#45 Is Prompting a Future-Proof Skill?

Will the evolution of the generative AI landscape make today's tech stack irrelevant??

Good morning, AI enthusiasts! Over the past few months, we have discussed the AI engineer’s toolkit for building reliable LLM products multiple times. We believe that combining RAG, prompting, and fine-tuning will be key to developing scalable solutions with generative AI. As LLMs evolve, the implementation of these techniques will also change, but we believe the fundamentals will remain relevant for a long time, and that’s why we wrote ‘Building LLMs for Production’ as a foundational resource for teaching the core principles of building production products with LLMs.

What’s AI Weekly

This week, in my other newsletter, we explore a timely question: Is prompting a skill we need to master or just a temporary necessity? With the evolution of LLMs, we see a shift in how we interact with these models (i.e., from GPT-3 to GPT-4o and now o1). Prompting is still here, but its complexity may be short-lived. Let’s understand how the landscape is changing and what it means for those of us who work (or interact) with AI daily. Read the full article on Substack!?

— Louis-Fran?ois Bouchard, Towards AI Co-founder & Head of Community

Learn AI Together Community section!

AI poll of the week!

We are really eager to know where you find the most value when it comes to learning AI (related to code, best practices, usage, etc.) Share it with us in the 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. Gere030199 is looking for a full-stack developer to help build the MVP as a co-founder. You will create oauth2 Google, set up Stripe and PayPal subscriptions, create a streaming section, and help with ideas and strategies. If this sounds interesting, reach out in the thread!?

2. Visrix is looking for an audio-video specialist to help with UI/UX design, AWS configurations, and scaling as the platform grows. If you are interested in producing and optimizing audio and video content, connect in the thread!?

3. Oppyalex is looking for someone interested in AI agents and using GenAI for software development to build plugins for an AI coding assistant called OppyDev. If you are passionate about software engineering and want to work on an interesting project in your spare time, contact in the thread!?

Meme of the week!

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TAI Curated section

Article of the week

Highlighting and Annotating PDFs on UI Using Streamlit for Retrieval-Augmented Generation (RAG) by Anoop Maurya

This article outlines creating an AI-powered document assistant that can extract information from PDF documents using Retrieval-Augmented Generation (RAG) and Streamlit. It discusses the architecture of the system, detailing how RAG enhances the assistant's ability to retrieve relevant information and generate accurate responses based on user queries. The article provides step-by-step instructions for implementing the solution, including data preprocessing, indexing, and integrating the Streamlit interface for user interaction. Practical examples demonstrate the effectiveness of this approach in transforming static documents into interactive, query-responsive tools, showcasing potential applications in various domains such as education and business.

Our must-read articles

1. RAG: The Power of Text Splitting for Improving Retrieval: A Developer’s Handbook by Md Monsur ali

This article discusses the significance of text splitting in enhancing the performance of Retrieval-Augmented Generation (RAG) systems. It explains how breaking down large text documents into smaller, manageable segments can improve the efficiency and accuracy of information retrieval. It covers various text-splitting techniques and their impact on retrieval performance, providing practical examples and guidelines for developers. By illustrating the benefits of effective text segmentation, the article aims to equip developers with strategies to optimize RAG implementations, ultimately leading to better AI-driven outcomes.

2. Developing A Virtual Psychologist With Gen-AI by Ori Cohen

This article explores the creation of a virtual psychologist using generative AI technologies. It discusses the potential of AI to provide mental health support and therapy through conversational agents. It outlines the design and development process of the virtual psychologist, including integrating natural language processing and machine learning techniques to facilitate empathetic and context-aware interactions. It also addresses ethical considerations, such as privacy and the importance of human oversight in mental health applications. Through practical examples, the article highlights the transformative potential of AI in making psychological support more accessible and personalized.

3. Advancing Genetic Algorithms and Their Applications by Shenggang Li

The article explains the foundational principles of genetic algorithms, including selection, crossover, and mutation processes, and how these concepts evolve with new techniques and optimizations. It highlights real-world applications of GAs in areas such as optimization problems, machine learning, and engineering design. Practical examples and case studies illustrate the effectiveness of genetic algorithms in solving complex problems. It emphasizes the ongoing research to enhance their performance and applicability in modern technology.

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