Analytics Vidhya

Leading with Data Ep 50 - 34K Github Stars in Less Than 3 Years: How a Side Project Became a Real Business: https://lnkd.in/gtSAH39r Celebrating 50 episodes of Leading with Data with Kunal Jain, this time, we’re joined by Didier Rodrigues Lopes, Founder and CEO of OpenBB, a company revolutionizing the space of open-source financial tools. Before founding OpenBB, Didier worked as a sensor fusion engineer at NURVV, where he played a pivotal role in enhancing the GNSS receiver’s time-to-first-fix, re-imagining altitude estimation with Kalman Filters, and designing a GPS filtering algorithm to improve accuracy. Here’s a sneak peek of what you can expect: - The story behind OpenBB’s inception and journey. - Didier’s unique strategies for stock trading. - How the community’s feedback shaped the product. - Building a business around open-source products. - Didier’s vision for OpenBB’s future. - Startups and examples that inspired him along the way. - The motivation behind OpenBB’s rebranding. - A look into OpenBB’s offerings and upcoming roadmap. - Exploring agentic workflows in OpenBB’s platform. Don't miss out on this thought-provoking conversation! #AnalyticsVidhya #LeadingWithData #GenerativeAI

Want to simplify the creation and management of AI workflows? CrewAI flows offer structured patterns for orchestrating AI agent interactions. They enable developers to effectively combine coding tasks and Crews, offering a powerful framework for developing AI automation. With Agentic Flows in CrewAI, you can design structured, event-driven workflows that streamline task coordination, manage state, and control execution within your AI applications: https://lnkd.in/g3BhVeiJ #AnalyticsVidhya #GenerativeAI #AIAgents

Elon Musk’s xAI recently released the Grok API for developers, offering $25 of free monthly credits. Currently, the API is available for the Grok-beta, enabling developers to explore and integrate advanced AI capabilities into their applications. The full rollout for the Grok-2 and Grok-2 mini models is anticipated soon, promising enhancements in performance and efficiency tailored for a range of applications, from lightweight tasks to more complex computations. This initiative marks a significant step in expanding access to robust AI tools and fostering innovation in the developer community. To check the capabilities of the xAI, I have built a social Media Writer Using the xAI API Key: https://lnkd.in/gQy3WqbR #AnalyticsVidhya #Groq #LLMs

Ever wondered about the potential of GUI agents that truly "see" and "understand" like humans? The recent work on ShowUI introduces a breakthrough in the realm of GUI automation by combining vision, language, and action models. 🖥️🤖 Key takeaways from this cutting-edge research: 1️⃣ UI-Guided Token Selection: Efficiently processes high-resolution screenshots, reducing redundant data by 33% and achieving a 1.4× training speedup. 2️⃣ Interleaved Vision-Language-Action Streaming: Seamlessly integrates multi-turn interaction histories for robust navigation and task execution across platforms. 3️⃣ Minimal yet Effective Dataset: By curating a small yet high-quality dataset, the model achieves 75.1% accuracy in zero-shot screenshot grounding while being lightweight and computationally efficient. Why does this matter? 👉 For developers: It opens doors to more accessible, resource-efficient automation for digital platforms. 👉 For organizations: A smarter, faster, and more intuitive way to streamline workflows and enhance user experience. 👉 For AI enthusiasts: A glimpse into the future of interaction between humans and digital systems. #AnalyticsVidhya #GenerativeAI #DataScience #AIAgents

The New Free Course on "Coding a ChatGPT-style Language Model from Scratch in PyTorch" is live now: https://lnkd.in/gp_dKdqq Key Takeaways of the course: ➡️ Understand transformer fundamentals with step-by-step guidance, including masked self-attention and position encoding. ➡️Build and train models using PyTorch, focusing on practical coding skills for NLP. ➡️Create a fully functional ChatGPT-style language model from scratch, ready for real-world use. The instructor of the course is Joshua Starmer PhD who is a Co-Founder and CEO of Statsquest Moreover, on a weekly basis we are launching a new free course. Stay tuned for the next course. #AnalyticsVidhya #FreeCourse #ChatGPT #PyTorch

ChatGPT has grown to become an everyday companion for most of us. Although we might use it on a daily basis, most of us have only been scratching the surface of what ChatGPT can do. Beyond writing essays or answering questions, this generative AI tool holds the potential to transform your workflows, spark creativity, and even offer some fun. In this article, we’ll explore 7 interesting and out-of-the-box prompts you can try on ChatGPT today: https://lnkd.in/gBa7YG4S #AnalyticsVidhya #ChatGPT #Prompts #GenerativeAI

Output parsers are essential for converting raw, unstructured text from language models (LLMs) into structured formats, such as JSON or Pydantic models, making it easier for downstream tasks. While function or tool calling can automate this transformation in many LLMs, output parsers are still valuable for generating structured data or normalizing model outputs: https://lnkd.in/gQFB5gug #AnalyticsVidhya #GenerativeAI #Agents #LLMs

AI agents are intelligent programs that perform tasks autonomously, transforming various industries. As AI agents gain popularity, various frameworks have emerged to simplify their development and integration. Atomic Agents is one of the newer entries in this space, designed to be lightweight, modular, and easy to use: https://lnkd.in/dMxG9uPa Atomic Agents provides a hands-on, transparent approach, allowing developers to work directly with individual components. This makes it a good choice for building highly customizable AI systems that maintain clarity and control at every step. In this article, we’ll explore how Atomic Agents works and why its minimalist design can benefit developers and AI enthusiasts alike. #AnalyticsVidhya #GenerativeAI #AIAgents #Agents

Fast GraphRAG, developed by the team at CircleMind AI, is the latest innovation in Graph-augmented Retrieval-Augmented Generation (RAG). Built with a focus on speed, cost efficiency, and adaptability, this library empowers users to overcome the limitations of traditional RAG setups. With its ability to dynamically generate knowledge graphs and seamlessly integrate them into production environments, Fast GraphRAG is a versatile, open-source solution that is easy to deploy and scales effortlessly to meet enterprise needs. In this article, we will explore: 1. Why Fast GraphRAG Matters: Understanding its significance over traditional vector database setups. 2. Key Features: Highlighting what sets Fast GraphRAG apart, including interpretability, scalability, and dynamic updates. 3. Implementation Guide: Step-by-step instructions on how to get started with Fast GraphRAG. Read more: https://lnkd.in/dX-K3_ys #AnalyticsVidhya #GraphRAG #RAG

The world today is powered by state-of-the-art generative AI models that offer new features and applications every day. In 2024, with AI Agents, AI adoption hit a new high, sparking a revolution in almost every industry. Owing to the ongoing developments in the field of generative AI, 65% of firms polled by McKinsey are already using GenAI tools on a regular basis. Let’s explore some of the upcoming generative AI trends and how they will impact businesses in the future: https://lnkd.in/dtC3e5bV #AnalyticsVidhya #GenerativeAI #DataScience