CIO Business Intelligence

APRIL 12, 2024

These roles include data scientist, machine learning engineer, software engineer, research scientist, full-stack developer, deep learning engineer, software architect, and field programmable gate array (FPGA) engineer. It is used to execute and improve machine learning tasks such as NLP, computer vision, and deep learning.

Deep Learning 122

Deep Learning IT Machine Learning IoT 122

CIO Business Intelligence

JUNE 7, 2022

In business analytics, this is the purview of business intelligence (BI). Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. Data analytics salaries.

Data Analytics 122

Data Analytics Diagnostic Analytics Management Analytics 122

CIO Business Intelligence

OCTOBER 4, 2023

We grew hand in hand with eBay and have continued to do so after separating in 2015.” Forward-looking disruptive technologies Although the brand has various cutting-edge technologies in its hands, one of the most relevant for the future development of the business is AI.

Digital Transformation 116

Digital Transformation Deep Learning Data Lake Risk 116

CIO Business Intelligence

DECEMBER 1, 2023

Laying the foundation for innovation None of this would have been possible without having migrated to the cloud, which LexisNexis began in 2015. But perhaps the biggest benefit has been LexisNexis’ ability to swiftly embrace machine learning and LLMs in its own generative AI applications. But it was an uphill climb to get to the cloud.

Cost-Benefit 110

Cost-Benefit Digital Transformation Machine Learning Optimization 110

CIO Business Intelligence

SEPTEMBER 19, 2023

AI personalization utilizes data, customer engagement, deep learning, natural language processing, machine learning, and more to curate highly tailored experiences to end-users and customers.

Enterprise 138

Enterprise Cost-Benefit Optimization Deep Learning 138

Domino Data Lab

JULY 2, 2019

Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. For more background about program synthesis, check out “ Program Synthesis Explained ” by James Bornholt from 2015, as well as the more recent “ Program Synthesis in 2017-18 ” by Alex Polozov from 2018.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105