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Data center hardware, by contrast, is a scarce commodity with rapidly growing demand, and therefore likely to capture most of the profits from AI and software development, if current market conditions persist.
Today's IT business trends represent a remarkable change in the industry compared to the situation 50 years ago, when startups like Microsoft and Oracle, whose business models were based exclusively on software development, challenged and overthrew the dominant player, IBM, whose primary source of revenue was from hardware.
Have you read John Carreyrou's award-winning book Bad Blood? Have you seen the HBO documentary directed by Alex Gibney that chronicles the rise and fall of Theranos and its blood-testing claims, The Inventor: Out for Blood in Silicon Valley. For my part, I have indeed read Carreyrou's book, and I watched Gibney's documentary, and I also followed the press coverage of Theranos and the criminal trial of Elizabeth Holmes. It is on the basis of all this evidence that I am speaking knowledgeably about the facts concerning Elizabeth Holmes, including the likelihood that she is a almost certainly guilty of the crimes for which she was convicted.
And what about you? Do you know anything about Holmes beyond the pseudo-documentary you just saw? The reason why I have replied to your question with a question is because you also seem to be talking in a "Holmesian" manner, taking everything she does and says at face value. So it seems like a valid question to inquire about your level of knowledge about her criminal record. Another interesting question is: Do you really believe, against all the evidence, that Elizabeth Holmes could be innocent?
There was a mountain of evidence against Holmes, and she was convicted in a criminal trial. So it seems like a safe assumption that she was guilty.
Does it follow then that, because she is almost certainly guilty, that she must be "incredibly self-aware"? Of course not. It's just as likely that she is totally lacking in self-awareness, and that she simply does not know when to shut her mouth because she has no idea how stupid she sounds.
Ian Ayres (2007) Super Crunchers: Why Thinking by Numbers is the New Way to Be Smart.
Joseph Healey (2020) Statistics: A Tool for Social Research [This is the textbook used in the class, which I highly recommend].
John Allen Paulos (1988) Innumeracy: Mathematical Illiteracy and Its Consequences.
Nate Silver (2012) The Signal and the Noise: Why So Many Predictions Fail, but Some Don't.
Nassim Nicholas Taleb (2005) Fooled by Randomness, second edition.
Nassim Nicholas Taleb (2010) The Black Swan: The Impact of the Highly Improbable, second edition.
Ian Ayres (2007) Super Crunchers: Why Thinking by Numbers is the New Way to Be Smart
Joseph Healey (2020) Statistics: A Tool for Social Research [This is the textbook used in the class, which I highly recommend]
Catherine Marsh and Jane Elliott (2008) Exploring Data: An Introduction to Data Analysis for Social Scientists, second edition
John Allen Paulos (1988) Innumeracy: Mathematical Illiteracy and Its Consequences
Nate Silver (2012) The Signal and the Noise: Why So Many Predictions Fail, but Some Don't
Nassim Nicholas Taleb (2005) Fooled by Randomness, second edition;
_______ (2010) The Black Swan: The Impact of the Highly Improbable, second edition
David Damrosch (2007) Buried Book: The Loss and Rediscovery of the Great Epic of Gilgamesh
https://www.amazon.com/Buried-Book-Rediscovery-Great-Gilgame...
It seems possible that AI will eventually become an abundant commodity, with cheap alternatives available from China and elsewhere. And if that happens, profits will be competed away, just like any other commodity in a competitive market.
One would imagine that a Silicon Valley legend like Larry Ellison - who built his business empire on the basis of proprietary software products and services - would understand this better than anyone.
https://forum.endeavouros.com/t/malicious-aur-checkup-script...
Yes, I agree, that's a good call. I would not try to check for anomalies manually with meatware. I would parse the data with python regex tools to establish a baseline and search for anomalous patterns.
I edited my post to reflect the change you suggested.
If you have a list of good CLI utilities, you could run them in a bash script (e.g., network-monitor.sh), which would run in the background, and then redirect the output data to another file (e.g., network-monitor.txt). The key concept here is "baseline" -- you need to know what normal baseline network activity looks like, so that you can identify anomalous behavior. The way to establish a baseline is to gather a lot of data from the system.
The following are a few useful command line utilities to use for a host intrusion detection system (HIDS) using a simple network monitoring bash script. However, I am not sure exactly how to tweak the options. Also need to find a way to check for data exfiltration:
-list open ports and processes that own them: netstat -lnp
-show open network ports: lsof -i; netstat -an | grep -i listen; netstat -nap
Then it would be relatively easy to write a python script with regex tools to parse the network-monitor.txt file, establish a baseline, analyze the data for patterns and search for anomalous behavior.
Besides network monitoring, there are other command line utilities you can use to check the system for possible intrusion, which you could run in a separate bash script as part of your Host Intrusion Detection System (e.g., hids-users.sh):
-show members of root group: cat /etc/group | grep root
-show users logged in: w #if you are the only user, you should not see more than one account logged in
-search for all accounts with UID of 0: grep :0: /etc/passwd #ideally there should be only one UID of 0 on the system, but attacker can create more.
-check that daemons who never log in have * or !, meaning no passwd: cat /etc/shadow
-look for orphaned files, possible sign of attacker temp account deleted: find / -nouser -print
-search for new user accounts that are not part of regular build: sort -nk3 -t: /etc/passwd #sort numerically third column (UID), colon delim (-t:)
EDITS: several small changes for clarity and also in response to comment below
US law enforcement agencies get much of their information from data brokerage firms, which collect and aggregate information from public records and private sources, e.g., drivers licenses, mortgages, social media, retail loyalty card purchases, professional credentials, charities’ donor lists, bankruptcies, payday lenders, warranty registrations, and other sources who sell personal data. This information is then sold to customers willing to pay for it. Not even the FTC can find out exactly where the data brokers get their information because brokerages cite trade secrecy as an excuse not to divulge their sources.
Law enforcement agencies not only uses data collected by private firms, they also use corporate IT platforms and proprietary software applications (e.g., Palantir, Microsoft, Amazon) to store, share and analyze data. Palantir provides an interface that runs on top of other data systems, including legacy systems, making it possible to link data points across separate systems.
Source: Sarah Brayne (2020) Predict and Surveil: Data, Discretion, and the Future of Policing, Oxford University Press, pp. 24-25, 41-42.
As a percentage of GDP, government debt is high by historical standards, and it is rising at a fairly rapid pace. That could be a problem if it continues unabated. But there are two solutions: reduce spending and/or raise taxes. Most U.S. federal expenditure goes toward either defense, entitlements or interest on the debt, so it seems unlikely that spending will fall very much. That means higher taxes. At some point, the country will need to find a political reformer who can sell tax increases to the electorate. Until then, the crisis just continues to quietly grow.
[1] Giovanni Arrighi (1994) The Long Twentieth Century: Money, Power and the Origins of Our Times
https://www.amazon.com/Long-Twentieth-Century-Money-Origins/...
Also, Egypt and the UAE are on opposite sides of the conflict in Sudan: Egypt supports the Sudanese Armed Forces (SAF), while the Emiratis support the Rapid Support Forces (RSF).
Dr. Pasricha adds: "I don’t get too concerned if my patients take one or two doses every now and then. But through regular use, such as several times a month or more, NSAIDs are well-known to increase intestinal permeability. In other words, NSAIDs can damage the lining of our guts. That’s because NSAIDs reduce the blood flow in the tiny vessels feeding our guts and disrupt the intestinal cells forming a barrier between the outside world and your insides. This has been proven over and over again through decades of research."
Conclusion: Acetaminophen is generally safer than ibuprofen, naproxen and aspirin.
https://www.washingtonpost.com/wellness/2024/12/09/ibuprofen...
Sarah Brayne (2020) Predict and Surveil: Data, Discretion, and the Future of Policing, Oxford University Press
https://www.amazon.com/Predict-Surveil-Discretion-Future-Pol...
An academic study about the use of surveillance technology at the Los Angeles Police Department, the book documents the LAPD's use of data brokerage firms (e.g., Palantir) that collect and aggregate information from public records and private sources, as well as automatic license plate readers like Flock, and Suspicious Activity Reports generated by police and civilians, which include reports of mundane activities such as using binoculars, drawing diagrams, or taking pictures or "video footage with no apparent aesthetic value." All this data ultimately gets parked in Fusion Center facilities, built in the aftermath of 9/11, where federal, state and local law enforcement agencies collaborate to collect, aggregate, analyze and share information. As the author observes, "The use of data in law enforcement is not new. For almost a century, police have been gathering data, e.g., records of citations, collisions, warrants, incarcerations, sex offender and gang registries, etc. What is new and important about the current age of big data is the role in public policing of private capitalist firms who provide database systems with huge volumes of information about people, not just those in the criminal justice system."
Virtually all the technology used by this Mexican company, Grupo Seguritech, is imported from other countries. As a university student, I completed a Master's thesis about export manufacturing industries in Mexico. Then as now, the vast majority of manufacturing exports were (and still are) produced by foreign capital. Today Mexican capital contributes relatively little to the total value of manufactured exports. This is an important consideration: even in Mexican firms like Grupo Seguritech that are operating in other countries, such firms are not really in control of this technology, they are only licensing it from abroad. Foreign capital owns and controls the tech, and foreign capital reaps a substantial share of the profits.
> Flock has recently expanded into other technologies... Most concerning are the latest Flock drones equipped with high-powered cameras. Flock's "Drone as First Responder" platform automates drone operations, including launching them in response to 911 calls or gunfire. Flock's drones, which reach speeds up to 60 mph, can follow vehicles or people and provide information to law enforcement.
What is the evidence to support such a hypothesis? President Trump himself recently revealed the existence of a new secret energy weapon that was used to disable Nicolás Maduro's security team during the raid to capture the Venezuelan president [1].
According to one of Maduro's guards quoted by the New York Post: “At one point, they launched something; I don’t know how to describe it. It was like a very intense sound wave. Suddenly I felt like my head was exploding from the inside,” the witness said. "We all started bleeding from the nose. Some were vomiting blood. We fell to the ground, unable to move. We couldn’t even stand up after that sonic weapon — or whatever it was."
[1] https://nypost.com/2026/01/24/us-news/trump-reveals-to-the-p...