Tag: Artificial Intelligence

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Artificial Intelligence Education Innovation Reading

Latest Read: AI and Machine Learning for Coders

AI and Machine Learning for Coders: A Programmer’s Guide to Artificial Intelligence by Laurence Moroney.

AI and Machine Learning for Coders: A Programmer’s Guide to Artificial Intelligence by Laurence Moroney

Laurence holds a BSc in Physics and Computer Science from Cardiff University, Postgraduate Diploma in Microelectronics Systems Design from Birmingham City University and a Graduate Certificate in Artificial Intelligence from Stanford University.

He was Global AI Advocacy Lead at Google for 10 years and Senior Developer Evangelist at Microsoft for 7 years. In fact, today he is Senior Fellow at The AI Fund, and Artificial Intelligence Advisor and Fellow at RealAvatar. Laurence has also taught millions of students through online platforms such as Coursera, Udacity, and edX.

This book is certainly an amazing guide designed for programmers looking to transition into AI and machine learning with a focus on computer vision, natural language processing (NLP), and sequence modeling with code samples and projects.

To no surprise Laurence is driving this on TensorFlow, Google’s tool for for building models on multiple platforms including Raspberry Pi for deployments on web, mobile (Android and iOS), cloud, and embedded systems.

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Artificial Intelligence Education Innovation Reading

Latest Read: Evolutionary Deep Learning

Evolutionary Deep Learning: Genetic algorithms and neural networks by Micheal Lanham.

Evolutionary Deep Learning: Genetic algorithms and neural networks by Micheal Lanham

Today Michael is a Lead AI Developer at Brilliant Harvest Inc. and also a Technical author at Manning Publications. Previously he worked at Symend as a Principle AI Engineer and Manager of ML Engineering.

This books expands upon his knowledge in deep learning, evolutionary computation, and genetic algorithms. This was a very enlightening read and will be very interesting for those interested in a comprehensive understanding of deep learning today.

The book is certainly written for data scientists using Python. This offers a very deep perspective on the combination of evolutionary principles with deep learning.

This results in enhanced model performance with the ability to solve complex problems with machine learning.

Michael is able to address multiple themes related to the link with computation and deep learning techniques. The book is structured in three main parts:

  1. Getting Started:
    Introduces evolutionary deep learning, evolutionary computation, and genetic algorithms using DEAP (Distributed Evolutionary Algorithms in Python).
  2. Optimizing Deep Learning:
    Covers automated hyperparameter optimization, neuroevolution optimization, and evolutionary convolutional neural networks.
  3. Advanced Applications:
    Explores evolving autoencoders, generative deep learning with evolution, NeuroEvolution of Augmenting Topologies (NEAT), and future directions in evolutionary machine learning..
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Artificial Intelligence Education Reading

Latest Read: Generative AI in Practice

Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society by Bernard Marr.

Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society by Bernard Marr

He holds degrees in business, engineering and information technology from the University of Cambridge and Cranfield School of Management. He has written several books and two that I have read include his 2015 release Big Data Using smart big data and his recent book Artificial Intelligence in Practice. That said, this book falls short. I feel this was a rushed effort to get into the Generative AI hype cycle.

So here, Bernard is focusing on Generative AI as the biggest advancement in technology in the history of the world and how ChatGPT is driving this new somewhat magic service. Actually the metrics seem to confirm: 10 million users within 30 days of launch and then a stunning 100 million within the next 60 days. Simply put, the fastest adoption of technology in the history of computing. But don’t forget the cost Bernard.

In the rush for all things Generative AI, this new subset of Machine Learning is driving the AI hype cycle even higher than many would conclude possible. Generative AI can of course create visual graphics, computer code, and music. Seems to be the ‘generative’ in Generative AI.

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Artificial Intelligence Education Reading

Latest Read: AI and Machine Learning for On-Device Development

AI and Machine Learning for On-Device Development: A Programmer’s Guide by Laurence Moroney.

AI and Machine Learning for On-Device Development: A Programmer's Guide by Laurence Moroney

Laurence holds a Bachelor of Science in Physics and Computer Science from Cardiff University, PgD, Microelectronics Systems Design from Birmingham City University and Graduate Certificate in Artificial Intelligence from Stanford University.

Today he is Chief AI Scientist at VisionWorks Studios. He previously was an AI Advocate at Google for 10 years and served as a Senior Developer Evangelist at Microsoft. He wrote this book in 2021 and previously published AI and Machine Learning for Coders in 2020.

While OpenAI’s ChatGPT kick started the LLM surge, AI will simply be a component installed upon our mobile devices. The OpenAI/Microsoft partnership is certainly enterprise focused, Google Gemini and Apple will drive their Android and iOS devices to simply adopt AI as part of their mobile ecosystem. Phones will simply remain the go to device.

So, there was a lot of buzz regarding new AI devices including Humane’s AI Pin or the Rabbit R1. Their rush to market to capitalize on the AI hype cycle leads to critical mistakes.

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Artificial Intelligence Education Reading

Latest Read: Your Face Belongs to Us

Your Face Belongs to Us: A Secretive Startup’s Quest to End Privacy as We Know It by Kashmir Hill.

Your Face Belongs to Us: A Secretive Startup’s Quest to End Privacy as We Know It by Kashmir Hill

Kashmir holds a masters degrees in journalism from New York University. Her writing has appeared in The New Yorker and The Washington Post. Kashmir is a technology reporter at The New York Times after having worked at Gizmodo Media Group, Fusion, Forbes Magazine, and Above the Law.

Perhaps of the most shocking books in fact that I have read in some time. Kashmir is documenting how a small AI company provided facial recognition to law enforcement, billionaires, and businesses. Yet, it should be no surprise this has eroded privacy as we know it.

Kashmir introduces readers to this chilling story as a skeptic. A tip regarding a mysterious app called Clearview AI held a claim it could with 99% accuracy identify anyone based upon a single photograph of their face. The app indeed provided a person’s online name, social media profiles, friends, family members, and their home address. This was just for starters and in the wrong hands, would be a very powerful surveillance tool.

Clearview AI was a start up run by Australian computer engineer Hoan Ton-That and Richard Schwartz, a former Rudy Giuliani advisor. The company was funded by conservative provocateur Charles C. Johnson and billionaire Donald Trump backer Peter Thiel. In contrast, Google and Facebook chose that this type of tool was too dangerous to release. However, via private investors, Clerview AI would be pitched to thousands of law enforcement agencies around the world.

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