LLMs
The AI engineering framework
Marvin is a lightweight AI engineering framework for building natural language interfaces that are reliable, scalable, and easy to trust.
Sometimes the most challenging part of working with generative AI is remembering that it's not magic; it's software. It's new, it's nondeterministic, and it's incredibly powerful - but... See more
Marvin is a lightweight AI engineering framework for building natural language interfaces that are reliable, scalable, and easy to trust.
Sometimes the most challenging part of working with generative AI is remembering that it's not magic; it's software. It's new, it's nondeterministic, and it's incredibly powerful - but... See more
PrefectHQ • GitHub - PrefectHQ/marvin: ✨ Build AI interfaces that spark joy
- Query the RAG anyway and let the LLM itself chose whether to use the the RAG context or its built in knowledge
- Query the RAG but only provide the result to the LLM if it meets some level of relevancy (ie embedding distance) to the question
- Run the LLM both on it's own and with the RAG response, use a heuristic (or another LLM) to pick the best answer
r/LocalLLaMA - Reddit
Announcing Together Inference Engine – the fastest inference available
November 13, 2023・By Together
The Together Inference Engine is multiple times faster than any other inference service, with 117 tokens per second on Llama-2-70B-Chat and 171 tokens per second on Llama-2-13B-Chat
Today we are announcing Together Inference Engine, the world’s... See more
November 13, 2023・By Together
The Together Inference Engine is multiple times faster than any other inference service, with 117 tokens per second on Llama-2-70B-Chat and 171 tokens per second on Llama-2-13B-Chat
Today we are announcing Together Inference Engine, the world’s... See more
Announcing Together Inference Engine – the fastest inference available
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
GitHub - ai-hero/llm-research-fine-tuning
Generative AI can automate simple tasks
By automating simpler, tedious tasks (generating boilerplate code, fixing linter errors, generating unit tests, etc.), generative AI can help engineers focus on more complex tasks.
Generative AI can improve quality & reliability
Since generative AI models are trained on large codebases, they have the potential... See more
By automating simpler, tedious tasks (generating boilerplate code, fixing linter errors, generating unit tests, etc.), generative AI can help engineers focus on more complex tasks.
Generative AI can improve quality & reliability
Since generative AI models are trained on large codebases, they have the potential... See more
Adam Huda • The Transformative Power of Generative AI in Software Development: Lessons from Uber's Tech-Wide Hackathon
The multiple cantilevered AI overhangs:
Compute overhang. We have much more compute than we are using. Scale can go much further.
Idea overhang. There are many obvious research ideas and combinations of ideas that haven’t been tried in earnest yet.
Capability overhang. Even if we stopped all research now, it would take ten years to digest the new... See more
Compute overhang. We have much more compute than we are using. Scale can go much further.
Idea overhang. There are many obvious research ideas and combinations of ideas that haven’t been tried in earnest yet.
Capability overhang. Even if we stopped all research now, it would take ten years to digest the new... See more

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