Meet Empower: An AI Research Startup Unleashing GPT-4 Level Function Call Capabilities at 3x the Speed and 10 Times Lower Cost

Large Language Models (LLMs) reach their full potential not just through conversation but by integrating with external APIs, enabling functionalities like identity verification, booking, and processing transactions. This capability is essential for applications in workflow automation and support tasks. The main choice lies between OpenAI’s GPT-4, known for high quality but facing latency and cost issues, and GPT-3.5, which is quicker and cheaper but less accurate. The market seeks a model that balances high performance with cost-effectiveness, a niche not fully met by current providers, including OSS models and companies like Fireworks, Anyscale, or Together AI, especially in complex interactions and parallel processing capabilities.

Empower, a start-up backed by Y Combinator, aims to break down barriers with its innovative, serverless, and fine-tuned LLM hosting platform. Comparable to GPT-4, their platform (Empower-Functions) prioritizes speed and affordability through a function-calling model.

Empower-Functions claims to have three times faster reaction times than its competitors. However, what sets them apart is their ability to reduce costs by tenfold. Their design focuses on practical use cases, setting them apart from generic models. Users can test the model in a live demo before making a commitment. Additionally, the business offers a powerful API that enables users to incorporate the model into their existing applications easily.

To make it easier for developers, Empower-Functions offers a fast start guide. The platform combines developer-friendly tools, speed, and affordability.

Empower-Functions is tackling the major obstacles that have hindered the widespread adoption of LLM through its unique approach.

  • LLM systems can be expensive to maintain. With Empower’s serverless deployment, users simply pay for the resources they utilize, making it a cost-effective alternative. 
  • Convenience: Users don’t need a high level of technical knowledge because there are pre-built, task-specific foundation models. In this way, developers of every skill level may harness AI’s potential without being mired down in model building and training details. 
  • By giving them the power to launch their models, Control: Empower gives users, pardon the pun, more initiative. Two significant benefits are encouraging ownership and ensuring that models are customized to unique needs. 

In conclusion 

With Empower, it is quite affordable to participate in AI development. Because of this, more companies and developers may be able to harness AI’s potential, which might lead to amazing new opportunities. 

Dhanshree Shenwai is a Computer Science Engineer and has a good experience in FinTech companies covering Financial, Cards & Payments and Banking domain with keen interest in applications of AI. She is enthusiastic about exploring new technologies and advancements in today’s evolving world making everyone's life easy.

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