on this repository

codeberg.org
5 points·by themgt·w zeszłym miesiącu·0 comments

"Super-Spreaders" and Person-to-Person Transmission of Andes Virus in Argentina

nejm.org
3 points·by themgt·2 miesiące temu·0 comments

IEA: The largest supply disruption in the history of the global oil market

iea.org
2 points·by themgt·4 miesiące temu·0 comments

The left is missing out on AI

transformernews.ai
13 points·by themgt·5 miesięcy temu·6 comments

Why is Bezos trolling Musk on X with turtle pics? Because he has a new Moon plan

arstechnica.com
5 points·by themgt·5 miesięcy temu·0 comments

Seven Pages of a Sealed Watergate File Sat Undiscovered. Until Now.

nytimes.com
4 points·by themgt·5 miesięcy temu·0 comments

Nested Learning: A new ML paradigm for continual learning

research.google
152 points·by themgt·7 miesięcy temu·10 comments

China claims domestically-designed 14nm logic chips can rival 4nm Nvidia silicon

tomshardware.com
4 points·by themgt·7 miesięcy temu·0 comments

Blue Origin says it's just getting started with the New Glenn rocket

arstechnica.com
5 points·by themgt·8 miesięcy temu·0 comments

Linux 6.18 Will Further Complicate Non-GPL Out-of-Tree File-Systems

phoronix.com
6 points·by themgt·8 miesięcy temu·0 comments

Capitol Hill is abuzz with talk of the "Athena" plan for NASA

arstechnica.com
5 points·by themgt·8 miesięcy temu·0 comments

Signs of introspection in large language models

anthropic.com
183 points·by themgt·8 miesięcy temu·126 comments

Origin of our own species pushed back by half a million years

nhm.ac.uk
1 points·by themgt·10 miesięcy temu·0 comments

Illiteracy Is a Policy Choice

theargumentmag.com
117 points·by themgt·10 miesięcy temu·17 comments

[untitled]

2 points·by themgt·10 miesięcy temu·0 comments

comments

themgt
·przedwczoraj·discuss
Zig is getting that Elm, etc vibe. Genius/visionary BFDL who's also personally incapable of leading the project towards healthy long-term viability.

Say what you will about Matz or José Valim, I don't think they'd ever write a "and don't let the door hit you on the way out" screed full of personal attacks ("stinky manager", "writing slop", "a total shit show") against a person who led a very prominent project and financially supported the language.
themgt
·3 dni temu·discuss
HubSpot has been building a different solution for our customers. On August 4, Contact Discovery launches — and for the first time, your team can find, verify, and add net-new contacts without ever leaving HubSpot.

To support that, we’re updating our Customer Terms of Service, Product Specific Terms, Privacy Policy, Sub-Processors Page and Data Processing Agreement, effective July 1, 2026. This post explains what’s changing and why.

The contacts you find through Contact Discovery are reliable because they’ve been checked for deliverability, accuracy, and whether that person is still at that company. You’re not buying a raw list and hoping for the best. Every contact that surfaces has been validated, and decision-makers are ranked first.

That quality is only possible because of a shared dataset. When you opt into enrichment, some of your business contact data helps keep that dataset current. Everyone who participates gets more accurate data back in return. You never pay for a contact already in your CRM, and there’s no separate contract.

These are the new leads. These are the HubSpot leads, data mined from your own HubSpot account. And to you they're gold, and you don't get them. Why? Because to give them to you is just throwing them away. They're for closers. I'd wish you all good luck, but you wouldn't know what to do with it if you got it.
themgt
·5 dni temu·discuss
What I have been doing in many places—the octopus thought experiment, stochastic parrots, the phrase “synthetic text-extruding machines”—it’s all about trying to make vivid to people who aren’t in the business of building language technology what these systems actually do

> Meanwhile, O, a hyper-intelligent deep-sea octopus who is unable to visit or observe the two islands, discovers a way to tap into the underwater cable and listen in on A and B’s conversations. O knows nothing about English initially, but is very good at detecting statistical patterns. Over time, O learns to predict with great accuracy how B will respond to each of A’s utterances. O also observes that certain words tend to occur in similar contexts, and perhaps learns to generalize across lexical patterns by hypothesizing that they can be used somewhat interchangeably. Nonetheless, Ohas never observed these objects, and thus would not be able to pick out the referent of a word when presented with a set of (physical) alternatives.

This seems kind of obviously wrong at least in the context of coding agents. These models get trained on actual output of the previous version of the model doing its job, often "IRL" on a real computer/project. It's like O is in the conversation for years now and learning from his own interactions between A <-> O <-> B, where A is the human and B is the computer.

The idea O ontologically has never "observed" "these objects" or referents is philosophically strained. Have I observed the moon, or a finger pointing at the moon? Have I observed `sed` more than Fable?
themgt
·5 dni temu·discuss
Yeah I went looking: https://github.com/langchain-ai/openwiki/blob/main/src/agent...
themgt
·7 dni temu·discuss
Forgetting? I think you mean to say your advice was auto-compacted to keep our context small and deliver better results.
themgt
·9 dni temu·discuss
afaik there's somewhat painful economics. Not sure back-of-napkin but something like:

   • 150-500B: Sonnet
   • 0.9-2T: Opus
   • 3-5T/10T: Fable / Mythos
So if bigger model is "smarter" but you effectively wind up with a "shared hosting" model where a coherent inherence node(s) that cost $2m or something can run max 10x customer workloads simultaneously ... not sure what that can be priced at.

If it turns out a $10m/10x shared node can host even smarter models, then what?
themgt
·16 dni temu·discuss
This is exactly it - the ultimate skill now is to be Rick Rubin with an LLM. Not a comfortable transition as a coder.
themgt
·16 dni temu·discuss
"Well, in our country," said Alice, still panting a little, "you'd generally get to somewhere else—if you ran very fast for a long time, as we've been doing."

"A slow sort of country!" said the Queen. "Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!"
themgt
·16 dni temu·discuss
I will just say, if you are any good at programming and have experience using agents, you're in the top 0.1% of the world in adoption of a critical new technology.

It may seem hopeless as a programmer, but imo you'd be much better off reframing your situation re: the above sentence.
themgt
·16 dni temu·discuss
I just tested GLM 5.2 out via Z.ai in pi for a little one-off project that was already scoped. It actually did a relatively decent job starting out, and figured important things out from context.

But the reasoning traces became increasingly hilarious, with it getting confused and going in loops, doubting itself. I began to feel almost sad, it was like listening to the internal monologue of someone with anxiety disorder.

It made pretty good progress but wound up going in a lot of goofy loops and doing things a bit "off" from standards I'd hoped it would infer, and finally started going a bit nuts, "This is very confusing.", "OH WAIT", seemingly hallucinating a whole side-quest that didn't make sense and looking at making internal system changes to try to achieve its (now very confused) goal when I pulled the plug.

Without seeing the reasoning traces from Claude/GPT it's hard to really know, but it definitely didn't feel like the same quality of reasoning, even if dogged persistence does wind up actually working eventually.
themgt
·18 dni temu·discuss
It's not like the job market was that much better before AI infested every single corner of the market, but it supercharged all of the worst aspects of everything. I've seen people supposedly smarter than I advocate for just giving in, conceding to AI coding as it's the future. But doing so means tossing out my friends who make art or the people who work their asses off to properly test and review code or the writers pouring all of their energy into even mundane dialogue. It means throwing out my dignity as a software engineer, as someone that truly gives a shit about security and code.

Don't let yourself get attached to any tech stack you are not willing to walk out on in 30 seconds flat if you feel the heat around the corner. That's the discipline.
themgt
·20 dni temu·discuss
instead of people’s vibe checks and pelican SVGs.

Right, what happened is everyone went to Fable and asked it to make the very best bicycle pelican SVG, no mistakes. And Fable's bicycle pelican SVGs were such timeless masterpieces, we all instantly got AI psychosis. Happily, you were immune to this.
themgt
·21 dni temu·discuss
This was never the question. The question was, will the export controls slow them down in the short/medium term to the point where it will give US companies an advantage?

I mean, I remember listening to the Biden people back in 2022 talking how they were going to cripple China's semis and therefore AI industry and keep them 5+ years behind the curve as Team America accelerates ahead. That was the pitch.

You've now got Huawei Ascend 950, GLM-5.2 at Opus 4.8 levels, China dominating OSS models, and Z.ai saying they'll have a Fable-level model by EOY. I would say the export controls have utterly, utterly failed.

https://www.csis.org/analysis/understanding-biden-administra...
themgt
·21 dni temu·discuss
That’s not what your quotes said. They said bigger models = plateau in intelligence, nothing about more data or increased hallucinations ... I’m pretty sure #1 is well known

Well known in a multiverse branch where Fable was a dud?
themgt
·21 dni temu·discuss
Great, got it. I'll update my running "how computing works" chart with this new information:

  | implementation = reality | magic  |
  |-----------------------------------|
  | 999,999,999,971 (+1)     | 0      |
themgt
·22 dni temu·discuss
That said, I can't wait for LLMs to stop being AI and start being just another tool.

From a horse's perspective, the internal combustion engine is just another tool for making scary noises and powering horse trailers to take me on fun horse adventures. So ... perhaps.
themgt
·23 dni temu·discuss
Putting something in a spec does not automatically make it true.

Terrible news for computing.
themgt
·23 dni temu·discuss
Just to self-promote, we've got a very early stage project with a lot of similar ideas at https://quidities.com/ - feel free to signup / reach out if you have real world use cases anywhere in this space - we've got a lot in the works already.
themgt
·24 dni temu·discuss
This "vaguely nationalistic world view around tech" is a direct consequence of the US government ... The EU was build on the principles of collaboration ... But this only works if it is reciprocal.

This sounds great but doesn't really make any sense. What skeptics are saying is there should be a pan-EU effort to build frontier models, rather than one-off toy models built by each country as a box-ticking exercise.

"We built the EU as a powerful supranational organization, so logically the EU's response to a great power challenge in the realm that may well define the 21st century is gonna be to shatter its efforts into 27 useless pieces, because Trump bad" is just absolutely ridiculous and will not lead to anything good. Be the change you want to see, etc.
themgt
·27 dni temu·discuss
My favorite gerrymandering story was when I learned an ~800 student local college had been split down the middle, so students were in different congressional districts depending on their dorm building.