Remove Experimentation Remove Manufacturing Remove Measurement Remove Testing
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Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Without clarity in metrics, it’s impossible to do meaningful experimentation. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ).

Marketing 363
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Only One Problem To Solve for Successful Data and Analytics

DataKitchen

Like in product manufacturing, finding and reducing errors are the keys to data and analytics manufacturing success. Manufacturing production errors refer to mistakes or defects that occur during the manufacturing process. The day-to-day production of data analytics is also a manufacturing process.

Analytics 130
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The pandemic pivot: 5 key leadership lessons that will last

CIO Business Intelligence

The early days of the pandemic taught organizations like Avery Dennison the power of agility and experimentation. It also taught the packing materials manufacturer how to use IT to create an adaptive organization flexible enough to respond to crises and create solutions. Employee crowdsourcing can yield breakthrough ideas.

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CIOs press ahead for gen AI edge — despite misgivings

CIO Business Intelligence

Gen AI boom in the making Many early and established forays into generative AI are being developed on the AI platforms of cloud leaders Microsoft, Google, and Amazon, reportedly with numerous guardrails and governance measures in place to contain unrestricted exploration.

Risk 130
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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. This personalized approach might lead to more effective therapies with fewer side effects.

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What Is DataOps? Definition, Principles, and Benefits

Alation

DataOps is essentially a mix of these methodologies: Lean manufacturing. Automated testing to ensure data quality. Alation provides robust DataOps solutions that help you foster collaboration, build trusted data solutions, automate testing & monitoring, and visualize data pipelines. Analytics is manufacturing.

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Frugal AI: Value at Scale Without Breaking the Bank

Dataiku

The research confirmed that, even on common AI models, the process can emit more than 626,000 pounds of carbon dioxide equivalent — nearly five times the lifetime emissions of the average American car (and that includes the manufacturing of the car itself). Today, in 2022, the code (i.e.,