ClassAndBurn (u/ClassAndBurn)

ClassAndBurn commented on Open models by OpenAI openai.com/open-models/... · Posted by u/lackoftactics

Open models are going to win long-term. Anthropics' own research has to use OSS models [0]. China is demonstrating how quickly companies can iterate on open models, allowing smaller teams access and augmentation to the abilities of a model without paying the training cost.

My personal prediction is that the US foundational model makers will OSS something close to N-1 for the next 1-3 iterations. The CAPEX for the foundational model creation is too high to justify OSS for the current generation. Unless the US Gov steps up and starts subsidizing power, or Stargate does 10x what it is planned right now.

N-1 model value depreciates insanely fast. Making an OSS release of them and allowing specialized use cases and novel developments allows potential value to be captured and integrated into future model designs. It's medium risk, as you may lose market share. But also high potential value, as the shared discoveries could substantially increase the velocity of next-gen development.

There will be a plethora of small OSS models. Iteration on the OSS releases is going to be biased towards local development, creating more capable and specialized models that work on smaller and smaller devices. In an agentic future, every different agent in a domain may have its own model. Distilled and customized for its use case without significant cost.

Everyone is racing to AGI/SGI. The models along the way are to capture market share and use data for training and evaluations. Once someone hits AGI/SGI, the consumer market is nice to have, but the real value is in novel developments in science, engineering, and every other aspect of the world.

[0] https://www.anthropic.com/research/persona-vectors > We demonstrate these applications on two open-source models, Qwen 2.5-7B-Instruct and Llama-3.1-8B-Instruct.

ClassAndBurn commented on Why Gumroad Didn't Choose Htmx htmx.org/essays/why-gumro... · Posted by u/rmason

ketzo · a year ago

> AI and Tooling Support: It’s worth noting that AI tools are intimately familiar with Next.js and not so much with htmx

This is stated as a very matter-of-fact downside, but this is a pretty crazy portent for the future of dev tools / libraries / frameworks / languages.

Predictions:

- LLMs will further amplify the existing winner-take-all, first-mover nature of dev tools

- LLMs will encourage usage of open-source tools because they will be so much more useful with more/better training data

ClassAndBurn · a year ago

This will not be true for future frameworks, though it is likely true for current ones.

Future frameworks will be designed for AI and enablement. There will be a reversal in convention-over-configuration. Explicit referencing and configuration allow models to make fewer assumptions with less training.

All current models are trained on good and bad examples of existing frameworks. This is why asking an LLM to “code like John Carmack” produces better code.. Future frameworks can quickly build out example documentation and provide it within the framework for AI tools to reference directly.

ClassAndBurn commented on Social engineering takeovers of open source projects openssf.org/blog/2024/04/... · Posted by u/mooreds

ClassAndBurn · a year ago

There's an awkward reckoning in open source software about inclusivity and protecting the long-term security of projects coming.

Authors from several countries were already suspicious, such as Iran. Anyone from Russia and China or unknown places are all potential risks now.

Combined with recent inclusive ideologies, it’s gonna cause hard conversations. There will be a furthering in segmenting the Internet. Why fight contributing to an open source project when you could fork it and contribute with your allies?

For true enemies, there’s no risk to licensing or copyright issues. You can merge changes from the original, no problem. China even falls into this as there’s a limited ability for US companies to litigate within the country.

People think the Network State is hot, but at the end of the day, the Internet still has borders.

ClassAndBurn commented on IBM to buy HashiCorp in $6.4B deal reuters.com/markets/deals... · Posted by u/amateurhuman

ClassAndBurn · a year ago

Hashi never sold me on the integration of their products, which was my primary issue with not selecting them. Each is independently useful, and there is no nudge to combine them for a 1+1=3 feature set.

Kubernetes was the chasm. Owning the computing platform is the core of utilizing Vault and integrating it.

The primary issue was that there was never a "One Click" way to create an environment using Vagarent, Packer, Nomad, Vault, Waypoint, and Boundry for a local developer-to-prod setup. Because of this, everyone built bespoke, and each component was independently debated and selected. They could have standardized a pipeline and allowed new companies to get off the ground quickly. Existing companies could still pick and choose their pieces. On both, you sell support contracts.

I hope they do well at IBM. Their cloud services' strategy is creating a holistic platform. So, there is still a chance Hashi products will get the integration they deserve.

ClassAndBurn commented on Speeding up Azure development by not using Terraform nitric.io/blog/terraform-... · Posted by u/elisselockhart

ClassAndBurn · a year ago

Others' concerns are valid; the separation of concerns makes infra changes safer and easier to understand. Infra-tooling is slow because of the inherent risk of managing stateful services.

Mixing the infra and application logic is the obvious path forward, though. Just as most applications don't need more than Rails and a single Postgres, most apps don't need customized infra. Simplifying the 80% unlocks cycles for more creative work. Suppose you are successful enough to have to define custom infra at some point. That's good for you. That's a great problem to have.

AI is going to standardize architectures going forward. Providing a simple set of tools in the same code as the logic makes the planner easier for Copilots and reduces the context windows. Terraform and application code have implicit dependencies. Colocating them lets you define explicit dependencies that are more understandable.

ClassAndBurn commented on Software 2.0 (2017) karpathy.medium.com/softw... · Posted by u/gtirloni

agentultra · 3 years ago

I think we need to train people to write formal specifications before we're going to see machine learning techniques generating useful programs.

Sure sometimes an LLM generates a correct program. And sometimes horoscopes predict the future.

I will be impressed when we can write a precise and formally verifiable specification of a program and some other program can generate the code for us from that specification and prove the generated implementation is faithful to the specification.

An active area of research here, code synthesis, is promising! It's still a long way off from generating whole programs from a specification. The search spaces are not small. And even using a language as precise as mathematics leaves a lot of search space and ambiguity.

Where we're going today with LLM's trying to infer a program from an imprecise specification written in informal language is simply disappointing.

ClassAndBurn · 3 years ago

I agree here. Formal models have to become easier to create through.

Today's ecosystem requires advanced knowledge of system design and still coding abilities.

To democratize model generation we need a more iterative and understandable way of defining intented execution. The problem is this devolves into just coding the damn thing pretty quickly.

ClassAndBurn commented on GitHub Copilot investigation githubcopilotinvestigatio... · Posted by u/john-doe

PythagoRascal · 3 years ago

> It is learning from it just as a human reader would

I don't see how that invalidates the copyright/license argument. So, instead of just a straight up license violation it's a license violation via plagiarism.

That argument wouldn't hold up even if it was a human that caused the violation. You can't just paraphrase someones licensed work and then lie about looking at and pretend you made it yourself, which is basically what seems to happen with co-pilot, as it doesn't also automatically reproduce the license of the code it reproduces.

ClassAndBurn · 3 years ago

It learns the same way a human does by learning patterns. It is not illegal to comprehend how to accomplish tasks by reading other people's source code.

The arguments against my point always assume perfect memory of everything this model is consumed. This is the plagiarism position. In reality, some patterns are more common than others and generate a code that looks nearly identical. I can’t speak for the reasons for this, as I’m not familiar with all of the methods. However, I don’t assume that is the current working state or intent of Codex.