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Unlike Bezos and Branson, they're going to stay there. Today we have space-based internet access and a terrestrial internet; within ten years, we'll have a space-based internet. Internet traffic will travel more miles in space than on terrestrial fiber. By that time, the great cloud data centers of Google, Amazon, Microsoft, and their competitors and successors will mostly be in orbit as well. Five years from now, this transition will be obvious, accepted, and well underway...
On the afternoon of June 17 of this year, there was a widespread outage of online services. In Australia, it impacted three of the country's largest banks, the national postal service, the country's reserve bank, and one airline operator. Further afield from Australia, the outage impacted the Hong Kong Stock Exchange and some US airlines. The roll call of affected services appeared to reach some 500 serv
Anyone who works in privacy is familiar with the term "data shadow": the digital record created by our transactions, our travels, our online activities. But where did the phrase come from? Who used it first? A number of authors have attributed it to Alan Westin, whose seminal book Privacy and Freedom (largely a report on the work of the Committee on Science and Law of the Association of the Bar of the City of New York) set the stage for most modern discussions of privacy.
The experience of interviewing a data scientist is like none other. Over the past year, we've interviewed more than 100 data scientists, and most, if not all, of them are brilliant. After all, they are a data scientist and have spent many years mastering their craft. The purpose of this post is to potentially assist technology leaders who are considering hiring a data scientist or a data science team. There are five items of consideration.
A few months ago, I reported on the broader market of which telecommunications infrastructure is a part. I mentioned data centers, cloud computing and data analytics (big data). All together, we can perhaps best call this digital infrastructure. While the importance of this merged set of infrastructures will benefit all economies and societies, I recently focused on regional developments as basically every region and every mid-size town will need to have a digital hub for local computing workloads and storage.
As the world becomes more and more reliant on electronics, it's worth a periodic reminder that a large solar flare could knock out much of the electronics on earth. Such an event would be devastating to the Internet, satellite broadband, and the many electronics we use in daily life. A solar flare is the result of periodic ejections of matter from the sun into space. Scientists still aren't entirely sure what causes solar flares, but they know that it's somehow related to shifts in the sun's magnetic field.
When valuing a stock, analysts and shareholders evaluate always revenue and profit. Big tech COFs are sitting on assets worth tens of millions of dollars of annual profit (not just revenue, but true profit) in the form of unallocated IPv4 addresses. By not selling or leasing these out, they are incurring expenses to hold them and missing out on tremendous profits. At a 20X multiple (for context, Cisco is trading at nearly 18X earnings, Google at just over 33X earnings, Shopify at well over 700X earnings), big tech CFOs are actively preventing over $250 billion in market capitalization for their shareholders.
Dear Chief Financial Officers of tech giants, the internet is in crisis, and you can lead your organization to help solve the problem. You'll be well compensated, and you'll enjoy massive public relations benefits. I fear that if you don't, global governments will force your hand. There is a shortage of available IPv4 addresses but we are years away (possibly a decade or more) from IPv6 viability and adoption in North America.
Happy New Year! There is no scarcity of Machine Learning Operations products being introduced to the industry. Since June of 2020, over 84 new ML toolsets incorporating but not confined to All-in-One, data-pipeline, and model training applications were born. In this list of almost 300 MLOps tools, there are 180 startups. Out of these 180 startups, more than 60 raised capital in 2020, and about two-thirds are fixated on data-pipelines and modeling-training.
Data analytics isn't just for large organizations anymore. As businesses and community collectives increasingly move their operations into digital spaces, the vast amounts of data being collected pose an opportunity for them to get to know their stakeholders better. While the security implications of this migration are hard to be taken lightly, the potential for game-changing insights is likewise enormous.
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