The Ad Tech Blog
MAY 4, 2024
Understanding Federated Learning in Ad Tech Key Points Federated learning allows multiple devices to contribute to machine learning models without sharing the data itself, enhancing privacy. Frequently Asked Questions What is federated learning? How does federated learning enhance privacy?
The Ad Tech Blog
MARCH 10, 2024
As healthcare technology ventures continue to push the boundaries of innovation, understanding the legal framework that governs patient data privacy is not just optional — it’s imperative. Can startups use patient data for machine learning without violating HIPAA? Why Compliance Matters ? – Yes, but with conditions.
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The Ad Tech Blog
OCTOBER 4, 2023
However, determining the exact stage of AI development with precision can be challenging due to the multiple dimensions and varied applications of AI technologies: Irruption: The irruption phase might be associated with the rise of machine learning and, more specifically, deep learning around the 2010s, capturing the world’s attention.
The Ad Tech Blog
APRIL 26, 2024
Yes, AUIs have applications across various industries, including healthcare, e-commerce, and education, where personalized user experiences can significantly enhance engagement and outcomes. It is crucial to implement robust data protection measures and ensure transparency in how user data is used.
Martech Series
SEPTEMBER 9, 2022
Marketing Technology News: Guide to Navigating the Future of Healthcare With Conversational AI. The ad tech industry is aware of this problem and has been working on various solutions: The IAB Tech Lab has recommended the use of “App Store IDs” to uniquely identify CTV apps.
MNTN
JUNE 3, 2022
Reimagine the Ad Experience – With easy access to streaming content, consumers are deciding when, where and how to watch their favorite content and expect excellence at every point. 8 Machine Learning Examples From Brands To Inspire Digital Marketers – Machine learning is making waves in the digital marketing world.
Martech
OCTOBER 21, 2021
Many call analytics platforms use a variety of natural language processing (NLP) and machine-learning algorithms to automatically assess calls and score leads. Call data privacy continues to be a priority, particularly for businesses in the healthcare and financial services markets, which must comply with HIPAA and HITECH regulations.
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