LLM Evals, RAG Visual Walkthrough, and From Pixels to Words #29

Author(s): Towards AI Editorial Team

Originally published on Towards AI.

Good morning, AI enthusiasts! First, thank you for all the love you have been giving the book. For those who missed the updates, we now have it available as a paperback, e-book, and hardcover!

The next big step for us at TAI is helping you all stay ahead of the curve, and we are putting together a lot more resources keeping precisely that in mind. Our community is undoubtedly a great reflection of what’s happening in the industry, and this week is no different. We have some exciting creations, articles, collaborations, and more coming shortly!

What’s AI Weekly

Have you ever wondered how we can determine which LLM is superior exactly? Isn’t it just generating words and ideas? How can we know one is better than the other? This week, I am exactly answering that. Let’s understand how we can accurately quantify and evaluate the performance of these models, understand the current methodologies used for this, and discuss why this process is vital. Read the article here, or if you prefer the video format, check it out here!

— Louis-François Bouchard, Towards AI Co-founder & Head of Community

Learn AI Together Community section!

Featured Community post from the Discord

Notedance created a repository to make building and training neural networks easy. It contains many layer modules, which are implemented based on TensorFlow. The layer modules allow you to build neural networks in the style of PyTorch or Keras. You can not only use the layer modules to build neural networks trained on Note but also use them to build neural networks trained with TensorFlow. Check it out on GitHub and support a fellow community member. Ask your questions in the Discord thread!

AI poll of the week!

It’s evident that ChatGPT is still the most preferred LLM among users despite the development of other well-performing models. While we agree ChatGPT is a great general-purpose/multi-purpose assistant, would you prefer any other model for specialized tasks such as coding? Share your opinion in the Discord thread!

Collaboration Opportunities

The Learn AI Together Discord community is flooding with collaboration opportunities. If you are excited to dive into applied AI, want a study partner, or even want to find a partner for your passion project, join the collaboration channel! Keep an eye on this section, too — we share cool opportunities every week!

1. Shakthemack is looking for an AI expert to help test, optimize, and add features to their AI companion app. Their ultimate goal is to build an AI companion so good that it feels human. If you find this interesting and can help with the project, connect with him in the thread!

2. _socialbutterfly_ wants to participate in the Gemini API Developer Competition and is currently looking for other members to join the team. If you want to do this together and have some interesting ideas, reach out to him in the thread!

3. Raiscodes is looking for a study partner who wants to learn AI and improve their skills. If you are also starting your AI journey, contact them in the thread!

Meme of the week!

Meme shared by bin4ry_d3struct0r

TAI Curated section

Article of the week

From Pixels to Words: How Model Understands? by Jaiganesan

This article explores multi-modal models, where numerical representations of different data types come together to achieve a common goal. Specifically, it explores how image feature representations are understood through text descriptions and how embeddings from different modalities are used to achieve the objective of a model or use case.

Our must-read articles

1. Retrieval Augmented Generation (RAG): A Comprehensive Visual Walkthrough by Jaiganesan

The article examines the problems RAG solves and how it addresses the limitations of traditional models like LLMs. It also dives into the inner workings of the RAG architecture, its mechanism, and how it generates content. It will help you clearly understand RAG and its potential to transform how we generate content.

2. Creativity in Language Models by Sushil Khadka

If you’ve used any generative AI models such as GPT, Llama, etc., there’s a good chance you’ve encountered the term ‘temperature.’ Temperature is a parameter that controls the creativity of generated content. This post explains temperature in generative AI models, especially LLMs, and mathematically shows how it works and powers creativity in these models.

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Published via Towards AI