Volga — On-Demand Compute in Real-Time AI/ML — Overview and Architecture
Author(s): Andrey Novitskiy Originally published on Towards AI. TL;DR Volga is a real-time data processing/feature calculation engine tailored for modern AI/ML. It is designed to support various types of features, including streaming (online), batch (offline), and on-demand features, via a hybrid push+pull …
The Power of Less: How Chain of Draft Makes AI Reasoning Faster and Cheaper
Author(s): MKWriteshere Originally published on Towards AI. In today’s AI landscape, large language models (LLMs) like GPT-4 and Claude can solve complex problems with impressive accuracy. But this capability comes at a cost, both in processing time and computational resources. What if …
Revolutionizing AI Deployment: How Automated LLMOps is Powering the Future of Intelligent Systems
Author(s): Rajarshi Tarafdar Originally published on Towards AI. Increased sophistication in artificial intelligence necessitates an appropriate development of an operational infrastructure framework. Large Language Model Operations (LLMOps) functions as a crucial operating system designed to manage the entire lifecycle process of large …
Custom dataset with Hailo AI Hat, Yolo, Raspberry PI 5, and Docker
Author(s): Luiz doleron | Luiz d’Oleron Originally published on Towards AI. The Hailo AI Hat Depending on your setup, running Yolo on the RPI 5 CPU provides 1.5 to 8 frames per second (FPS). Even though this performance is impressive for a …
Can Traditional LSTMs Trained From Scratch Compete With Fine-Tuned BERT Models?
Author(s): S Aishwarya Originally published on Towards AI. In today’s digital era, fake news spreads faster than the truth, and the consequences can be serious. From influencing elections to spreading health misinformation, tackling fake news is more important than ever. Fake news …
MCP with PydanticAI
Author(s): Barrett Studdard Originally published on Towards AI. Building a basic MCP server and interacting with PydanticAICredit to Kenny Eliason on Unsplash In my prior article on building a streaming approach with Pydantic AI, I built a pattern around streaming with API …
Is This the Future of Financial Analysis? RAG & Multi-Agent Systems Explained
Author(s): Saurab Originally published on Towards AI. The modern financial sector is drowning in data. The large volume and complexity are exploding, overwhelming traditional analysis methods. Quickly and accurately extracting insights from this digital ocean isn’t just an advantage anymore — it’s …
Deploy an in-house Vision Language Model to parse millions of documents: say goodbye to Gemini and OpenAI.
Author(s): Jeremy Arancio Originally published on Towards AI. TL;DR: We deployed an AI feature to extract structured data from documents (e.g., invoices, reports) using Qwen-2.5-VL and vLLM — no training nor data collection needed. The solution is containerized with Docker and uv, …
TAI#149: OpenAI’s Agentic o3; New Open Weights Inference Optimized Models (DeepMind Gemma, Nvidia Nemotron-H)
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, OpenAI finally released its anticipated o3 and o4-mini models, shifting the focus towards AI agents that skillfully use tools. DeepMind also made …
DeepSeek-V3 Explained Part 4: Multi-Token Prediction
Author(s): Nehdiii Originally published on Towards AI. Vegapunk №04 One Piece Character Generated with ChatGPT This is the fourth article in our DeepSeek-V3 series, where we explain the final major architectural innovation in DeepSeek [1, 2] models: multi-token prediction. In previous articles, …
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