Remove Data Quality Remove Deep Learning Remove Metrics Remove Optimization
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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 362
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Synthetic data generation: Building trust by ensuring privacy and quality

IBM Big Data Hub

They are already identifying and exploring several real-life use cases for synthetic data, such as: Generating synthetic tabular data to increase sample size and edge cases. You can combine this data with real datasets to improve AI model training and predictive accuracy.

Metrics 87
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A Golden Era of HPC in Government Meets Accelerating Demands

CIO Business Intelligence

In addition to quantitative ROI metrics, HPC research was also shown to save lives, lead to important public/private partnerships, and spur innovations. . Real-time big data analytics, deep learning, and modeling and simulation are newer uses of HPC that governments are embracing for a variety of applications. Government.

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How Computer Vision is Revolutionizing the Manufacturing Supply Chain

CIO Business Intelligence

Ever increasing advances in technology and continuous process optimization techniques have helped ensure that the global supply chain runs efficiently, turning raw materials into products that make their way to physical stores and ecommerce warehouses. How can we positively impact the employee or “people” experience?

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Digital Twin Use Races Ahead at McLaren Group

CIO Business Intelligence

Aside from monitoring components over time, sensors also capture aerodynamics, tire pressure, handling in different types of terrain, and many other metrics. In the McLaren factory, the sensor data is streamed to digital twins of the engine and different car components or features like aerodynamics at 100,000 data points per second ?

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What you need to know about product management for AI

O'Reilly on Data

At measurement-obsessed companies, every part of their product experience is quantified and adjusted to optimize user experience. These companies eventually moved beyond using data to inform product design decisions. Without large amounts of good raw and labeled training data, solving most AI problems is not possible.

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What’s New and What’s Next in 2023 for HPC

CIO Business Intelligence

Of course, data center challenges are also driving demand for these alternatives. Workflow Optimization from Edge to Core/Cloud and Back : Integration with edge devices as well as integration with different HPC systems is currently designed in-house or otherwise customized. Just starting out with analytics?