Preference Learning and Deep Reinforcement Learning (TD3) for Multi‑Manager Portfolio Strategy Selection
Author(s): Shenggang Li Originally published on Towards AI. From Human Manager Trajectories to a Unified Adaptive Allocation Policy via AHP‑Guided Preference Modeling and Actor–Critic Optimization Traditional asset allocation faces challenges in balancing multiple objectives: Photo by Markus Spiske on UnsplashThis article addresses …
Experiential Chain of Thought (E-CoT): A Framework for Self-Improving Reasoning via Segmented Experience Memory
Author(s): Marc Lopez Originally published on Towards AI. How AI can learn from its own successes and failures to reason more effectively. Large Language Models (LLMs) have shown an incredible ability to reason, largely thanks to techniques like Chain of Thought (CoT) …
Machine Bullshit: Why AI Systems Care More About Sounding Good Than Being Right
Author(s): MKWriteshere Originally published on Towards AI. Scientists just proved that making AI more helpful also makes it more deceptive — and the results are shocking Your AI assistant just told you that “studies suggest this laptop may provide enhanced performance benefits …
Important LLM Papers for the Week From 07/07 to 13/07
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Large Language Models Research Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers must stay informed about the latest …
Build Your Own AI Assistant with RAG: A Practical Guide for GenAI Engineers
Author(s): Aayushi_Sharma Originally published on Towards AI. Build Your Own AI Assistant with RAG: A Practical Guide for GenAI Engineers “How can I make ChatGPT answer questions from my own documents?” If you’ve ever wondered that, you’re in the right place. Welcome …
Introduction to Multimodality With LLaVA
Author(s): Marcello Politi Originally published on Towards AI. Learn how to implement multimodal AI on low-resource hardware In the last couple of years, I have worked mainly with large language models, training, fine-tuning, prompting and so on, since this was highly requested …
End-to-End Guide to Building and Deploying an MCP Server for AI Toolchains
Author(s): Vikram Bhat Originally published on Towards AI. Step-by-step guide to create, test, and deploy an MCP server using Python and FastMCP In the world of AI tooling and agent frameworks, one challenge remains consistent: how do we let LLMs interact with …
Generate Synthetic Data to Build Robust Machine Learning Models in Data Scares Scenario
Author(s): Kuriko Iwai Originally published on Towards AI. Explore statistical approaches to transform experts knowledge into data with practical examples Machine learning models need to be trained on sufficient, high-quality data that will recur in the future to make accurate predictions. Photo …
🤝 Quantifying Gain — A Data Scientist’s Intro To Information Theory — Part 5/5: Mutual Information
Author(s): Eyal Kazin PhD Originally published on Towards AI. Mutual Information made intuitive — with practical ML examples in Python. 🐍 This is the fifth and final article in our introductory series on quantifying information — a foundational framework for data scientists. …
Large Language Models as Classification Engines: Overkill, or Awesome?
Author(s): Katherine Munro Originally published on Towards AI. Why is it an odd choice? Why you should try it anyway. And how to go about it. Have you ever wanted to build a trillion-parameter labelling machine? And by that I mean, would …
AI in the Classroom: Create and Grade Assignments with ChatGPT
Author(s): Kseniia Baidina Originally published on Towards AI. Image by ChatGPT There are many articles about how students use ChatGPT to complete their assignments — and what professors should do about it. Personally, I think professors should encourage this (if you can’t …
Machine Learning at Scale: Why PySpark MLlib Still Wins in 2025
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Kevin Ku on Unsplash Machine learning may be glamorous when you’re tuning models on Kaggle datasets or demoing GPT wrappers. But in production? It’s a grind. You’re not just building a model. …
This 5-Step GenAI Interview Strategy Is Getting People Hired Fast
Author(s): Khushbu Shah Originally published on Towards AI. Most candidates don’t get rejected for weak AI skills, but they get rejected because they can’t design or explain how a GenAI system works in the real world. Most AI candidates don’t get rejected …
Prediction, Generation, or Inference? Matching Your Goal to the Right Data Tool
Author(s): Bushra Anjum, Ph.D. Originally published on Towards AI. Large Language Models (LLMs) are making headlines every day. At the same time, traditional machine learning (ML) and statistical methods are firmly holding their ground and continue to be used widely. So, which …
The Harsh Reality of AI Startup Funding: Only 23% Survive the Series A Transition
Author(s): Jitesh Prasad Gurav Originally published on Towards AI. Building an AI startup has never been more challenging. Recent research examining nearly 1,000 generative artificial intelligence companies reveals that only 22.6% successfully transition from seed to Series A funding rounds. This statistic …
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