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What are Large Language Models? What are they not?

What are Large Language Models? What are they not?

This is a high-level, introductory article about Large Language Models (LLMs), the core technology that enables the much-en-vogue chatbots as well as other Natural Language Processing (NLP) applications. It is directed at a general audience, possibly with some technical and/or scientific background, but no knowledge is assumed of either deep learning or NLP. Having looked at major model ingredients, training workflow, and mechanics of output generation, we also talk about what these models are not

Sigrid Keydana

Jun 20, 2023

Best Practices Artificial Intelligence Ai Meta Concepts Natural Language Processing

blog post

Deep Learning and Scientific Computing with R torch: the book

Deep Learning and Scientific Computing with R torch: the book

Please allow us to introduce Deep Learning and Scientific Computing with R torch. Released in e-book format today, and available freely online, this book starts out by introducing torch basics. From there, it moves on to various deep-learning use cases. Finally, it shows how to use torch for more general topics, such as matrix computations and the Fourier Transform

Sigrid Keydana

Apr 5, 2023

Machine Learning Best Practices Ai Torch Meta Concepts Packages Releases

blog post

Beyond alchemy: A first look at geometric deep learning

Beyond alchemy: A first look at geometric deep learning

Geometric deep learning is a “program” that aspires to situate deep learning architectures and techniques in a framework of mathematical priors. The priors, such as various types of invariance, first arise in some physical domain. A neural network that well matches the domain will preserve as many invariances as possible. In this post, we present a very conceptual, high-level overview, and highlight a few applications

Sigrid Keydana

Aug 26, 2021

Best Practices Ai Concepts Meta

blog post

Starting to think about AI Fairness

The topic of AI fairness metrics is as important to society as it is confusing. Confusing it is due to a number of reasons: terminological proliferation, abundance of formulae, and last not least the impression that everyone else seems to know what they’re talking about. This text hopes to counteract some of that confusion by starting from a common-sense approach of contrasting two basic positions: On the one hand, the assumption that dataset features may be taken as reflecting the underlying concepts ML practitioners are interested in; on the other, that there inevitably is a gap between concept and measurement, a gap that may be bigger or smaller depending on what is being measured. In contrasting these fundamental views, we bring together concepts from ML, legal science, and political philosophy

Sigrid Keydana

Jul 15, 2021

Best Practices Ai Concepts Meta Society

blog post

First mlverse survey results – software, applications, and beyond

First mlverse survey results – software, applications, and beyond

Last month, we conducted our first survey on mlverse software, covering topics ranging from area of application through software usage to user wishes and suggestions. In addition, the survey asked about thoughts on social impacts of AI/ML. This post presents the results, and tries to address some of the things that came up

Introducing: The RStudio AI Blog

This blog just got a new title: RStudio AI Blog. We explain why

So, how come we can use TensorFlow from R?

Have you ever wondered why you can call TensorFlow - mostly known as a Python framework - from R? If not - that’s how it should be, as the R packages keras and tensorflow aim to make this process as transparent as possible to the user. But for them to be those helpful genies, someone else first has to tame the Python

Sigrid Keydana

Aug 29, 2019

keras3 Machine Learning Best Practices Ai TensorFlow Keras Meta Concepts

blog post

Math, code, concepts: A third road to deep learning

Math, code, concepts: A third road to deep learning

Not everybody who wants to get into deep learning has a strong background in math or programming. This post elaborates on a concepts-driven, abstraction-based way to learn what it’s all about

Sigrid Keydana

Mar 15, 2019

keras3 Best Practices Ai Meta Concepts