Meta’s Gaia2 Test of AI Agents Real World Readiness
Meta’s Gaia2 benchmark is redefining AI evaluation. It assesses agents’ real-world readiness by testing adaptability,
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.
A Deep Dive into Open-Source AI Researcher Tongyi DeepResearch
What if an open-source AI agent could rival proprietary giants like OpenAI in complex web-based
Hands-On Guide on Teable Turning Data into Action
Teable is an AI-powered database agent that transforms raw data into insights, workflows, and apps,
Chartered Data Scientist (CDS™)
The highest distinction in the data science profession. Not just earn a charter, but use it as a designation.
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.
Implementing RAG over Excel Sheets through LlamaIndex
Using LlamaIndex and LlamaParse for RAG implementation by preparing Excel data for LLM applications.
Stability.ai’s Stable Audio Open: A Text-to-Audio Generation Model
Stability.ai’s new Stable Audio Open generates audio from text prompts, enhancing creative possibilities in sound
Hands-On Guide to Running LLMs Locally using Ollama
Explore how Ollama enables local execution of large language models for enhanced privacy and cost
Thought-Augmented Reasoning through Buffer of Thoughts (BoT)
Enhance the robustness and accuracy of LLM through thought-augmented reasoning based on the Buffer of
Observing and Examining AI Agents through AgentOps
Explore how AgentOps monitors, debugs, and tracks costs for LLM-based AI agents in various contexts.
Self-Organising File Management Through LlamaFS
Implement LlamaFS, an AI-driven file management system, based on Llama3 and Groq.
GNN-RAG: Enhancing the Reasoning Capabilities of LLMs using GNNs
GNN-RAG, a recent development, synergises GNNs and LLMs to excel in KGQA.
Implementing RAG-as-a-Service using Vectara
Discover Vectara and simplify RAG-as-a-Service for seamless generative AI application building.
