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Understanding Artificial Intelligence, Machine Learning, and Deep Learning

Daniel Burrus

While several companies are on course to use artificial intelligence (AI), machine learning (ML), and deep learning (DL), others hardly understand the fundamental differences between these powerful technologies. Machine Learning ? Deep Learning. What Exactly Is AI ?

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Challenges of Artificial Intelligence Adoption, Dissemination and Implementation

Innovation Excellence

Sickcare artificial intelligence products and services have a unique set of barriers to dissemination […]. Here is what you should know about dissemination and implementation.

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Revolutionize Your Innovation: Embrace the Power of Lean Startup Methodology

Leapfrogging

It draws inspiration from lean manufacturing principles and applies them to the context of entrepreneurship and product development. At its core, Lean Startup emphasizes the importance of building a minimum viable product (MVP), measuring its performance, and learning from the feedback to make rapid adjustments.

LEAN 100
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2024 Innovation Resources Wrapped: Entrepreneurial Books, Podcasts, and Tools

Innovators Alliance

Heres to a new year filled with growth, innovation, and even more inspiring ideastogether, were shaping the future of entrepreneurship. These resources represent just a glimpse of the knowledge exchanged within our network over the last few months. Lets keep the momentum going in 2025. Looking for more resources from IA members?

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A Brief History of AI: From Neural Networks to ChatGPT

Planview

Artificial Intelligence (AI) often seems like an overnight success story, but its roots stretch back more than 80 years. The era of machine learning The 2000s marked the beginning of machine learning infiltrating our lives through applications like Google, Yelp, and Waze. Here are some examples.

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Checking for the global pulse of innovation

Paul Hobcraft

The scope of “ breakthrough innovation ” is coming increasingly reliant on digital technologies, automation, data processing and artificial intelligence (AI) the view is this has a longer-term impact and is potentially drawing from the immediate and medium-term innovation as this shift in innovation continues to gather momentum.

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How Communities Are Leveraging Technology to Address Racial Equity

IdeaScale

One of the most uncomfortable discoveries in the early years of machine learning was that long-standing social biases emerged from data. While machine learning and data science were being embraced with enthusiasm, these were reminders that biases were built into data sets and needed to be compensated for.