genxy

Once they get good enough, they won't even ship the models, they will just replace all the jobs themselves. This is where Anthropic, OpenAI and Google are heading, esp Google with GSuite, it already is up in your business doing your business.

All your jobs are belong to them.

That is google trying to keep their 10% worth something.

Easy, all the damn time.

It is great news, it means that C++ can slowly wither as other organisms occupy the same niche.

This video on the device itself (from the readme), not about the robot suit itself.

How I See from Inside Robby — AMT630A Heads-Up Display https://www.youtube.com/watch?v=0eQ94DHOay0

It isn't that it is dead, it is just pushed out really really far. So the bathtub curve turns into, "if it survives birth, it lives forever"

> facet is a library for Rust which provides run-time reflection. By annotating your struct with #[derive(facet::Facet)], you get a SHAPE associated type which can be inspected at runtime.

https://github.com/facet-rs/facet

> The core crates give types a SHAPE associated constant with their kind, layout, fields, documentation, attributes, and type-specific operations. facet-reflect builds, reads, and mutates values through those shapes while preserving their invariants.

> Serialization and integration crates build on that reflection layer: JSON, TOML, YAML, MessagePack, Postcard, ASN.1, XDR, CSV, XML, URL-encoded forms, SQLite, Axum, schema generation, structural diffing, and more.

Side by side comparison with SERDE https://facet.rs/guide/serde/

RIP Robin Williams

Shelley Duvall was amazing in Popeye.

AOC

You really need to work on your rhetorical combat, hn is not for amateurs.

I said "techniques in DSPy", your agentic workflows are already using them. Read the GEPA paper. I'll put the link here and you can scroll down and read it.

https://github.com/stanfordnlp/dspy

Your agentic loops are already doing these things.

It is for execs

Just use the post-one-off-project-to-huggingface-skill.md

Techniques in DSPy are still extremely valuable. Your comment is akin to saying, we don't need feedback because open loop control is so good now. It is until it isn't. I don't need a deep understanding of the underlying theory because my gut reaction is always right, until it isn't.

You should have working programs that demonstrate the features you want them to use, and then the skills. Working programs they can mutate in an RL gym.

Maintenance when you don't have access to an LLM?

How small of a model can complete the operation you described above? If writing a parser still requires a software forge with 2T of vram and a petabyte of training data, then I still see value in PEGs.

Maybe the smaller local models, given a structured grammar can use a PEG to generate a parser.

First AI came for the parrots and I did nothing, at least I can stand for the neanderthals.

There are so many parallels between what TV could have become and the progression of AI, a nearly free conveyance for culture, education, art and discourse. Yet, we allowed it spiral in a positive feedback loop, creating a cognitive gyre that now razes society.

At least the youngest now use "that's AI" as a pejorative, as in that is bullshit.

My favorite quip in response to asking for something to get improved inside of Google is, "no one ever asked for this", knowing full well the opportunity to ask was near zero and no one ever looked.

Google is a crazy town, data driven by cherry picked post-hoc rationalizations driven by perf. The user never enters the equation.

> We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.

If we want to ensure that we stay true to Amara's Law, we will need to spend the next 10 years ensuring that we use AI across all of civilization to enshittify everything and prevent young people from meaningfully entering society.

https://en.wikipedia.org/wiki/Roy_Amara

> I know I am a jackass who usually vibecodes my way through assignments but even I don't want to write a cookie-cutter intro for my paper.

+1 point for honesty.

-100 for being pathetically pathetic

Plan forced the model to write down and outline what it was going to do before writing the code. As Boris said up thread, he created it to prevent it from just rushing into writing code. So that regard, it did act like a permission system.

It helps to think more abstractly when approaching problems like this.

> neanderthal levels of intelligence

were gonna need a citation on this one.

But they confidently dismissed the research and said don't worry.

Which is why we should target VMs directly. Then that VM can be brought forward to new platforms rather than emulating the entire machine, not that emulating the entire machine is bad. One could argue that the emulation stack you outline was made possible by putting in the work to make simple, fully specified and documented hardware.

I like Linus's work, but that post smells of rotting strawmen. All the examples look manipulated into throwing the opposition under the bus.

Who is the editor on this article? Why would they expect the reader to know what the SAVE database is and what its original purpose was for?

https://en.wikipedia.org/wiki/Systematic_Alien_Verification_...

> Systematic Alien Verification for Entitlements (SAVE) is a program managed by United States Citizenship and Immigration Services (USCIS), a branch of the US Department of Homeland Security (DHS). SAVE was created in 1986 and facilitates lookups on the immigration and nationality status of individuals in the United States.

The wikipedia article is written ambiguously, or they bury the actual purpose of the SAVE database

> a system for verifying the immigration status of non-citizen applicants applying for (medicad, food stamps, unemployment, student loans and housing assistance)

It wasn't designed to be a citizenship database.

https://apnews.com/article/save-database-noncitizen-voters-t...

https://www.cbsnews.com/news/supreme-court-trump-save-system...

Then say what you mean, instead of having coy false confusion and this addled manic line of conversation.

Very little was gained.

I don't understand people leveling criticisms at the output of AI, when that is exactly how you program them. Have people all forgotten the "prompt engineer" phase of our roles?

Give them 2 positive examples. A list of things to do, a list of things not to do and you have them giving you the exact output you want.

"Write a readme make no misteaks" is not deft usage.

If they would bring a barebones electric station wagon to the US that would be heavenly.

When the refcount goes to zero the knowledge is consumed. Your take is overlay pedantic without benefit.

Both definitions of knowledge creation can used. If one creates a book and it is never read, has it been produced? Isn't knowledge also its access and how widely it is disseminated?