and medium companies achieve success in building Data and ML platforms, building AI platforms is now profoundly challenging. This post discusses three key reasons why you should be cautious about building AI platforms and proposes my thoughts on promising directions instead. Disclaimer: It is based on personal views and does not apply to cloud providers …
Stop Building AI Platforms | Towards Data Science Read More »
Image by Author Claude Opus 4 is Anthropic’s most advanced and powerful AI model to date, setting a new benchmark for coding, reasoning, and long-running tasks. It can autonomously handle complex, multi-hour tasks, maintaining focus and delivering exceptional results over thousands of steps. In this tutorial, we will learn how to use Claude Opus …
Today, Eliza McNitt’s short film, “ANCESTRA,” premieres at the Tribeca Festival. It’s the story of a mother, and what happens when her child is born with a hole in its heart. Inspired by the dramatic events of McNitt’s own birth, the film portrays a mother’s love as a cosmic, life-saving force. This is the first …
combining generative AI with live-action filmmaking Read More »
of activity in the AI world over the last few weeks, a recent important announcement by Streamlit that it now supports OpenID Connect (OIDC) login authentication almost passed me by. User authorisation and verification can be a crucial consideration for data scientists, machine learning engineers, and others involved in creating dashboards, machine learning proofs of …
User Authorisation in Streamlit With OIDC and Google Read More »
Sponsored Content Recommender systems rely on data, but access to truly representative data has long been a challenge for researchers. Most academic datasets pale in comparison to the complexity and volume of user interactions in real-world environments, where data is typically locked away inside companies due to privacy concerns and commercial value.That’s …
Bridging the Gap: New Datasets Push Recommender Research Toward Real-World Scale Read More »
, I wrote an article about the theory (and some applications!) of density estimation, and how it is a powerful tool for a variety of methods in statistical analysis. By overwhelmingly popular demand, I thought it may be interesting to use density estimation to derive some insight on some interesting data — in this case, data related …
Applications of Density Estimation to Legal Theory Read More »
Image by Author DeepSeek-R1-0528 is the latest update to DeepSeek’s R1 reasoning model that requires 715GB of disk space, making it one of the largest open-source models available. However, thanks to advanced quantization techniques from Unsloth, the model’s size can be reduced to 162GB, an 80% reduction. This allows users to experience the full …
in an enterprise organization, you’ve probably felt the paradox firsthand. AI dominates your strategic decks, fills your review meetings, and weaves into roadmap discussions. However, when you actually try to turn these AI visions into practical solutions, you’re often left wondering: What’s actually working? Where do we start to see measurable value of AI? Right …
Not Everything Needs Automation: 5 Practical AI Agents That Deliver Enterprise Value Read More »
Image by Author | Canva When it comes to error handling, the first thing we usually learn is how to use try-except blocks. But is that really enough as our codebase grows more complex? I believe not. Relying solely on try-except can lead to repetitive, cluttered, and hard-to-maintain code. In this article, I’ll walk …
5 Error Handling Patterns in Python (Beyond Try-Except) Read More »
is magical — until you’re stuck trying to decide which model to use for your dataset. Should you go with a random forest or logistic regression? What if a naïve Bayes model outperforms both? For most of us, answering that means hours of manual testing, model building, and confusion. But what if you could automate the entire …
How I Automated My Machine Learning Workflow with Just 10 Lines of Python Read More »
