Working Up

by Dwayne Phillips

AI capabilities are increasing fast. Too fast for some of us. What do we call this?

This past week, Anthropic showed people what Mythos could do. WOW! That is amazing. Why only a few months ago… Where were we way back then? And, by the way, how do you pronounce Mythos?

There was this thing called the Claude Bot or Clawed Bot or some clever spelling. Why that was the revolution people wanted. Does anyone remember it? That was in November of last year. Uh, does anyone remember that far back?

I bought a book recently on AI Agents. It’s a good book. Well researched and written and … hopelessly outdated. Unless you write a book in a week and have it on the shelves a day later, it is outdated when the topic is AI. What a shame.

This is all moving fast. That is a gross understatement.

Remember Moore’s law? It described how the density of processors on a chip would double every 18 months. I propose such a law for AI capability. We could call it Moore’s law for AI. I like the idea of calling it Phillips’ Law:

The capability of AI systems doubles every month or sooner in some cases.

Phillips’ Law doesn’t have the ring to it that Moore’s law does. And there is that awkward placement of the apostrophe when your name ends with an “s.” So be it, let’s see if anyone else adopts the title of the law let alone pays attention to the content. This is my little attempt.

by Dwayne Phillips

I would hope that journalists would understand AI and software better than this. I am disappointed.

I recently read this story about a rogue AI Agent:

A rogue AI agent recently triggered a major security alert at Meta Platforms, by taking action without approval that led to the exposure of sensitive company and user data to Meta employees who didn’t have authorization to access the data.

Ooooooo, rogue AI Agents. Here comes the Terminator and the like. Just like the movies. Hide under the bed; flee to the mountains and hide in caves.

Good grief! Someone wrote software, didn’t test it adequately, and things happened that the programmer didn’t intend.

Have you ever written a C program that allocated memory in a recursive function and … uh oh. I didn’t intend to gobble all the memory and lock the supercomputer and have to call the technician to cycle the power to the entire building and call the fire department and police department and … and that didn’t involve any AI.

Come on folks! AI Rogue Agent? It is software someone wrote. “The computer is down.”

Did the AI Rogue Agent delete files? Surely you have backups of the files to recover, right? Oh, you didn’t? Hmm. Well, another lesson. Surely you weren’t connected to the Internet so that everyone’s personal information was pumped out there for all to see? Oh, you were? Hmm. Well, another lesson.

We don’t need AI to do stupid things and suffer the consequences. Let’s do better.

by Dwayne Phillips

Big iron is back. The mainframe is back. And we hate it more now than ever.

A long time ago, in a galaxy far, far away… well it was 1979, Baton Rouge, Louisiana and a friend of my father worked for the computer company of America (IBM). He walked me through the BIG ROOM holding the mainframe computer of the state’s university system. It was a variant of the model 360 computer held in a room that had more square feet than my house. It had 16 MegaBytes of memory. People gasped when we said that number. It was all liquid cooled. How do you cool a computer with cold water?

That was the mainframe computer. That was the computer center. We used the cycles in that mainframe on our class assignments. We didn’t know it, but we were told it was so. The computer center was the dwelling place that few of us ever trod. It was like that place in Petra that Indiana Jones and Sean Connery entered in that movie. It was amazing.

Then some group in Massachusetts (yes the spelling checker got that one right for me) created these PDP-## and VAX-## mini-computers and later some guys in California built a computer using a microprocessor that you put on your kitchen table.

And then we fast forward a few decades and now we have the datacenter or data center (I have yet to resolve that question). Ah! that sacred ground in which few trod, but we are all using the computers inside or at least people tell us we are using the computers inside.

Big iron is back. It is the datacenter. And it is hated by those who hate buildings that occupy acres of land that used to be farms. Funny how those who hate the buildings never worked on a farm yet criticize the grandchildren of the farmers for selling out to big iron and all that stuff. I digress.

The other funny thing is that computers are much smaller and much more powerful than the mainframe of 1979, but we need a bigger building to house them. What happened with all that? I digress again.

Today’s datacenter is the mainframe computer and the computer center of days gone by. We sort of laughed at the mainframe when we saw a computer with an apple sticker on it. Then the logo of the computer company of America appeared on a computer that I could put on the kitchen table. We laughed a bit more. The mainframe went away for a while. The computer center changed its name to data center. What happened to the computer? What is this data stuff?

We awed at the computer center and the mainframe. Then we chuckled at them. Now we disdain the datacenter. Well, at least those of use who weren’t paid all that money for all that land, and concrete, and steel, and copper, and fiber optics, and … the list continues. Since I didn’t get any of that money, I guess I am one of the disdain-ers.

Time moves on. We circle back.

by Dwayne Phillips

We all make mistakes. Some are allowable and some not. There is the mistake budget.

We all make mistakes. The sooner we acknowledge and live that the better we will be (IMHO). Some mistakes, like typographical errors in blog posts, are embarrassing but that’s about the cost. Other mistakes, those that cost a million dollars of taxpayers’ money, are a bit more consequential.

I work with government documents much of the day. The folks who created those documents, the government’s employees, make lots of mistakes. Companies must follow the letter of the law or the letter of those documents. When people see the mistakes, they send questions to the government employees who then send answers. This Q&A costs time and salary money. That money doesn’t just add up, it multiplies. Stating “Friday the 13th” when Friday is the 12th, costs the taxpayers a million dollars. I am not exaggerating; it costs that much.

Now we come to the mistake budget. I learned this from the late author and consultant Jerry Weinberg. He had a few employees. Being people, these employees were mistaken now and then. Jerry would record the mistake and the cost it brought in dollars and cents. As long as the sum of the cost was below a set number (a month’s salary or something), things were fine. If, however, the cost became too high (a subjective but agreed upon number), the employee was no longer an employee as they were unaffordable.

This is all to state that while we all make mistakes, some are allowable and some are not. In government employment, there are no mistake budgets. I think that is a mistake, but that is just my opinion. Note, that there is a tool that we can use or not use. Not using the mistake budget is probably a mistake that itself may be allowable or not. To date, those who manage work in government have decided it is an allowable mistake. Perhaps that may change, but probably not.

by Dwayne Phillips

History repeats itself as the computer can be fully occupied by the efforts of just a few programmers.

There was a time in computing history when there were few programmers. The computers weren’t powerful. A couple of programmers could keep a big computer busy all the time. Then the computers became more powerful. More programmers were needed to keep them busy.

Then the computers became much more powerful, much less expensive, and much smaller. Every person could have their own personal computer. We needed hundreds of millions of programmers to keep all these personal computers busy.

Now we are sort of back to the beginning where the number of programmers needed has shrunk to an alarming level. What happened? I think the really smart programmers put the rest of the programmers into the unemployment line.

A few really smart programmers figured out how to tie a bunch of computers together so they looked like one computer. The Beowolf cluster was one instance of this. There are many others. People let someone else use the CPU cycles of their home computer at night, etc. This sort of falls under Distributed Computing.

Then came the datacenter. I don’t know how many individual computers there are in a datacenter. Probably a million or so. Once you reach a number like that, who knows?

Then some really smart programmer figured out how to run one big program on a million processors in a datacenter. One datacenter—one programmer. One solution to solve all the world’s problems. Well, sort of, but that is a detail.

So we are back to a computer needing only a couple of programmers. Except today, that computer is an entire building full of a million computers. Used to be an entire building filled by one computer. One? A million? what’s the difference (a few zeros).

What’s next? Not sure, but it could be fascinating.

by Dwayne Phillips

Working with text and changing file formats just got a lot easier.

This little essay was written to be posted in a WordPress blog. I have been doing this blog writing bit for a few years and have over 1,800 posts. Seems like a lot, but a couple of posts a week for a few years and it adds up.

From time to time, I take these blog posts and turn them into a more traditional book. Here is one example on Amazon. That used to be quite a chore: download an export from WordPress, run some Python code, convert to HTML, convert to MS Word, convert to some Amazon Kindle format, upload, and on and on.

The hard part for me was the Python code to pull the content from the XML into something that HTML could read. (Pardon my falling down into a pit of endless details.)

Well, it all just got a lot easier (Pardon the collapse of grammar.)

Along comes these chattering bots and their continual improvement. Now I ask one of them (the leading ones all have this capability) to do what I want and viola’, out comes a system that does everything for me. Well, I do have to go the WordPress site and export the blog to an XML file. After that, bing, bang, bong, done.

General tip, if it involves text and file formats, ask a chattering bot to do the work. It is quite amazing but, then again, these chattering bots were built to work with text. Don’t ask them to solve basic math and logic problems, but text and file formats are a breeze.

by Dwayne Phillips

Remembering Chuck Norris and his influence on one American family.

Chuck Norris died a few days ago at age 86. To some, Mr. Norris was an American hero of the last half century. To some, Mr. Norris was a caricature of something funny.

Mr. Norris affected my family in ways that bring fond memories. He starred in a couple (more than that) movies in the late 1970s. I was in college. My younger brother was in high school. My younger brother loved martial arts and studied and practiced them achieving a black belt in something or other. That comment shows my little interest in the topic.

My younger brother had to see the Chuck Norris movies. Okay, so we piled into my little car and drove the ten miles to Hammond, Louisiana to see them. I felt they were crummy movies. He felt they were significant milestones in Hollywood. Regardless, attending those movies together meant something to our relationship for the rest of our lives.

Fast forward to the 1990s and Mr. Norris starred in Walker, Texas Ranger. Okay, it ran nine seasons, so it was a success. Critics didn’t like it…so much for critics. I lived in Lagos, Nigeria with my wife and kids. One night a week, my wife and I would watch an episode on Armed Forces Radio and Television Service. It was a small highlight of the week to see Norris deservedly kick the bad guys and nurture a budding romance. My wife and I enjoyed it. We still talk about it now and then. It was part of our relationship during an otherwise odd part of our marriage.

So, we will miss Mr. Norris. In these and other ways, he played a role in my family. That was something.

by Dwayne Phillips

Another rant about writing that makes no sense (to me).

This system uses three times less (memory, weight, time, space, effort, and whatever) than that system.

I understand what it means to use three times more weight (15 pounds instead of 5 pounds), but what does it mean to use three times less weight? I think this means to use a third of the weight (5 pounds instead of 15 pounds).

There is something wrong about increasing a decrease that makes no sense to me. At first I only saw this peculiar increase of a decrease from journalist and other illiterates who also never understand percent change in anything. Now I am reading this from supposedly well-educated scientist and engineers.

Did I fall into a deep sleep and awaken a century later in a place with a new brand of the English language and a redefinition of mathematics? Enough of an old man ranting. Let’s move on.

by Dwayne Phillips

These new tools, ahem all that AI, are boosting productivity in our work. And then we hit the bottleneck and come to an emergency inducing crisis.

Yesterday and today I have been using one of these new tools (some folks them AI, I don’t). I have accomplished in an hour what would have taken a week. I am not exaggerating on that. This new tool enables 20 or 30 times the work product in the same amount of time. This is amazing. As a side note, it is a commentary on the work I am doing. If it is so easy to do faster, what good is it?

Back to the topic at hand. Whoosh! I’m done with this task. Now I pass the results on to the next person. Maybe they have new tools and WHOOSH they do their task 30 times faster. We are rolling.

And then we stop rolling. We come to the bottleneck. Sometimes the bottleneck is one person. Sometimes the bottleneck is one task for which their is no new gee whiz tool. Whatever, the bottleneck is the bottleneck.

Nothing happens at the bottleneck. Tasks from three different projects are waiting at the bottleneck. It will be a month before the output of my task is considered at the bottleneck. The rest of us, those for whom new tools provide all this speed, twiddle our thumbs or something.

The bottleneck stalls progress so long that… wait, oh no! We have a crisis. We have an emergency. We all need to work all-nighters to make the big final deadline.

Huh? What happened to all that productivity?

I think we can do better.

by Dwayne Phillips

Please tell me what we are doing. Please don’t read from a catalog.

Person beaming with confidence: Look. Here is a block diagram of our system. You see we are using Snowflake, Spark, Databricks, Kafka, Tableau, ThoughtSpot, and toss in a little Excel for good measure.

Person baffled but interested: Interesting. I would like to know what we are doing or what functions we are performing. Do you have something showing that?

Person beaming with confidence: silence

I’ve been in this conversation too many times and walked away with too many headaches and too much heartburn. I want to know what we are doing, i.e., the function. I really don’t want to see the names and cute little logos of products.

Consider, as one example, Excel from Microsoft. It is a fine product. It is such a fine product that it can function in many ways. Excel can be a database of people with name, phone number, email address, home address, and so on. Excel can be the repository in a data call where there are 50 questions and places for 50 different organizations to place their 50 answers all in one thing. Excel can be a project organizer where each sheet contains information on each phase of the project and each participant. And, guess what, Excel can function for the finance folks to keep track of money (wow, I think it was created to do that last one).

The same can be said for each of the products that Person beaming with confidence said at the beginning.

Please, tell me what we are doing. Then tell me what product we are using for each function we perform. Please try harder to communicate how we engineered a system to do something useful for people.

We can do better. Let’s do better.