LLMs
Here's my read on the situation:
* The TAM is massive, still so many businesses trying to figure out AI
* If you do deployments you’ll need to spend a of time hand holding clients through scoping projects (not unlike other dev works) since the material is so new
* Lot’s of opportunity in education
* The hard part isn’t the expertise, it’s distribution... See more
* The TAM is massive, still so many businesses trying to figure out AI
* If you do deployments you’ll need to spend a of time hand holding clients through scoping projects (not unlike other dev works) since the material is so new
* Lot’s of opportunity in education
* The hard part isn’t the expertise, it’s distribution... See more
Greg Kamradt • Tweet
First of all, I'd say you have a bigger problem where your company is trying to find nails with a hammer. That is where your sentiment comes from, and could be an obstacle for both you and the company. It's the same deal when I see people keep on talking about RAG, and nowadays "modular RAG", when really, you could treat everything as a software... See more
r/MachineLearning - Reddit
We identified 30 types of tasks that UX professionals used generative AI tools for in their work. We grouped these tasks under four roles: content editor, research assistant, ideation partner, or design assistant.
- Content editor : Generating and editing text, from microcopy to social media posts, based on specifications or copy given by UX
Mingjin Zhang • AI as a UX Assistant
Langfuse is an open source observability & analytics solution for LLM-based applications. It is mostly geared towards production usage but some users also use it for local development of their LLM applications.
Langfuse is focused on applications built on top of LLMs. Many new abstractions and common best practices evolved recently, e.g. agents,... See more
Langfuse is focused on applications built on top of LLMs. Many new abstractions and common best practices evolved recently, e.g. agents,... See more
langfuse • GitHub - langfuse/langfuse: Open source observability and analytics for LLM applications
core components of Deep RL that enabled success like AlphaGo: self-play and look-ahead planning.
Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion... See more
Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
These two components might be some of the most important ideas to improve all of AI.
🤖 Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
- Why CrewAI
- Getting Started
- Key Features
- Examples
- Local Open Source Models
- CrewAI x AutoGen x ChatDev
- Contribution
- 💬 CrewAI Discord Community
- Hire Consulting
- License
joaomdmoura • GitHub - joaomdmoura/crewAI: Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
The next-generation command line.
The source of truth for your team’s secrets, scripts, and SSH credentials.
The source of truth for your team’s secrets, scripts, and SSH credentials.
Fig
Setting up the necessary machine learning infrastructure to run these big models is another challenge. We need a dedicated model server for running model inference (using frameworks like Triton oder vLLM), powerful GPUs to run everything robustly, and configurability in our servers to make sure they're high throughput and low latency. Tuning the... See more
Developing Rapidly with Generative AI
📦 Service Deployment - Ray Serve (https://lnkd.in/eAV-Y6RN)
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Traces (https... See more
🧰 Data Transformation - Ray Data (https://lnkd.in/e7wYmenc)
🔌 LLM Integration - AIConfig (https://lnkd.in/esvH5NQa)
🗄 Vector Database - Weaviate (https://weaviate.io/)
📚 Supervised LLM Fine-Tuning - HuggingFace TLR (https://lnkd.in/e8_QYF-P)
📈 LLM Observability - Weights & Biases Traces (https... See more