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Latest Read: 97 Things Every Data Engineer Should Know

97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts. Edited by Tobias Macey, host of the popular Data Engineering Podcast.

97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts by Tobias Macey

This book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will benefit from the wisdom and first hand experiences of their peers.

The Data Engineer is a rather new role. However, the management of data has been well known for over a generation. Data engineers tune data for use in analytics and machine learning. Today AI, Data Lakes, Predictive Analytics, and Data Science all roll up into the modern Data Engineer. This is a series of high level insights from various professionals. They work at Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn.

Readers who seek insights will certainly find this a good reference. Since the topics range widely there is a good probability you will need to keep this reference within reach. It is refreshing to see contributions crossings areas that will be new to most readers.

Admittedly, the chapter on Data Security for Data Engineers by Katharine Jarmul from Thoughtworks is certainly a must read. In addition, Privacy Is Your Problem by Stephen Bailey must be on your list. The variety of topics is also appealing, so be ready to gain insights. Their shared postings have good ideas, warnings, and best practices all melting together.


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Artificial Intelligence Cyberinfrastructure Education Reading

Latest Read: Cybersecurity: The Insights You Need

Cybersecurity: The Insights You Need from Harvard Business Review.

Cybersecurity: The Insights You Need from Harvard Business Review

So let’s start with the end in mind to avoid all misunderstandings: this is targeted to every leader and board member regardless of market or industry. They simply must fully comprehend why cybersecurity has been and always will be an ongoing risk.

This is a well written, high level and most importantly a non-technical overview of cybersecurity. This risk can no longer be overlooked by organizations and delegated like it was 1994. Today more than ever before cybersecurity impacts your bottom line, including non-technology based organizations.

And in 2024 we can simply cut to the chase. If your organization’s cybersecurity service is not AI based, it is time to pivot to a vendor that deploys machine learning services to protect your organization, your data and most importantly, your customer data. Just query your insurance carrier for a list of approved vendors that deploy AI cybersecurity services. For the most part the pandemic made this pivot mandatory.

In fact, cyber risk management can no longer be isolated to your organization’s CIO and CISO. This is simply an organization-wide issue. Today every organization’s technology services group have become the key component for organizational success.

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Artificial Intelligence Education Reading

Latest Read: Generative AI : The Insights You Need

Generative AI: The Insights You Need from Harvard Business Review

Generative AI: The Insights You Need from Harvard Business Review

The world discovered Generative AI in the beginning of 2023. ChatGPT introduced over 100 million users to the possibilities of Generative AI. In less than 18 months society has shifted. With Wall Street and Madison Avenue literally banking on new markets, business, education and our globally connected society are witnessing transformation. Microsoft’s $10 billion investment in OpenAI is perhaps the strongest indicator of what GenAI will be expecting to produce. However, there certainly remains a big hill to climb.

New AI startups are creating GenAI business models around generating text, images, code and even animation and video via Sora at rather amazing speeds. GenAI is certainly altering how humans create content on a scale and speed not previously understood by society, government, business and education. So get ready for disruption.

This book will help understand the baseline of GenAI and the potential to change the world. Yet for the organization who decides to jump right in, make sure you understand Chapter 3:?A Framework for Picking the Right Generative AI Project. AI is not the web and GenAI is not html. Organizations must understand risk. Just ask Samsung and you will quickly understand why tech companies are banning GenAI within their internal networks.

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Artificial Intelligence Education Reading

Latest Read: Introduction to Generative AI

Introduction to Generative AI by Numa Dhamani and Maggie Engler.

Introduction to Generative AI by Numa Dhamani and Maggie Engler

Numa holds degrees in Physics and Chemistry from the University of Texas at Austin. She has served as the Principal Investigator on the United States Department of Defense’s research program. Today she is a Principal Machine Learning Engineer at Kungfu.ai.
Numa is an adjunct instructor at Georgetown University.

Maggie holds Masters in Electrical Engineering from Stanford University. She is a safety team member at Inflection AI. Previously Maggie was a Data Science Fellow at the Center for New Data and a Senior Machine Learning Engineer at Twitter. Maggie is also an adjunct instructor at the University of Texas at Austin School of Information.

Perhaps this book should be required reading for any organization’s AI planning team. Yes, your AI staff should have this well understood. However Numa and Maggie convey a grounded understanding of large language models (LLMs). In addition, you will understand the new rush for integrating generative AI (Microsoft and OpenAI) into your organizational workflows. To be fair, they also are addressing organizational benefits, risks, and limitations.

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Artificial Intelligence Education Reading

Latest Read: The Language of Deception

The Language of Deception: Weaponizing Next Generation AI by Justin Hutchens.

The Language of Deception: Weaponizing Next Generation AI by Justin Hutchens

He holds a masters in Computer Security Management from Strayer University and is a candidate Executive MBA at Texas A&M University.

Justin is a former Director, Cybersecurity Implementation & Operations at PwC and Cybersecurity Instructor at The University of Texas at Austin. Today he is a principal at Trace3.

Justin has written an insightful book. In fact, this should be recommended reading for everyone managing AI projects, they’re teams and of course cybersecurity professionals.

So, remember the hype cycle for AI peaked after OpenAI introduced ChatGPT in November 2022? The amazing explosion of ChatGPT’s adoption rate overshadow very basic security flaws within AI systems. Justin is addressing to reveal how AI services are not secure by the companies who are heavily promoting their AI services. And this allows for exploits to thrive since all the attention continues to focus on AI’s hype cycle.