Identifying Generative AI Opportunities for Your Enterprises
Author(s): Leapfrog Technology Originally published on Towards AI. In the ever-evolving landscape of technology, businesses are constantly seeking ways to stay ahead of the curve. One of the most transformative technologies of our time is Artificial Intelligence (AI). At Leapfrog Technology Inc., …
Vector Search Techniques for AI in Pinecone
Author(s): Leapfrog Technology Originally published on Towards AI. Written by Aayush Karn & Aayush Shrestha In the fast-evolving world of Artificial Intelligence (AI) and Generative AI, understanding the nuances of various search techniques is crucial. Our previous blogs introduced the concept of …
Key Steps to Prepare Your Enterprise for AI Integration
Author(s): Leapfrog Technology Originally published on Towards AI. Artificial Intelligence (AI) is transforming industries by enhancing efficiency, fostering innovation, and providing competitive advantages. As businesses seek to integrate AI into their operations, understanding the necessary steps and strategies becomes essential. In this …
Evaluating Large Language Models: What, Why, and How for Chatbots
Author(s): Shivang Doshi Originally published on Towards AI. Introduction In the age of AI chatbots and conversational assistants, one question often gets overlooked amid the excitement: How do we evaluate these large language models (LLMs)? You might have a state-of-the-art model powering …
Comparing Four Time Series Forecasting Methods: Prophet, DeepAR, TFP-STS, and Adaptive AR
Author(s): Shenggang Li Originally published on Towards AI. A practical evaluation of models from Meta, Amazon, Google, and a new adaptive AR approach Time series forecasting is everywhere — in business, finance, retail, and even public policy. The challenge is simple to …
AI Creating Everyone’s Digital Twin
Author(s): Akhilesh Kulkarni, Ph.D. Originally published on Towards AI. AI Creating Everyone’s Digital Twin One day, you might wake up to find another version of yourself, not in the mirror, not across the room, but in the digital world. What once felt …
Risk-Adjusted Returns with Python (Part 1): The Treynor Ratio
Author(s): Siddharth Mahato Originally published on Towards AI. “Risk comes from not knowing what you’re doing.” — Warren Buffett Most investors chase returns. But ask any seasoned fund manager, and you’ll hear a different question:“Am I being rewarded fairly for the risks …
We’ve Been Measuring AI Reasoning All Wrong. Here’s How to Fix It.
Author(s): Kaushik Rajan Originally published on Towards AI. A new research paper reveals how we can teach language models to actually think, not just guess the right answer. Imagine a math student who consistently aces every test. You’re impressed. But one day, …
How REFRAG Delivers 30× Faster RAG Performance in Production
Author(s): MKWriteshere Originally published on Towards AI. Intelligent context compression reduces latency and infrastructure costs for development teams If you’ve ever built a Retrieval-Augmented Generation system, you know the pain. Your chatbot pulls 20 relevant documents, feeds them to your LLM, and …
XAI: Graph Neural Networks
Author(s): Kalpan Dharamshi Originally published on Towards AI. What are Graph Neural Networks? Graph Neural Networks (GNNs) combine the representational power of neural networks with the complex structure of graphs. Deep neural networks, particularly those leveraging a multi-head attention framework, excel at …
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