solutions test-drive 
DataKitchen
NOVEMBER 5, 2024
By storing data in its native state in cloud storage solutions such as AWS S3, Google Cloud Storage, or Azure ADLS, the Bronze layer preserves the full fidelity of the data. This foundational layer is a repository for various data types, from transaction logs and sensor data to social media feeds and system logs.
CIO Business Intelligence
NOVEMBER 22, 2024
Unfortunately, despite hard-earned lessons around what works and what doesn’t, pressure-tested reference architectures for gen AI — what IT executives want most — remain few and far between, she said. I think driving down the data, we can come up with some kind of solution.”
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AWS Big Data
OCTOBER 23, 2024
response = client.create( key="test", value="Test value", description="Test description" ) print(response) print("nListing all variables.") variables = client.list() print(variables) print("nGetting the test variable.") Creating a test variable. Creating a test variable. Creating a test variable.
CIO Business Intelligence
MAY 22, 2025
When developing AI solutions, training the model and reducing common AI problems like hallucination, data protection, privacy and unlearning the model can be costly on the real system and hence developing a digital twin solution in AI can help to simulate the real system and tune the system before deploying to productionized environments.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.
CIO Business Intelligence
JANUARY 7, 2025
The one that drives the greatest call to action from your board, executives, and employees because maintaining the status quo is a sure path to disruption. CIOs must also drive knowledge management, training, and change management programs to help employees adapt to AI-enabled workflows. AI transformation is the term for them.
O'Reilly on Data
FEBRUARY 19, 2021
The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. The Time Is Now to Adopt Responsible Machine Learning.
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