Leveraging Browser-Based Computing: The Cost and Compute Advantages of AI Squared’s Model Cards

By Praneeth Chandu — April 1, 2024

Leveraging Browser-Based Computing: The Cost and Compute Advantages of AI Squared’s Model Cards

By Praneeth Chandu (Software Engineer at AI Squared) — April 1, 2024

In the digital age, where data is a critical asset for businesses, efficient data management and visualization are paramount. AI Squared’s browser-based model cards offer a transformative approach that not only enhances data interaction, but also significantly optimizes cost and computational efficiency. Let’s explore model cards in more detail.

The Technical Edge of Browser-Based Model Cards

Model cards are a unique offering from AI Squared that change the traditional dynamics of data visualization and processing. Unlike conventional methods that rely heavily on server-side computation, model cards are designed to execute directly within the browser. This shift leverages client-side computational power, leading to a more efficient use of resources.

Here’s how model cards work:

  • Client-side processing: Model cards perform data processing and rendering in the user’s browser, utilizing local computational resources. This reduces server load, lowers data transfer requirements, produces faster response times, and lowers bandwidth usage.
  • Data caching and lazy loading: To optimize performance, model cards employ caching mechanisms that store processed data in the browser’s local storage, minimizing redundant data fetching and processing. Lazy loading techniques ensure that data is only loaded and processed as needed, reducing initial load times and memory usage.
  • Feedback-driven model improvement: One of the key benefits of AI Squared’s platform is the ability to gather feedback directly from the end users who interact with the model cards. This feedback loop allows businesses to quickly identify areas for improvement and iterate on their models more effectively. By incorporating user insights into the development process, companies can refine their models to better meet the needs of their audience, ultimately leading to more accurate and useful data insights.

Accelerating the Model Development Cycle

Traditionally, the model development cycle can be a lengthy and costly process, often taking up to two years and requiring several hundreds of thousands of dollars to create a production-ready model. This is due in part to the iterative nature of model development, where adjustments and refinements are made based on trial and error, leading to extended timelines and increased expenses.

AI Squared’s platform dramatically changes this by enabling businesses to gather feedback and iterate on models much faster. By leveraging the insights gained from model card interactions, companies can focus their efforts on specific areas of improvement, eliminating guesswork and streamlining the development process. This not only saves time but also significantly reduces the costs associated with bringing a model to a production-ready state.

Quantifying Compute Savings: A Comparative Analysis

The cost and time savings offered by AI Squared’s implementation become even more apparent when we examine the average compute expenses associated with traditional model development across different business sizes:

  • Small and medium-sized businesses (SMBs): Typically, SMBs spend around $50,000 to $100,000 annually on computing resources for model development, with a development cycle spanning 12 to 18 months.
  • Mid-market companies: These organizations often see compute costs ranging from $200,000 to $500,000 per year, with development cycles lasting up to 24 months.
  • Enterprises: For large enterprises, the expenditure on compute resources can exceed $1 million annually, with complex models taking over two years to reach production readiness.

In contrast, AI Squared’s browser-based model cards significantly reduce these costs and timeframes by offloading computational tasks to the client side. This approach not only decreases the demand for server-side compute resources but also allows for quicker iterations based on user feedback, further accelerating the development cycle.

For instance, an SMB utilizing AI Squared’s platform could potentially reduce its model development costs by up to 50%, bringing the expense down to $25,000 to $50,000, with a reduced cycle time of 6 to 9 months. Similarly, mid-market companies and enterprises could see proportionate savings, both in terms of costs and time to market.

Streamline Model Development with AI Squared

The innovative approach of AI Squared’s model cards, with their emphasis on browser-based computation and feedback-driven development, offers a cost-effective and time-efficient solution for businesses of all sizes. By optimizing computational resources and streamlining the model development process, AI Squared empowers companies to harness the full potential of their data, driving informed decision-making and fostering growth in an increasingly data-driven world.

Ready to get started? Request a pilot to see how AI Squared can help you develop models more effectively.