Perhaps this[0] will help in understanding them then:
Foundations of Large Language Models
This is a book about large language models. As indicated by
the title, it primarily focuses on foundational concepts
rather than comprehensive coverage of all cutting-edge
technologies. The book is structured into five main
chapters, each exploring a key area: pre-training,
generative models, prompting, alignment, and inference. It
is intended for college students, professionals, and
practitioners in natural language processing and related
fields, and can serve as a reference for anyone interested
in large language models.
My apologies for being unclear and/or insufficiently explaining my position. Thank you for bringing this to my attention and giving me an opportunity to clarify.
The original post stated:
Since LLMs and in general deep models are poorly understood ...
This is demonstrably wrong.
The person having the account name "__float" replied to my post thusly:
That doesn't mean we _understand_ them, that just means we
can put the blocks together to build one.
That doesn't mean we _understand_ them ...
.. can serve as a reference for anyone interested in large
language models.
>> This is demonstrably wrong.
> That doesn't mean we _understand_ them ...
The previous reply discussed the LLM portion of the original sentence fragment, whereas this post addresses the "deep model" branch.
This article[0] gives a high-level description of "deep learning" as it relates to LLM's. Additionally, this post[1] provides a succinct definition of "DNN's" thusly:
What Is a Deep Neural Network?
A deep neural network is a type of artificial neural
network (ANN) with multiple layers between its input and
output layers. Each layer consists of multiple nodes that
perform computations on input data. Another common name for
a DNN is a deep net.
The “deep” in deep nets refers to the presence of multiple
hidden layers that enable the network to learn complex
representations from input data. These hidden layers enable
DNNs to solve complex ML tasks more “shallow” artificial
networks cannot handle.
Hopefully the above helps demystify this topic.
0 - https://mljourney.com/is-llm-machine-learning-or-deep-learni...
1 - https://medium.com/@zemim/deep-neural-network-dnn-explained-...
2 - https://learn.microsoft.com/en-us/dotnet/machine-learning/de...
3 - https://www.sciencenewstoday.org/deep-learning-demystified-t...