Newsletter: What Do They Not Tell You About Building Open-Source Projects with LLMs?
Unleash the Power of Language Models & Conquer Production Challenges – A Fun, Insightful Guide for Developers!
With all the hype around GPT, we couldn't resist the urge to try our hand at building our own open-source project using these LLM beasts. Along the way, like any other developer, we discovered a lot about their current state and learned a ton about building an end-to-end project. So, we decided to write a blog series of short, fun, and engaging blogs documenting our work, hoping you can learn from our mistakes and avoid them too! Join us on this exciting adventure and have a blast hacking away at your next LLM-based project!
In this first instalment, we'll explore the lesser-known aspects of building open-source projects with LLMs. We'll kick off our journey by examining the types of applications that work best with LLMs and discussing their strengths and limitations. As we dive deeper into the world of LLM products, we'll uncover the challenges and opportunities that lie beneath the surface.
LLMs in Production Conference Highlights
But first, let's take a moment to talk about an incredible conference on LLMs that we recently attended. It left us in awe of the wealth of knowledge, innovative ideas, and engaging discussions shared throughout the event. It was one of those rare conferences where we didn't feel like leaving, and we were genuinely disappointed to miss out on the talks happening in other tracks. The effort and dedication demonstrated by the organizing team in bringing together top experts in the field on the same day to discuss their experiences with LLMs were truly remarkable.
Diego Oppenheimer's keynote speech on the history, evolution, and future of LLMs
Daniel Jeffries' vision of Large Thinking Machines (LTMs) and the importance of fixing LLM bugs
Hanlin Tang's insights on training LLMs and making the process more manageable
Harrison Chase's LLM Framework and practical applications
Tanmay Chopra's reminder to remain grounded and realistic about LLM challenges
The Hidden Challenges of Deploying LLM Products
In this blog, we'll delve into the less-discussed challenges of deploying open-source LLM products. From the lack of SLAs or commitments to endpoint uptime and latency to the ambiguous nature of prompt engineering, creating a reliable LLM product can be a daunting task.
We'll also discuss the issues with reproducibility, prompt compatibility between different API endpoints, and the ever-present concerns of trust and security. As we explore these challenges, we'll share our insights and experiences from building our own LLM product and shed light on the obstacles that you may not have anticipated.
In the second half, we talk about some best practices and design patterns for overcoming the challenges of building open-source LLM products. From fine-tuning your model to finding the right balance between using APIs and training your own LLM, we'll discuss strategies for building a successful LLM product.
In addition, we'll share our tips for crafting effective prompts, focusing on minimizing ambiguity and making them context-aware. As you develop your own LLM product, remember that the prompts you create are as valuable as your API keys. They can be the deciding factor that sets your product apart from the competition, and understanding their importance is crucial for success.
The Undiscovered Potential of LLM Products - Integration and Growth
In the final blog of this series, we'll look to the future and explore the untapped potential for the growth and refinement of LLM products. As we work to improve our own LLM product, we'll share our plans to integrate open-source LLMs and add new features based on our vision of how LLM products will evolve over time. Subscribe below so you don’t miss that when we release it next week!
Stay tuned as we continue to share our experiences and insights in the world of LLM products, and join us on this exciting journey to uncover the hidden possibilities of LLMs in the world of AI.
Introducing Our Open-Source LLM Project
Now, you must be curious about the product we've been working on. Did you know that more than half of the world's population speaks at least two languages, and many people tend to think and work in their native tongue? As a result, communication often gets lost in translation, especially for non-English speakers.
So, knowing about these pain points, we developed a Chrome extension aimed at improving English writing skills for non-native speakers. To learn more about our project, join us at 10:30 pm EST this Friday at FOSS Asia.
You can live stream our talk through this link. During the presentation, we will cover more details about the project, including areas where you can contribute if you're interested.
If you can't attend the talk, not to worry – we will delve deeper into our project in next week's blog post. In the meantime, don't forget to check out some of the other amazing talks happening at FOSS Asia this week!
