Ep 5. How to Overcome LLM Context Window Limitations скачать в хорошем качестве

Ep 5. How to Overcome LLM Context Window Limitations

➡️ Subscribe to our email list: https://hubs.ly/Q02d4MT50 📹 ABOUT THIS VIDEO You might feel overwhelmed by the relentless stream of AI news, and rightly so. We're at the onset of an unprecedented technological shift in human history, arriving more swiftly than most can fathom. Regrettably, there's scant discussion about overcoming the tangible challenges of building AI solutions. That's what you'll find in this newsletter. Consider our Episode 4, where we addressed using "reasonableness" checks to combat LLM hallucinations: https://hubs.ly/Q02d4N8s0 In Episode 5, we'll tackle a challenge you're bound to face: the constraints of an LLM's context window, or how much data it can process in one go. Most solutions your customers seek will necessitate access to multiple data sources, such as various databases. Without proper guardrails, it's easy to overfeed the LLM with data and exceed its context window. We'll explore different solutions to this problem, with Episode 5 focusing on the most straightforward approach: Identify a business problem that you can resolve with data fitting within the context window. Implement basic guardrails to guide the user in interacting with the LLM as planned. Here's the crucial insight: These solutions must be guided by the analytics leader or product manager. This approach primarily involves a strategic decision on the selection of the initial problem. Here's an example you can emulate: focus on solutions for a single customer aspect, such as sales, marketing, or customer service. By narrowing your first problem to a single customer, you can achieve a high-impact solution while minimizing the risk of overloading the LLM with excess data. The video further explains this strategy. 📚 SUPPLEMENTARY MATERIALS 👇 📹 EPISODE 3 - THIS IS THE KILLER APP OF ENTERPRISE AI: UNIFIED NLQ: https://hubs.ly/Q02d4N1m0. In this video, we introduce Unified NLQ, which enables various stakeholders - including executives, employees, customers, prospects, and partners - to pose questions about data in natural language and receive relevant responses. 📹 EPISODE 4 - SUPERCHARGE DATA ANALYTICS WITH LLM AGENTS: https://hubs.ly/Q02d4N8s0. In this video, we explain how GPT-4 can query across multiple databases, potentially replacing every report, dashboard, application screen—essentially every interface where you serve data—into an interactive conversation. 🧑 💻 GITHUB REPO WITH DEMO SOFTWARE - Yep, you can download and run the code locally if you have basic software skills such as git, conda, etc. If you have questions about installation, just ask us on our Discord channel: https://hubs.ly/Q02d4N9s0. 🏢 ABOUT PROLEGO 👩‍💻 Prolego is an elite consulting team of AI engineers, strategists, and creative professionals guiding the world’s largest companies through the AI transformation. Founded in 2017 by technology veterans Kevin Dewalt and Russ Rands, Prolego has helped dozens of Fortune 1000 companies develop AI strategies, transform their workforce, and build state-of-the-art AI solutions. Get in touch at hello@prolego.com.