Large Language Models: How Large is Large Enough?

Показать описание

When it comes to large language models, one of the first things you may read about is the enormous size of the model data or the number of parameters. But is "bigger" always better? In this video, Kip Yego, Program Marketing Manager explains that the truthful answer is "It depends". So what are the factors that will drive this decision? Kip breaks them down and explains one-by-one how to decide.

#llm #ai #generativeai #ml

Рекомендации по теме

Комментарии

These videos are fantastic!
Thank you so much for making them available :D

thatdudewiththething

Well done video, Get kip to more of these please.

dominiquecoladon

Thank you, this is the information I was searching for. I was explaining the concept in theory to someone. The idea was to use smaller models that are trained for specific domains. By eliminating or reduce all the other domains, the model should perform better and reduce messy results.

ttjordan

Great video Kip!

At the moment it seems that bigger equals better. Time to change that perception accordingly

YvesNewman

Thank you, that was informative. One question I have is how you determine domain specificity, and perhaps potential lost opportunity?
For example, using financial services tasks as in your example. If you ask someone working in finance about what insights they'd be looking for, tax or perhaps transfer pricing may not be what they consider as part of their domain. However, transfer pricing and tax could have a huge impact on what finance should consider when taking decisions. How do you ensure the domain specificity is not too narrow?

rich

The MBA in me says, beyond some point, the trade-off isn't worth it. Then again, that's probably what they said about the Apollo mission.

gjjakobsen

5:38 THANK YOU BRO. Definitely feel more confident after hearing that.

Alice

How can we find a domain specific models or how to train them?

nirmal

My llm's so large, it reaches almost every 1 and 0 it can write on; you can literally call it a "wipe"

IsaacFoster..

I see no point whatsoever in comparing a domain specific finetuned model to a non finetuned model to draw conclusions or suggest any insights doing this.

aberobwohl

bro you got worse handwriting than me!!! Good info though. lol

Alice

Large Language Models: How Large is Large Enough?

How Large Language Models Work

How large language models work, a visual intro to transformers | Chapter 5, Deep Learning

[1hr Talk] Intro to Large Language Models

Introduction to large language models

Large Language Models (LLMs) - Everything You NEED To Know

What are Large Language Models (LLMs)?

Introduction to Large Language Models

Large Language Models: How Large is Large Enough?

Large Language Models from scratch

Large Language Models Explained | What Is Large Language Model (LLM) | Machine Learning |Simplilearn

A Practical Introduction to Large Language Models (LLMs)

Can Large Language Models Understand Meaning?

The Epic History of Large Language Models (LLMs) | From LSTMs to ChatGPT | CampusX

Large Language Models: Aufbau, Anwendung & Nutzen

Foundation Models vs. Large Language Models Explained

What's the difference between Large Language Models (LLMs) and Generative AI?

How Chatbots and Large Language Models Work

Why Large Language Models Hallucinate

A Complete Look at Large Language Models

What is an LLM (Large Language Model)?

What are Generative AI models?

Inside GPT – Large Language Models Demystified • Alan Smith • GOTO 2024

simpleshow explains: Generative AI, Large Language Models and ChatGPT

Beyond the Hype: A Realistic Look at Large Language Models • Jodie Burchell • GOTO 2024