On-Premise or Cloud - Where Should You Host Your AI Applications?
The more reliant a task is on a large and private dataset, the more likely it is that a workflow application will be dominant instead of a model. The best software companies function as a system of record, a repository for the most important data (customer IDs, product analytics, or credit card numbers), and they’ll be able to offer superior produc
... See moreA solution is to self-host an open-sourced or custom fine-tuned LLM. Opting for a self-hosted model can reduce costs dramatically - but with additional development time, maintenance overhead, and possible performance implications. Considering self-hosted solutions requires weighing these different trade-offs carefully.
Developing Rapidly with Generative AI
For example, an application may use Microsoft Azure for storage, AWS for compute, IBM Watson for deep learning, and Google Cloud for image recognition.
Thomas M. Siebel • Digital Transformation: Survive and Thrive in an Era of Mass Extinction
Expensive to build and often needing highly skilled engineers to maintain, artificial intelligence systems generally only pay off for large tech companies with vast amounts of data. But what if your local pizza shop could use AI to predict which flavor would sell best each day of the week?
TED • How AI Could Empower Any Business | Andrew Ng | TED
Cloud apps like Google Docs and Trello are popular because they enable real-time collaboration with colleagues, and they make it easy for us to access our work from all of our devices. However, by centralizing data storage on servers, cloud apps also take away ownership and agency from users. If a service shuts down, the software stops functioning,... See more
Mark McGranaghan • https://www.inkandswitch.com/local-first/
The human-centric platform for production ML & AI
Access data easily, scale compute cost-efficiently, and ship to production confidently with fully managed infrastructure, running securely in your cloud.
Access data easily, scale compute cost-efficiently, and ship to production confidently with fully managed infrastructure, running securely in your cloud.
Infrastructure for ML, AI, and Data Science | Outerbounds
While a cloud is cheap compared to buying a system, if only a few processes need to be run, a cloud can actually cost more than having an in-house system.
Bill Franks • Taming The Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics (Wiley and SAS Business Series)
This great convenience and productivity booster also brings a whole new form of lock-in. Hybrid/multi-cloud setups, which seem to attract many architects' attention these days, are a good example of the kind of things you'll have to think of when dealing with lock-in. Let's say you have an application that you'd like to deploy to the cloud. Easy en... See more