STAC AI Working Group

STAC uses the term "artificial intelligence" (AI) as an umbrella term for machine learning, deep learning (and other neural approaches), and any other techniques for getting computers to do what only humans could do a few years ago. (We're not trying to get into philosophical debates, but we need a vocabulary.)

The use of AI to develop models is now commonplace in trading and investment, and the reasons are not hard to understand. They all boil down to one cause: markets are increasingly competitive. Whether the business imperative is reducing time to market for new algorithms, improving model quality, or reducing costs, financial firms have to offload major aspects of model development to machines in order to achieve the necessary productivity.

But the field of AI is both blessed and cursed by an enormous variety of techniques and technologies. There are dozens upon dozens of AI algorithms; at least ten AI frameworks or libraries with implementations of those algorithms; nearly two dozen processor architectures vying for AI workloads; infrastructure-as-a-service and machine-learning-as-a-service offerings from all the major cloud providers; and countless software and software-as-a-service providers promising to simplify, accelerate, or otherwise enhance AI workflows. Data scientists and the technologists that support them face a tyranny of choice.

The mission of the STAC Benchmark Council is to fight such tyranny. The Council develops benchmark standards that are based on real world use cases and that measure things that matter to a business. This enables customers, vendors, and STAC to make apples-to-apples comparisons of techniques and technologies, thus making architectural and product choices easier for customers. It also provides the vendor community with use cases developed by multiple customers (like a multi-customer POC) that they can focus on in product development.

The STAC AI Working Group will develop and promote benchmark standards for key AI workloads in finance. To request involvement, please click on the "Enable me!" button to the right.

STAC AI Reports

Learning and running this benchmark suite

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