Build and Customise AI Models

In today's fast-paced world, AI is no longer a futuristic concept but a reality. Mastering the ability to tailor Large Language Models (LLMs) is crucial for staying ahead. These skills empower you to build custom AI applications, enhance existing AI responses with up-to-date information, and streamline your coding workflow, saving you valuable time and resources.

The AI landscape offers a spectrum of models, from powerful, general-purpose LLMs to specialized, niche SLMs. However, pre-trained models often fall short when dealing with private, domain-specific data or when requiring highly customized response behaviors.

That's where building your Small Language Model (SLM) becomes essential. To guide you through this process, we've curated a detailed 4-part series. This series will explain to you the core components of SLM training, covering crucial steps like data preprocessing, vectorization, positional encoding, and the intricate transformer architecture, empowering you to create AI solutions tailored to your unique needs.

LLMs, while powerful, often lack real-time information or access to your private datasets. To bridge this gap, we can construct a dynamic graph architecture that orchestrates the flow of information. Imagine an AI that, when faced with a prompt requiring external knowledge, intelligently selects from a list of specialized tools and answers your query.

First, we provide the LLM with a description of the available tools and their respective uses. Then, we craft prompts that enable the LLM to autonomously determine whether and when to invoke these tools, potentially iterating multiple times until it gathers sufficient information to provide a detailed answer. This sophisticated workflow, easily implemented using tools like LangChain, empowers your LLM with real-time data and access to private knowledge.

Explore our detailed guide on integrating a web search tool (specifically, Wikipedia) with your AI model and witness the transformative power of this approach.

We've all faced the daunting blank editor screen or wrestled with debugging code that should have been straightforward. Imagine coding as a collaborative, creative process rather than a frustrating battle. That's the promise of GitHub Copilot – your AI pair programmer.

It goes beyond simple autocompletion, understanding your code's context and intent to transform your ideas into functional solutions with remarkable speed. Built on a vast dataset of millions of GitHub repositories, Copilot is arguably the most powerful AI assistant for programming across various languages and complexities. Significantly boosting your productivity and streamlining your development workflow. Learn how to use Copilot for your everyday programming needs.

Find us on social media:

If you have any queries or suggestions, write to us at [email protected].

Consider sharing this and recommending this to your friends!

Thanks and regards,
Pruthvi Batta
AI ML Universe