Viewing profile — rockinghigh

For small models, tokenization can reach 1-10% of total inference time.

A coding agent driven by a large LLM can delegate smaller tasks to a faster model. For example searching through the codebase for references, examples, or established patterns. The…

Open-weight models were lagging 4 months behind OpenAI/Anthropic at the beginning of the year. They are now just 4-6 weeks behind.

The US is also falling behind Chinese manufacturing. They had to ban Chinese cars because legacy American automakers couldn't compete.

Same here, I fine tune LLMs for specific use cases. How can I trust Anthropic models not to introduce bugs to preserve their moat?

Imagine if your IDE started injecting bugs into your project just because your code looked like it implemented a competing IDE.

Consumers don't control zoning laws or risk mitigation details.

Gemini tends to be faster and the Flash and Flash Lite models outperform ChatGPT's equivalent models.

It may be a push from advertisers who want access to this format. Google Search competes for their money against the competition.

They own tons of engagement data associated with that index from being the default search engine on most devices.

Why wouldn't getting more customers the plan? Anthropic doesn't acquire companies to have a lower market share. There is clearly a consolidation and a rush to get as much of the de…

The MoE experts are quantized to int4, all other weights like the shared expert weights are excluded from quantization and use bf16.

They could release data to back up that claim.

Are there any protections from industrial espionage when using Anthropic, Cursor, Gemini, or OpenAI?

Their revenue was $57.4 billion last year. Just in Q4; cloud revenue $6.7 billion, cloud infrastructure $3.0 billion, cloud application $3.7 billion, Fusion Cloud ERP $1.0 billion,…

It's the number of attempts at answering the question.

He founded the team that worked on fasttext, llama and other similarly impactful projects.

He founded FAIR and the team in Paris that ultimately worked on the early Llama versions.

It can also be used to simplify existing code bases.

It's a lot simpler. These models are not optimized for ambiguous riddles.

How is this riddle relevant to a coding model?

They do. Pretty much all agentic models call linting, compiling and testing tools as part of their flow.

It's called problem decomposition and agentic coding systems do some of this by themselves now: generate a plan, break the tasks into subgoals, implement first subgoal, test if it …

A language model in computer science is a model that predicts the probability of a sentence or a word given a sentence. This definition predates LLMs.

How do you join two datasets using r-trees? In a business setting, having a static and constant projection is critical. As long as you agree on zoom level, joining two datasets wit…