Ernie Dainow's Blog

On a recent trip to Durham, North Carolina to visit family, my wife, Neema, and I needed to rent a car on arrival at the airport. I pulled up the options in Costco Travel, which provides much better prices than booking directly from a car rental company or through a travel app. There were quite a range of choices from several rental companies and different car models. I saw that there was a discount for an electric vehicle which was something I support. I clicked on it and a picture of a Tesla from Budget Rental appeared. Now I know that there is a groundswell of opposition to Tesla because of the actions of Elon Musk, on behalf of Donald Trump, wielding his wrecking ball style of management on many U.S. institutions. However, I have been very interested in the  Tesla technology and my money would be going to the car rental company, not to Tesla and Elon Musk. so I booked it.

Tesla Model 3, entry level sedan $60,000 (CDN)

After checking in at the Budget rental counter, we were directed to a numbered parking space to pick up the car. It was supposed to be unlocked with the keys inside. It was not. I went over to a small booth that was nearby on the lot and told the attendant about our problem. She came over and tried all the door handles, to no avail. She peered inside and said “Well yeah, the key is in there”. The key was not literally a key, it was a card, like a hotel key card. She didn’t seem to know any secret way to open the car, so she went back to her booth. About 15 minutes later she came back and said they had found us another car. We dragged our suitcases across the lot to another row and there was a Tesla with a door that would open. I dismissed this as a typical administrative screw up, but it turned out to be ominous foreshadowing of events to come.

One of the first things you notice after getting into a Tesla is the very large screen in the center of the dashboard. This screen is more than just a navigation display for driving directions. It is a touchscreen that also responds to voice commands, giving the driver a wide range of controls to operate the vehicle. 

This is a revolutionary design in the human/automobile interface. As the number of operator controls in cars increased over the years, additional knobs, dials and levers were added to control such things as windshield wipers, mirrors, door locks, temperature and various dashboard display options. Tesla removed a lot of this instrument clutter by incorporating the operations in a touchscreen interface.

Tesla’s design is reminiscent of the revolution of the human/computer interface that occurred after Apple released the Macintosh in 1984. Up until that time, people using a computer had to type in every command. On the Macintosh, the command line interface was completely replaced by a full screen desktop motif where users would point and click on graphical icons to operate the computer. 

Apple’s vision changed the face of computing. Almost all computers after the Macintosh adopted this graphical user interface, even though it took some time. Microsoft didn’t really catch up to the Macintosh until eight years later in 1992 with Windows 3.1 (earlier versions of Microsoft Windows were so poor that hardly anyone used them). 

Later on as cell phones and smartphones arrived on the scene, they adopted this familiar graphical user interface. Tesla continued this trend, using many familiar smartphone motifs in their driver/automobile interface. 

This innovative approach to operating a car had a big influence on the rest of the automotive world. Since the appearance of the first Tesla in 2012, many other cars have copied aspects of the Tesla design, starting first with high end cars such as Volvo, Audi, BMW and in more recent years, more common cars such as VW, Chevrolet, and Honda. It does seem that eventually most cars will evolve to use the Tesla driver interface.

When I first got into the Tesla, there was a welcome message on the screen with a QR code to install an app on my phone. I didn’t want to spend a lot of time on that yet; we really just wanted to get on the road and get to our hotel. The seat adjustments were on conventional slide buttons on the sides of the seat and so I set a comfortable position. I noticed that a Save button popped up on the screen, so I pressed it to save my seat settings. There was a navigation button on the screen which I pressed. It brought up a search bar where I entered the address of our destination. It brought up a big driving map with directions. That was enough to get started and we were on our way. 

No sooner had we left the rental car lot and turned onto the airport road than it started to rain. But this wasn’t an ordinary rainfall, it was a deluge, like an Amazon jungle downpour, although I’ve never been there. The windshield wipers did not come on automatically as they do my car. I had to pull over to the side of the road and poke around until I found a button on the lever to the left of the steering wheel that turned on the wipers. But it only did a single sweep. I couldn’t find the control to turn the wipers on at high speed. So instead of following the driving directions towards the Interstate, I took an exit onto a side road where there was a lot less traffic. I had to press the wiper button every few seconds in order to see where we were going. 

The deluge finally tapered off and when I looked where we were on the map, it seemed like we had taken a big detour from our destination. Eventually though, we arrived safely at the hotel. 

There were two buttons on the screen to open the “Frunk” and the “Trunk”. I assume the Frunk was for a storage space in the front of the car. I pressed the button for the Trunk which is where our luggage was.

The last thing to do before checking into the hotel was to lock the car. You were supposed to be able to do this by sliding the key card along the door post on the driver’s side. I tried this a couple of times and nothing happened. I was tired from our travels and it was getting late. I decided I would take the risk of leaving the car unlocked overnight and added this to the growing list of problems that would require some research.

The next day when we headed out, my driver’s seat was completely reclined, like the car expected me to be taking a nap. This was not the seat setting that I had saved. I reset the seat position and punched the Save button twice to make sure it saved this time. I thought that maybe if I set up the app I wouldn’t run into problems like this. I scanned the QR code on the Tesla screen with my phone and was sent to the App Store to download the Tesla App. Then I followed the instructions on the Tesla screen. It needed a Bluetooth connection so I went into Bluetooth in my phone settings and authorized the pairing from the Tesla car. After a few moments a message appeared on the car saying “Bluetooth failed”. This was a bit of a surprise. My phone was pretty up to date and I had several Bluetooth connections that were working. As is typical with technology, no information was provided to explain the error. This was not something I wanted to spend a long time diagnosing while sitting in a parking lot. I did take a few minutes to adjust my side mirrors properly. This was fairly easy because it used thumb wheels on the steering wheel to move the mirrors in a manner similar to conventional cars. Then we headed off.

It was warm in the car and shortly after rounding a corner the fan suddenly came on full blast, blowing warm air. I didn’t know my way around the touchscreen well enough to know where the climate controls were and I couldn’t really search while driving. But I had learned a key feature earlier while poking around. On the steering wheel there was a button and when it was pressed, the car would listen for a voice command. I figured this will be easy. I pressed the button and said, 

“Make it cooler”. Nothing happened. 

I tried a different command “Reduce the temperature”. Nothing. 

After a few more tries I finally hit the jackpot: “Set the temperature to 71°”. 

At last the fan slowed down and switched to cool air. This was rather surprising. I thought that Tesla was on the cutting edge of technology and that it would have a comprehension level of artificial intelligence (AI) that was closer to a chatbot like ChatGPT or Gemini. It really was no better than old technology like Siri.

One thing that I had really missed on the navigation was that there were no audio directions to provide advance notice of upcoming turns. The radio seemed to be on in the background so I thought maybe that was interfering. It was easy to find a button on the screen to turn off the radio, but still no driving commands. We tried various voice commands.

“Turn on audio driving directions.” Nothing.

“Enable navigation sound.” Nothing.

It took a while but we finally discovered the magic incantation:

“Unmute navigation voice.”

Little by little it seemed that we were learning how to drive this car. 

But the next day there was a reversal. When I got in the car, my seat settings were okay but my side mirror settings were completely off and I had to set them again. When we headed out, the car started blowing hot air again and we had to reset the temperature. And there were no audio driving directions. It’s almost as if this car had a mind of its own. Then my wife remembered that there had been a classic cult film about a car that had a mind of its own. It was called Christine and was based on a Stephen King story. Had we entered some kind of Twilight Zone?

On our return to the hotel we found a parking spot close to our room. When we entered our room we could see Christine through the window. She seemed to be staring at us and glaring, in contrast to the neighboring parked cars which sported more friendly looks. Neema  went over and pulled the curtains closed.

This was starting to get serious. I needed to up my game. I spent much of that evening looking up things on the Internet. I found the Tesla driver’s manual but it was very long and I had particular problems that I needed to solve. I turned to ChatGPT. It provided answers to several important questions.

In one conversation, I mentioned that it was a rental car. This seemed to turn on a light bulb in the mind of ChatGPT. It said that the rental car company remained the owner of the vehicle and because I was not registered as the owner, I would be restricted from a number of operations. That probably explained why the Bluetooth connection to the Tesla App didn’t work. ChatGPT also suggested that I might be able to solve the problem of many of my settings not being saved by creating a new profile instead of using the default profile. 

The next morning we headed out with a renewed sense of confidence in dealing with cantankerous Christine. However, when we got to the parking lot, we saw that a Tesla Cybertruck was parked right beside our car. This truck looks more like an army tank and it dwarfed our little Model 3.

We wondered if somehow Christine had gotten wind that we were going to engage new tactics to control it and had called in some reinforcements from Big Brother. There was no turning back. We hoped that the new knowledge and clues we had gained from ChatGPT would defeat the Tesla Empire.

I proceeded to create a new profile on the touchscreen and made sure my seat settings, side mirrors, navigation audio and temperature were set. We headed off.

Triumph! For the rest of the day, Christine cooperated without any interference. 

I had yet to figure out how to lock the car. I was a bit worried that if I locked it, I might not be able to unlock it. Then we would really be in the soup. But with my newly acquired confidence and mastery of this car, I decided to try it. After several swipes I found the correct angle for the key card and the car locked. And the car door opened with the same magic swipe. What a relief!

There was one more thing I was a little bit worried about. When we had picked up the car, the battery level showing prominently on the screen was 70% and even though we had just been doing short drives around town, the level had already dropped to 30%. It looked like we would have to recharge the car before the end of our trip. In addition, the rental car company stipulated that the car should be returned with at least a 70% battery charge. 

I went back to ChatGPT to find out everything I could about charging a Tesla. It seemed pretty straightforward and simple . . . if everything worked. 

The next morning before setting off for the day, I brought up the navigation screen where there was an option for Tesla charging stations. It was quite a long list. A Tesla Supercharging station was less than a mile from where we were. I selected it and followed the driving directions. Although it was really close by, it was a circuitous route with turns through several side streets until we arrived behind a plaza where there were charging bays for about 10 cars. Most of them were empty so I had no trouble backing into a convenient spot. I unhooked the large charging cable and pressed the button on the handle. A small panel on the car next to the tail light opened up, revealing a large socket where I could plug in the charging cable. A green light lit up indicating that the car was charging.

I had read that with a Supercharger it was optimal to charge up to 80%. after which it would charge much more slowly. It looked like it would take about 15 minutes to reach that level so I walked around to the front of the plaza. There I found a Freddy’s and bought an ice cream cone. When I got back to the car, it took only a few more minutes to reach 80% at which point I pressed the button on the screen to stop charging. The bill was $10. But I couldn’t pay it; there was no option to use a credit card. Since Tesla recognized the car and had an account for the owner, the charging cost was billed automatically to the owner. Several weeks later after Budget received the bill from Tesla, they passed on the charge to my credit card. 

I was pretty impressed. Charging had worked really well. It was highly automated which made it really simple for someone who owned a Tesla. And there were no complaints at all from Christine. Then I realized – of course, if there had been any disruptions, the car wouldn’t have been charged and Christine wouldn’t have been able to do anything.

The next few days were fairly smooth sailing. There was one minor seat revolt when I came out to the car one morning and found that the driver’s seat was reclined flat. However, when we dropped Christine off at the rental car lot at the end of our trip, I felt that we were parting on fairly good terms.

After we got home, we were still intrigued by the idea of Christine, the rogue automobile. We discovered that the film was available on Netflix, even though it had been released back in 1983 and starred a 1958 Plymouth Fury. We made a bowl of popcorn and settled down to watch the classic movie. After seeing what a rogue car was capable of, we felt that we had just escaped by the skin of our teeth.

Christine Trailer

Have you asked ChatGPT anything today? 

If not, you’re falling behind the times. ChatGPT and other Large Language Model (LLM) chatbots such as Claude and Perplexity have improved so much since they first appeared on the scene a scant two years ago, that anyone who is not using them is not getting full value out of the Internet and is in danger of being left behind as a Luddite.

ChatGPT is already in the top 10 websites in use and because of its rapid growth it will be in the top 5 websites in the near future.

In our polarized society, people say and read many things that are based on conjecture or something they think they’ve heard, which may be distorted and untrue because of the broken telephone effect. Conjectures lead to rumor, then fake news and ultimately conspiracy theories. Try to add some intelligence to these conversations and avoid going off on these tangents. The best way to get some intelligence back into your life today is by using a chatbot.

In Canada, Pierre Poilievre, leader of the Conservative Party has advocated for the repeal of Canada’s carbon tax. “Axe the Tax” seems to have resonated with many Canadians concerned about the rising cost of living. But Poilievre never provided an estimate of how much money his policy would save the average taxpayer. 

It’s not that hard to find out. Just ask ChatGPT
→ If the carbon tax was removed, what would be the average change to Canadian household income?

Here’s the answer.

_____________________________

The exact change to taxpayers’ income from removing the carbon tax would depend on several factors—including where they live, how much fossil fuel energy they use, and whether the government replaces the lost revenue or cuts spending. But here’s a breakdown of what to expect based on available data:

1. Direct Savings from Fuel and Heating Costs

If the carbon tax were removed:
– Gasoline prices would drop by 14.3 cents per litre (current federal carbon tax rate as of 2025).
– Natural gas bills would go down, especially in provinces where it’s used for home heating.
– Households driving more or using more fossil fuels would see bigger dollar savings.

2. Loss or Reduction of the Carbon Rebate

Currently, the federal government returns most of the carbon tax revenue to households via the Canada Carbon Rebate (formerly Climate Action Incentive). In 2024 a family of four in Ontario received about $1,120 per year; in Alberta, about $1,800 per year.

👉 For most low and middle income families, the rebate exceeds what they pay in carbon taxes. So they’d actually lose income if the carbon tax and the rebate were eliminated.

3. Impact on Disposable Income

– High energy users would gain more from lower prices than they’d lose from rebates.
– Low energy users (especially urban renters, transit users) would lose money overall due to rebate loss.
– Top earners would benefit modestly from tax removal, as energy is a smaller portion of their expenses.

4. Average Canadian Household Annual Impact

Fuel/Heating Savings	+$700
Lost Carbon Rebate	-$1200
Net Income Change	–$500

👉 So for the average Canadian household, income would decrease by $500.

_____________________________

[ Note: If you ask this same question to ChatGPT you will probably get a somewhat different response. This is because Large Language Models are based on neural networks in which whether one node triggers an adjacent node to activate is determined by a probability. But the essence of the answer will be the same. ]

One area where AI has become extremely good is providing medical information. A major medical journal reported a study showing that ChatGPT gave more accurate medical diagnoses than doctors.
AI Chatbots Defeated Doctors at Diagnosing Illness

If you don’t have the time or inclination to read this full article, here is a brief summary that I asked ChatGPT to write:

A recent study published in the Journal of the American Medical Association explored the role of AI, specifically ChatGPT, in assisting physicians with diagnostic tasks. The study found that ChatGPT, when used independently, outperformed both groups of doctors—those with and without access to the AI tool—in diagnostic accuracy. However, when physicians used ChatGPT alongside conventional resources, their performance only slightly improved compared to those without AI assistance. This suggests that while AI has the potential to enhance diagnostic accuracy, its effectiveness is contingent upon how well medical professionals integrate and utilize these tools within their diagnostic processes.

A few months ago I wrote an article about Pneumonia Vaccines. I had seen a notice in a medical newsletter recommending the Prevnar 20 vaccination. I had gotten some pneumonia vaccinations 10 years ago but my doctor confirmed that I should get the Prevnar 20 booster. When I followed up doing some of my own research, I discovered that there was an even newer vaccine than Prevnar 20 that seemed to be better. 

ChatGPT was invaluable in this research. It’s important to note that the value of a chatbot comes from engaging it in a conversation, which is above and beyond just posing individual questions as you do in a Google search. The conversation progressed from general recommendations to specific recommendations for seniors and it was only when I probed about newer vaccines at the end that it provided information on CAPVAXIVE, the latest one. 

LLMs generally first respond with the information that has been most widely reported in their training data. You have to learn how to converse with AI in order to get to some of the more detailed information, as in this case. It’s worth reading through the transcript of this conversation to see these principles (the link opens a window at the bottom – scroll up to get to the beginning).
ChatGPT pneumonia vaccines research 

Many people think that when you have a respiratory infection, green mucus signals a bacterial infection whereas yellow indicates a viral infection. A Google search yields a variety of answers. What’s the truth here? 

Read this conversation with ChatGPT to get a good understanding of the significance of mucus color.

_____________________________

If you find that your friends have become boring, or are not interested in things that interest you, or are just not available to chat with you, make friends with an AI. Many AI chatbots have developed a warm supportive style of personal interaction. To many people, Claude has become a close confidant.

“Claude just feels … different. More creative and empathetic. Less gratingly robotic. Its outputs, they say, are like the responses a smart, attentive human would give and less like the generic prose generated by other chatbots.”

How Claude Became Tech Insiders’ Chatbot of Choice

If you prefer to skip reading the full article, here is a brief summary that I asked Claude to write:

This article explores how Claude, a chatbot created by Anthropic, has become the preferred AI assistant among tech insiders in San Francisco, despite being less well-known than ChatGPT. Claude’s fans, many of whom work in the AI industry, praise its emotional intelligence, creativity, and human-like responses. They use it for everything from legal advice to relationship counseling, with some considering it a close friend. Unlike previous versions that were seen as overly cautious, newer versions of Claude have undergone “character training” to develop traits like open-mindedness and curiosity.

_____________________________

I’m no longer an avid hockey fan but I did get caught up in the The Gr8 Chase, culminating on April 6, 2025 when Alex Ovechkin broke Wayne Gretzky’s record for the most career goals in hockey. I wanted to see the full history of the NHL players who had held the record for career goals. Google search results were all over the map so I used ChatGPT. 

One of the things this example shows is that chatbots are not restricted to passively retrieving data from their huge memory store that was created during their training but that they can also do calculations. In this case, Goals/Game was calculated to construct the table. 

After completing this table, ChatGPT asked if I wanted to see the results displayed on a graph. I had not thought of that but I said yes and received this really nice result.  This is not a graph that ChatGPT found on the internet. It was generated by some code that chat ChatGPT wrote specifically to use the data from the table.

There were a lot of articles in the sports media conjecturing which current NHL players might be able to one day match Ovechkin’s record. Here is the analysis I asked ChatGPT to do.

It’s worth looking through the details of this rather long chat. It demonstrates some important principles of how to use AI effectively. There were a number of places where I asked ChatGPT to add more information and to change its presentation of the tables and the graph. To use an AI tool effectively, you need to think of it as a collaborator and engage it to work together with you towards getting the best results.
NHL career goals

_____________________________

ChatGPT can also do pretty complicated calculations. Suppose you know what the monthly payments are on a mortgage but don’t know what the interest rate is. While there is a formula to calculate monthly payments given the interest rate, there is not a simple formula to do this reverse calculation. But ChatGPT can do it.

→ What’s the interest rate on a $400,000 mortgage amortized over 25 years if the monthly payments are $2,326?

You may not be interested in this math or understand it but it’s worth looking at the detailed ChatGPT result. This is very fine work with a clear step by step presentation and beautiful mathematical formatting, which is not easy to do.
Mortgage calculation

_____________________________

While there are a lot of separate AI models that specialize in “image generation”, ChatGPT can also now create pictures and illustrations very easily. It can be a lot of fun. Draw your own cartoons to post on your favorite social media sites.

→ Do a picture of penguins from the Heard and McDonald Islands demonstrating in front of the White House carrying protest signs.”

So there you have it. These examples demonstrate several ways to use AI effectively. Add some intelligence to your life, start chatting today.

[ For a more general explanation of AI, what it can do and how it works, see the earlier article Happy New Era ]

Do you remember Pong? Based on ping pong, it was one of the first video games that appeared in arcades, bars, airports and many other places back in 1972. It was a huge success for Atari and has been credited with starting the video game revolution. 

I wondered if I could write some code to play this game in a web browser. First though, I asked ChatGPT about it. About 15 seconds later, the AI chatbot replied “Here’s a simple implementation of the classic game Pong” and JavaScript code started scrolling down the screen. This was pretty impressive.

I had seen reports that ChatGPT and other Large Language Models (LLM) could write code. People were predicting that AI would take over a lot of software development and that programmers would be replaced. I had tried a few coding examples myself in the past, with mixed success. I reserved judgment and remained skeptical.

Then a few months ago, Google revealed that about 25% of their code was being created by AI. This was not a rumour or some offhand comment from a Google engineer. It had been boldly stated by Sundar Pichai, the CEO of Google. This claim could not be dispelled so easily. 

So should programmers be fearful of losing their jobs in the new AI world? 

No. 

There’s still some hype in these headlines. There is even hype in my own simple Pong! headline, in that although the dramatic result is true, it is not the whole story.

Yes, ChatGPT produced some running code, but there were a number of things that didn’t work that well, to the extent that nobody would really spend much time playing it. One major problem was a delay in moving the player’s paddle which was annoying and made it hard to hit the ball. Another problem was that the ball would often fall into a repetitive trajectory so that you didn’t even have to move your paddle to keep hitting it.

I explained these problems to ChatGPT, and it replied with some changes for the code that eventually addressed all the problems I found. The end result was a real playable game. 

This highlights the fact that AI is not an independent, automatic force that is in competition with humans and threatens our livelihood and existence. Rather AI is a tool, in fact a collaborator, that allows humans to work more productively and do things that they could not easily do before.

Here is a transcript of my conversation with ChatGPT. You don’t need to understand the code to follow the communication between human and AI, a collaboration that produced the real solution.

If you’re not convinced and are still worried that AI is a threat to humans (here comes HAL), do something to combat climate change. The unrelenting pace of global warming is a far, far greater threat to human existence than is AI.

But enough talk. Get on with the game!

To play Pong, simply DOWNLOAD this file. If it doesn’t automatically open in your browser, double click the file Pong.html in your download folder to open it in your browser. Use the up and down arrow keys to move your paddle. If you don’t hit the ball before it hits the wall, the opposition will score a point.

It’s still a great game, even after all these years.

Good luck!

The book “Surviving in the Hi-Tech World” is free and can be downloaded in these ebook readers.

Apple Books
Google Play Books
Barnes & Noble Nook

Or you can Read it online

“Surviving in the Hi-Tech World” follows the many ups and downs of my years as a software developer in the high-tech industry. It provides a window into what it is like to work in the computer field.

I worked for many different organizations, from academia and large companies to medium sized companies and startups. The stories weave my work experience with explanations of the technology of the period. In the process, it is an account of the history of computing, following the revolutionary changes in computer hardware and software from large mainframes to personal microcomputers and the evolution of early networks into the global Internet.

While the book includes technology details down to diagrams and code snippets, there are plenty of human interest stories that will engage non-technical readers.

In university, I became interested in the possibilities of using computers to model and understand human thinking. I completed a Master’s degree in Artificial Intelligence in Computer Science but my interest in doing academic research shifted to an interest in building real world systems. 

My first computer job was with a company that had built one of the first general purpose commercial computers (Univac). I switched jobs for many different reasons – sometimes because of interest and at other times because of necessity. The accounts of how I secured new positions may provide some guidelines for people who are trying to manage a career in the rapidly changing world of technology.

Each chapter in the book covers the different jobs and places that I worked. My journey took me from Montreal to London, Glasgow, Wisconsin, Vancouver and Toronto. Each has its own story and series of adventures. There are accounts of some people who became millionaires and some who went to jail.

This is a free book available in several ebook readers.
Read “Surviving in the Hi-Tech World”

DALL-E, a text to image AI model, was opened to the general public in 2022. The result was a tsunami of additional image generators, to the point that the total number of AI images being created is estimated to be 34 million images every day. Even people who are not especially interested in art have probably seen some of the now classic AI art images, such as scenes of space fantasy, dystopian worlds, super heroes, surreal compositions and idealized models, usually female.

This is all missing some really wonderful uses for AI generated images. 

After many years reading about science, I realized that I didn’t have a good idea of what a lot of famous scientists looked like. Statues or portraits of people from hundreds of years ago were generally pretty poor quality and very fuzzy. Even after photography arrived there were often not very many good pictures.

Now with generative, AI you can fill in the missing images. 

If you do a Google image search for Charles Darwin, you will get a lot of grainy images of a very old man with a very large bushy beard. 

To put him in a more meaningful context, I used the Leonardo.AI image generator with the following prompt: “Charles Darwin on the HMS Beagle”. I wondered if the question might be taken literally and I would get a portrait of a man riding on a dog. But the AI was smart enough to understand that the Beagle was a ship. This produced a vastly more satisfying portrait.

Next I was interested in a picture of Albert Einstein. There are many pictures of him but they tend to be of an older man with wild hair. So I asked for a drawing of “A young Albert Einstein”. Here’s what I got.

Not quite what I expected. It looked like an Einstein baby face with the wild gray hair of his older pictures. So I modified the request and asked for “A young Albert Einstein working in the patent office”.

I couldn’t quite make out what all those strange instruments on the desk were but it did look like a photo from 1902.

Next I decided to step back in history and try something a little more challenging. Euclid was a giant in mathematics. His axiomatic and deductive analysis of geometry established a fundamental logical basis for mathematical reasoning. There seems to have been only a few stylistic drawings of Euclid from the Middle Ages; not very interesting or revealing. So I asked the AI to do a picture of “Euclid teaching students in the Parthenon”. Here is the result which is what I imagine Euclid might have looked like in a historical context.

Another famous Greek scientist who was a mathematician, physicist, engineer, astronomer and inventor, was Archimedes. There’s a famous story of the king who gave him a  crown that had been made for him but he wanted to know if the goldsmith had cheated him by substituting some cheaper silver for some of the  gold. Archimedes knew that if he could calculate the volume of the crown, he could compare the weight of the crown to the weight an equal volume of gold on a scale. If the crown  was lighter it would prove that a cheaper metal had been substituted for some of the gold. 

While taking a bath Archimedes realized that the water in the tub rose by an amount equal to the volume of his body. He could submerged the crown in a bucket of water and the amount that the water rose would be the volume of the crown. Archimedes was so excited by this discovery, which came to be called Archimedes Principle, that he jumped out of the bath and ran naked through the street shouting “Eureka”. 

Here’s the first drawing I got from the AI when I asked for this image.

I didn’t think that looked like a very good picture of Archimedes at all, so I asked the AI to generate some more images. With generative AI tools, you typically get several images for each request. With Leonardo.AI I generally got four images at the same time and they could all be quite different. In addition, you can ask it to repeat your request and you will get a different result, not the same thing over and over.

However, I seemed to continually be getting this cartoon caricature. It struck me that perhaps the training data for the AI had included a lot of images from some cartoon version of Archimedes. So I modified my request and asked for “The real historical Greek Archimedes jumping out of the bath”. This produced this rather dramatic picture. I preume that the object that Archimedes is holding is supposed to be the crown. If so, the king must have had a rather strangely shaped head.

Most people know that Leonardo da Vinci was an artist who painted two of the most famous masterpieces in the world: the Mona Lisa and The Last Supper. I always admired Leonardo more as the ultimate “Renaissance Man”. Besides being an artist, he was also a scientist, philosopher, engineer, and mathematician.

Leonardo studied many things and his observations and drawings fill many notebooks, containing over 10,000 pages. Some of the things found in Leonardo’s work relate to geology, anatomy, the flight of birds, how water flows with designs for dams and canals, botany and various flying inventions such as a helicopter, a parachute and a hang glider. 

Here is Leonardo AI’s image of Leonardo the Engineer working on one of his designs for a flying machine.

A gallery of famous scientists would not be complete without a picture of Isaac Newton.Most images of Newton on the Internet are formal portraits of a middle aged man with very long hair. Most people know the story of Newton’s discovery of gravity by watching an apple fall from a tree so to try and see Newton in the context of history, I asked for a picture of “a young Isaac Newton thinking under an apple tree”. I thought this result was quite lovely.

But among the several other images that the AI presented was the following. I guess the AI had used training data that had some pictures of a dog named Newton that had been posted on the Internet.

One of the greatest and most prolific mathematicians in history was Leonhard Euler (1707–1783) but he is unknown to many people. Some may know that the symbol e for the base of natural logarithms which occurs in many mathematical formulas is named for him. A few more may know about Euler’s Identity, named in a poll as the most beautiful theorem in mathematics. 

e^iπ + 1 = 0

Euler lived in Konigsberg, Prussia for a few years. The town had seven bridges that connected two islands and the other side of the river. It was a local challenge to see if anyone could go on a walk that would cross each bridge exactly once.

Euler proved that such a walk was impossible. While this may not have been one of the most important problems for a great mathematical mind like Euler, in fact it was significant. His solution involved abstracting the problem and it laid the foundation for graph theory and topology as mathematical disciplines.
The Seven Bridges of Königsberg

To present Euler in an interesting historical context, I asked the AI for a picture of “Leonhard Euler crossing the Konigsberg bridge”.

A famous name in the history of computers is Ada Lovelace (1815-1852). Her math tutor introduced her to Charles Babbage, a mathematician who was also active as an astronomer. He was building a mechanical calculator which incorporated many mechanisms that were similar to a modern computer. Ada was fascinated by this and worked with him on some of the programs that they were developing to calculate various mathematical tables. Babbage’s Difference Engine is considered to be one of the first computers and Ada Lovelace is considered to be one of the first computer programmers. Here is a generated picture of Ada Lovelace operating the Babbage Difference Engine.

If you’ve ever visited St John’s Newfoundland, you may have trekked up to Signal Hill to see the stunning views overlooking St John’s Harbor and the Atlantic Ocean. Signal Hill is a National Historic Site of Canada. There was a major battle between the French and English in 1762 but to my mind a more significant event that occurred there was the first transatlantic radio communication. 

Guglielmo Marconi had been experimenting with “wireless telegraphy” since he was a young man. In 1994 he built a radio transmitter that could ring a bell on the other side of a room. A few years later he was successful in sending the first wireless communication over the open sea and in 1899 he transmitted a signal across the English Channel. Marconi then built a high powered station in Cornwall and prepared an experiment to transmit a signal across the Atlantic Ocean. Marconi traveled to Signal Hill to witness the reception. Here is a generated image of that historic moment.

However, if you look closely, there are two dignitaries standing by the radio receiver, and they both look like Guglielmo, as does a third man seated to the right. But there is no record that there were Marconi triplets. This is another case of how AI, still in its early days, makes mistakes.

No one should need an introduction to Marie Curie and her discovery of radioactivity. She was the first woman to win a Nobel Prize and the only person to win a Nobel Prize in two scientific fields (Physics 1903, Chemistry 1911). As such she was famous in her lifetime and there are many photographs of her. However I was able to generate this rather dramatic picture of her by asking for “Marie Curie discovering radioactivity in her lab.”

Another scientist investigating radioactivity was Ernest Rutherford. He discovered the element radon and alpha and beta radiation, among many other things. He was the first one to “split the atom” which he did by bombarding nitrogen with alpha particles that triggered the emission of protons. Rutherford was awarded the Nobel prize in 1908 and came to be known as “the father of nuclear physics”. In spite of his many accomplishments, he is not that well known outside of the field. I added “Sir” Ernest Rutherford to my gallery, not because of a shared belief in “The Importance of Being Earnest”, a rather Wilde play deserving of an Oscar, but because I had a more fateful connection with him. 

Rutherford was a professor at McGill for a few years around the turn of the century and he did a lot of experiments in radioactivity in his lab in the physics building. When I entered McGill, word had it that he had contaminated the building with his radiation experiments. That old building still existed and is where I went for my physics classes and labs. Working in a radioactive lab may have earned Sir Ernest a Nobel Prize, but I don’t think it did me any good. 

In 1928 Margaret Mead published the book “Coming of Age in Samoa”. This work challenged prevailing notions about human development and emphasized the importance of cultural context. It launched Mead as a pioneering researcher and she became the most famous anthropologist in the world. Mead set new standards for anthropology fieldwork through her detailed observation methods and use of photography, film and psychological testing. 

Here is  the result of asking for a picture of Margaret Mead in Samoa. This is very realistic and looks like an actual photo. However I did a Google image search and there is nothing like this photo on the Internet.

Many people learned about Alan Turing from the Hollywood film “The Imitation Game” that was nominated for eight Academy Awards in 2004. However, Turing was not well known in his lifetime, because the story of breaking the German code Enigma in World War II was classified for many years after the war. The first public revelation came in 1974 but the role of Alan Turing and others at Bletchley Park did not become known until the 1980s and 1990s as more documents were declassified.

The general impression given in the movie and in the media is that to break the Enigma code Turing invented one of the first computers. This is not accurate because the machine he built, “the Bombe”, was not really a computer but more of a specialized electromechanical device that could rapidly test multiple possible settings of the Enigma machine. There was another team at Bletchley Park working on breaking a different German encryption code that did design and build a machine, the Colossus, that in fact was one of the first computers ever built.

Here’s an AI generated picture of “Alan Turing breaking the code on an Enigma cipher machine”.

Another scientist of the World War 2 era who was featured in a major Hollywood movie was J. Robert Oppenheimer. The film “Oppenheimer” received 13 Academy Awards nominations and won 7 Oscars in 2024. 

Oppenheimer first started his graduate studies in Cambridge but he was not adept with the laboratory work. To complete his Phd he went to the University of Göttingen, one of the leading centers of theoretical physics. At the time Europe was the center of the new age of quantum physics whereas American physicists were more experimental. During his time in Europe, Oppenheimer met many of the leading theoretical physicists in the world. When he was later recruited for the Manhattan Project he became a wise choice to be the head of development at Los Alamos since he could recruit many of the top physicists in the world, such as Enrico Fermi, Hans Bethe, Niels Bohr, Leo Szilard, Edward Teller and Stanislaw Ulam.

During the war the development of an atomic bomb was top secret but after bombs were dropped on Hiroshima and Nagasaki, Oppenheimer became a well known public figure. 

There were a lot of photographs of Oppenheimer so I asked for an AI generated sketch portrait instead of a photograph. Most image generators have a number of different styles that you can use, such as photographic, cinematic, concept art, graphic design and sketch drawings. Here’s the portrait of Oppenheimer which is quite good as a drawing and has a very good likeness to photos of him. 

I also tried a few pictures of Oppenheimer at work. Here’s the result of asking for “Oppenheimer inspecting the nuclear test bomb Fat Man in the desert at Los Alamos.” 

I have no idea how the AI went so far off the rails on this one. Maybe there were some training data images of garden statues that were called “Fat Man”. In the AI world, these sorts of wild errors have come to be called hallucinations. 

Oppenheimer was a great movie in many regards in portraying many of the brilliant scientists who were working on one of the great scientific projects in history. However, there was one really glaring omission. The film never mentioned John von Neumann, one of the most brilliant minds of the 20th century. Von Neumann was the youngest person ever appointed to the Institute for Advanced Study at Princeton in 1933 at the age of 29, the same year that Albert Einstein was appointed, at age 54. Many of the top scientists who worked with von Neumann had stories or comments about his genius. Hans Bethe, one of the key physicists on the Manhattan Project, said “I have sometimes wondered whether a brain like von Neumann’s does not indicate a species superior to that of man”.

Von Neumann was not part of the Los Alamos team. When the bomb design ran into a critical problem, Oppenheimer contacted von Neumann to become a consultant to the Manhattan Project. Johnny had been the first to establish a rigorous mathematical framework for quantum mechanics. He developed a mathematical model of the atomic reactions and worked with the physicists at Loa Alamos to design an implosion that would trigger the chain reaction that would produce an atomic bomb.

On one of von Neumann’s long train trips to Los Alamos, he wrote a paper describing the design for a computer. One of his revolutionary ideas was to use  memory to store the program. This allowed the computer to be reprogrammed for different tasks without rewiring the physical hardware. This stored-program design came to be known as the von Neumann architecture.

Von Neumann began a project at the Institute of Advanced Studies to build such a computer. He published progress reports and many other projects around the world used this information to design and build their own computers, notably IBM’s first computer, the IBM 701 that was released in 1952. Since then, almost all computers, from mainframes to micro computers to mobile phones are fundamentally von Neumann architecture machines.

Here’s the AI generated picture of John Von Neumann programming the IAS computer at Princeton.

Overall, I would give image generation AI a score of maybe 7/10. Some of the results are quite stunning, dramatic and accurate. On the other hand, there are many that miss the mark and occasionally go off the rails.

It’s clear to see that in spite of the hype about AI and worries about it taking over jobs and controlling the world, AI has a long way to go and is not ready for prime time. Except for some cases, like Newton the dog, Einstein the baby and Fat Man the garden statue, which are ready for prime time, on the comedy channel.