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Amazon Q data integration adds DataFrame support and in-prompt context-aware job creation

AWS Big Data

The TICKIT dataset records sales activities on the fictional TICKIT website, where users can purchase and sell tickets online for different types of events such as sports games, shows, and concerts. We use the allevents_pipe and venue_pipe files from the TICKIT dataset to demonstrate this capability.

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Introducing Cloudera Fine Tuning Studio for Training, Evaluating, and Deploying LLMs with Cloudera AI

Cloudera

Hosting Costs : Even if an organization wants to host one of these large generic models in their own data centers, they are often limited to the compute resources available for hosting these models. Build and test training and inference prompts. The Need for Fine Tuning Fine tuning solves these issues.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

dbt Cloud is a hosted service that helps data teams productionize dbt deployments. By using dbt Cloud for data transformation, data teams can focus on writing business rules to drive insights from their transaction data to respond effectively to critical, time sensitive events. or a later version) database.

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US Air Force seeks generative AI test pilots

CIO Business Intelligence

Not instant perfection The NIPRGPT experiment is an opportunity to conduct real-world testing, measuring generative AI’s computational efficiency, resource utilization, and security compliance to understand its practical applications. For now, AFRL is experimenting with self-hosted open-source LLMs in a controlled environment.

Testing 119
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IT infrastructure complexity hindering cyber resilience

CIO Business Intelligence

Forty-three percent of 1,700 IT and security leaders worldwide ranked the challenge as a major barrier to an improved ability to recover from serious cyber events, nine percentage points above the second-placed issue: legacy security and IT issues.

IT 98
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What to Do When AI Fails

O'Reilly on Data

If our model generates false negative predictions for tumor detection, organizations could combine automated imaging results with activities like follow up radiologist reviews or blood tests to catch any potentially incorrect predictions—and even improve the accuracy of the combined human and machine efforts. How Material Is the Threat?

Risk 364
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Perform Amazon Kinesis load testing with Locust

AWS Big Data

Building a streaming data solution requires thorough testing at the scale it will operate in a production environment. However, generating a continuous stream of test data requires a custom process or script to run continuously. In our testing with the largest recommended instance (c7g.16xlarge),

Testing 93