Machine Learning Research Training 
TechCrunch
APRIL 7, 2021
One of the more tedious aspects of machine learning is providing a set of labels to teach the machine learning model what it needs to know. It also announced a new tool called Application Studio that provides a way to build common machine learning applications using templates and predefined components.
O'Reilly Media - Data
DECEMBER 12, 2019
For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. 8] Data about individuals can be decoded from ML models long after they’ve trained on that data (through what’s known as inversion or extraction attacks, for example). ML security audits.
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O'Reilly Media - Data
NOVEMBER 25, 2019
In this interview from O’Reilly Foo Camp 2019, Dean Wampler, head of evangelism at Anyscale.io, talks about moving AI and machine learning into real-time production environments. In some cases, AI and machine learning technologies are being used to improve existing processes, rather than solving new problems.
CIO
SEPTEMBER 8, 2022
Machine learning (ML) is a commonly used term across nearly every sector of IT today. This article will share reasons why ML has risen to such importance in cybersecurity, share some of the challenges of this particular application of the technology and describe the future that machine learning enables.
CIO
OCTOBER 28, 2024
Despite its wide adoption, researchers are now raising serious concerns about its accuracy. In a study conducted by researchers from Cornell University, the University of Washington, and others, researchers discovered that Whisper “hallucinated” in about 1.4% Whisper is not the only AI model that generates such errors.
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.
AWS Machine Learning - AI
NOVEMBER 27, 2024
Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters and larger input sequence length. This approach reduces memory pressure and enables efficient training of large models.
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