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Executing Data Projects in the Age of Data Privacy

Dataiku

With some industry experts naming 2019 as the year of increased data regulation, it’s certainly true that at this point, there is no looking back - the use of data across roles and industry will only become increasingly restricted. But that doesn’t have to mean a pause or paralyzation in data use.

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3 data security disciplines to drive AI innovation

CIO Business Intelligence

AI hype and adoption are seemingly at an all-time high with nearly 70% of respondents to a recent S&P report on Global AI Trends saying they have at least one AI project in production. The surging interest in implementing AI has directly increased the volume of data that organizations store across their cloud environments.

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Gen AI’s ultimate potential? Hive mind teamwork

CIO Business Intelligence

This enemy could form a plan, execute it on the battlefield, and be onto their next target before we knew what was happening. They could execute quickly, adapt on a dime, and strike with devastating effect. Organizations with execution processes built for speed will be positioned to gain the most from LLMs. Our solution?

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Why you should care about debugging machine learning models

O'Reilly on Data

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. Not least is the broadening realization that ML models can fail.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. According to a survey by the MIT Sloan Management Review, nearly 85% of executives believe generative AI will enable their companies to obtain or sustain a competitive advantage.

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Enterprises need generative AI tailored to their unique needs, with their own unique data

IBM Big Data Hub

According to a Gartner® press release detailing executive survey insights, “On average, 54% of AI projects make it from pilot to production.” According to a Gartner® press release detailing executive survey insights, “On average, 54% of AI projects make it from pilot to production.”

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5 Ways Your Retail Banks Can Use Data to Better Serve Digital Natives

Smart Data Collective

There is no disputing the fact that data technology has changed the future of the financial industry. One of the sectors most impacted by big data has been banking. Big data is even more important to the banking sector as more of their services become digitalized. billion by 2026.

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