Deep dives of the week
Generative AI keeps rolling out with breath-taking advancements. Last week, Google Cloud unveiled a slew of generative AI tools for developers for application development, ML modeling, and more. Meanwhile, Microsoft continues to up the ante: Azure introduced new VMs for generative AI that exa-scale LLMs by 30x over the previous generation.
In this week's special package of NPW Insights, we're showcasing four diverse developments from Google, Netflix, Azure, and Shopify that demonstrate the wide-ranging innovation driven by AI/ML today.
Our other spotlight this week is on serverless technology, which has been one of the most consequential technologies in cloud computing lately. But with the enterprise-ification of this technology, says an experienced cloud architect, new challenges are emerging. A must-read musing.
Finally, don't miss the fascinating story of an engineering team that took on the unconventional task of migrating from Lambda to Kubernetes, how they successfully bridged the gap between the two technologies for a smooth transition.
Google Cloud rolls out generative AI tools for developers
PaLM API, a service that lets you build on top of Google’s LLMs, and MakerSuite, which brings features for prompt engineering, synthetic data generation, and model tuning, were the core highlights. In addition, text generation features coming to Google workspace. UPDATE
Generative AI support in Vertex AI lets you implement from a selection of use cases like content generation, chat, summarization, etc. Offers Google + DeepMind and 3rd party models, tuning solutions.
Generative AI App Builder which connects conversational AI with search experiences, offers native intent inference techniques, blueprints for key use cases, multimedia search and response support. GCP services will also infuse generative AI features to inspect and explain model behavior, for product Q&As, query generation, and more. UPDATE
Insights from Netflix’ media understanding platform
To help creatives perform dialogue, visual, and reverse-shot search on its content library without having to watch it, Netflix engineers first developed a tightly coupled application, where ML algorithms were tied to backend and UX code. This impeded scalability and development of new use cases, which led to the development of a media understanding platform – which serves as an abstraction layer between apps and ML algorithms. It lets apps interact via a GraphQL or gRPC interface, which forwards queries to a Search Gateway. The latter modifies queries to match the target dataset, and maps it to multiple searchers which then execute it. STORY