LLMs
Jail-Breaked & Offline Appliances: It’s becoming increasingly clear that we’ll be able to interact with everyday appliances and devices with natural language. As locally run LLMs become more efficient and powerful, the prospects of having a conversation with your coffee machine in the morning aren’t unreasonable. After all, who wants to tinker with... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
So right now, LLMs (Large Language Models) are all the rage. But in the future, it’s possible that the way we get things done is composing things with a combination of LLMs, SMMs (Small, Mighty Models), agents and tools.
It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).
This is how we... See more
It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).
This is how we... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
API wrappers, general-purpose AI tools and third-party AI tools for big platforms.
API wrappers have a weak moat.
General AI tools try to be the jack-of-all-trades.
Big platforms will eat up small apps by adding similar AI features themselves.
API wrappers have a weak moat.
General AI tools try to be the jack-of-all-trades.
Big platforms will eat up small apps by adding similar AI features themselves.
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
In general, I see LLMs to be used in two broad categories: data processing, which is more of a worker use-cases, where the latency isn't the biggest issue but rather quality, and in user-interactions, where latency is a big factor. I think for the faster case a faster fallback is necessary. Or you escalate upwards, you first rely on a smaller more... See more
Discord - A New Way to Chat with Friends & Communities
We went to OpenAI's office in San Francisco yesterday to ask them all the questions we had on Quivr (YC W24), here is what we learned:
1. Their office is super nice & you can eat damn good croissant in SF!
2. We can expect GPT 3.5 & 4 price to keep going down
3. A lot of people are using the Assistants API to build their use cases
4. It costs 2M$ to... See more
1. Their office is super nice & you can eat damn good croissant in SF!
2. We can expect GPT 3.5 & 4 price to keep going down
3. A lot of people are using the Assistants API to build their use cases
4. It costs 2M$ to... See more
Paul Venuto • feed updates
Easily chunk complex documents the same way a human would.
Chunking documents is a challenging task that underpins any RAG system. High quality results are critical to a sucessful AI application, yet most open-source libraries are limited in their ability to handle complex documents.
Open Parse is designed to fill this gap by providing a flexible,... See more
Chunking documents is a challenging task that underpins any RAG system. High quality results are critical to a sucessful AI application, yet most open-source libraries are limited in their ability to handle complex documents.
Open Parse is designed to fill this gap by providing a flexible,... See more
Filimoa • GitHub - Filimoa/open-parse: Improved file parsing for LLM’s
The context size of the input is too small for when you want to analyse CSV's with 1000's of rows and embedding doesn't really work because it loses context.
r/LLMDevs - Reddit
Menlo Ventures released a report on ‘The State of Generative AI in the Enterprise’ and found that adoption is trailing the hype. Details below:
Generative AI still represents less than 1% of cloud spend by surveyed enterprises, including just an 8% increase in 2023.
Safety and ROI continue to be prime concerns, and the tangible advantages of being... See more
Generative AI still represents less than 1% of cloud spend by surveyed enterprises, including just an 8% increase in 2023.
Safety and ROI continue to be prime concerns, and the tangible advantages of being... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Fine-Tuning for LLM Research by AI Hero
This repo contains the code that will be run inside the container. Alternatively, this code can also be run natively. The container is built and pushed to the repo using Github actions (see below). You can launch the fine tuning job using the examples in the https://github.com/ai-hero/llm-research-examples... See more
This repo contains the code that will be run inside the container. Alternatively, this code can also be run natively. The container is built and pushed to the repo using Github actions (see below). You can launch the fine tuning job using the examples in the https://github.com/ai-hero/llm-research-examples... See more