Saved by sari
ML Infrastructure Tools for Model Building
However development time, and maintenance can offset these savings. Hiring skilled data scientists, machine learning engineers, and DevOps professionals can be expensive and time consuming. Using available resources for “reimplementing” solutions hinder innovation and lead to a lack of focus. Since You not longer work on improving your model or pro... See more
Understanding the Cost of Generative AI Models in Production
Building a Knowledge base for custom LLMs using Langchain, Chroma, and GPT4All
cismography.medium.com
- Traditional AI - The most secure, understandable, and performant. However, Good implementations of traditional AI require that we define the rules behind the system, which makes it unfeasible for many of the use cases that the other 2 techniques thrive on.
- Supervised Machine Learning- Middle of the road b/w AI and Deep Learning. Good when we have
Devansh • How to Pick between Traditional AI, Supervised Machine Learning, and Deep Learning [Thoughts]
When selecting your first AI/ML project, focus on three key factors: data availability, process characteristics, and impact.
Ben Dickson • How to choose the first machine learning project for your organization
Models All The Way Down
knowingmachines.org