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Showing 20 results · Page 2 for “gcp”. More results are available below.
GCP-CDL · Innovating with Google Cloud artificial intelligence
Large language models generate plausible text but can hallucinate facts. Grounding connects the model to trusted sources so answers cite and rely on real data. Retrieval-augmented generation…
GCP-CDL · Innovating with Google Cloud artificial intelligence
Models inherit the biases in their training data, so a hiring model trained on skewed history can discriminate. Responsible AI practices address this with fairness testing, explainability to…
GCP-CDL · Innovating with Google Cloud artificial intelligence
Google offers ready-made APIs for common tasks: Vision for image labelling, Speech-to-Text and Text-to-Speech, Translation, Natural Language for sentiment and entities, and Document AI for e…
GCP-CDL · Modernize infrastructure and applications with Google Cloud
Compute options trade control for convenience. Compute Engine provides virtual machines with full control of the OS, suited to legacy or licensed software. Google Kubernetes Engine runs cont…
GCP-CDL · Modernize infrastructure and applications with Google Cloud
A virtual machine includes a full guest operating system on top of a hypervisor, so it is heavy, slow to boot and isolated at the hardware level. A container packages only the application an…
GCP-CDL · Modernize infrastructure and applications with Google Cloud
Lift and shift, or rehost, moves an application largely unchanged and is fastest, using tools like Migrate to Virtual Machines. Replatform makes modest changes such as swapping a self-manage…
GCP-CDL · Modernize infrastructure and applications with Google Cloud
An application programming interface lets systems exchange data through a defined contract, which is how a mobile app talks to a backend or how partners integrate. Modernisation often wraps …
GCP-CDL · Trust and security with Google Cloud
Google is responsible for the physical data centres, hardware, network backbone and the software that runs its services. The customer is responsible for their data, identities, access polici…
GCP-CDL · Trust and security with Google Cloud
Identity and Access Management binds a principal (a user, group or service account) to a role on a resource. Roles are collections of permissions. Basic roles like Owner, Editor and Viewer a…
GCP-CDL · Trust and security with Google Cloud
Google Cloud encrypts all customer data at rest automatically and encrypts traffic in transit between its facilities, with no action required. Customers who need control over keys can use Cl…
GCP-CDL · Trust and security with Google Cloud
Traditional perimeter security assumed anything inside the corporate network was safe. Zero trust drops that assumption and authenticates and authorises every request based on user identity,…
GCP-CDL · Scaling with Google Cloud operations
Cloud Billing budgets send alerts at chosen percentages of a target spend so surprises are caught early; they notify but do not stop resources by default. Sustained use discounts apply autom…
GCP-CDL · Scaling with Google Cloud operations
A service level indicator is a measurement such as request latency or error rate. A service level objective is the internal target for that indicator, for example 99.9 percent of requests un…
GCP-GAIL · AI security boundaries
This concept review develops the reasoning needed for ai security boundaries. Start by identifying the relevant assets, permissions, evidence and trust boundaries. Distinguish what the obser…
GCP-GAIL · Cloud security
Moving a workload to a provider does not remove the need to manage permissions, secrets and sensitive information. Map where data enters, is stored and leaves, then identify the identities a…
GCP-GAIL · Generative AI systems
A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…
GCP-GAIL · Responsible AI evaluation
Aggregate accuracy can hide poor performance for particular users or situations. Evaluate representative subgroups and realistic failure cases, and consider privacy, misuse and human oversig…
GCP-PAA · AI security boundaries
This concept review develops the reasoning needed for ai security boundaries. Start by identifying the relevant assets, permissions, evidence and trust boundaries. Distinguish what the obser…
GCP-PAA · Cloud security
Moving a workload to a provider does not remove the need to manage permissions, secrets and sensitive information. Map where data enters, is stored and leaves, then identify the identities a…
GCP-PAA · Generative AI systems
A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…
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