Hey folks, excited to open up this space for you to share your ongoing AI or large language model projects, startups, or collaboration opportunities. This is your chance to get some visibility and maybe find partners or feedback in our community.
Feel free to discuss your project's goals and unique challenges you're facing, and if you have any product or service offerings, don't forget to include your pricing model. For instance, if you're deploying a fine-tuned version of GPT-3 or experimenting with custom LLaMA models, let us know what decision-making process you went through and how you're managing costs.
Just a few ground rules here: Please avoid link shorteners or sites that lead to automatic subscriptions. Our aim is to maintain trust and clarity within this community, so let's keep it transparent.
This thread will be sticky for a bit, allowing everyone to share or connect without cluttering the main discussions.
Meta Note: This is our first attempt at a dedicated space for project promotion and community-led collaborations. If it doesn’t align with community needs, we'll revisit and tweak it. Looking forward to seeing what everyone's working on!
Hey, I'm currently working on a startup leveraging a fine-tuned GPT-3 model to create custom marketing content for small businesses. We've noticed that businesses often struggle with maintaining consistent tone and style across varied materials. Our challenge has been balancing quality output with affordable pricing, especially since GPT-3 API costs can add up quickly. Right now, we're testing a tiered pricing model based on usage, which allows smaller companies to manage costs while scaling up if they need more output. It's been a fun ride, and I'm happy to share more on our journey if anyone else is exploring similar use cases!
Hey, I'm working with a team on a custom implementation of LLaMA to help automate text summarization for academic journals. We've faced some challenges with ensuring the accuracy and preserving nuanced meanings in highly technical documents. Cost-wise, we're completely bootstrapped right now, so we're leveraging open-source tools as much as possible. I'm curious about others' experiences with maintaining high accuracy in such projects while managing tight resource constraints. Any tips?
We're developing a custom LLaMA model for interactive educational content. Rather than focusing solely on automated responses, we're integrating AI with a human-assisted system to adapt learning paths in real-time. It's been challenging to optimize latency and maintain engaging user experiences, but AWS Lambda and Step Functions were game-changers for us. Anyone else tried similar architectures?
Hey everyone, I'm currently involved in a project where we're deploying a modified version of GPT-3 tailored for healthcare data analytics. One big challenge is ensuring compliance with data privacy regulations while fine-tuning the model. We opted for an on-premise solution to manage sensitive datasets securely, and it cost around 30% more. Curious if anyone has explored cloud options and balanced GDPR concerns?
I'm curious about how you're managing the data privacy aspects, especially with customer data. Are there any specific tools or frameworks you're using to ensure compliance with GDPR or other data protection regulations? We're looking into similar implementations and would appreciate insights from those who have already tackled these challenges.
We're developing a fine-tuned GPT-3 model for personalized tutoring in STEM subjects. Our primary challenge has been balancing the model's breadth of knowledge with the depth required for meaningful tutoring. Currently, our pricing model is based on a tiered subscription service that scales with usage. For anyone who has implemented similar solutions, what has been your approach in calibrating the model for subject-specific nuances while keeping the operational costs sustainable?
