MLOps & model serving on GCP
Managing the full ML lifecycle on Google Cloud, from data labeling and training to model registry and serving endpoints. It's also the primary way to access Google's foundation models (Gemini, PaLM) via API and fine-tune them on custom data within GCP.
Enable the Vertex AI API in your GCP project from the Google Cloud Console. Install the google-cloud-aiplatform Python SDK and authenticate with gcloud auth. You'll need a GCP project with billing enabled and appropriate IAM roles for Vertex AI resources.
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Intelligent World
CEO of Intelligent World and one of the most prominent AI influencers globally. Expert in enterprise AI agents, logistics, manufacturing, and infrastructure applications. Advises organizations on AI strategy and digital transformation.
Google DeepMind
CEO and co-founder of Google DeepMind, the world's leading AI research lab. Led breakthroughs including AlphaGo (defeating world Go champion), AlphaFold (solving protein folding), and pioneering AGI research. Nobel Prize-winning contributions to computational biology.
Google Cloud
Director of Analytics & AI Solutions at Google Cloud. Author of 'Machine Learning Design Patterns' and 'Data Science on the Google Cloud Platform' (O'Reilly). Prolific technical content creator on Vertex AI and production ML patterns.
Stanford University / World Labs
World-renowned AI researcher, Stanford professor, and co-director of Stanford's Human-Centered AI Institute (HAI). Created ImageNet, the dataset that revolutionized deep learning and sparked the modern AI era. Founded World Labs, a spatial intelligence startup valued at $5B+. Former VP at Google Cloud. Named to TIME's 100 Most Influential People.
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