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Articles by D. Sculley
Why over 140,000 developers took our five-day generative AI course
Because the field of AI is moving so fast, it’s more important than ever that developers, enthusiasts and learners around the world can build their skills by learning directly from the leading experts. That is why Google and Kaggle created our free, five-day Gen AI Intensive live course. The content was thoughtfully designed to give participants a strong understanding of generative AI, from the basics of large language models (LLMs) to actually using gen AI with tools in production.
Why over 140,000 developers took our five-day generative AI course
Now Intel CEO resigns after a disastrous tenure CNN — Intel Monday announced CEO Pat Gelsinger has resigned after a difficult stint at the company. The once-dominant chipmaker’s stock cratered as it missed the AI boom and was surpassed by most of its rivals. Gelsinger took over as Intel’s chief executive in February 2021, returning to the company … Now 7 Free Generative AI Courses For 2025 Generative AI is the future of innovation and creativity for businesses and professionals.
Machine Learning: The High Interest Credit Card of Technical Debt – Google Research
Download Google Scholar Copy Bibtex Abstract Machine learning offers a fantastically powerful toolkit for building complex systems quickly. This paper argues that it is dangerous to think of these quick wins as coming for free. Using the framework of technical debt, we note that it is remarkably easy to incur massive ongoing maintenance costs at the system level when applying machine learning.
Reliable Machine Learning
Book description Whether you're part of a small startup or a planet-spanning megacorp, this practical book shows data scientists, SREs, and business owners how to run ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization.
Machine Learning: The High Interest Credit Card of Technical Debt
Machine learning offers a fantastically powerful toolkit for building complex systems quickly. This paper argues that it is dangerous to think of these quick wins as coming for free. Using the framework of technical debt, we note that it is remarkably easy to incur massive ongoing maintenance costs at the system level when applying machine learning. The goal of this paper is highlight several machine learning specific risk factors and design patterns to be avoided or refactored where possible.
Hidden Technical Debt in Machine Learning Systems
A note about reviews: "heavy" review comments were provided by reviewers in the program committee as part of the evaluation process for NIPS 2015, along with posted responses during the author feedback period. Numerical scores from both "heavy" and "light" reviewers are not provided in the review link below. Machine learning offers a fantastically powerful toolkit for building useful complexprediction systems quickly. This paper argues it is dangerous to think ofthese quick wins as coming for free.
Machine Learning: The High Interest Credit Card of Technical Debt
Machine learning offers a fantastically powerful toolkit for building complex systems quickly. This paper argues that it is dangerous to think of these quick wins as coming for free. Using the framework of technical debt, we note that it is remarkably easy to incur massive ongoing maintenance costs at the system level when applying machine learning. The goal of this paper is highlight several machine learning specific risk factors and design patterns to be avoided or refactored where possible.
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