Fine tune your own custom LLM with Canonical Charmed Kubeflow and Feast
So you want your own pet LLM huh? Knowing where to start can be quite tricky, so luckily for you I’ve put together this end-to-end guide. It’ll get you not just started; you’ll end with a fully working chatbot that you’ve fine tuned on the dataset `nampdn-ai/tiny-webtext`, which is a training dataset designed to improve […]
Read the full story on Canonical BlogHave you worked with this?
The story is what was announced. Nobody has discussed it yet, so if it touches your team, a short post about what you’ve seen helps the next reader.
More from Canonical
Recent updates from Canonical, so you can tell whether this is a one-off or part of a pattern.
Scaling Android™ development without scaling hardware
How shared Android capacity helps engineering teams move beyond fixed device labs In the first blog of this series, we discussed how programmable Android environments can replace manual device preparation with a repeatable lifecycle. A workflow requests an environment with a predefined configuration, executes the required task, collects the results, and releases the resources once […]
Attach an Ubuntu Pro subscription to your AWS Image Builder image
We are pleased to announce that you can now attach an Ubuntu Pro subscription directly to any base image in AWS Image Builder, allowing you to create enterprise-grade custom images from the get go.
Beyond the 10-year mark: Extending Ubuntu Pro 16.04 LTS security coverage
A decade ago, Canonical launched Ubuntu 16.04 LTS (codenamed “Xenial Xerus”). As a Long-Term Support (LTS) release, it comes with 5 years of standard security coverage, which is doubled to a total of 10 years through Expanded Security Maintenance (ESM) for users with an Ubuntu Pro subscription.
More in Containers & Kubernetes
What other companies in Containers & Kubernetes are doing. The category page shows who’s active, side by side.
Bringing enterprise Linux to the robotics frontier: ROS2 adds Red Hat Enterprise Linux as a tier-1 supported platform
The convergence of enterprise IT and physical computing is accelerating. As artificial intelligence transitions from purely digital environments into autonomous systems, industrial automation, and smart edge devices, the software foundation behind these systems must be as resilient as the physical machines themselves.To power this next generation of intelligent systems, we’re pleased that Red Hat…
Best practices guide for customizing Gemini models via Reinforcement Learning (RL)
Reinforcement learning (RL) has been a keystone of modern LLM post-training, but it demands large training clusters and access to model internals that external customers can't have with proprietary models like Gemini. So here at Google Cloud, we packaged it into a managed RL fine-tuning service (RLFT service) — you bring prompts and a reward function; we handle the infrastructure and the…
Breaking the AI productivity paradox: an intelligent migration factory to modernize infrastructure and applications
The rise of generative AI promised a silver bullet, but for most enterprises, especially banks, digital transformation remains a slow, complex, and costly endeavor. Early reports suggested massive developer productivity gains. But when AI is applied to complex enterprise systems, organizations often collide with what we call the AI productivity paradox.According to a Stanford software engineering…
AI Reliability Engineering for Dependable Humans | Solo.io
Learn AI reliability engineering (AIRE): how AI agents help SRE and platform teams triage incidents faster and stay dependable.