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devilankur18

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Ask HN: How user behaviour have evolved in post ChatGPT world?

1 points·by devilankur18·3 anni fa·0 comments

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1 points·by devilankur18·3 anni fa·0 comments

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1 points·by devilankur18·3 anni fa·0 comments

Top Problems with LLM App Development

2 points·by devilankur18·3 anni fa·3 comments

Ask HN: Prompt Engineering: A Skill or Role? Whats the Future?

8 points·by devilankur18·3 anni fa·11 comments

Show HN: Open-Source Microservices Framework for Cross-LLM Apps

sugarcaneai.dev
10 points·by devilankur18·3 anni fa·2 comments

comments

devilankur18
·2 anni fa·discuss
Looks good !!
devilankur18
·3 anni fa·discuss
Hasgeek Ai Community - https://hasgeek.com/generativeAI
devilankur18
·3 anni fa·discuss
where problem do you think take the most time ?
devilankur18
·3 anni fa·discuss
what differentiates a normal prompt engineer from super. A few things i can think of - Cross LLM experience - Understanding how to accuracy faster - Expereince with LLM Tools

Anyhting else come to mind ?
devilankur18
·3 anni fa·discuss
I can agree thats going on these days. But important questions is whats the future hold for this.
devilankur18
·3 anni fa·discuss
Agreed, question is what is the timeline for this? 2year or 5 year or much later ?
devilankur18
·3 anni fa·discuss
What about from LLM App development role prospective ? Similar to a backend or frontend enginnering ?
devilankur18
·3 anni fa·discuss
Followup - How many prompt engineers would be needed in next 2 years of time ?
devilankur18
·3 anni fa·discuss
Sugarcane AI provides an Open Source Microservices Framework for cross-LLM workflow/plugin development, allowing developers to prioritize business logic over LLM selection, cost, and performance.

Framework comprises - LLM as a Service for Data Scientists, empowering data labelling and fine-tuning - Prompt as a Service for Prompt developers, streamlining prompt management - Workflow as a Service for Plugin developers to construct workflow plugins, facilitating the distribution of LLM, Prompts, and Plugins via APIs.

The Open Source framework encourages collaborative dataset development and enhances reusability of prompt packages and fine-tuned LLMs, facilitating sharing and monetization on an open marketplace.