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How to Use Big Data to Cash in on the Firearms Market

Smart Data Collective

If you’ve never been aware of big data in the firearms industry, you’re in for a treat. Statistics over time have proven that the firearms industry does exceptionally well under two conditions: right before a presidential election and during a national crisis. Currently, the U.S. is facing both of these conditions at once.

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” What are the problems with quantitative data? or “how often?”

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Generative AI that’s tailored for your business needs with watsonx.ai

IBM Big Data Hub

Building transparency into IBM-developed AI models To date, many available AI models lack information about data provenance, testing and safety or performance parameters. For many businesses and organizations, this can introduce uncertainties that slow adoption of generative AI, particularly in highly regulated industries.

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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

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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. The AGI would need to handle uncertainty and make decisions with incomplete information.

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New Thinking, Old Thinking and a Fairytale

Peter James Thomas

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. Here we come back to the upward trend in searches for Data Science. King was a wise King, but now he was gripped with uncertainty. Source: Google Trends.