drphilwinder

7 ms·

1.
by drphilwinder 10mo ago
This is a great point. Not that far. We also snapshot the desktop for "slow" non-streaming updates to the UI. We could push these into Claude itself to act on or describe or whatever.
2.
by drphilwinder 1y ago
Hi all. This is an announcement post for a project I'm looking to get very early feedback on. I've been using an AI coding assistant for a while (Cursor, Cline, etc.) and found that quite a few problems are caused by the model not
3.
EU AI Act Summary: Obligations and Exceptions for Businesses(winder.ai)
3 points by drphilwinder 2y ago|0 comments
4.
A Comparison of Open Source LLM Frameworks for Pipelining(winder.ai)
2 points by drphilwinder 2y ago|0 comments
5.
Testing and Evaluating Large Language Models in AI Applications(winder.ai)
1 points by drphilwinder 2y ago|0 comments
6.
by drphilwinder 2y ago
For me, one of the most important parts of the spec is formulation of the DAG of tasks. Whether that be calling other LLMs or some retrieval mechanism. What does everyone think about the pros/cons of a formal DAG specification vs using
7.
by drphilwinder 2y ago
Check out https://unify.ai/chat if you're interested in a router optimised for cost/ttft/performance for commercial language models.
8.
Build a Voice-Based Chatbot with OpenAI, Vocode, and ElevenLabs(winder.ai)
3 points by drphilwinder 2y ago|0 comments
9.
by drphilwinder 2y ago
Under the hood right now it's on-prem llama3 + a pretty basic RAG pipeline. The coolest thing about this technically is that it's all running totally privately. But the main goal is to make websites more efficient. To get your cus
10.
by drphilwinder 3y ago
Your sentiment is correct, but it's more of a spectrum. Fine tuning can learn facts (otherwise how would the foundation models learn facts?). But it needs those facts in the training dataset. If you have an infinite amount of facts, th