MetaLearner, an independent AI-powered data science platform, is transforming enterprise analytics by integrating Meta's Llama AI models. The company's swift adoption of Llama 3.1 is democratising access to advanced data science tools for businesses using ERP systems like SAP and Oracle.
The platform's journey with Llama began with workflow orchestration but quickly expanded to encompass more complex functions. Lim Ting Hui, Head of Technology at MetaLearner, explains, "We were impressed by Llama's leap in model performance and ability to efficiently manage AI workflows, setting it apart from other LLMs." This initial adoption laid the groundwork for MetaLearner's rapid evolution alongside Llama's development.
With the integration of Llama 3.1, MetaLearner has significantly enhanced its offerings. The platform now utilises both the 8B and 70B models to power core functionalities, enabling users to derive insights, automate processes, and make data-driven decisions more effectively. Remarkably, the MetaLearner team implemented this upgrade within 30 minutes of Llama 3.1's release, demonstrating their agility and commitment to providing cutting-edge solutions.
The open-source nature of Llama has been crucial to MetaLearner's success. Rafael Nicolás Fermín, Head of Product at MetaLearner, emphasises the transformative impact of open-source AI: "Open source is the driving force behind the next generation of innovation. This model has empowered us to compete with tech giants by unlocking opportunities to leverage state-of-the-art technologies like Llama without the massive R&D budgets of large corporations."
MetaLearner's commitment to the open-source community is evident in their contributions, such as the Rust engine. This tool converts Python pandas data frames to Excel reports, achieving a remarkable 95% reduction in compute time compared to leading Python engines.
The integration of Llama into MetaLearner's platform hasn't been without challenges. Initially, the team faced difficulties with tool invocation in their orchestration engine. However, through persistent refinement and model fine-tuning, they optimised their system for smooth, accurate performance.
The impact of MetaLearner's AI-powered solutions is already being felt in the industry. Ben Levicki, AI Architect at Cleveland Cavaliers, an early adopter of MetaLearner, notes, "With Llama, MetaLearner can efficiently provide critical access to advanced data science workflows and share cutting-edge AI capabilities to the heart of operational decision-making."