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That's a good call, I'll try to remember that for next time.

by simonw 1y ago

Imustaskforhelp 1y ago
I just wanted to say that I really liked your this comment which just showed professionalism and just learning from your mistakes/improving yourself. I definitely consider you to be an AI influencer, especially in hackernews communities and so I wanted to say that I see influencers who will double down,triple down on things when in reality, people just wanted to help them in the first place. I just wanted to say thanks with all of this in mind, also that your generate me a pelican riding a bicycle has been a fun ride and is always going to be interesting, so thanks for that as well. I just wanted to share my gratitude with ya.
typpilol 1y ago
Have you thought about benchmarking models a month or two after release to see how it competes vs the day 1 release
- simonw 1y ago
  For that to be useful I'd need to be running much better benchmarks - anything less than a few hundred numerically scored tasks would be unlikely to reliably identity differences. An organization like Artificial Analysis would be a better fit for that kind of investigation: https://artificialanalysis.ai/ https://artificialanalysis.ai/
  - westurner 1y ago
    Manually, From https://news.ycombinator.com/item?id=40859434 https://news.ycombinator.com/item?id=40859434 : > E.g promptfoo and chainforge have multi-LLM workflows. > Promptfoo has a YAML configuration for prompts, providers,: https://www.promptfoo.dev/docs/configuration/guide/ https://www.promptfoo.dev/docs/configuration/guide/ openai/evals//docs/build-eval.md: https://github.com/openai/evals/blob/main/docs/build-eval.md https://github.com/openai/evals/blob/main/docs/build-eval.md From https://news.ycombinator.com/item?id=45267271 https://news.ycombinator.com/item?id=45267271 ; > API facades like OpenLLM and model routers like OpenRouter have standard interfaces for many or most LLM inputs and outputs. Tools like Promptfoo, ChainForge, and LocalAI also all have abstractions over many models. > What are the open standards for representing LLM inputs, and outputs? > W3C PROV has prov:Entity, prov:Activity, and prov:Agent for modeling AI provenance: who or what did what when. > LLM evals could be represented in W3C EARL Evaluation and Reporting Language "Can Large Language Models Emulate Judicial Decision-Making? [Paper]" https://news.ycombinator.com/item?id=42927611 https://news.ycombinator.com/item?id=42927611 "California governor signs AI transparency bill into law" (2025) https://news.ycombinator.com/item?id=45418428 https://news.ycombinator.com/item?id=45418428 : > https://sb53.info/ https://sb53.info/ Is this the first of its sort?: > CalCompute

That's a good call, I'll try to remember that for next time.

by simonw 1y ago

That's a good call, I'll try to remember that for next time.

I just wanted to say that I really liked your this comment which just showed professionalism and just learning from your mistakes/improving yourself. I definitely consider you to be an AI influencer, especially in hackernews communities and so I wanted to say that I see influencers who will double down,triple down on things when in reality, people just wanted to help them in the first place. I just wanted to say thanks with all of this in mind, also that your generate me a pelican riding a bicycle has been a fun ride and is always going to be interesting, so thanks for that as well. I just wanted to share my gratitude with ya.

typpilol 1y ago

Have you thought about benchmarking models a month or two after release to see how it competes vs the day 1 release

simonw 1y ago
For that to be useful I'd need to be running much better benchmarks - anything less than a few hundred numerically scored tasks would be unlikely to reliably identity differences. An organization like Artificial Analysis would be a better fit for that kind of investigation: https://artificialanalysis.ai/ https://artificialanalysis.ai/
- westurner 1y ago
  Manually, From https://news.ycombinator.com/item?id=40859434 https://news.ycombinator.com/item?id=40859434 : > E.g promptfoo and chainforge have multi-LLM workflows. > Promptfoo has a YAML configuration for prompts, providers,: https://www.promptfoo.dev/docs/configuration/guide/ https://www.promptfoo.dev/docs/configuration/guide/ openai/evals//docs/build-eval.md: https://github.com/openai/evals/blob/main/docs/build-eval.md https://github.com/openai/evals/blob/main/docs/build-eval.md From https://news.ycombinator.com/item?id=45267271 https://news.ycombinator.com/item?id=45267271 ; > API facades like OpenLLM and model routers like OpenRouter have standard interfaces for many or most LLM inputs and outputs. Tools like Promptfoo, ChainForge, and LocalAI also all have abstractions over many models. > What are the open standards for representing LLM inputs, and outputs? > W3C PROV has prov:Entity, prov:Activity, and prov:Agent for modeling AI provenance: who or what did what when. > LLM evals could be represented in W3C EARL Evaluation and Reporting Language "Can Large Language Models Emulate Judicial Decision-Making? [Paper]" https://news.ycombinator.com/item?id=42927611 https://news.ycombinator.com/item?id=42927611 "California governor signs AI transparency bill into law" (2025) https://news.ycombinator.com/item?id=45418428 https://news.ycombinator.com/item?id=45418428 : > https://sb53.info/ https://sb53.info/ Is this the first of its sort?: > CalCompute