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.
A Deep Dive into ElasticSearch and Kibana’s Semantic Capabilities
ElasticSearch’s vector search capabilities enable intelligent, context-aware applications through AI-powered semantic understanding.
A Practitioner’s Guide on Inferencing over 1-bit LLMs using bitnet.cpp
Explore 1-bit LLMs and bitnet.cpp for faster, efficient inferencing in large language models.
A Hands-on Guide to Airtrain AI: A No-code Compute Platform
Airtrain AI simplifies LLM fine-tuning with a no-code interface and high-quality models.
Multi-agent Orchestration through OpenAI’s Swarm – A Hands-on Guide
OpenAI’s Swarm framework explores multi-agent orchestration, showcasing simple routines and handoffs in action.
MongoDB Atlas Vector Search for RAG powered LLM Applications
MongoDB Atlas Vector Search combines document databases with semantic search for smarter LLM applications.
A Hands-on Guide on CometLLM for LLM Explainability
CometLLM enhances LLM explainability through prompt logging, tracking, and visualization, facilitating transparency and reproducibility in
A Hands-on Guide to Arize Phoenix for LLM Observability
Robust monitoring and observability tool Arize AI’s Phoenix aids LLM deployment and optimization.
AnythingLLM for Local Execution and Inferencing of LLMs: A Deep Dive
AnythingLLM excels in local execution of LLMs, offering robust features for secure, no-code LLM usage.
LangGraph Studio for Implementing AI Agents: A Hands-on Guide
Explore LangGraph Studio, the first AI agent IDE that simplifies agent visualization, interaction and debugging
Building RAG-Powered LLM Applications with LlamaIndex Workflows
LlamaIndex workflows enable flexible RAG-powered LLM applications, surpassing traditional DAG-based approaches.
