Machine Learning Research Systems Review 
CIO
NOVEMBER 27, 2024
Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.
O'Reilly Media - Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. We’ll review methods for debugging below. Not least is the broadening realization that ML models can fail.
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CIO
OCTOBER 29, 2024
Imagine a hacker compromising a healthcare database and simply changing the blood type of every individual in a research study or the entire patient population. Maintaining a clear audit trail is essential when data flows through multiple systems, is processed by various groups, and undergoes numerous transformations.
CIO
JANUARY 8, 2025
Increasingly, however, CIOs are reviewing and rationalizing those investments. While up to 80% of the enterprise-scale systems Endava works on use the public cloud partially or fully, about 60% of those companies are migrating back at least one system. Judes Research Hospital St. We see this more as a trend, he says.
CIO
JANUARY 5, 2025
Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1]
TechCrunch
AUGUST 19, 2023
So until an AI can do it for you, here’s a handy roundup of the last week’s stories in the world of machine learning, along with notable research and experiments we didn’t cover on their own. This week in AI, Amazon announced that it’ll begin tapping generative AI to “enhance” product reviews.
CIO
MARCH 11, 2025
A successful agentic AI strategy starts with a clear definition of what the AI agents are meant to achieve, says Prashant Kelker, chief strategy officer and a partner at global technology research and IT advisory firm ISG. Its essential to align the AIs objectives with the broader business goals. Agentic AI needs a mission. Feaver says.
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