Hannes Hapke

In February 2025, Members of the Digits machine learning team were invited to speak at the Google Developer Group Seattle on the topic of LLM deployments on Google Cloud.

Meta's recent release of Llama 3.2 has sent shockwaves through the AI community, and for good reason. This latest iteration isn't just an incremental upgrade; it's a significant step forward in making large language models (LLMs) more accessible, efficient, and responsible.

At Digits, we are constantly pushing the limits of production machine learning, therefore we were beyond excited in being selected for one of the few and rare tickets of the inaugural IRL event hosted by the CUDA Mode community in San Francisco, a gathering organized by Accel and NVIDIA on September 21st, 2024. This event, brought together some of the brightest minds in the Torch and CUDA ecosystem, was a testament to the vibrant and ever-evolving world of AI.

Hosting large language models (LLMs) like Llama 3.2 presents unique challenges, requiring specialized infrastructure and deployment strategies. This is where vLLM comes in, a cutting-edge framework designed to optimize LLM deployment on Kubernetes, the industry-leading container orchestration platform.

In the world of machine learning, the allure often lies in the dazzling advancements: the latest models, cutting-edge techniques, and breakthrough success stories. It's comparable to admiring the tip of an iceberg without recognizing the substantial structure beneath the surface that keeps it afloat.

This July, Digits was invited to present our latest lessons learned from our Open Source Large Language Model journey.

This July, Digits was invited to present our latest lessons learned from our Open Source Large Language Model journey.

This May, Digits was invited by Google to join Google I/O and participate in the exclusive, invitation-only developer advisory board.

This April, Members of the Digits machine learning team were invited to speak at the University of Washington on the topic of GenAI in Finance.

This April, Digits was invited by NVIDIA to show our latest ML/AI projects at Google Cloud Next'24.

This September, Digits was invited to present at Google Cloud's Next - their premiere event to explore Generative AI, learn from experts, connect with builders, and see how AI/ML are reshaping our world.

Is Machine Learning commoditized?

Using a machine learning model to classify an object (be it text, image, tabular data) with a label that the model has never seen before, Zero-Shot Classification, seems like an impossible task.

In our previous blog post, we introduced how we use similarity-based machine learning for accounting use cases. In this blog post, we will focus on how we use generative machine learning at Digits.

Early in 2022, Digits released Boost to help accountants save time by automating their work. Boost instantly spots inconsistencies in their client's ledger. Every second, Digits sifts through every single transaction and performs a deep analysis. Digits' Boost alerts accountants if it finds errors like transactions in unexpected categories and suggests categories for transactions with missing categories.

Understanding banking transactions as they happen, in real-time, is core to our mission with Digits Search. You can't answer important finance questions with bad data.