Mcgovern hyundai route 2

Predictmedix – a great way to surf the Artificial Intelligence wave.
​
https://preview.redd.it/p6vawwx2ig3b1.png?width=741&format=png&auto=webp&s=16344b32088e8959d3e838a528a893994685ec85
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:

1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.

I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.

Predictmedix – a great way to surf the Artificial Intelligence wave.
​
https://preview.redd.it/gj9fc2nzhg3b1.png?width=741&format=png&auto=webp&s=f87c4488fd2fac4388b4b65e352e8b286af88c9c
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:

1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.

I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.

Predictmedix – a great way to surf the Artificial Intelligence wave.
​
https://preview.redd.it/madn1nknhg3b1.png?width=741&format=png&auto=webp&s=afdc89b341aef03eb0099910359090687d69568d
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:

1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.

I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.

Predictmedix – a great way to surf the Artificial Intelligence wave.
​
https://preview.redd.it/1euasjh6hg3b1.png?width=741&format=png&auto=webp&s=bca3509be737c63b59eab69398f5a735d746c185
There is a saying attributed to Mark Twain that goes, “History doesn’t repeat itself, but if often rhymes.” This means circumstances might be different but similar events often recur. This is good because securities regulators demand that you make it clear that in the financial markets, “Past performance is no guarantee of future results.”
However, investment analysts continue to use rhymes and here’s one that could help you see sizeable investment returns from Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF). This is how the rhyme comes together:
A. The 1990s technology boom: The parallel I see is between the current Artificial Intelligence cycle and the dot-com stock market cycle of ≈1990 to ≈ 2002. As background, the 1990s either developed or laid the groundwork for changes that completely transformed the world we live in. Out of that time came many new technologies and related developments and each was highly disruptive. Here is a very brief list of some of those developments:
(1) Nokia was the first mass-produced cellphone offered in 1992 with the ability to send and receive phone calls as well as store data (e.g. phone numbers).
(2) The World Wide Web, a.k.a. the Web browser was proposed in 1990 and debuted in 1991. This was the start of the Internet, Websites, e-mails and a massive amount of information that would become available to everyone.
(3) With the explosion of data available, finding it became a challenge. Mosaic started as the first search engine in 1993 followed by Yahoo in 1994 and Google in 1998. Today, Google has risen to the top and become synonymous with an Internet search. Google it.
(4) Other important developments of that time included the growth in the capacity of microprocessors, Photoshop, texting, rechargeable lithium-ion batteries, realistic videogames for a more adult market, collecting and using DNA, the start of e-tailing and more.
(5) Finally, we have the stock market. Cisco, Dell, Intel and Microsoft are sometimes referred to as the four horsemen of the 1990s tech boom. But we can’t ignore Apple and Google and there were many more that benefited. The smaller, new, Initial Public Offering companies came to the fore with incredibly high returns in the second half of the 1990s.
The chart to the right shows how stock markets performed during the 1990’s high-tech boom. A few things are worth noting:
(1) The Dot.Com stock market cycle lasted a long t time. Essentially, more than the decade of the 1990s. It’s length reflected the importance of the fundamental changes taking place.
(2) There was an important development regarding the stock market that has become part of the stock market legend. On December 5, 1996, Federal Reserve Board Chairman Alan Greenspan in a televised speech used the term “irrational exuberance” to describe a stock market that he thought was highly speculative and overvalued. His comment was intended as a warning from the Fed that the stock market, driven by the high-tech developments described above, was overvalued. His timing was five years early which is a lifetime in the stock market.
(3) The five years after Greenspan’s “irrational exuberance” statement was the most profitable for investors of the entire ten years plus of the stock market cycle.
As you sit reading this brief, imagine your life without a cell phone, the Internet, e-mail and text messages. How different would your life be without just these four products that emerged from the 1990s. A more relevant question might be how different would your life be if you had purchased shares in Apple or Cisco or Dell or Google or Microsoft back then?
B. The Artificial Intelligence Boom (AI): The term Artificial Intelligence was created in 1955. The idea was to have a machine that could take data, and find patterns that would enable it to make predictions and reach conclusions (make decisions). The Oxford Dictionary defines AI as “The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
It was Moore’s Law in 1975 that stated the capacity of semiconductors would continue to double every two years which enabled computers to be able to put into practice the AI Boom that is taking place today. Current forecasts say the AI industry will grow to $900 billion by 2026 and $15.7 trillion by 2030. AI growth in the 1920s could dwarf anything high-tech was able to accomplish in the 1990s.
(1) There is an Artificial Intelligence (AI) boom going on and many people don’t yet realize it is even happening. AI is used in:
i. Self-driving and parking cars. AI is used by Audi, Mercedes-Benz, Tesla, Toyota and Volvo.
ii. Maps and navigation. Enter where you are and where you want to go by car and Google Maps, for example, will give you a choice of routes, the time optimal route taking into account construction and traffic.
iii. Facial detection or recognition. Facial detection identifies a human face or facial recognition that identifies a specific face that can be used for surveillance and security.
iv. Digital assistants such as Amazon’s Alexa, Apple’s Siri, Google’s Now and Microsoft’s Cortana. When combined with search and recommendation AI, Alexa or Siri is able to learn your preferences and recommend things you are interested in.
v. Customer service chatbots that answer frequently asked questions, track orders or direct calls. Often people will be unaware they are dealing with a machine.
vi. Vehicle recognition use computer vision and deep learning to find a specific car on a surveillance video.
vii. Robot vacuums can scan a living area, look for and remember objects in the way, remember the best route for cleaning the area and decide how many times it should repeat cleaning a specific area.
It is estimated that by 2030, between 400 and 800 million jobs will be displaced by Artificial Intelligence and 375 million people will have to change to a totally different type of work. It is also forecast that it is not just lower-paying, blue-collar jobs that will be replaced by AI. Jobs such as accountants, lawyers, doctors, investment advisors and portfolio managers might all be substantially eliminated. AI will impact all industries and the rate of change will be exponential, that is, the rate of change will accelerate.
For example, what does a doctor do? In general, a doctor gathers new information, refers to a patient’s medical history, refers to a medical book or today’s Internet, makes a diagnosis and provides s treatment. This is also what a lawyer does. AI might reach the point where it can do it faster and better than a human..
AI does present threats to human existence. As AI is changing exponentially, it will happen faster than the technology boom of the 1990s. It took technology 20 years to produce the changes we discussed above. AI could produce equivalent changes in 10 or 15 years. For example, ChatGPT, an AI product went from zero to 100 million users within months making it the fastest-growing consumer software product in history. There will be others.
(2) The AI shift could drive economic change and a stock market cycle at least as significant as the last “dot.com” cycle. The “go-to” companies today for participation in AI are the likes of Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta (NASDAQ: META), Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA) and Oracle (NYSE: ORCL). These are very large companies. GOOGL has a market cap of $1.6 trillion, AMZN has a market cap of $1.2 trillion, META has a market cap of $$648 billion, MSFT has a market cap of $2.4 trillion, NCDA has a market cap of $963 billion and ORCL has a market cap of $282 billion.
(3) While these are excellent businesses, they are also amongst the world’s largest companies. In 2022, GOOGL, META and MSFT purchased 2 out of every 3 AI chips. In my opinion, it is almost unthinkable that GOOGL can be a ten-bagger from a base market cap of $1.6 trillion or AMZN from $1.2 trillion. But it is clear these stocks now have a major component of their value derived from involvement in Artificial Intelligence and it is not surprising that early adopters would choose a lower risk/lower return approach to gain exposure to an emerging Artificial Intelligence industry.
(4) The changes created by AI also carry some risks. The speed of change will be challenging to human beings. There are forecasts that say one in four workers globally will see their jobs disappear and one in eight workers will have to be retrained in a totally unrelated field. During the industrial revolution and the tech boom, there was always the promise of more and better jobs. With AI we may have reached the point where machines actually do replace workers.
(5) Cathie Wood is a well-known and widely followed money manager with a reputation for expertise in the Artificial Intelligence sector. Wood manages a range of portfolios including the ARK Innovation Exchange Traded Fund (ARKK) and since its founding in 2014, Bloomberg estimates NDVA has contributed 13% of the fund’s 112% total return only behind Grayscale Bitcoin Trust, Invitae Corp and Tesla. That is all positive but Wood sold the ARKK holding in NVDA in January 2023 just before it rallied strongly adding some $560 billion to its market cap with $200 billion coming on one day after reporting earnings. Wood’s investors have basically missed the huge rally in the stock and the sector in 2023.
(6) But there is another phase I would look for and that is the participation of smaller, retail investors. Whether it was in the tech cycle I discussed above, the “meme” stocks or commodity exploration and development cycles in the past, the retail investor buys in before the bull market ends. Market pundits such as Citi global asset allocation and Vanda Research make the same observation: where is the retail investor?
We know the institutional investors have been getting in. So far in 2023 according to Bloomberg, the top 4% of stocks in the S&P 500 have contributed 94% of the index return and 8 of the top 20 include Apple, Microsoft, Amazon, Alphabet Class A, NVIDIA, Alphabet Class C, Tesla and Meta. In other words, the top 2% of the stocks in the S&P 500 contributed 94% of the return. Through mid-May, if the AI stocks are omitted, the S&P Index would be down -1.4% instead of up +8.3%. All of these stocks are AI leaders and each of them is an institutional stock. Yet, I believe the retail investor will come into the market and when they do, it is stocks like PMED for which they have always had an appetite.
C. I think investors will get more bang for their buck by investing in a small company like Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) with a total commitment to AI. From a base market cap of $16.6 million and, as I have pointed out in recent reports, many different business verticals to get them higher, I see PMED as a unique opportunity for aggressive growth investors. It is hard to imagine any decade having more of an impact on the ensuring socio-economic decades than the 1990s. Imagine your activities today without your cellphone, Internet, email and texting.
I expect the cycle driven by AI to be a long one, similar to the dot-com cycle that lasted longer than the decade of the 1990s. To the right is a chart published by Luke Lango’s Hypergrowth Investing. It shows the stock market in the 1990s and overlays current results. The parallels Lango sees include:
• Federal Reserve’s tight money policy slowed economic growth in 1990 as it is doing currently.
• In 1990, the markets were down around 20% and in 2022 stocks dropped around 25%.
• In late 1990, the Fed started reducing interest rates and the markets rebounded.
• In late 2022, the Fed has turned less hawkish and into 2023 has slowed the pace of interest rate increases. The markets have been recovering.
• In the early 1990’s, the dot-com stock market rally began and the market would advance generally higher for the rest of the decade and into the new millennium.
• Today, it is Artificial Intelligence that is pushing stocks higher and given my expectations for AI, it could stock prices higher until at least 2030.
Conclusion: I believe Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is exceptionally well positioned to participate in the upcoming boom in Artificial Intelligence. There are many different ways to describe market cycles that evolve around such drivers. Here is mine:

1. Accumulation: the earliest buyers tend to be larger institutions that gain the information necessary to be early adopter. I have given several statistics to show this has been happening.
   
2. Retail Participation/Speculation: as the story gains acceptance, less experienced investors enter the market and prices begin to rise more quickly. After two to three years of combined buying by large and small investors, it is possible to identify speculative activities such as very rapid increases in a stock price or underwritings of companies based on questionable valuations. This is the next phase I see ahead for the current AI cycle.
   
3. Distribution/Sale: At some point, toward the end of the Retail Participation/Speculation phase, some investors will begin to sell. It is popular to believe that institutional investors or “smart money” sell at this stage. During the many years, I have spent in the investment business, this is not true. Institutions can hold on to their AI stocks for far too long and end up seeing their portfolios incinerated. This is still many years away. The challenge today with a stock like PMED is not getting out; it is getting in.
   
4. Bear Market: eventually there will be a broad sell-off of AI stocks. Some institutions will sell without regard for their impact on the market. Margin buyers will get margin calls and may be forced to sell again without regard to price. At this time, over half of the AI companies trading at that time will simply disappear. Some will be successful but remain smaller. Some will merge with another AI company. Some will be acquired. Very few will survive and become leaders in the industries. They will become the Alphabets, Amazons, Metas, Microsofts, Nvidias, and Oracles of the 2040s and 2050s.
   

I started out with the quote “History doesn’t repeat itself, but it often rhymes.” So I don’t think the AI cycle of the 2020s will be the same as the high-tech cycle of the 1990s but I think it will be similar. If you agree, Predictmedix Inc. (CSE: PMED, OTCQB: PMEDF) is a stock to buy for your portfolio.

$shlynderella
I’m case you didn’t understand.. that’s an order.

So I was solving this puzzle and I was trying to find my way to the most obvious route of separation which is the bottom of the gold bit. But I thought there has to be something more sneaky and beautiful about this puzzle that isn't so simple. So searching for a unique move I found this. From here you just pull them apart. They go apart like butter here. As I was putting it back together I found the right solution. And after video confirmation I saw that there are 2 solutions here. Curious is anyone else found this or if maybe mine is defective?

An Alternative Theory of Base Design:
The Strongline Approach
Link to Google Drive Version: https://docs.google.com/document/d/1EC6GgdczEUDktYFOgpZBQGByIw58RVpK_90_Jep_0XI/edit?usp=sharing
TL; DR Summary:
All warfare is Based – Sun Tzu, emphasizing the importance of good base construction.
Current base-design thinking, and practice, is dominated by a focus on expansive bases with multiple layers of redundancy. While not disregarding redundancy altogether, I advocate for a different approach. I contend that a more compact base with a focus on a strong front line (a Strongline if you will) which can be easily manned and repaired with only a minor level of redundancy or layering is superior. In my opinion this approach better optimizes bases for Navigability, Force Concentration, Funneling, and Cost-Effectiveness at the expense of some Redundancy. Current base design seems to revolve around controlling as large a volume of the build-area as possible, pushing the base right up to the bug entry points. But this is not a necessary or efficient use of resources. The objective is to defend the ARC, not the surrounding area. Better to build a smaller cheaper base which better defends the ARC rather than a larger, more expensive, more difficult to navigate, and more unwieldly base which (poorly) controls a large area. This is the central concept of Strongline Design Theory. If you want additional detail but not the underlying theory, skip to the section labelled “Strongline Base Design.”
https://preview.redd.it/tvti1xb1bg3b1.png?width=952&format=png&auto=webp&s=6af8c413b389b5166314c1f0b53e61753d69b6fb
The Five Principles of Base Design
Figuring things out for yourself is the only freedom anyone really has – Jean Rasczack
In order to understand and compare the current theory of base design with my alternative theory, we must first describe the 5 Principles of a good base.
I. Navigability
Battles are won by slaughter and maneuver. The greater the general, the more he contributes in maneuver, the less he demands in slaughter. -Churchill
Navigability is how easily and quickly troopers can traverse the base. Traversal includes: Combat Troopers moving from fighting position to fighting position to reinforce areas under heavy/special attack, Combat Troopers easily and securely exiting the base to hunt Grenadiers, and Repair Troopers easily and quickly checking and repairing base components.
Navigability is important because it allows Troopers to bring firepower and repairs where they are most needed and respond effectively to variations in distribution of threats across the line over time. Navigability is accomplished by having a more compact base with fewer interior fortifications blocking traversal. A low-navigability base will impede troopers from assisting each other or responding to changes in threats across the line and will function more as a series of smaller isolated bases than as a cohesive whole.
II. Redundancy
Redundancy is ambiguous because it seems like a waste if nothing unusual happens. Except that something unusual happens-usually. – Nassim Taleb
Redundancy is how well the base can tolerate a breach. It entails creating multiple layers of defense lines, compartmentalizing lines so that breaches do not grant the bugs access to a larger interior volume.
Redundancy is important because breaches are inevitable, and troopers must be able to contain and ideally patch a breach. Strong redundancy fighting positions enable this. Redundancy is accomplished by having more internal layers of fighting positions and by sealing/compartmentalizing areas of each line with further internal layers. A base with low redundancy will suffer catastrophically from small breaches as bugs are able to rapidly invade a large volume of the base.
III. Force Concentration
A major battle in a theater of operations is a collision between two centers of gravity; the more forces we can concentrate in our center of gravity, the more certain and massive the effect will be. – Von Clausewitz
Force Concentration is how well the troopers are to concentrate their firepower and repair capabilities along a narrow front. A narrow front with more troopers means firepower and repair capability can be used more efficiently and troopers can more easily support each other without having to travel a long distance. More troopers on a smaller area also minimizes the probability that a trooper will overlook/miss something (like a small bug slowly destroying the wall he is standing on) without his comrades noticing. This concept is somewhat more abstract than the previous concepts, so here illustrative example: an area of high force concentration would be a bunker which sticks out from a defense-line and enables a concentration of troopers within to engage bugs on 3 sides vs a long wall dotted with spread-out troopers.
Force concentration is important because concentrated troopers are able to support one another with equipment/deployable items and multiplies the value of these items. Force concentration can be accomplished by constructing fighting positions (ideally bunkers, but groups of walls/towers work as well) which enable troopers to cover a large area or chokepoint(s) while remaining near to one another. A base with poor opportunities for force concentration will make it difficult for troopers to assist each other and use equipment/deployables multiplicatively.
IV. Funneling
If you have an enemy, then learn and know your enemy -Denzel Washington
Funneling is how well the base directs bugs towards the intended defense/fighting positions. Funneling is closely related to and must be thought of in conjunction with Force Concentration. However, Funneling is more about understanding how the bugs will approach and react to the base.
Funneling is important because the bugs must be directed towards the fighting positions to…well…fight them. Additionally, a large, concentrated mass of bugs can be better engaged by AoE weapons. One can build the most navigable and concentrated fighting positions with superior redundancy, but that hardly matters If the bugs attack/concentrate elsewhere. Good Funneling can be achieved by understanding the Bug’s mind. The Bug strongly preferences the shortest and most direct routes to the ARC, by placing obstacles and fighting positions with this preference in mind one can direct defenders to these avenues, and good Funneling can be generated. A base with poor funneling will see the bugs spread over a large front or concentrate on an unexpected/less defensible section of front, typically leading to a breach.
V. Cost Effectiveness
Cost is more important than quality, but quality is the best way to reduce cost. -Genichi Taguchi
Finally, Cost Effectiveness is how well your base performs given the level of resources (“blue stuff”, “Baja blast”, “Smurf juice”, “blue raspberry flavoring”, “the good stuff”, etc.) has been gathered/invested. Cost effectiveness is more relevant in ARC mode than in the other mode but is still important in all cases.
Cost-Effectiveness is important because you can only gather so many resources/spend so much time before the bug attack begins or you must leave to do something else. Getting the most bang for your buck will help you to build your base quickly and finish out rounds to gain XP. Certainly, a bigger more expensive base is often ‘better’ than a smaller, cheaper one, but a smaller cheaper one may be good enough or even stronger in some areas and may be built much sooner so that the game can progress. A base with poor cost effectiveness may be unfinished by the time the bug attack begins or may simply take so long to finish that players become bored/stop having fun.
Trade Offs Between Principles
There are no solutions; there are only trade-offs. – Thomas Sowell
1. The Big One: Redundancy vs Everything Else
​
https://preview.redd.it/lr3fplt7bg3b1.png?width=709&format=png&auto=webp&s=1a487c815df9bc6a90d6907d45afd358d5d368bd
Redundancy is by far the most controversial and difficult principle to optimize for. This is because it is in opposition to every other principle. Additional interior walls and compartments make navigation more difficult, divide up defenders, make it harder to predict where bugs will engage, and increase costs dramatically. On the other hand, the occasional breach is inevitable, so some level of redundancy is required.
Be careful however, just because you have the resources does not mean you should add another interior or exterior wall, if adding that wall decreases navigability and concentration more than it improves your defensive redundancy. Layers can in fact be suboptimal, and my opinion on this has produced no small amount of onion-themed shrieking from mental midgets in VC. Weigh these factors carefully and keep this trade off in mind as you go, it is the easiest and most tempting balance to get wrong. As elaborated later, I advocate focusing more on building a solid line you can maintain/repair rather than a series of lines designed to fail.
2. Force Concentration vs Grenadiers
As it says in the Bible, God fights on the side of heaviest artillery – Robert Heinlein, author of science fiction classics you may have heard of.
Concentrating your force makes them more vulnerable to Grenadier artillery hits. Clustering your men or your defensive positions can make it easy for a single shell to severely weaken or even breach your defenses. However, for reasons elaborated under III. Force Concentration and IV. Funneling, the solution is not to spread your force along a broader front. Additionally, a broad front is no less vulnerable to grenadier fire as it is much harder to repair the damage or quickly respond to breaches in a large, broad front-style base. Instead, Grenadiers should be strongly prioritized and dealt with offensively. As soon as you or any other trooper are aware of Grenadier fire, repair the effected area and determine the direction of the Grenadier bug. An offensive team/squad should be dispatched immediately, and the remaining troopers rotated to cover whatever gaps may arise from sending a squad out of the base.
3. Force Concentration and Funneling vs Surface Area
Small is the gate and narrow the way that leads to life -God, in his hit work The Bible (Mathew 7:14)
Critics of my approach have argued that maintaining a small front (a consequence of good Force Concentration and Funneling) weakens the base as the large mass of bugs are attacking a small surface area of wall/bunker and thus doing a lot of damage to a small number of props rather than a little damage to a large variety of props. They contend, not incorrectly, that this can increase the likelihood of a breach. I would argue, that while that is true, a smaller front is also far easiefaster to repair and has significant advantages in navigability, item-sharing, AoE weapon usage, and cost. For these reasons I argue that the trade off between Force Concentration/Funneling and the Surface Area (effectively HP pool) of the base, is strongly weighted towards minimizing Surface Area.
Important Addenda
I know it’s getting a bit long, I apologize, bear with me.
A. Bunker Usage
They say I get into too many bunkers. But it is no problem. I am the best bunker player. -Seve Ballestros
Bunkers are by far the best defensive structure. They have extremely high health pools, defend multiple angles, and bugs cannot enter them. Bunkers should be the anchors of any defensive line and represent the best options for Force Concentrations and targets for Funneling. I recommend placing them directly along but routes to the ARC sticking out from the walls if possible and covering as many angles as possible. It is desirable to pull bugs onto bunkers rather than walls as their superior health and defensibility make them easier to defend and repair. A good base will maximize the surface area of bunker available for bugs to attack and will place bunkers so that they attack the bunker before the trying to hit the far weaker walls.
For example, here is a very simplified scenario of suboptimal bunker usage:
​
https://preview.redd.it/olbardxbbg3b1.png?width=419&format=png&auto=webp&s=27c62f59dbacb08921e0a850e48851e89d31ba41
In this layout, the bunker effectively defends one chokepoint, and has line of sight on the other if the wall should fall, but it does not physically block the bugs on the right if they should breach the small wall.
Consider instead, the following usage:
​
https://preview.redd.it/jgokdaflbg3b1.png?width=423&format=png&auto=webp&s=a660a7d9dbe07e8ba3eb0882ab02bb7611879c4e
In this layout, the bunker does not directly block the chokepoint, but does lie along the most direct paths between the bugs and the ARC from both entrances. This will naturally funnel the bulk of the bugs onto the bunker, where they can be easily destroyed. The bunker does not need to actually block the chokepoint, most of the bugs will still hit it rather than the surrounding walls if it is along the most direct path to the ARC. Rather than pulling some of the bugs onto a weak wall, this layout concentrates the bugs onto the far tougher bunker. In both examples, there would likely be additional defenses and terrain complications, but I have simplified this scenario to illustrate bunker usage.
B. Scale
Above all, keep it simple – Auguste Escoffier, providing some advice I perhaps should have heeded before I set out to write this damn thing.
As the previous example implied, a smaller more compact base can be superior to a large base. I will not belabor the point as I have previously mentioned it several times, but a smaller base is more navigable, cheaper, and concentrates both defenders and bugs in favorable ways. Even if you have extra resources, do not neuter a good compact base with strong external sight lines and internal navigability by adding unnecessary outer or inner walls. Keep it as small as possible and no smaller.
C. Ammunition Box Placement
Don’t be a damned ammunition wagon. Be a Rifle! – Carl R. Rogers
Ammunition is stored in the bunkers. Period. Every second the troopers run around the base retrieving ammunition is time they are not fighting or repairing. Put the ammo where they do the shooting, which if you’ve done your job well, will be the bunkers. Standardize this, make it law, ensure that never again will anyone be unsure of where to look to find ammo.
D. Electric Wall placement
Controversy is only dreaded by the advocates of error – Benjamin Rush, foreshadowing that I am about to piss everybody off.
Stop putting electric walls around the ARC. It is far better to use your limited supply of extremely powerful stunwalls to strengthen your frontline than to stick them far in the rear as a last-ditch backup for failure. The Strongline approach is all about committing to a strong front line which can be relied on not to fold. Electric walls are simply too powerful and too expensive to be used only as backup. Electric walls can be easily shot through and thus it makes the most sense to place them in front of bunkers as your first line of defense. They function best delaying/holding bugs off bunkers to increase bunker survivability. Place them in front of bunkers, in chokepoints if possible. When a front gets quiet, send a repairman out to repair them. Bunkers with forward E-walls is an incredibly strong and effective combo and should not be overlooked.
Strongline Base Design
If everyone is thinking alike, then somebody isn’t thinking - Patton.
To illustrate the practice of Strongline Base Design Theory, there is an attached example diagram. This example illustrates a simple but ideal base design. It is in a simplified environment without complex elevation changes, and with a centrally located ARC for clarity. Real implementation will necessarily deviate from this ideal configuration, but this provides a clear view into the fundamentals of Strongline design.
​
https://preview.redd.it/054chsqobg3b1.png?width=949&format=png&auto=webp&s=032ddbba323488cd16e24eaeef40bf8c438451de
The ideal here is to hold a strong single frontline. Note that the interior of the base has open routes for troopers to navigate between positions, has only 1 very minor level of redundancy (the interior wall around the ARC), is compact to concentrate defenders in a few critical locations, funnels the bugs effectively onto those locations, and is extremely cost effective. This base would likely withstand attacks far stronger than its cost would suggest and could be built and manned quickly and easily. If you have extra resources, a second layer of exterior walls in some places to carefully reinforce vulnerable segments could be added, but I have kept the diagram simple to illustrate key principles.
Prevailing Base Design Theory: Aggressive Layering
I will also provide an example of the typical Aggressive Layering Type base design. This design is extremely expensive, usually pushes directly up to the entry points to try and control the entire area, then fills in layers of redundancy behind that. These layers are effective at containing breaches, but their difficult navigability, lack of force concentration, and ineffective funneling make it difficult to prevent, predict, or contain breaches. They are redeemed only by their immense redundancy, which unfortunately comes at a high resource cost. This arrangement is still superior to many of the bases where players randomly place walls, bunkers, and turrets, but it is far from optimal.
​
https://preview.redd.it/h7jr8lsqbg3b1.png?width=870&format=png&auto=webp&s=4ccee1dcbd428e52ff254cdee0e2affab5cb7df1
This layout, while suboptimal, would likely still survive, but would consume far more time and resources to construct.
Appendix
1. Gates
Gates are generally bad. They break up your walls by not having a connecting raised walking area. They are often accidentally left open. They don’t speed up navigation as the time to open and close them is significant. And finally, they are redundant with walls and bunkers as both can be easily climbed. Gates are not needed, just build walls and bunkers unless you find yourself in the very specific situation of needing access up a ramp, in which case it is impossible to climb a wall/bunker. Gates have a small number of situational usages such as in tunnels where bunkers/walls are not easily climbable.
2. Build Order
Bunkers first, then ramp walls and walls, then auxiliary defenses. Fully plan out and lock in your 4 bunkers as soon as possible. Then build ramp walls and walls to seal off approaches completely. Finally, place turrets, towers, and electric walls as needed to complete your defense. Only then should you spend time or resources on costly redundant internal defenses.
3. Turret Placement
Turrets are best placed in the center of bunker roofs. If you’ve done your job, the bunkers will see the most action and thus benefit the most from turrets. There is some argument for putting turrets on the bug-facing edge of bunkers, as this enables them to shoot down into bugs directly abutting the bunker. However, they can be more easily damaged by the bugs in this edge-placement, and having one more thing to worry about repairing is not optimal. If the bunkers and base have been designed with good Funneling, there should be plenty of bugs approaching but not yet abutting the bunker for a center mounted turret to engage at any time. Troopers inside can and should handle any that reach the bunker itself.
4. Tower Placement
Generally, depends on the terrain and situation. If no obviously preferable locations occur to you, placing them on the leading edge of the bunker is usually excellent. While they will take damage from bugs, it is less severe if a tower becomes damaged/destroyed than if a turret were at risk, and the bunker edge-mounted towers provide excellent forward firing positions/sniper nests.
5. Kill Mazes
I have not tested this yet, but I have seen it proposed so it bears mentioning. Instead of blocking bugs’ access to the ARC, build a winding but open path. Basically, force them to play a tower defense game with you. I have not tested to see if the bug AI will follow a long but open path or if they will attempt to smash through to create a shorter path but kill mazes could be a very interesting solution.
6. Complex Structures
More complex structures like bastions, starforts, or U-shaped kill boxes are possible, but I have not thoroughly experimented with them. Maybe in a future even more insane document.
7. Disclaimer
All claims subject to changes from patches, updates, etc.