Remove Cost-Benefit Remove Experimentation Remove Optimization Remove Statistics
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Achieving cloud excellence and efficiency with cloud maturity models

IBM Big Data Hub

” Given the statistics—82% of surveyed respondents in a 2023 Statista study cited managing cloud spend as a significant challenge—it’s a legitimate concern. Optimized: Cloud environments are now working efficiently and every new use case follows the same foundation set forth by the organdization.

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Bringing an AI Product to Market

O'Reilly on Data

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs. This allowed us to derive insights more easily.”

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Unleashing the power of Presto: The Uber case study

IBM Big Data Hub

With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. This allowed them to focus on SQL-based query optimization to the nth degree. But the simplicity ends there. Every transaction, every cent matters.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. While cost wasn’t the primary driver, it reflects a growing belief that the value generated by gen AI outweighs the price tag.

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Experimentation and Testing: A Primer

Occam's Razor

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. That’s the reward.

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