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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Two big things: They bring the messiness of the real world into your system through unstructured data. By contrast: ML-powered software introduces uncertainty due to real-world entropy (data drift, model drift), making testing probabilistic rather than deterministic. What makes LLM applications so different?

Testing 168
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An AI Data Platform for All Seasons

Rocket-Powered Data Science

One example of Pure Storage’s advantage in meeting AI’s data infrastructure requirements is demonstrated in their DirectFlash® Modules (DFMs), with an estimated lifespan of 10 years and with super-fast flash storage capacity of 75 terabytes (TB) now, to be followed up with a roadmap that is planning for capacities of 150TB, 300TB, and beyond.

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Predictive Analytics Improves Trading Decisions as Euro Rebounds

Smart Data Collective

Predictive analytics tools can be particularly valuable during periods of economic uncertainty. Predictive Analytics Helps Traders Deal with Market Uncertainty. However, predictive analytics will probably be even more important as global uncertainty is higher than ever. Analytics Vidhya, Neptune.AI

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The genAI opportunity: From ‘data to insight’ to ‘context to action’

CIO Business Intelligence

There’s a constant risk of data science projects failing by (for example) arriving at an insight that managers already figured out by hook or by crook—or correctly finding an insight that isn’t a business priority. And some of the biggest challenges to making the most of it are well-suited to the skills and mindset of data scientists.

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The state of data quality in 2020

O'Reilly on Data

The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. They’re still struggling with the basics: tagging and labeling data, creating (and managing) metadata, managing unstructured data, etc.

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Powering the future: How Gen AI and AI illuminate utility companies

CIO Business Intelligence

While international conflict, economic uncertainty and climate change are affecting businesses of all kinds, energy companies and utilities are also dealing with aging infrastructure, constant cyberattacks, increased regulation and rising customer expectations.

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Covid Data: An anomalous blip, or the new normal?

Cloudera

Insurance and finance are two industries that rely on measuring risk with historical data models. They have traditionally been slower-moving to adopt new structured and unstructured data inputs as regulatory considerations are always top of mind. This can be done at speed, and at scale.