Building a Screen-Aware AI with ScreenEnv and Tesseract
Learn how to build screen-aware AI using ScreenEnv and Tesseract for dynamic, real-time screen content
ADaSci Expert
Sachin Tripathi
Sachin Tripathi is the Manager of AI Research at AIM, with over a decade of experience in AI and Machine Learning. An expert in generative AI and large language models (LLMs), Sachin excels in education, delivering effective training programs. His expertise also includes programming, big data analytics, and cybersecurity. Known for simplifying complex concepts, Sachin is a leading figure in AI education and professional development.
The CXO’s Role in Building Agentic AI-Ready Talent
CXOs must lead talent transformation to build Agentic AI-ready teams through upskilling, mentoring, and applied
Redefining Governance, Risk and Compliance for AI Systems with GRC 2.0
As AI systems become more autonomous, organizations face new governance and compliance challenges. This article
Chartered Data Scientist (CDS™)
The highest distinction in the data science profession. Not just earn a charter, but use it as a designation.
Hands-on Guide to LLM Caching with LangChain to Boost LLM Responses
LLM caching in LangChain addresses deployment challenges by storing and reusing generated responses.
Implementing RAG Pipelines using LightRAG and GPT-4o mini
LightRAG simplifies and streamlines the development of retriever-agent-generator pipelines for LLM applications.
A Hands-on Guide to llama-agents: Building AI Agents as Microservices
Discover the power of llama-agents: a comprehensive framework for creating, iterating, and deploying efficient multi-agent
RAVEN for Enhancing Vision-Language Models with Multitask Retrieval-Augmented Learning
RAVEN enhances vision-language models using multitask retrieval-augmented learning for efficient, sustainable AI.
Lightweight Text Extraction with NuExtract – A Deep Dive
NuMind’s NuExtract model for zero-shot or fine-tuned structured data extraction.
A Comprehensive Hands-on Guide to Deep Lake Lakehouse for RAG
Deep Lake: an advanced lakehouse for efficient AI data storage and retrieval, perfect for RAG
Hands-on Guide to Vision Language Tasks using Microsoft’s Florence-2
Explore Microsoft’s Florence-2: Unifying vision and language tasks with prompt-based AI integration.
A Comprehensive Guide to Vector Databases and their Utilities
Compare and contrast between different vector databases and understand their utilities.
Diving into AutoGen Studio for Building Multi-Agent Systems
Discover Microsoft’s AutoGen Studio for easy multi-agent system development and deployment.
Nvidia’s Nemotron-4 340B for Synthetic Data Generation
Discover Nvidia’s Nemotron-4 340B models, revolutionising synthetic data generation and LLM training challenges.
