
Matt Casey
Articles
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Nov 25, 2024 |
snorkel.ai | Matthew Casey |Matt Casey |Venkatesh Rao
Large Language Models (LLMs) are redefining what’s possible across industries. They represent a significant leap forward in transforming enterprise processes and enhancing customer interactions. However, LLM evaluation poses complex challenges for enterprises who wish to deploy them. LLMs behave differently from traditional models, meaning data scientists must assess them differently. Traditional record-by-record assessments used in machine learning don’t apply.
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Nov 19, 2024 |
latitudemedia.com | Matt Casey
The reality is that there are multiple types of AI, like machine learning or deep learning, that can be utilized in nuanced, specific ways that don’t involve the rollout of an autonomous, black-box solution — like merging disparate data sets to inform more accurate forecasts, or analyzing image-based data to anticipate potential equipment failure.
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Nov 15, 2024 |
adage.com | Matt Casey
Today, there’s a podcast for every listener, whether they want captivating storytelling, deep dives into passion points, fascinating conversations or emotional journeys. That means there’s also a podcast for every advertiser—and savvy brands are all-in. With nearly 100 million Americans tuning in weekly—and 86% of frequent listeners recalling podcast ads better than any other channel¹—podcasts are a welcome space for advertisers looking to connect with an engaged, ad-receptive audience.
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Nov 14, 2024 |
latitudemedia.com | Matt Casey
The story is even more stark for the PJM grid region, with the report finding that in 2023 almost 70% of renewable power generated within PJM was undeliverable to Virginia’s Dominion Energy’s territory, amidst an anticipated 11 GW of demand from new data centers in Northern Virginia expected by 2030.
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Nov 13, 2024 |
snorkel.ai | Matthew Casey |Matt Casey |Minhajul Hoque
What is AI data development? AI data development includes any action taken to convert raw information into a format useful to AI. This definition covers everything from the point of acquiring data to the point at which a data scientist exports a model for deployment.
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