Summary of the Video Transcription
Introduction
- The speakers are Isaac and VTor, who lead the Solutions Engineering team at Poolside, a company building the Next Generation AI for software engineering.
- Poolside is a full-stack solution that includes a new foundation model specific to software development, fine-tuned on code and developer interactions.
Why Poolside Exists
Poolside was founded on three core convictions:
- The future belongs to domain-specific models, as opposed to general language models.
- General language models are not relevant to customers' older code bases, and are only helpful for greenfield projects.
- As AI adoption has increased, more data is being sent to the cloud for inference, which raises security and privacy concerns.
Limitations of General Language Models
- General language models understand software development just as much as they understand French literature or car maintenance.
- They are "taught about code" but do not know how to code, which is a significant limitation.
- Poolside's focus is solely on software development, allowing them to make different architectural decisions in building their language model.
Addressing Challenges in Building Language Models
- Compute: Poolside's recent Series B funding allowed them to procure GPUs for the next 3 years, enabling them to be at the forefront of building frontier models.
- Data: The challenge is that not all available code data is useful for training. Poolside has developed a unique solution called "Reinforcement Learning via Code Execution Feedback" to address this.
Reinforcement Learning via Code Execution Feedback
- Poolside looks at the top open-source repositories, hides the code, and has their model attempt to code against the repositories.
- They can then evaluate whether the model's code compiled, passed tests, and was secure, providing feedback to the model.
- This process has been automated and scaled to over 500,000 open-source repositories, teaching the model to think like a developer.
Relevance and Fine-tuning
- General language models often provide the same generic results, lacking the context and understanding of a specific business.
- Poolside's models are fine-tuned on the customer's code, data, and user behavior to become highly relevant and tailored to their needs.
- The goal is to create a "Software Intelligence Layer" that knows more about a company's software business than any single human developer.
Security and Privacy
- As models demand more capability and data, there is a tradeoff between performance and the amount of data sent to the cloud.
- Poolside's solution is to provide the model within the customer's security boundary, allowing all data circulation and fine-tuning to happen within their network.
Conclusion
- Poolside is building the most capable models for software development through their unique approach of reinforcement learning via code execution feedback.
- The fine-tuned models are tailored to the customer's needs and can be deployed within their security boundary, addressing privacy and security concerns.