Creating a Secure Machine Learning API with FastAPI and Docker
Machine learning models deliver real value only when they reach users, and APIs are the bridge that makes it happen. Source link
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Attention May Be All We Need… But Why?
A lot (if not nearly all) of the success and progress made by many generative AI models nowadays, especially large language models (LLMs), is due to the stunning capabilities of their underlying architecture: an advanced deep learning-based architectural model called…
Creating a Qwen-Powered Lightweight Personal Assistant
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How to Combine Pandas, NumPy, and Scikit-learn Seamlessly
Machine learning workflows require several distinct steps — from loading and preparing data to creating and evaluating models. Source link
Roadmap to Python in 2025
Python has evolved from a simple scripting language to the backbone of modern data science and machine learning. Source link
Custom Fine-Tuning for Domain-Specific LLMs
Fine-tuning a large language model (LLM) is the process of taking a pre-trained model — usually a vast one like GPT or Llama models, with millions to billions of weights — and continuing to train it, exposing it to new…
Agent-Based Debugging Gets a Cost-Effective Alternative: Salesforce AI Presents SWERank for Accurate and Scalable Software Issue Localization
Identifying the exact location of a software issue—such as a bug or feature request—remains one of the most labor-intensive tasks in the development lifecycle. Despite advances in automated patch generation and code assistants, the process of pinpointing where in the…
A Step-by-Step Guide to Build a Fast Semantic Search and RAG QA Engine on Web-Scraped Data Using Together AI Embeddings, FAISS Retrieval, and LangChain
In this tutorial, we lean hard on Together AI’s growing ecosystem to show how quickly we can turn unstructured text into a question-answering service that cites its sources. We’ll scrape a handful of live web pages, slice them into coherent…
Study shows vision-language models can’t handle queries with negation words | MIT News
Imagine a radiologist examining a chest X-ray from a new patient. She notices the patient has swelling in the tissue but does not have an enlarged heart. Looking to speed up diagnosis, she might use a vision-language machine-learning model to…
This AI Paper Investigates Test-Time Scaling of English-Centric RLMs for Enhanced Multilingual Reasoning and Domain Generalization
Reasoning language models, or RLMs, are increasingly used to simulate step-by-step problem-solving by generating long, structured reasoning chains. These models break down complex questions into simpler parts and build logical steps to reach answers. This chain-of-thought (CoT) approach has proven…