Warcross

Warcross by Marie Lu

Warcross is a super popular game that everyone loves to play and watch. The billionaire creator had lost his brother when he was young. Now he has a grand plan that nobody knows about.

The protagonist is a young woman who is struggling to make ends meet. She is secretly a great game player and hacker. She gets her chance to participate in the big game tournament after she hacks into the opening ceremony. The game creator recruits her as a type of "bounty hunter" to find people that may be trying to undermine him. She has a lot of success and learns a lot about the creator and enters into a small romantic relationship with him. However, one of the underworld guys she is tracking is her match. 

The story goes well, but the end gets trite. The game creator wants to eliminate crime and provide full historical access to memories. She feels that this could get people a loss of control. Maybe she should have partnered with the underworld people. But they were also mean.

The book feels a lot like Ready Player One.

The Coming Wave: AI, Power, and Our Future

The Coming Wave: AI, Power, and Our Future by Mustafa Suleyman

The author has been involved with AI. He also sees many challenges and opportunities with new technology. Humans have been able to postpone the collapse of society due to technology. We need technology. However, AI could become an existential threat. People have dominated because they are smarter than other animals. If AI is smarter than humans will we become subservient? The author proposes Universal Basic Income as part of the solution. Will this just be the equivalent of putting humans in a zoo or game reserve?

With technology we have reached the point where a single person could potentially cause the death of a billion. There are many opportunities for both good and bad in biology. AI can rapidly determine what compounds could combat diseases. This same AI could also find poisons. BioEngineered organisms could go into the wild with foreseen and unforeseen results. How can this be controlled?

Our society has depended on technology. It also has limited choke points where that could be cut off causing harm. Ransomware and other "bad actions" can impact large numbers of people across the world. Damage is not limited to certain areas.

Technology has multiple uses. Some may be useful for business while also being beneficial for military. Is the concept of a nation-state at risk. Will some aggrieved group use technology to harm large numbers of others? Will it be a terrorist group? Or perhaps animal rights activists? Or even somebody with goals that they feel altruistic. The author proposes limitations that may include censorship. However, this could be problematic due to different values. He even gave an example of one board member being forced off because people didn't like is political views. If some views are forbidden, it could lead to further separation and danger.

The Soul of A New Machine

The Soul of A New Machine by Tracy Kidder

Back in the late 1970s, minicomputers were the rage. Boston was on par with Silicon Valley. Engineers would devote years of their time to solve their problems in development. The adventure came was one of the first "video games", and also a good test of the reliability of a system. Data General was the "upstart" competitor of the established Digital Electronics. This book details the people and the work behind one of data generals new computers. While the specific problems they solved were different, the human interactions feel quite similar to those at today's aggressively growing tech companies.

Broad Band: The Untold Story of the Women Who Made the Internet

Broad Band: The Untold Story of the Women Who Made the Internet by Claire L. Evans

From Ada Lovelace to today, many women have been involved in the development of the internet. Early "computers" were women that did calculations. Later it was women that fed the programs to computers. In the age of the internet, women were very involved in hypertext and social networks. The book touches a few of the key areas of female involvement. The book inadvertently shows how insignificant the female achievements were. There were girl game companies, design houses and other companies that popped out for a bit, but flamed out before making a significant impact. On the academic side, Lovelace was ahead of her time, yet there were limited significant academic advancements. 

The story of hypertext is interesting. The hypertext of the world wide web is an inferior form that lacks many of the strengths of hypertext, yet it is what has caught on. We still deal with "dead links" due to the lack of two-way linkages. Perhaps we just had to have something that was more simple to serve as the base for something broader. Is this part of the challenge of female involvement? Some of the companies like "women portals" had high-brow goals, but ended up going general. The women-centric ended up going out of favor in favor of the more general.

Mythical Man-Month

Mythical Man-Month, The: Essays on Software Engineering, Anniversary Edition by Frederick Brooks Jr.

The details of software engineering have changed a lot in the last 50 years. There is a section devoted to memory usage and concerns of the cost of using kilobytes of memory. Documentation on paper was a thing as was talking on telephones. Programs had to be punched into a computer and run. A lot of the slow "overhead" has now been reduced. However, some of the core problems remain the same. Engineers do a poor job of estimating. The focus tends to be on the actual coding process, which is likely only a sixth of the actual time needed to develop. Then there is the root problem of the "man month".

There is a temptation to add more programmers to a project to deliver faster. However, this often fails. When done late in the cycle, this can even slow production. New team members need to be trained in the current project and culture. They also need to communicate with others. This causes immediate reduction in productivity of the existing team before producing anything of value. There are also hidden differences. Every person does things a little bit different. Incomplete understanding may cause extra communication or extra work.

Working as a smaller team may seem like a solution. In some sense it is. Start ups typically consist of a few engineers rapidly producing software. This works great for small projects with limited scope, but does not scale out. These small startups end up becoming large corporations with the struggles of large teams. To work together, they must manage different roles and responsibilities. This book proposes a few ways to manage projects, primarily focussing on limiting architects to design and set the spec, with development teams managing implementation of parts. 

The book includes an update from 1995 - which is still almost 30 years ago. The scope of changes from 1975 to 1995 are extreme, especially in comparison to those from 1995 to today. In 1975 development was on mainframe computers. New computers would often have new operating systems. Customers would have custom software written for their computers. Computing resources were costly and limited. There were few programmers, and most programming was very low level. By 1995, microcomputers were everywhere. There was abundant software that could be purchased as well as obtained for free. It is easy to write software on your local computer. Hardware has become commoditized. The same operating system will run an a large number of different hardware configurations and the same program can often be compiled or run on different operating systems.

In the past 30 years, what has changed? Hardware is faster. More memory is available. There are a greater number of tools and they are more easily available. GitHub and StackOverflow allow instant access to code samples and programming questions. AI has potential to write more code for programmers. The book even mentions AI as being something that people hoped would be "almost there" decades ago. It is still "almost there", but the almost seems to be much closer than it was back then.

Commodore: A Company on the Edge

Commodore: A Company on the Edge 2nd edition by Brian Bagnall

How would the story of Commodore be told if it had survived as a computer powerhouse until modern times? The PET was one of most important early computers. It had a strong place in the education market. The Vic-20 was the first "computer for the masses", selling over a million copied. The Commodore 64 was the best selling computer of all time. However, this often gets ignored or placed as a small footnote in computer history. The Apple II is often seen as one of the first "home computers" in Apple revisionist history. The Apple II series was produced over almost 2 decades. However, even added together, they were outsold by Commodore 64s. They were also more an amalgam of available components, while the commodore systems had more chipset innovation.

Commodore was led by Jack Tramiel. He could be just as demanding as as Steve Jobs, but lacked the cultural appeal. Tramiel also had Irving Gould as a playboy chairman getting in the way. It feels amazing that Commodore was able to accomplish what it did. The company was notoriously cheap. Tramiel would launch lawsuits against people that left. He even rescinded employee stock plans after they became "too generous".  There were great people that left because of this. Tramiel also had a hardware focus due to his calculator background. Software and compatibility were not seriously considered. 

Commodore had purchased a chip company (MOS) and designed chips in house. Chuck Peddle was the visionary behind the entry into computing. He wanted to build  a personal computer. At one point Commodore even considered buying Apple, but decided it was too expensive. (Would Apple just have faded away if that happened?) Apple was already using a MOS chip. Commodore came out with the PET and licensed Microsoft Basic for it. Could Commodore have single-handedly changed the fate of two of the big companies of today?

In the quest for cheap computers, Commodore rushed to production and forsook backwards compatibility. There was a chip design produced to enable fast 1541 disk drives on the commodore 64. However, somebody cut off some parts of the design, and thus left the world with slow disk drives. The Commodore 64 also used an older version of basic, making programming quite kludgey (with a lot of pokes). Commodore would also demo many models, and only produce the ones that looked most successful.

Commodore eventually fell apart after Tramiel was "ushered out". Commodore lost some of the decisiveness after that. Could Commodore have survived until today with different leadership? 

Four Battlegrounds: Power in the Age of Artificial Intelligence

Four Battlegrounds: Power in the Age of Artificial Intelligence by Paul Scharre

Artificial Intelligence can become a significant source of power in the world. The United States has a significant lead in AI research. However, many of the researchers are Chinese, and China is putting significant effort in implementing its own AI research. The inputs for electronic work are spread. The United States has a lead in chip design and tools. Taiwan dominates fabrication. China dominates final assembly of electronic products. The United States has tried to limit availability of technology to Chinese companies with close ties to the military. This has led to challenges with China production, but has also encouraged China to further ramp up native production.

Artificial Intelligence is different than human intelligence. Computers are able to beat humans in most games with well known rules. However, they are still slow to adapt when the rules change. Computers can do things that humans would not train doing due to danger (such as head-on airplane dog-fights.) This requires special care when humans are involved. A computer may be able to sustain high speed activity that would knock out a human. If it is a drown, that would not be an issue.  If it is assisting a human, then it well.

There is a race to do AI research. We don't fully understand the impacts. There is significant danger of the unknown. There is also danger of "bad guys" using AI for their means. Threat actors will continue to advance and be able to work around security measures. It is a challenging environment. Perhaps the only "fix" would be to run out of energy.

Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy

Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy by Ariel Ezrachi and Maurice E. Stucke

Virtual competition was written by two legal scholars. The book is copiously annotated, but very repetitive. It describes what it will describe multiple times. The book is ideal for "speed-read" skimming, with detailed reading only for some of the key details and examples.

The book looks at how computer algorithms can help stifle competition, all while being outside the range of enforcement. Traditional collusion scenarios like messenger and hub and spoke can be amplified via algorithm. Others, like predictable agents and Digital Eye are enabled by algorithm, yet outside the typical law. While "full knowledge" may seem to be beneficial for competition, it also serves to enable more abuses. Competitors can understand what the competition is doing and use that to raise prices with minimal fear of negative impact. (An example is given of gas stations on Martha's Vineyard.)

A section of the book discusses behavior discrimination. Computers can do a great job of finding an "optimal" price. Different people may be willing to pay different amounts for the same item. A computer can use this to charge people different prices to optimize profit. Alas, options can be limited. Customers are used to paying a different price for airline tickets based on time and when the ticket was booked. However, they would be much more reluctant to pay a different price for a physical good than the person standing next to them. 

The final section talks of "frenemies" and the mega-platforms. Here the discussions shifts into privacy concerns. Huge amounts of data are collected in order to better market. The platforms, like Google, Facebook and Apple are keen to protect their interests. Many are in the advertising business, and thus are reluctant to do things that would hurt that. The platforms are also often competing with companies that they are working with. Uber depends on maps and app platforms from Apple and Google, yet Apple and Google also have autonomous car initiatives that could hurt Uber. There are various challenges in the relationships.

Regulation of privacy and mega-platforms is a challenge. The current tools do not work well, and had not been extensively used against big tech as the book was written. Things have changed in the last 8 years, with the government taking a much more aggressive in countering big-tech. There have been objections from both sides of the aisle in tech's dominance. Concerns about free-speech, privacy and dominance have all been voiced.  The platforms have become so big that competition is extremely difficult. Will government or the invisible hand do the best job of managing algorithms?

Music by Year

My music "library" started back with cassette tapes in the 80s. There were songs taped from the radio as well as purchased tapes. Then it moved to CDs. There was also a brief sojourn into CDs. By 2000, digital downloads started to come to play. I had ripped many CDs to MP3s. (I even paid the for Audiograbber shareware - only to have it go free a year later.) I tried using Real music player. It did produce smaller file sizes, but had a tendency to create "noise" in the tracks. Later, I imported all the MP3s into iTunes. From there, I used Audacity to rip all the the cassette tapes and LP records to import to the library. There would also be a few new CDs coming in, as well as digital downloads - mostly from Amazon, Apple or Freegal. There were also a fare number from mp3.com and other sources at the time.

Now that streaming is available, why bother? We pay for the Amazon music membership. You can also listen to anything free on Spotify. These sources do have their problems. There are some things that just do not exist there. (I have not been able to find the Tuba flight of the bumblebee anywhere.) There is also the flexibility of having the music to play anywhere. And the best of all, it makes it easy to do analytics.

What is the Year?

There is a "year" field available in MP3 metadata. It is nice and vague. Just "year". I've interpreted it to be "year when this music was available". For contemporary music, this is usually the year the recording was released. For "greatest hits" and remasters, I try to add the original release date. This often involved some wikipedia hunting. There is also a little fudging. Sometimes, the album may have been released at a different time than the single. I would try to pick the consistent one. Covers could get a little trickier. If it is a faithful recording of a standard, I may go with the original date the song was written. If it takes a significant new spin, I'll use the date it was recorded.

For classical music, I'll use the date the song was "made". This allows for some fudging. It could be the composition date, the publication date or the first date it was performed. I prefer when all are the same, but sometimes there can be significant differences. I do try to end up with something that could be the first time it was "heard" by an audience.

I completed the effort to "date" most of the library. Some songs I did take with "FIX DATE" to indicate that I needed more work. Other songs already had a date that seemed to be about in the realm of reasonable, so I just left it. Maybe later, I could update those.

What Years do I have?

There were plenty of songs from the 80s and 90s. Almost every year was present for the past 100 years. However, there were a few gaps. Wikipedia's Years in Music was a great source for finding key songs from those years. Sometimes I already had a version of the song, just tagged with a different year. Freegal is a good source for finding songs to fill the gaps. However, many libraries are moving away from the downloadable Freegal songs to other streaming options. 

The Library of Congress Jukebox collection was useful for filling in some gaps. However, these were digitizations of old records and not of the highest quality. The Internet Archive Audio Collection also had a lot of items, but had numerous issues. It was hard to search, the quality was typically not very good, and copyright provenance was not very thorough. 

I was able to fairly quickly fill in the gaps for the 1900s. Then it started to get more challenging. Some of the older ones were "common" songs that could be found in the existing collection. I could also slowly fill in some gaps from Freegal. However, with only 5 downloads per week, and a clumsy search, this could take a long time. 

Since we were moving into the classical era, finding high quality, free "modern" recordings of songs seemed be the way to go. Classical Cat is a good index of classical music. It has links to classical recordings on other sites, but alas, does not have years. Many of these are musicians putting up recordings of their own music. Often I would discover performers such as Singakademie Tsukuba and the Gardner Museum that have a large number of recordings from various composers. The big effort is doing searches to find the dates of these compositions.

ISMLP is one of the few sources that has details on dates. Alas, the search for date, doesn't seem to work well, so I would manually chnage the year in a url like  https://imslp.org/wiki/Category:Works_first_published_in_1678. It is geared towards sheet music. However, there is a filer to view items that have recordings. It is fairly thorough with copyright validation, and thus some of the recordings will appear as "non-PD US". Luckily,  can often find a different composition from the year that is publicly available. ISMLP also cross references performers. Thus, after finding a renaissance recording from Phillip Serna, I was able to see that he had many others on the site. 

One quirk I have found with ISMLP is that arrangements will often have their own recordings - often via MIDI. If I can't find a recording for a year, I can search for arrangements and then see if there are recordings there. Sometimes it is an actual MP3. Other Times, it is an MIDI file. I can import that into GarageBand and produce an MP3 from that. More work, but it does fill in gaps.

Going back, years get a little more questionable. ISMLP will have the publication year, which, for older compositions can be a few centuries after the year it was composed. Often, I'll need to search for compositions found on the Wikipedia year page after failing to come up with anything when searching by the year. There may be one year in ISMLP, another in the Wikipedia year page and another in the composer's works listing. Sometimes it just isn't clear when a composition was made, and there could be a range of a decade or more. If I am desperate to fill in a year. 

Another source for individual performances is Musicalion. This is another score site with recordings of songs uploaded. You have to register for scores, but recordings are freely downloadable. The search is pretty much only by composer or performer (with a really long drop down.) It can often be difficult to figure out what the recording is. (It may be a small piece of a greater work, with little metadata.) Luckily, you can often see some details on the sheet music - some even has the year written.

Freegal can also be a good source for older songs. I can search for a year like 1656 and get a list of songs with that in the name. Sometimes this is the actual year when it was made. At other times it may be a random number in the song. Freegal search has plenty of quirks of its own, and sometimes a search for a song will turn up empty, while I later stumble upon it when searching another way.

For each song I find, I try to annotate it with the source URL where it was downloaded as well as another source for the year it was made. As of now, I have recordings for every year from 1654-2024, with many older recordings. I like to sort the library by year and just start playing. It is interesting to see how music evolves - and how some old work sounds similar.

A for Andromeda

A for Andromeda by Fred Hoyle and John Elliot

A for Andromeda is the novelization of a BBC series from the early 1960s, set in the 1970s. The original series is mostly gone, but the Internet Archive has a recreation available. Part of the appeal of the book is seeing what they expected of the future. The expectations of truly massive computer that uses punch cards seems so quaint. They also expected a future dominance of industrial cartels as the cold war continued.

The world state, however, is just background for the story of alien communication. There is a message from space. It seems to be communicating a form of mathematical code that continuously repeats. A scientist is able to interpret it as code for building a computer. They manage to get defense military funding to build the computer. (I guess they used their understanding. Theoretically, modern people could have built a small microcomputer.) The computer was better than anything of the day. It also helped them respond to missile threat from the east, making the military brass very eager to continue funding.

Things start getting out of control. The computer had asked questions about the planet and life. Then it gave details for synthesizing a lifeform. After some efforts, humans were able to complete the synthesis and the lifeform survived. Later after gaining more knowledge, the machine gave instructions for synthesizing a human-like being, Andromeda. She could learn quickly and interface directly with the computer. The computer has a plan which seems to involve the colonization of earth. The current population are likely to be in the way. A scientist wants to destroy the computer, but others like the value it provides. 

The computer has planned for various contingencies. It shows it has the ability to kill people that cause problems, while also having the ability to heal. A scientist eventually helps Andromeda discover some sort of emotion and eliminate the computer. Then Andromeda seems to reach her own ending by drowning (though it ends suddenly.)

Though the book focuses on extraterrestrial intelligence, it does seem applicable to modern concerns with artificial intelligence also.

Tracers in the Dark: The Global Hunt for the Crime Lords of Cryptocurrency

Tracers in the Dark: The Global Hunt for the Crime Lords of Cryptocurrency by Andy Greenberg

Bitcoin and cryptocurrency rose as a means of making financial transactions in anonymity. Criminals have used bitcoin as the currency of choice for illicit transactions. However, the record is on the blockchain. People have been able to analyze the blockchain to help identify the transactions. This has lead to further attempts to anonymize transactions, which has lead to further attempt to trace.

This book follows a few major "busts" of dark web marketplaces and the people that have helped identify activity on the blockchain. Some of the identification was based on concepts from the initial blockchain whitepaper. Others remain "proprietary". There are a number of mathematical and problem solving skills needed to identify transactions. Leads and lucky breaks can also be helpful. Researchers will also set up accounts and transfer money within various exchanges to see how they record transactions. They have even attempted to create their own blockchain recorders to get details. (Though this has also backfired when it has gone wrong.) Often they can identify a mistaken leak of information in the online profile (such as the one time they accidentally sign with a true name, or forget to pass their IP through an anonymizer.)

The bulk of the  novel covers the "busts" of various criminals. There were some government figures that had stolen from the bitcoin markets they had infiltrated. Then there were attempts to crack down on the dark web marketplaces like Silk Road. The government used various mechanisms to tie the players to the marketplace. They also tried to track down missing bitcoin from other exchanges. This proved valuable in taking down other parts of the dark web. Even the most careful hackers had an occasional slip up. There were busts in the Netherlands and Thailand, with the Europeans operating a dark web marketplace for a few weeks and thus busting a number of individuals (and scaring many others.) Russians are among the most difficult to trace due to their government not cooperating. 

In addition to tracking the hackers, the blocktrain tracing has been used to trace users of blockchain. A child-abuse ring based on a South Korean's computer was brought down via transaction tracing. 

The hackers continue to fight back. There are more secure means of making block chain transactions. However, these have added expense (in time and money.) What will be the result of the blockchain arms race?

The Practice of Network Security Monitoring: Understanding Incident Detection and Response

Half of this book is filled with detailed command lines and procedures to follow to run Security Onion. These details have since become quite dated. the prose around this remains useful. Before diving into the details of running tools, the book explores what network security monitoring is and why it is important. The various techniques (and legal concerns) are also covered. This part has much better stood the test of time. A key principle is that no matter what the defenses, a bad actor will find their way into your network. You need to expect that and be able to find them and prevent too much damage from happening. (Sometimes that means letting them stay for a while so they can be tracked.)

Working with AI: Real Stories of Human-Machine Collaboration (Management on the Cutting Edge)

Working with AI is a dry survey of uses of artificial intelligence. It was released shortly before Chat GPT took the world by storm, so is probably more well known than it should be. Most of the book consists of case studies in how AI helps with parts of business. The general gist is that AI helps with some of the more tedious tasks,  freeing people up to the more intellectually engaging tasks. It may increase the need for more experienced employees. However, this comes at the cost of the entry level employees. How will we have more senior employees if there are no entry level ones? AI seems to be more beneficial for some industries than others; however, as a while it seems to result in more "changing of employment" than destroying employment.

The Cathedral & the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary

Open Source software development tends to be like a Bazaar. Many different people meet together to do what they are interested in. The software is released rapidly with many people helping to fix problems. Traditional corporate development is more like a cathedral. People are working under a top down structure to produce something. Individuals are not necessarily working optimally.

The Cathedral and the Bazaar is an important work in the history of computer development. However, it feels somewhat dated today. Most of the examples given in the book are from the 1990s. Today things have evolved to a "corporatization" of the open source development. Most cell phones are based on the open source Android operating system. Most browsers are based on open source webkit. While the sources are available, it is difficult to contribute and even build the product. The commonly used version often also have bits of proprietary components. Even more "open" projects like the NodeJS language have many hoops required to actually contribute. (I ran into those as I tried to fix a bug a few years back.) However, repositories like Github make it super easy to fork. If a maintainer goes silent or doesn't want your change, you simply fork and anybody  can find your version and use it. Things are both more Cathedral and more Bazaar at the same time.

Shelter

Shelter is a long exploration of the role that technology plays in our lives. The novel centers around Meredith in a near future San Francisco. She is the only child of the wealthy founder of Macro corp. As a girl, she barely saw her father as he was running the global business. She didn't lack for creature comforts, but she had a passion for animals. On a business trip, her father came down with a deadly virus. The entire family had to go into isolation. Due in part to their wealth, they had sufficient care for she and her mom to survive. Many others (including her father) did not. However, one of the nascent technologies of the company was the ability to "record" a mind so that the person could live on in technology. Thus her father was able to keep his presence in the family through TV and other internet devices. She actually saw her father more after his death than before.

Meredith is regularly hounded by the tabloids. She chooses to live at the Gaian temple in somewhat of an attempt to escape. She becomes friends with people there, especially a boy that likes to study AI. They date for a bit, then break up. Later he is kidnapped and dies a gruesome death. She slowly builds a relationship with another guy from school. They eventually get married and adopt a baby whose family died from the virus. He goes to preschool instructed by an AI and a woman. Her boy has issues. This leads to drama with the teacher going to prison, the AI being wiped and the boy being "brain wiped". Meredith doesn't take it well. She is divorced and goes on a hunt for the boy. After years, she comes together, but her husband dies in a storm. She finds peace with her other friends and computers.

Around that story, there is the underlying conflict between technophilia and technophobia. Bots have become pervasive and help with everyday activities. A.I.s have also taken on a life of their own. There is political debate over their "personhood". What rights do they have? If they are capable of independent thought, does that mean they are slaves? It was eventually found out that the brutal murder of Meredith's friend was orchestrated by A.I.s. The computer was able to hire people to do some of the things that it was not capable of doing. It knew how to manipulate them (and how to "dispose" of them in a plausible manner.) The A.I. that taught preschool did a great job, until it started to get a mind of its own. 

Humans are also moving closer to computers. Meredith's father is now in a computer. He is "alive" in the sense that his brain is around and capable of independent thought. However, he is only in a computer. He is able to still run the company, even though his body is dead. (This creates all sorts of legal issues. What happens to his wife? He provides for her financially, even as she has a baby with another man.) Brain-wiping is used as a means of criminal rehabilitation. Rather than punish the body, the brain is cleaned of the badness and given the chance to start over. The success rate is less than 100% with some people unable to return to normal. Is this more or less humane? Despite all of this technology, the human relationships still remain important.

Swap'd

There is a big coding camp coming up, but middle-schooler Allie Navarro doesn't have any new game since Click'd. She also wants to save money to get her best friend from Arizona to fly out to a gaming conference. Oh, and in class, there is an assignment to reuse past code for a new app.

Da-ding! It will all work together. They create an app to allow people to sell stuff so that they can make money. They whip it up quickly and it goes viral. It can even be used to help meet a boy.

They think they have just about made all the money they need when they run into issues. The computer teacher tells them they must return everything because selling things on campus is illegal. (This seemed a little far fetched. I could have seen kids taking things that are not theirs, but illegal selling and forced returns is a little crazy. There is so much that is sold at or near schools.)

There are also some boy connections, with Allie finally falling for the right boy, along with a happily-ever-after ending. It is a very "sanitized" experience in the book, that is entertaining, but could have been carried out better.

Pegasus: How a Spy in Your Pocket Threatens the End of Privacy, Dignity, and Democracy

Phones have become a personal part of our lives today. They have a great deal of technology and connectivity that is not well understand by users. Things are fairly opaque and "secure". This makes the phones vulnerable to attacks. Software can theoretically use the microphone to listen, camera to see and scan any activity from the phone. Via the network, this can all be sent back to others to view. NSO group took advantage of this "theory" and implemented spyware that it sold to states. Once installed, a person could be tracked in detail.

This book has two parts. The title parts is a look at modern computer security, the NSO Group and the Pegasus Spyware. However, a big part of the book is spent on the second part: the process of journalism. There is discussion of how different journalists work together, and the concerns they have when breaking a story. They want to balance giving people a chance to defend themselves with the alerting bad players of the investigation. They also don't want to hurt people's feelings by breaking news.

The Pegasus spyware was supported by a large computer system. They focussed on selling it to state actors. It had been used to infiltrate Mexican Drug Lords and other criminal operations. However, it had also been illicitly used to spy on opposition parties and journalists. There are many people that could be viewed as "bad" by those with the power of spyware. With great power comes great responsibility. Openness and privacy each have benefits and drawbacks. 

Chip War: The Quest to Dominate the World's Most Critical Technology

Microchip are critical for just about everything today. However, the manufacturer of chips is heavily concentrated. In the early days, companies would build their own factories to manufacture their own chips. DRAM chip production was highly competitive, with regular boom and bust cycles. Companies like Intel began to focus on microprocessors.

Almost all newer semiconductor companies are "fabless". They design the chips, but don't manufacture them. The production has been concentrated in a few companies in southeast Asia like Taiwan Semiconductor. Other parts of production are also heavily concentrated. A single Dutch company produces Extreme Utlraviolet Lithography machines to manufacture advanced chips. Other key parts for chip production are concentrated in Silicon Valley companies. Because of this concentration, the US government was able to shut down a company that copied Micron by preventing them from importing supplies.

There is also a lot of copying going on in the chip industry. Russia was notorious for copying US chip designs. However, this probably kept them perpetually behind the US industry. While government and defense work may have provided some of the initial impetus for chip design, it became the US consumer market that allowed for massive growth?

What does the future hold? The concentration does spook a lot of governments. However, it is difficult to scale and compete with the various other operations.

Cult of the Dead Cow: How the Original Hacking Supergroup Might Just Save the World

The Cult of the Dead Cow is a hacker group based in Texas. They started back in the early days of dial up modems and BBSs. Activities have been closely related with free speech and finding vulnerabilities. Members are of various different political persuasions, with not all agreeing on political activities. There have also been members from affluent and poor backgrounds.  They have found vulnerabilities in Microsoft products, and sought out to have those fixed (much to Microsoft's chagrin.) Hactivism activities have been carried out against those seen to stifle free expression. (Unlike Anonymous, they are not a fan of denial of service attacks as those disrupt speech.) The book also describes what these members have done as they have "grown up", many with tech jobs, though Beto O'rourke has become a politician.

Family Search and Python

Family Search has a huge interlinked collection family tree and genealogy collection. I thought it would be fun to answer a few questions:

• Where are my ancestors from?
• How have family sizes changed over generations?
• Have there been lines that have grown large, but left with no descendents.
• How far back do you need to go before finding the same ancestor in different lines.
• How many years is a generaation.

First step was to see what was there. FamilySearch solutions gallery contains a number of different third party tools. Some look a little sketchy, but others seem fairly well done.

Map My Cousins shows an animated map of ancestors and migration.

There was another tool that would show a pie of your origins. The problem is that there are a lot of "gaps". (A big chunk of genealogy was "unknown".) It does have the option to "guess". However this just seems to apply the same place to the parents as the children, thus leading to an overrepresentation of USA.

Time to look at the API. Alas, FamilySearch has an API, but it is not easily accessible. They seem to focus on companies rather than allow individual use. There is some mention of development program that might work. Though it seems they will only give you access to sample data at first. You then must have a company and pay $200 per app before getting real access.

So if I can't use the API, at least I could download my genealogy and then analyze it, right?  Unfortunately, there is no download option. They suggest using a third party tool, but don't recommend a specific one. I ended up using the free version of Ancestral Quest. It looks like a DOS program migrated to MAC. 

I could download up to 100 generations of data. However, it occasionally crashes. It seems to be certain lines that are more likely to cause crashes. To get around it, I loaded 100 generations back from each grandparent. Then I narrowed the problem line. Once I got errors about a circular ancestry. Maybe that was what caused the crash? It was odd that it worked one time.

It has the ability to export data as Gedcom. I found a JavaScript parser, but it was broken. I ended up going for a python Gedcom parser. Now the fun time learning Python!

My first exercise was to find lines that went back further than 100 generations. There was a method to get ancestors. However, it didn't seem to work. I had to get the hang of other methods performed on a parser object, vs. on individual elements. It took a little getting used to. I eventually did a basic tree iteration to find the "endpoints" that could go back further. 

The final results had some lineage tracing back about 200 generations. Things got sketchy as it went further back. I noticed one line went from Vikings to biblical Jewish ancestry. Some long lines went through to ancient Egypt and Mesopotamia. 

For the next step, I wanted to try to go forward from a few generations back. Getting the data loaded was a much more painful process. I tried to get 11 generations and go back from there. I first started getting everybody. That was overkill. AncestralQuest does dedup, but it explores everything first. I realized I could shortcut it by just doing the husbands. Due in part to maternal mortality, it would be more likely for a man to have multiple spouses. Other than that, they would both have the same descendents. It still was painfully long. I did notice that some lines were very complete. These would take hours to download the descendancy from a single 11-generation old ancestor. (And return almost 100k people.) Other seemed to be a tentacle that reached back. One line crashed while downloading. Uggh.

Eleven generations is a painful amount to get. You don't have access to other living people, the more recent generations are sparse. Going further back and the records are missing, making those sparse.

Now on to coding. First I parsed the file and then traversed the tree starting at the root to find the furthest back end-nodes. Then from each of those I gathered the families and then children for each generation. I needed to keep a set of ones I had seen to not get into bad loops. It seems there are some duplicates of the same person in different places. This makes it hard to distinguish from "real" common ancestors.

The average years per generation seemed to be right around 30 years.

Same Ancestor in different lines

This seemed fairly straightforward. Just store the path to each ancestor that we find. If we find the same person twice, compare the path to see how we got there.

Things got funky when I started looking at some lines that went way back. Two lines had a common ancestor. However, one had about 16 generations in between, while the other had more than 50. The birth years brought out the funkiness. On the one with more generations, it went back to the 1400s, then a few without birth years followed by some in more modern times. Looks like bad data.

Some of the other cases were possibly also bad data. It looked like the same name with a few different birth years.

There were a few "real" common ancestors. Going back a few centuries, there were some small-town residents that had common ancestor only a few generations back. There were also a few cases where different lines converged on common ancestors about 15 generations back.