Analect
On Developing an AI Strategy
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You’ve been tasked with developing an AI strategy for your business …
… and you’ve read about foundation models …
… and you’ve heard there are software solutions out there …
… that might get you started on that journey.
As you research the field, it seems that AI tooling is just a subset of Machine Learning tooling.
Soon, you’re overwhelmed.
So we’ve put together a blog-series to get you started, instead.
is a machine learning or deep learning model that is
trained on vast datasets so it can be applied across a
wide range of use cases.
Generative AI applications like Large Language Models
are often examples of foundation models.
Building foundation models is often highly resource-intensive,
with the most advanced models costing hundreds of millions of
dollars to cover the expenses of acquiring, curating, and
processing massive datasets, as well as the compute power
required for training.
…
AI Strategy Series
This is a collection of five blog-posts intended to introduce the reader to how they may begin to think about introducing AI or machine learning to their business. It is deliberately not diving into the technologies. Rather, it is a distillation of my own thinking as well as readings from elsewhere that I have found valuable in evolving a better understanding of what’s needed to succeed, ancillary to the tooling and technologies.
| Date | Reading Time | Title | Author |
|---|---|---|---|
| Feb 3, 2025 | 13 min | 1. Framing an AI Strategy: Where Do You Start? | |
| Feb 10, 2025 | 13 min | 2. AI is Here, But its Business-Applicability may not be Obvious | |
| Feb 14, 2025 | 13 min | 3. Platform Engineering for Evolving AI / ML Solutions | |
| Feb 28, 2025 | 22 min | 4. DataOps: Emerging powerful modular tooling | |
| Mar 7, 2025 | 25 min | 5. LLMs: Key Emerging Components of the AI Tech Stack |
About Analect
I have been working at the intersection of finance and technology most of my career. While all my roles in finance involved leveraging technology, I focused on deepening my technical knowledge with my own start-up, Analect, formed in 2012. My motivation at the time, as a financial analyst, was to bring some of the compelling open-source tooling in the scientific community to the finance domain. More recently, my focus has been on cloud-based platform engineering for machine-learning use-cases (MLOps). Direct hands-on experience with these systems is a necessary part of being able to articulate ideas and strategy around how they can be leveraged within a financial services domain but also other industry domains too. Let’s collaborate together.
