r/MachineLearning

r/MachineLearning - Reddit

RelatedHighlights

AutoGen's design offers multiple advantages: a) it gracefully navigates the strong but imperfect generation and reasoning abilities of these LLMs; b) it leverages human understanding and intelligence, while providing valuable automation through conversations between agents; c) it simplifies and unifies the implementation of complex LLM workflows as... See more

r/singularity - Reddit

Nicolay Gerold added

Chaining LLM Agents instead of LLM calls. Seems like a pretty heavy prompt engineering effort. They are pushing for agents that are specialized in a certain tasks through RAG / finetuning, where CAMEL and other frameworks failed. One interesting area for exploration might be finetuning LLMs for collaboration before finetuning them for tasks.

Renil added

What We Learned From a Year of Building With LLMs

Bryan Bischof oreilly.com

and added

Retrieval-Augmented Generation (RAG): A Technical AI Explainer

youtube.com

added

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]

Nicolay Gerold added

Where would I add generative AI? Generative AI has the ease of accessibility of traditional AI, where people think it is understandable, but it does not have that feature in itself. It also has the opaque and costly nature of DL. Many companies are at the moment rushing into developing things with generative AI without having any prior foundation in AI and any processes set up to manage it: data ops, devops, …

Traditional AI forces you to think about how something works, understand the system, and then define the rules for it. ML lets you use features and feature importance to shortcut some. Deep Learning allows you to brute force it. Generative AI allows you to brute force without any background in DL.

Some tasks are easier to improve via system design. While LLMs appear to follow remarkable scaling laws that predictably yield better results with more compute, in many applications, scaling offers lower returns-vs-cost than building a compound system. For example, suppose that the current best LLM can solve coding contest problems 30% of the time

Matei Zaharia, Omar Khattab, Lingjiao Chen, et al. • The Shift From Models to Compound AI Systems

Nicolay Gerold added

Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]

app.shortwave.com app.shortwave.com

Nicolay Gerold and added

Retrieval Augmented Generation and Reranking in Custom ChatGPT

Rafal Zawadzki chatwith.tools

Michael Iversen added