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.
Super fact 92 : College tuition and fees increased by 207% between 1997 and 2022, which corresponds to a tripling. Since 2022 it has continued to increase. Adjusted for inflation this corresponds to a 60% increase, more than any other major economic sector.
Students are sucked into a hole with money for college tuition. Shutterstock Asset id: 335014478 by alphaspirit.it.Data source: US Bureau of Labor Statistics (2026). OurWorldInData.org/technological-change. Note: Some services such as medical care are not adjusted for quality, some treatments have decreased in price rather than increased. To visit the original page for this graph click here or on the picture.
To read about the graph above in greater detail click here. To read more about the increase in college tuition click here, here, here, or here. To calculate the inflation for different periods of time click here (the inflation calculator).
It should be noted in the graphs above that Televisions have decreased in price by 98%, which seems implausible. However, it is not an April 1st joke. It is not April 1st in Texas yet (where I live). The reason for the large decline in price of Televisions is that quality is taken into account. 20 years ago, you could not easily buy the kind of TVs you can today and if you did you would cost you an enormous amount of money. You get a lot more for a few hundred bucks than you did 20 years ago.
This is a superfact because it is true, shocking, and important to how we live.
An example of heavy spending on amenities is college sports. I studied at a university called Uppsala University, which is a very large University founded in 1477. It is considered one of the world’s top Universities (top 50). However, they do not have any competitive teams associated with the University itself. In 1987 I was sent as an exchange student (electrical engineering) to Case Western Reserve University, in Cleveland, Ohio. Case Western Reserve University has some competitive teams associated with the University but only a small college football stadium.
However, I quickly came to realize that many American universities have huge college football and baseball stadiums. This is an added expense that you rarely encounter in the rest of the world. Universities are for studies and for learning. Sports teams, whether it is soccer, or American football is a separate issue.
BLOOMINGTON, US – Aug 04, 2025: Side-angle drone view of Indiana University Memorial Stadium with field, stands, and cityscape on a clear summer day. . – Shutterstock Asset id: 2700467103
Superfact 91: Without greenhouse gases, the Earth’s average surface temperature would drop from the current 15 Celsius (59 Fahrenheit) to approximately -18 Celsius (0 Fahrenheit), which is an average temperature drop of 33 degrees Celsius. If you removed carbon dioxide from the atmosphere but let the other greenhouse gases stay the drop would be 30 degrees Celsius. In both cases most of the planet would freeze. This is referred to as snowball Earth.
Shutterstock Asset id: 2750019199 by Shutterstock AI
Our planet is much warmer than it otherwise would be because of greenhouse gases. Carbon dioxide, or CO2, is the most important of the greenhouse gases. We are rapidly warming the atmosphere with our carbon dioxide emissions as explained by these articles from NASA and NOAA. If we did the opposite and removed CO2 from the atmosphere we would be cooling the atmosphere. As mentioned, if we removed all greenhouse gases from the atmosphere the planet’s average temperature would drop by 33 degrees Celsius and this NASA article claims it would take 50 years to reach that temperature.
If we removed only carbon dioxide and let all the other greenhouse gases remain, we would get an almost as big temperature drop of 30 degrees Celsius according to the calculations done by this article. Some of you may know that water vapor provides a larger portion of the warming than CO2. In fact, 75% of the greenhouse effect is caused by water vapor and clouds. This seems contradictory. However, when the atmosphere cools, the water vapor will rain out of the atmosphere unlike CO2. Basically, water vapor will adjust to the temperature whilst CO2 is forcing the temperature. It is crucial to understand this difference. That is why CO2 is the most important greenhouse gas. In summary, we need just the right amount of CO2 for a healthy climate.
I consider this a super fact because it is true, it is an important fact, and I believe it is a surprising fact to many, especially those who doubt carbon dioxide’s importance to the global warming we are experiencing. I called it global warming but whether you call it global warming, climate change, or climate disruption, we are talking about the same thing.
Snowball Earth
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Scientists believe there have been at least two major “Snowball Earth” events between 720 and 635 million years ago where ice and snow covered nearly the entire planet. These snowball earth events were triggered by natural events, likely a plunge in sunlight, followed by a plunge in carbon dioxide not entering the atmosphere, and amplified by sunlight reflecting back into space. All three effects made Earth cooler. The recent ice ages were likely caused primarily by earth’s orbital cycles. Climate changed in the past due to natural phenomena, but that does not mean that the current very rapid warming (rapid geologically speaking) is natural.
If you want to understand why we can be so sure that it is our CO2 emissions that is causing the current global warming, not the sun, not volcanoes, not orbital cycles, and not another natural process, please check out the list of evidence in the second part of this post “Global Warming is Happening and is Caused by us”.
Hothouse Venus
Image taken by the NASA MESSENGER as it approached Venus on June 5, 2007. NASA/Johns Hopkins University Applied Physics Laboratory/Carnegie Institution of Washington, Public domain, via Wikimedia Commons. The image is taken from this Wikipedia article.
The opposite of snowball Earth is hot Venus. Venus is the hottest planet in the solar system due to an extreme runaway greenhouse effect. Surface temperatures are averaging around 465 degrees Celsius (870 degrees Fahrenheit). The thick atmosphere of Venus is composed primarily of carbon dioxide with clouds of sulfuric acid. This causes a greenhouse effect that traps heat.
Despite the fact that Mercury is much closer to the sun (58 million kilometers versus 108 million kilometers) and receives nearly four times as much sunlight per unit area than Venus, Mercury is on average much cooler. The reason is that Mercury’s atmosphere is thin and without a greenhouse effect.
The YouTube video below from NASA explains the greenhouse effect on Venus. It is just one minute long.
Grant from “Grant at Tame Your Book” have written an excellent and well researched post about the dark side of Artificial Intelligence. It has nearly a hundred references and it is very professionally written. It is called Don’t Confuse AI with a Benign Tool. With this post I just wanted to highlight this important post. Please check it out.
Superfact 90: Large Language Models (LLMs) such as ChatGPT, Claude, Llama and Gemini are just one type of popular applications of Artificial Intelligence among hundreds of applications of Artificial Intelligence, and LLMs represents just one branch of Artificial Intelligence.
Artificial intelligence and research concept. Shutterstock Asset id: 2314449325 by Stock-Asso
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.
Applications of Artificial Intelligence other than what Large Language Models are used for include robotics, 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.
There are probably many applications and types of Artificial Intelligence that we have not yet invented.
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. Related to this post is my previous post Artificial Intelligence is Not New. We have only just begun.
I consider this a super fact because it is true, kind of important, and I believe that the multitude of Artificial Intelligence algorithms and applications is a surprise to many.
The many Artificial Intelligence Algorithms
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Due to the great improvement and success of Neural Networks, they have become very popular and Large Language Models use very large Neural Networks with multiple hidden layers (employing the Rumelhart back propagation algorithm). You can read more about that here.
However, there are many other AI algorithms, hundreds, maybe thousands. One example is genetic algorithms. These are types of algorithms that mimics evolution. They iteratively select a set of the best candidate solutions, then combine them (crossover), and also add random changes (mutation) to generate new solutions. Then select the best solutions and then you do it again. Selecting the best solutions corresponds to natural selection. I tried out such algorithms at my work, and over many iterations / generations you can get some impressive results. It is easy to understand how a complex organ such as an eye can evolve in a similar way in nature.
One type of decision tree based machine learning algorithm that I used specifically for classification tasks at work was C4.5 and C5. More specifically I used this type of machine learning algorithm for evaluating the results from automatic mail sorting systems. Basically, how well can a result from a certain machine be trusted. I don’t remember exactly but my classes were something along the line of super reliable, pretty reliable, average, and this result probably sucks. Other examples of this type of machine learning are ID3, Random Forest, Gradient Boosting, and CART. These types of algorithms are still very popular.
One advantage of using decision tree based machine learning over neural networks for the same task is that when a decision has been made you can follow the decision tree backwards and see why a decision / classification was made. In fact, if you have less than 100 parameters you could likely do it over a lunch. When a neural network makes a decision all you have is a large bunch of numbers that were spit out by an algorithm that looped possibly thousands of times and changing all the numbers every time. You can’t backtrack and figure out exactly how a decision was made. You just have to trust the neural network. The advantage of a neural network in this situation is that if it is trained properly, it is likely to have a better result.
Another type of algorithm used in Artificial Intelligence is search algorithms. For robot motion planning I used an algorithm called A* or A-star, which is a very efficient pathfinding algorithm. It comes in dozens of variants and there are hundreds of other types of search algorithms.
These are just a few examples, but there’s also knowledge based agents, AI-agents with reinforcement learning algorithms, algorithms based on Bayes’ Theorem, Vector Machines, Markov Decision Processes, clustering algorithms, K-nearest neighbor (KNN) algorithm, simulated annealing, hill climbing, the ant colony optimization algorithm, and of course neural networks and there are also many types of neural networks. I used a relatively unknown form of artificial intelligence called reflex control for my robotics research. The point is, there is zoo of artificial intelligence algorithms out there. Deep learning neural networks are very popular AI algorithms but far from the only ones.
My Personal Experience with Artificial Intelligence
In 1986, when I was in college in Sweden, I took a class in the LISP programming language. LISP was the first Artificial Intelligence programming language, and it was invented in 1958. In 1987, as a university level exchange student, I took a class called Artificial Intelligence at Case Western Reserve University. That same year I also took a class called Pattern Recognition which introduced neural networks to me.
In 1986 a landmark paper was published by David Rumelhart, Geoffrey Hinton, and Ronald Williams introducing the Rumelhart backpropagation algorithm. Geoffrey Hinton received the Nobel Prize in physics in 2024. David Rumelhart and Ronald Williams were both dead and could therefore not receive the Nobel Prize. The Nobel Prize was also given to John J. Hopfield, another pioneer in neural networks. He invented the Hopfield network. You can read more about neural networks and the Nobel Prize in physics in 2024 here.
The Rumelhart backpropagation algorithm was a giant leap forward for neural networks and for Artificial Intelligence and it is the algorithm used by ChatGPT and the other large language models. Geoffrey Hinton is often interviewed in media and often presented as the father of Artificial Intelligence. He is not, but he us arguably partially responsible for the greatest leap forward in neural networks, as well as Artificial Intelligence.
In the pattern recognition class, we used the Rumelhart backpropagation algorithm on a simple neural network to read images with text. Later I did research in the field of Robotics where I implemented various Artificial Intelligence algorithms as mentioned above. I have a PhD in Applied Physics and Electrical Engineering with specialty in Robotics. Later I would use artificial intelligence algorithms in my professional career.
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 potential harm of AI is a related and important topic that I did not address. I don’t know much about this topic. However, Grant from “Grant at Tame Your Book” have written an excellent, well research and professional post about this issue called Don’t Confuse AI with a Benign Tool. Please check it out.
Superfact 89: There is overwhelming scientific evidence supporting so called macroevolution. Evidence for macroevolution includes the fossil record, molecular biology and DNA, biogeography, comparative anatomy, embryology, suboptimality, vestigial structures, etc.
It is difficult to deny that so called microevolution is happening since it can be directly observed. However, it is quite common to come across claims that there is no evidence for macroevolution or that macroevolution is impossible and unscientific. These claims do not come from mainstream scientists but from creationists. There is no magical barrier between microevolution and macroevolution. Rather, macroevolution is just an accumulation of microevolutionary steps, and it is a fact that those changes have been slowly accumulating over millions and billions of years.
Microevolution is small changes resulting in large changes over time. There is no magical wall stopping multiple microevolution changes from turning into macroevolution.
It is often said that macroevolution is when a species evolves into another and that this represents a special barrier, impossible to breach. The existence of fuzzy boundaries between species and the existence of ring species demonstrate that this idea is faulty. See the next section for more information on this. Next after that, I am listing 10 selected types of evidence for macro evolution. If you wish to see an overview of 29+ Evidences for Macroevolution, click here. I can add that scientists do not like to use the terms microevolution and macroevolution since they are nebulous. These terms are more of a creationist thing. That’s why I been prefixing microevolution and macroevolution with “so called”.
Roughly a third of Americans believe the creationist claim that macroevolution is not possible, or that there is no evidence for it, even though we know that there is Strong evidence for macroevolution. Therefore, I consider this a super fact. Note, 97% of scientists support the theory of evolution. This is a brief Wikipedia article on evolution.
Note, this post is long, but if you are interested in it, you could just read a few instead of the evidences instead of all ten.
Speciation is considered relative
It is often said that two animals belong to the same species if they can interbreed in nature and produce viable, fertile offspring. However, it is not that simple.
An animal A may be able to successfully interbreed with an animal B, and that animal B may be able to successfully interbreed with an animal C, but animal A and C cannot interbreed. Animal A could be said to be a different species relative to animal C, but animal B could be said to be the same species as both animal A & C using the definition above. A great geography related example of this is ring species. In a ring species, gene flow occurs between neighboring populations of a species, but at the ends of the ring the populations don’t interbreed.
Illustration of ring species, an example of how speciation can be relative. All the circles next to each other can interbreed but at the end it no longer works. Andrew Z. Colvin, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons.
Next up are ten selected types of evidence for Macroevolution in no particular order.
The Fossil Record Show an Evolution from Simple to Complex Species
The fossil record is quite extensive and represents 250,000 different species, but it is very far from complete. That is expected. Fossilization is an extremely rare event, and fossils are hard to find. Among the 250,000 fossils from different species there are no Precambrian rabbits or Mesozoic human fossils. If there were, that would have falsified evolution and been evidence for a creator. This example shows first of all that the theory of evolution is falsifiable (all scientific theories have to be falsifiable) contrary to some creationist claims and it constitutes a form of evidence for evolution.
If evolution is true then a scan through the entire sequence of rock strata should show early life to be quite simple, with more complex species appearing only after some time. In addition, the youngest fossils should be those that are most similar to living species. The fact that this is the case is strong evidence for evolution, specifically macroevolution. You can read more about this in this relatively short book, The Evidence for Evolution, by Alan R. Rogers.
The fossil record is a lot more solid and much less problematic than the creationist books I have read claimed. Shutter Stock Photo ID: 1323000239 by Alizada Studios
We can Follow Lineages in the Fossil Record
In the fossil record we can also follow lineages; species of animals and plants changing into something different over time. The fossil records show fish changing into amphibians, reptiles changing into mammals, dinosaurs into birds, artiodactyl like mammals into whales, apes into humans, etc. Creationists used to mock the fact that there were no transitional fossils between land mammals and whales and then they found Pakicetus in 1983 and then a lot more. As time passes the more transitional fossils we find.
Closeup of fossilized scary petrified Archaeopteryx transitional fossil between dinosaur and modern birds remains. Shutterstock Asset id: 1913076019 by Natalia van D.
The fact that we can follow lineages and that they are consistent with the various dating methods is powerful evidence for evolution. Dating methods include radiometric dating methods (uranium-lead, potassium-argon, carbon-14), and sequencing and superposition, and conditions encoded in fossils such as the length of the day (varied throughout natural history) and more. To read more about dating methods and how we know Earth is billions of years old click here. The picture below illustrates the skull changes of hominids by time.
Molecular biology and DNA may be our best evidence for macroevolution. Our understanding of DNA has greatly increased over the last couple of decades. The human genome has been sequenced along with that of many other species, and we are able to compare the DNA and the genes of various species, and trace origins.
Geneticist sequencing human genome Asset id: 2479929725 by FOTOGRIN
Of special interest are pseudo genes, the millions of transposable elements (transposons and retroelements) as well as useless sequences, introns. These segments are especially interesting because they are unaffected by natural selection and therefore mutations pile up in them at a fairly constant rate. By comparing two such segments in two species we can tell how far the species are apart and even how far back in time their common ancestor lived.
Based on the similarity in transposons we know that the closest related living animals to whales and dolphins (outside their order) are Hippopotamus, which confirms what we know from the fossil record of whales and the mammals that whales evolved from. Whales and Hippopotamus have a common ancestor and since we’ve found dozens of intermediate fossils between land mammals and whales, the evolution of whales is no longer a mystery.
All living cetaceans including whales, dolphins, porpoises, sperm whales and hippopotamids / hippopotamus belong to a suborder of artiodactyls called whippomorpha. Hippopotamus and whales have a common ancestor. Note: I created this image by inserting a few pictures from Wikipedia commons including a mother sperm whale and her calf off the coast of Mauritius, a gray whale in captivity, a hippopotamus and two pre-historic whales (from the section Evolution of Whales – Intermediate Fossils).
Based on the similarity in transposons, pseudo genes, and genes in general (all of the genome) we know that the closest related living animals to humans are chimpanzees and bonobos. In fact, chimpanzees and humans are more closely related than chimpanzees and the other great apes. Based on the genetic record chimpanzees are no longer classified as great apes but as Hominini together with humans. Also based on the genetic record we know that chimpanzees and humans had a common ancestor that lived about six million years ago. The fossil for this common ancestor has not been found, but the information in the DNA can often tell us more than the fossil record.
Comparison between human and chimpanzee karyotypes isolated on background. Shutterstock Asset id: 2432966649 by kanyanat wongsa.Evolution of humans via phylogenetics and differentiation between humans, chimpanzees, and other primates. Shutterstock Asset id: 2448150743 by kanyanat wongsa.Simple cladogram showing evolution of modern man from Hominid Ancestor Shutterstock Asset id: 2093535535 by CLOUD-WALKER.
The book Relics of Eden, the powerful evidence of evolution in human DNA by Daniel Fairbanks is good fairly in depth book on this topic.
Biogeography
Biogeographic evidence for evolution / macroevolution is among the oldest types of evidence (Charles Darwin used it) and yet it is very powerful. Biogeographic evidence for evolution shows that species’ geographic distributions result from descent with modification and environmental adaptation, rather than just similar habitats. Key types of biogeographic evidence for macroevolution include species existing only on a certain island, adaptive radiation (e.g., Galápagos finches), tectonic-driven species distribution (e.g., marsupials), and convergent evolution of unrelated species in similar environments.
Adaptive radiation is a rapid evolutionary process where an ancestral species diversifies into a multitude of new species (or subspecies) to fill vacant ecological niches. Shutterstock Asset id: 2707584123 by VectorMine.
One example of biogeographical evidence for macroevolution is with so called oceanic islands. Oceanic islands are not part of a continent but are formed from the sea bottom typically through volcanic activity. Oceanic islands lack native freshwater fish and amphibians, and they rarely harbor native mammals and reptiles. However, freshwater fish, amphibians, mammals and reptiles thrive when introduced to oceanic islands. It’s just that they have to get there in the first place.
Instead, oceanic islands typically feature birds, insects, and plants that can more easily spread long distances. In addition, the species on oceanic islands are typically closely related and appear in relatively few groups. Add the fact that the species on oceanic islands resemble species on nearby continents but they are not the same. This strongly supports the narrative that some species from nearby continents migrated to newly formed oceanic islands and evolved.
The evidence gets even better if you look in more detail. For example, the Hawaiian Islands (oceanic islands) were formed in chronological order from west to east, as the divide between the continental shelves moved. The species on the different islands show a gradual transition in their physical properties and in their DNA as you go from west to east. This supports the narrative that the species hopped from one island to the next as the islands emerged, and then they evolved.
Comparative Anatomy
Similar anatomical structures in different species, such as the similar bone structure in a human arm, a bat wing, and a whale flipper indicate shared ancestry. Another is the heart structures in fish, amphibians, reptiles, birds, and mammals which show a homologous progression of development.
Embryology
Different species share similar developmental stages. For example, early embryos of reptiles, birds, and mammals, including humans, develop pharyngeal pouches that are similar to fish gills. Baleen whale embryos have teeth that are lost by birth, human embryos develop a tail that are later lost, and human fetuses develop hair around week 16-20 that is usually lost but remain on premature babies. The development of embryos goes through stages of similar embryos of fish, then amphibians, reptiles, and then mammals.
Suboptimality
There is a lot of evidence based on so called suboptimality. Our bodies and that of other animals are full of imperfections that make perfect sense from an evolutionary perspective but not much sense if we were created by a creator. One example is the “vas deference”, which follow a circuitous route from the testis up and around the ureter and back down to the penis, instead of going straight to the penis. As the testis gradually moved from inside our bodies (as it was in fish) to the outside, vas deference got stuck around the ureter like a water hose can get stuck around a tree. This makes perfect sense from an evolutionary perspective.
Vestigial Structures
Vestigial structures are non-functional anatomical features, organs, or behaviors that were functional in a species’ ancestors but have lost most or all of their original purpose through evolution. Examples include the whale hind legs, flightless bird wings, the human appendix, the tailbone, wisdom teeth, and goosebumps in humans.
Atavisms
Atavisms are rare reappearances of a lost ancestral trait in an individual. This could happen because ancestral genes are preserved but suppressed but, for example, a mutation allows the gene to be expressed. Examples include a human baby born with a tail, a snake with limbs or a chicken with teeth, dolphins with back flippers, or teeth in chickens. It is rare but evidence for evolution.
Traces of Common Descent
Traces of common descent in species, for example, homologous anatomical structures, similar embryological development, shared genetic codes, and phylogenetic mapping allows the construction of the tree of life. Phylogenetic mapping suggests that organisms inherited fundamental traits from a common ancestor. All life except viruses can be traced back to a common ancestor that lived 4.2 billion years ago. This also constitutes evidence for evolution / macroevolution.
I can add that when I was young, I read a lot of creationists books. I was totally sold on creationism but as I started learning about science that changed. One thing all the creationist books that I read had in common was that they avoided discussing the evidence for evolution and they did not provide evidence for creationism. Instead, they focused on trying to discredit evolution. As I learned more about science I came to realize that not even one of those objections were valid. An example is super fact #73 below.
Super Facts 