Learn AI Together — Towards AI Community Newsletter #16

Author(s): Towards AI Editorial Team

Originally published on Towards AI.

Good morning, AI enthusiasts! This week, we curated some exciting discussions, opportunities, and resources from the community. Diving first into the current What’s AI series covering the impact of AI in today’s industries. Enjoy the read!

What’s AI Weekly

Today, AI can analyze medical scans of your body with an accuracy that often outperforms professionals. It can transform radiologists’ work, making diagnosing conditions like multiple sclerosis easier and more precise, and this is just the tip of the iceberg of AI’s potential in healthcare. This week in What’s AI Weekly, Louis-François Bouchard explores the future of AI in healthcare. AI will make healthcare more accessible and cheaper, enhance diagnostic precision, personalize patient care, streamline administrative processes, save professionals’ time, save lives, and much more. This video and article are a product of discussions with medical AI experts, including Mona Flores, head of Medical AI at NVIDIA and previous chief medical officer and certified cardiac surgeon, who gave me amazing real-world examples of how AI is currently being used from the nearby hospital up to your wrist if you’re using a smartwatch!

Tune in on YouTube or read the complete article here!

Learn AI Together Community section!

Featured Community post from the Discord

Asad_182 developed Basiclingua, a Gemini LLM-based Python library that provides functionalities for linguistic tasks such as tokenization, stemming, lemmatization, and more. It can solve a wide range of NLP tasks for developers, covering everything from pattern extraction to OCR text extraction. It aims to tackle the increasing complexity and difficulty of handling text data as its size and complexity increase. Check it out on GitHub and support a fellow community member. Share your questions and feedback in the thread!

AI poll of the week!

Seeing that our community has successfully navigated through ChatGPT’s capabilities is exciting. We would love to hear some tips on how to get there; share them 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. Heyy_99963 needs help to create a chat WebUI GPT. The design is ready, but they are facing an error in the code. If you can help fix the code, reach out to them in the thread!

2. Patsch05 is looking for a beginner-intermediate learning group to study AI and ML concepts. If you are a developer or an advanced learner, you can join the thread and help the community members learn faster.

3. Axer128 is hiring programming / AI interns to join an AI-enhanced dating platform. The primary responsibility is to assist in developing slick, performant user interfaces using HTML5, C++, Java, JavaScript, and Python and working alongside other developers to integrate your work. Find more information in the thread!

Meme of the week!

Meme shared by rucha8062

TAI Curated section

Article of the week

LangChain SQL Agent for Massive Documents Interaction by Ruben Aster

Aggregation Queries and Data Relationship Exploration are some questions that cannot be solved just with RAG. Instead, we need to leverage LangChain’s SQL Agent to generate complex database queries from human text. In this article, the author explains the steps to finally ask complex questions about an extensive collection of documents.

Our must-read articles

1. From Code to Cloud: Building CI/CD Pipelines for Containerized Apps by Afaque Umer

This blog will demystify CI/CD, explore its role in data science, and discover how it can elevate your projects to new heights. We’ll learn how to tame the beast of CI/CD for our projects, using Streamlit to navigate the frontend (think of it as our trusty GPS), GitHub Actions to automate like clockwork, and Docker Hub for containerized deployments.

2. RAG-based Job Search Assistant by Kyosuke Morita

Despite LLMs’ powerful performance, one of their shortcomings is that their knowledge is limited to the data they have learned in training. To address that challenge, two primary methods exist to inject new knowledge into LLMs. This post demonstrates how to create a RAG-based job search assistant using LlamaIndex.

3. From Data Science to Production: Generating API Documentation with Swagger by Wencong Yang

This article is a tutorial on utilizing Swagger UI for Python API services, specifically those written with the Tornado web framework. It will also demonstrate the application of Swagger UI in a real-world data science project scenario.

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