Earlier in August 2023 I changed roles within Red Hat. My new role is “Chief AI/ML Platform Strategist”, and organizationally is part of Red Hat’s OpenShift AI product group.

I’d been in my previous role for ~5 years, and celebrated my 14th anniversary at Red Hat last month 🫶 . My previous team (Red Hat Service Delivery) afforded me endless technical challenges, opportunities to launch new services, present, help define technical strategy and build cross-org engineering teams to support that strategy, from the ground up. Equally important to me was the opportunity to mentor as many Red Hatters as I possibly could.

And now, on to the next chapter. Red Hat’s CEO Matt Hicks did an interview recently that describes how Red Hat will participate in the AI/ML ecosystem as a platform company, specializing in machine learning operations (MLOps). My role involves working with engineering and product leaders to devise a strategy that will deliver a sustainable open source, enterprise software business around artificial intelligence and machine learning.

If I could summarize this north star in one sentence, it would be answering this:

I trust Red Hat as a strategic partner in the AI/ML space because…

Prospective Customer (Exec, Engineering personas)

The OpenShift AI product group encompasses:

• Development teams that design, build and operate Red Hat OpenShift Data Science (both as a SaaS and on-premise).
• Product / business teams that provide the vision, mission and roadmap (for an extremely fast-moving space!).
• Community participation in opendatahub.io and other upstreams

By bridging development, product, upstream communities, partners and consortia, we aim to increase Red Hat’s participation and brand association in strategic AI/ML areas through deliberate and substantial technical and business contributions to the ecosystem.

In many ways this is akin to work I and others did for the OpenShift product group in the 2013-2018 timeframe, when a similarly fast-moving space was in its gold-rush phase. Red Hat needed a voice in strategic upstreams (mainly Docker, Kubernetes, Linux Kernel) so that we could build a successful, sustainable product that covered workloads our customers cared about.

I’d personally gotten involved from the performance/scalability standpoint as an SME for running performance-sensitive applications on OpenShift (including GPUs). A lot of foundational work needed to be done — and Red Hat’s philosophy is to participate in, and catalyze open source communities to complete foundational work that allows the ecosystem to thrive, and deliver on participant business goals.

As I sit here, it all feels very “full-circle” for me, as I come back to a space I’m wildly passionate about, and that as an infrastructure platform company, Red Hat is uniquely positioned to provide differentiated value for.

In summary — in the few weeks I’ve been (re)digging into this AI/ML Cambrian explosion, it looks just like the early 2010’s. Most importantly, I am convinced that there is enough “real” here to justify the current hype. We are headed for industry consolidation. There are daily land-grabs going on in terms of marketing / positioning. And, as with many new technologies, there are important ethical, legal and governance questions yet un-answered (especially wrt LLMs, GDPR and compliance). Over time this space will settle down a bit, and one of my primary goals is to position Red Hat appropriately, as that occurs.

Hopefully $subject makes a bit more sense now. Onward!

P.S this blog contains 0% AI-generated content. All grammar errors are mine 💪