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When we meet a new technology – LLM Applications – some of us tend to jump right in, sleeves rolled up, ready to start tinkering. Others choose a more cautious approach: reading a few research papers, or browsing through dozens of blog posts, with the aim of understanding the context in which these tools appeared.
This week's featured articles come with a decided “Why not?” Attitude towards AI agents, LLMS, and their day-to-day use cases. They highlight the importance of understanding complex systems from the ground up, but also insist on a great mix of theory with possible and detailed Pragmatic Insight. If a hybrid learning strategy sounds promising, read it – we think you'll find it rewarding.
Agentic AI from scratch: A demonstration
With a strong understanding of agentic ai, Mariya Mansurova describes a comprehensive assessment of their key elements and creative patterns. His deep dive zooms in on the display, moving on from frameworks that exist in the initial implementation of text-based operations to SQL that includes tight loops.
It doesn't need to be a chatbot
For Janna Liperkova, successful AI integrations differ from those that have failed in one important way: they are built with a concrete understanding of the value AI Solutions can truly add.
What does “Thinking” and “Reasoning” really mean in AI and LLMS
To see how LLMS works – and why it's important to understand their limitations in order to work on their latest use – don't miss the latest Maria Mouschoutzi Changer.
This week's most read stories
Don't miss the articles that made the biggest splash in our community last week.
Deep learning: 0 to 100, by vedant jum
Using dirty skills with neo4J, by Tomaz Bratanic
Farkwork's power is great: What qualified scientists need to know, by Chinmay Kakatkar
Some recommended reading
Here are a few stand-up stories we're looking to put on your radar.
- From classical models to AI: predicting energy consumption and water performance in data centers, by Theophano Mitsa
- Bringing visual linguistics to ColPali, by Julian Yip
- Why should we care about quantum computing in ML?: By Erika G. Gonçalves
- Measuring transform transformers to a billion parameters, by Kirill КHrrylchenko
- Data interpretation explained (Part 4): Essential Python review, by Murtaza Ali
Meet our new writers
We hope you take the time to check out the excellent work from TDS Antwerp's latest cohort:
- Ibrahim Salami kicks things off with stellar, the first nunpy tutorial friendly series.
- Dmitry Lesnik shared a logic-based algorithm with couteimational logic and how it can be applied to the arrangement of state vectors.
Whether you're an existing or new author, we'd love to take a look at your next article – so if you've recently written an interesting project walkthrough, tutorial, or theoretical reflection on any of our main topics, why not share it with us?
