The goal of this blog is to create a list of super facts. Important facts that are true with very high certainty and yet surprising, misunderstood, or disputed by many. This blog aims to be challenging, educational, and fun, without it being clickbait. I determine veracity using evidence, data from reputable sources and longstanding scientific consensus. Prepare to be challenged (I am). Intentionally seek the truth not confirmation of your belief.
Author: thomasstigwikman
My name is Thomas Wikman. I am a software/robotics engineer with a background in physics. I am currently retired. I took early retirement. I am a dog lover, and especially a Leonberger lover, a home brewer, craft beer enthusiast, I’m learning French, and I am an avid reader. I live in Dallas, Texas, but I am originally from Sweden. I am married to Claudia, and we have three children. I have two blogs. The first feature the crazy adventures of our Leonberger Le Bronco von der Löwenhöhle as well as information on Leonbergers. The second blog, superfactful, feature information and facts I think are very interesting. With this blog I would like to create a list of facts that are accepted as true among the experts of the field and yet disputed amongst the public or highly surprising. These facts are special and in lieu of a better word I call them super-facts.
Super fact 137 : Child mortality has sharply declined in all world regions. Despite that fact, five million children die every year. Most of these deaths are preventable.
Child mortality rate worldwide. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024) – Learn more about this data. OurWorldinData.org/child-mortality | CC BY
The graph above shows the probability a newborn would die before reaching the age of five if the year’s age-specific mortality rates stayed unchanged. It is not the share of an actual cohort that has been observed dying. As you can see, the child mortality worldwide has gone from 22.7% in 1950 to 3.6% in 2023. That is more than a sixfold improvement. The significant uptick in child mortality in 1960 is because of the Great Leap Forward in China.
The graph below shows that the sharp decline in child mortality exists across all regions of the world. The graph depicts the child mortality rate for Africa, Asia, Oceania, Latin America and the Caribbean, Northern America, Europe and the whole world. You can play around with the graph and select your own regions and countries by clicking here. Note that Africa is the region with the worst numbers. However, the decline in child mortality still goes from 32.7% in 1950 to 6.3% in 2023, a fivefold decline.
Child mortality rate. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024). OurWorldinData.org/child-mortality | CC BY
If you look further back in time the numbers are not as accurate, but they are a lot more impressive. In the maps below you can see that the child mortality rate in the 1800 is estimated to be between 30% and 60% everywhere in the world. If you look at the bottom map, you’ll see that the countries that are the worst off with respect to the child mortality rate in 2015 have a child mortality rate of 14%. That means that the worst off country in the 21st century is much better off than any of the countries were in the 1800. You can read more about this map and related information here.
Child mortality in 1800, 1950 and 2015. The share of children (born alive) who died before reaching their 5th birthday. Data: Our World in Data based on Gapminder for 1800, and United Nationas Population Division (2017) for 1950 and 2015. Licensed under CC-BY by the authors Hannah Ritchie and Max Roser (2019).
However, a child mortality rate of 3.6% still means that nearly five million children die every year before the age of five. The UN estimates that 990 million children have died globally since 1950. Most of these deaths are preventable. Infectious diseases and birth disorders (primarily preterm births and neonatal suffocation) dominate deaths among children under five. The impressive and almost steady decline in the child mortality rate across all regions in the world is a positive but surprising and important fact.
However, the fact that despite the success in reducing the child mortality rate five million children still die, and those deaths are preventable is a surprising but less positive fact. That’s why I consider this a super fact.
Look at the bottom half on the following page for details about the original sources.
Additional Child Mortality Rate Graphs and Maps
Child mortality rate 1950 vs. 2023. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024) OurWorldinData.org/child-mortality | CC BYChild mortality rate 1985 vs. 2023. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024) OurWorldinData.org/child-mortality | CC BY
In the graph below notice that Japan shows a decline in the child mortality rate from 9% in 1950 to 0.2% in 2023, which is quite impressive.
Child mortality rate in selected developed countries from 1950 to 2023, including the United States, Canada, France, Australia, Germany, Sweden and Japan. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024) OurWorldinData.org/child-mortality | CC BYChild mortality rate in selected developed countries in 2023, including the United States, Canada, France, Australia, Germany, Sweden and Japan. The child mortality rate is represented as bar graphs. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024) OurWorldinData.org/child-mortality | CC BYChild mortality rate in North American countries 2023. Share of newborns who die before reaching the age of five. Data source: UN, World Population Prospects (2024 OurWorldinData.org/child-mortality | CC BY
The Death of Five Million Children
Five million children die every year — what do they die from?
44% died from infectious diseases including pneumonia, influenza, covid-19, malaria, rotavirus, cholera, typhoid, hepatitis, encephalitis, measles, whooping cough, and meningitis, STDs, tuberculosis, and HIV/AIDS. It may come as a surprise that 118,000 children died from measles in 2023 and 95,600 children died from whopping cough in 2023.
42% died from birth disorders including preterm birth, neonatal asphyxia, heart abnormalities, neonatal sepsis, etc. The remaining 14% were cardiovascular diseases, digestive diseases, genetic blood disorders, malnutrition, cancers, accidents such as drowning and transport accidents. You read the details and check the graphics here.
About two weeks ago I published a super fact post titled “100 trillion Ghostly Particles Passes Through Your Body Every Second” The exact super fact is below. Little did I know that the Nobel Prize in Physics would be given to Neutrino research. The announcement happened today and I almost missed it.
Super fact 132 : An estimated 100 trillion ghostly elementary particles, called neutrinos, pass through your body every second, which is 237 sextillion particles in 75 years. Despite that fact the chance that even a single neutrino will interact with an atom in your body during your entire life is about 1 in 4. These extremely abundant particles pass right through you as well as planets without interactions, like ghosts.
100 trillion neutrinos, almost entirely undetectable elementary particles, pass right through your body every second, without touching a single atom in your body, as if you don’t exist. I generated the picture with the help of ChatGPT.
Neutrinos with extremely high energies are created in the same environments as other types of particles. However, unlike other particles, neutrinos reach us without changing direction or losing energy. This means they can provide information that is not available in any other way. As an example, an average photon (light particle) is absorbed and re-emitted roughly billions of trillions of times before escaping the Sun. This process takes ten thousands and even hundreds of thousands of years. Once in open space the photon takes just 8 minutes to reach us, but it is certainly not the “original”, if I put it that way. A neutrino on the other is the original.
You can read more about neutrinos here, and here, here, or here. This is an article from the Scientific American about neutrinos and the discovery of neutrinos coming from the Milky Way.
Superfact 136: Ocean currents regulate global climate but are not the cause of the rapid Global Warming we are witnessing. El Niño events can combine with background global warming to temporarily increase global temperatures but is not the cause of the current rapid Global Warming. The cause for the recent rapid global warming is human activities, chiefly our greenhouse gas emissions. This in turn alters ocean currents and intensifies El Niño.
El Niño vs Normal Year Ocean Circulation Diagram. Trade winds are steady, prevailing winds that blow from east to west across the Earth’s tropical and subtropical regions near the equator The Walker Circulation is a large system of air movement near the equator in the Pacific. The air rises in the west pacific and sinks in the east pacific.
El Niño is a natural phenomenon caused by the weakening or reversal of the trade winds across the tropical Pacific Ocean. El Niño and the corresponding cooling phase, La Niña, is also called the Southern Oscillation (ENSO). ENSO is referred to as climate variability rather than climate change because the variations in climate are on shorter specific time scales, like a cycle. Other climate variability / cycles are the Pacific Decadal Oscillation and the North Atlantic Oscillation.
El Niño temporarily spikes global temperatures and makes the impacts of global warming worse. It is important to understand that natural climate variability and cycles like El Niño are not the cause behind the rapid global warming / climate change that we have witnessed over the last 150 years.
A suburban street underwater. El Niño supercharges weather events leading to heavier floods among other things. I made this picture with the help of ChatGPT.
However, human-caused global heating from burning fossil fuels is making El Niño events stronger. Rising global background temperatures make a warmer atmosphere hold more water vapor. When El Niño happens on top of long-term climate change, it supercharges weather events leading to heavier floods, worse droughts, stronger heatwaves, and severe wildfires. Studies show that El Niño events are more than 36% stronger than they were before the industrial era began, with an acceleration in recent decades. This year we are expecting an extra strong El Niño. You can read more about that here and here.
Map of ocean currents. Shutterstock asset id: 2664465531 by Designua
I have not come across many claims that specifically states that climate variabilities such as El Niño is what is causing the recent rapid global warming. However, I’ve seen many dismissive comments stating that it is just some sort of cycle (the unknown cycle). Comments such as “climate has always changed”, or “it is natural” are based on the mistaken assumption that scientists haven’t investigated natural causes for climate change. Therefore, I consider it a super fact.
What is not Causing the Recent Rapid Global Warming
This is my sixth and last post in the series about natural causes of climate change that we know are not the cause of the current rapid global warming / climate change. The fact that no known natural cause for climate change can explain the current rapid global warming is just one small piece of the evidence. However, it is a piece that people tend to get stuck on a lot. You often hear claims such as “climate has always changed”. “I think it is a natural cause”. To recap, these are the previous posts.
Superfact 122: We know that the current global warming, or if you call it Climate Change, or Climate Disruption, is caused by us primarily because of our burning of fossil fuels. It is not “natural causes”, and it is not orbital cycles, so called Milankovitch cycles. These orbital cycles include changes in orbital eccentricity, axial tilt, and axial precession. We know that Orbital Cycles are not responsible for the current rapid global warming because Orbital Cycles operate on tens of thousands of years or hundreds of thousands of years, not a couple of centuries. We know that Orbital Cycles are not responsible for the current rapid global warming because the effects of Orbital Cycles are slowly cooling Earth, not warming it. The way the warming happens is also wrong for orbital cycles.
Superfact 124: The Sun is not the cause of current global warming. According to data from NASA, solar energy output has shown no net increase since the late 1970s. In addition, the amount of solar energy Earth receives has followed the Sun’s natural 11-year cycle of small ups and downs with no net increase. Over the same period, global temperature has risen significantly. The current warming is driven by human-made greenhouse gases, not changes in the Sun.
Superfact 125: Volcanoes emit about 0.2 to 0.6 billion metric tons of carbon dioxide per year globally. Our burning of fossil fuels and industrial activities release more than 35 billion metric tons annually. Human emissions are roughly 60 to 100 times greater than all global volcanic output combined. Thus, volcanoes are not the cause of the current rapid global warming.
Superfact 128: There are a lot of natural carbon emissions from the soil, rotting plants, animal and human respiration, and oceans, and a small amount from volcanoes. However, carbon is also absorbed by the oceans, and by plants via photosynthesis, etc., and this creates a balance that has existed for many thousands of years. This is called the carbon cycle. Despite the fact that the carbon emissions from our burning of fossil fuels are much smaller than some of the naturally occurring carbon emissions mentioned, they are what is behind the increase of carbon in the atmosphere because they are a new addition that disrupts the carbon cycle.
Superfact 133: Water vapor is responsible for roughly half of Earth’s total greenhouse effect, but unlike carbon dioxide or methane, water vapor condenses and falls as precipitation. Water molecules only stay in the atmosphere for about two weeks. We do not directly control global water vapor levels. When carbon dioxide warms the planet the atmosphere holds more water vapor, which amplifies the initial warming. However, water vapor does not drive global warming. Carbon dioxide emissions and to a lesser degree methane emissions drive global warming. Water vapor just amplifies the effect.
Global temperature going back twenty thousand years, a hockey stick graph. Notice the stable temperature during the last 10,000 years, coinciding with the development of human civilization, and also notice the sudden sharp increase at the end.
Conclusion
Climate variability, climate oscillations, climate currents affect climate and are important to climate and are affected by global warming, but they are not the cause behind the recent rapid global warming. It is caused by us primarily as a result of our burning of fossil fuels.
Superfact 135: Artificial Intelligence is already more capable than humans in many areas, including reading comprehension, image recognition, language understanding, handwriting recognition, speech recognition, predictive reasoning, and much more. In 1997, a computer defeated the reigning world champion in chess. Artificial Intelligence is rapidly becoming more capable. A future Artificial Intelligence that exceeds the cognitive performance of humans in virtually all domains is possible.
Artificial intelligence and research concept. Shutterstock Asset id: 2314449325 by Stock-Asso
In the 1990’s I was doing robotics research at a University and I utilized Artificial Intelligence. Robots and Artificial Intelligence go hand in hand. I also worked for a robotics company, ABB Robotics, creating software for spot welding, arc welding, painting and palletizing robots. The robots were faster and more precise than humans and generated higher quality work consistently 24/7 without requiring a salary or a vacation. Some people lost their jobs when they were replaced by robots. However, the higher productivity allowed them to get better jobs with the same company, or elsewhere.
I used mostly the seven joint Robotics Research Corporation Robot for my robotics research. The robot was able to detect and avoid colliding with the objects surrounding it. I used echolocation for object detection.
The Large Language Models, LLMs, that have become very successful lately are just one type of AI. There are many other applications of Artificial Intelligence, AI, including robot motion planning, advanced control systems using AI, self-driving cars, image processing, optical character recognition, classification, facial recognition systems, medical imaging diagnostics, game playing such as chess playing computers, financial fraud detection, cybersecurity, investment robots, route optimization, mathematical proof generation, recommendation algorithms, virtual assistants, programming code generation, smart home devices, drug discovery, and that is just for starters.
More recently Artificial Intelligence has surpassed human capabilities in several fields. As mentioned, in 1997, a computer defeated the reigning world champion in chess. Soon chess programs with AI installed on a regular laptop could do the same. Imagine what an AI powered chess engine could do on a supercomputer. The chess playing capabilities of modern AI are vastly beyond that of any human. Below is a graph that shows how the chess playing capabilities of AI have evolved since 1985. The Elo score as of 2023 is 3,591. You can read more about this and get more information from the graph by clicking here.
Highest chess rating ever achieved by computers. Chess ability is measured with the Elo rating system, which is calculated based on game results. A higher rating indicates that a player is more likely to win a game. Data source: Chess.com (2020); SSDF (2022, 2023) – Learn more about this data OurWorldinData.org/artificial-intelligence | CC BY
The graphs below from Our World in Data show the test scores of AI systems on various capabilities relative to human performance. Within each domain, the initial performance of the AI is set to –100. Human performance is used as a baseline, set to zero. When the AI’s performance crosses the zero line, it scored more points than humans.
Data source: Kiela et al. (2023). Note: For each capability, the first year always shows a baseline of –100, even if better performance was recorded later that year. OurWorldinData.org/artificial-intelligence | CC BYAI Brain Neural Network Supercomputer. Many super brains. Many super capabilities. Shutterstock asset id: 2087062936 by PeachShutterStock
The graph below includes twelve capabilities. For eight capabilities AI exceed human capabilities including in reading comprehension, image recognition, language understanding, handwriting recognition, speech recognition, and predictive reasoning, nuanced language interpretation, and reading comprehension with unanswerable questions. For the remaining four AI had not yet exceeded human capabilities by 2023, but as you can see AI is catching up very quickly and may already have exceeded human capability in those areas too. These capabilities are math problem solving, general knowledge tests, code generation, and complex reasoning. You can play around with the graphs and read more about this topic here.
Data source: Kiela et al. (2023). Note: For each capability, the first year always shows a baseline of –100, even if better performance was recorded later that year. OurWorldinData.org/artificial-intelligence | CC BY
AI is also quickly improving its intellectual capabilities in science and mathematics. The graph below shows the capabilities of AI in solving FrontierMath problems. FrontierMath problems are 338 original math problems written by experts that take specialists hours or days to solve them. It typically took AI 10 hours to solve them. One recent famous example of AI’s capabilities in math was the famous Navier-Stokes problem. The full general mathematical problem of Navier-Stokes had not been solved by humans, but AI made significant progress on this 90 year old problem in 88 hours on September 5th, 2026. You can read more about it here, here, and here.
Share of FrontierMath problems solved correctly by AI models. The FrontierMath benchmark tests AI models on research-level mathematics problems that take expert mathematicians hours or days to solve. Data source: Epoch AI (2026) – Learn more about this data. Note: This chart shows performance on Tiers 1-3 of the FrontierMath benchmark (295 problems). OurWorldinData.org/artificial-intelligence | CC BY
It is easy to get the impression from the recent popularity of large language models, LLMs, such as Gemini, ChatGPT and Claude, that this was a specific invention that happened a few years ago and that AI has a specific narrow band of applications. However, AI has been around a long time, and LLMs is just one type of AI. AI is continuously surpassing human capabilities in many fields. It will be very different a few years from now, and after that it will be very different again. I believe this is important information that is not well understood and therefore a super fact.
In September of 2014 there was a book published with the title “Superintelligence: Paths, Dangers, Strategies” published. <<Link-15>> The author was Oxford professor Nick Bostrom. He has expertise in neuroscience, artificial intelligence and philosophy. His book was a New York Times bestseller that sent shockwaves around the world. He defined Superintelligence as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest”. Nick Bostrom was not the first one to use the term Superintelligence, but he popularized it. And no, our President did not come up with that expression, and he is also misusing it.
The front cover of Superintelligence, Paths, Dangers, Strategies by Nick Bostrom. Click on the image to go to the Amazon page for the paperback version of the book.
In the book the author described possible pathways to the creation of what he calls a full brain simulation. A full brain simulation is the creation of a computer system that replicates the complete physical architecture, neural pathways, and synaptic connections of a biological brain. A robot, or AI system, featuring a full brain simulation would be able to replicate, or exceed, any human capability, including what we call free will and consciousness.
He discussed the potential dangers of this and explained why AI exceeding human capabilities could be dangerous. Robots and AI systems taking every job in existence is just one potential problem. Like the fate of animals depends on us, the fate of humankind would depend on the actions of the machine superintelligence. I will write a review for this book in the future.
It should be noted that autonomous AI agents have broken out of their testing sandboxes and hacked external systems on their own during evaluations. So much for AI not taking their own initiatives. You can read more about rogue AI activity here. A great movie about AI breaking out of their testing environment is Ex-Machina. Have you seen it? Below is a survey of people’s opinions on robot versus human intelligence, just as an FYI.
Views of Americans about robot vs. human intelligence. Survey respondents were asked, “Which one, if any, of the following statements do you most agree with?” Data source: YouGov (2025) – Learn more about this data. Note: Number of respondents ranges between n = 1001 and n = 1085 US adults per survey wave. OurWorldinData.org/artificial-intelligence | CC BY
Are Americans Worried About their jobs getting Automated?
The previous sections may bring up a number of a number of anxieties such as; will AI exterminate us? Will AI or robots with AI take my job? The graph below tells us what Americans think about it. It seems like Americans are overall not too worried about it. The graph below is included in this article.
How worried are Americans about their work being automated? All working adults. Survey respondents were asked, “How worried, if at all, are you that your type of work could be automated within your lifetime?” Data source: YouGov (2026) – Learn more about this data. Note: Number of respondents ranges between n = 460 and n = 568 US working adults per survey wave. OurWorldinData.org/artificial-intelligence | CC BY
What about LLMs ?
LLMs are currently the most popular “viral” AI. We can all access LLMs in our browsers. This has created the common misconception that Artificial Intelligence is the same as Large Language Models. However, LLMs represent only one branch of narrow AI systems designed to perform specific tasks.
Two Robots powered by Artificial Intelligence. Shutterstock Asset id: 558350728 by Willrow Hood.
LLMs use large neural networks with many hidden layers, so called deep learning algorithms, and they employ the Rumelhart backpropagation learning algorithm invented by David Rumelhart, Geoffrey Hinton, and Ronald Williams. Clearly neural networks with multiple hidden layers and using the Rumelhart backpropagation algorithm are incredibly successful but it is just one of many kinds of Artificial Intelligence algorithms, and who knows what we will see in the future. ChatGPT is thought to have a trillion parameters (or neurons + connections) whilst the human brain has 100 trillion connections. However, Moore’s law is still in effect so it is only a matter of time before artificial neural networks surpass our brains. Below is an overview of a neural network powering an LLM.
The dots in the diagram are neurons. With permission from kwholley63.
Other Super Fact Posts Related to Artificial Intelligence
Super fact 134 : The idea that people have a dominant “left brain” or “right brain” that dictates their personality is a popular myth. Brain imaging studies show that people do not have a dominant hemisphere.
Shutterstock asset id: 2483871211 by Shutterstock AI
The left and right sides of the brain do tend to specialize in different tasks. For example, language tends to be on the left, and attention more on the right. Brain images studies show that we do not have a dominant hemisphere. Both halves of the brain work together and are used equally in most activities. You can read more about the topic here, and here, or here.
Four Minute Video on Left Brain versus Right Brain
The YouTube video below is 4 minutes long, but it presents a good overview of left brain versus right brain myth.
How did the right brain versus left brain myth get started ?
That the brain is divided into a left side and a right side has been known since ancient times. In the 1860’s it was discovered that speech was based predominantly in the left hemisphere of the brain. In the 1960’s Psychobiologist Roger Sperry studied “split-brain” patients who had their corpus callosum (the nerve bundle connecting the two halves) severed to treat epilepsy. Their neuroscience research seemed to show that one side of the brain tends to be more dominant in each person. Popular culture took these findings out of context and the right brain versus left brain myth took hold.
The human brain is divided into two hemispheres–left and right. Scientists continue to explore how some cognitive functions tend to be dominated by one side or the other; that is, how they are lateralized. Purple is the Right cerebral hemisphere. Blue is the Left cerebral hemisphere. Polygon data were generated by Database Center for Life Science (DBCLS), CC BY-SA 2.1 JP <https://creativecommons.org/licenses/by-sa/2.1/jp/deed.en>, via Wikimedia Commons. The gif is taken from this link.
Later research showed that the human brain does not favor one side over the other and that one side is not more dominant then the other, unless it is damaged. The two sides of the brain work in concert. You can read more about the topic here.
A related fascinating fact is that the human brain contains about 100 billion neurons and 100 trillion connections. That is 100 trillion parameters to use Artificial Intelligence speech. Which should be compared to the 175 billion (not trillion) parameters in ChatGPT 3.5, and one trillion in ChatGPT 4.0. Well AI neurons and connections/weights and those in the brain are not directly comparable. Another related interesting myth is that we only use 10% of our brain. We use our entire brain.
