Tag: Thomas Stig Wikman

Large Language Models is just One Branch of Artificial Intelligence

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.

White female AI robot using a microscope in the scientific laboratory | Large Language Models is 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.

C3P0 and R2D2 from Star Wars
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

AI Humanoid Face Concept. Technology Digital Robot Head Side View with Circuit Board Components. Tech Blue Background. Artificial Intelligence Agent or Assistant Concept. Vector Digital Illustration. | Large Language Models is just One Branch of Artificial Intelligence
Shutterstock Asset id: 2645975149

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.

A picture of a large silver colored industrial robot.
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.

My previous posts on Artificial Intelligence, “Artificial Intelligence is Not New”, and “The Nobel Prize in Physics and Neural Networks”, describe how neural networks work in greater detail.

Note on potential harm of AI

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.

To see the Other Super Facts click here

Wind Energy is Indeed Clean Energy

Superfact 87: Wind energy is a clean, renewable, and sustainable power source that produces no atmospheric emissions or water pollution during operation. Manufacturing and installation have a small carbon footprint that is much smaller than the carbon footprint of the fossil fuels they potentially replace.

Wind turbines with a background of mountains, clouds and a blue sky. | Wind Energy is Indeed Clean Energy
Photo from pexels.com

There is a lot of disinformation being spread about wind power. One recent example is the TV series Landman which presents demonstrably false claims as facts. In Texas where I live the problem with deceitful anti-renewable propaganda is especially severe. It is important to check with reputable sources before you believe what you come across. Wind energy is not 100% clean and not without issues but it is much safer and cleaner than the fossil fuels they potentially replace. Below is a two minute video that explains this.

The graph below from Our World in Data depicting lifetime greenhouse gas emissions (construction, operation, disposal) show that the lifetime greenhouse gas emissions of coal power are 88 times higher than those of wind power and kill 615 times as many people as wind power. The lifetime greenhouse gas emissions of natural gas are 40 times higher than those of wind power and kill 460 times as many people as wind power. The difference is staggering. When someone tells you that there’s nothing clean about wind power, they are not just lying to you, they are lying very big.

In the graph below, greenhouse gas emissions is measured of CO2 equivalents per Gigawatt-hour of electricity over the lifecycle of the power plant. 1 Gigawatt-hour is the annual electricity consumption of 150 people in the EU. Death rate from accidents and air pollution is measured as deaths per Terawatt hour of electricity production. 1 terawatt hour is the annual electricity consumption of 150,000 people in the EU.

The graph depicts death rates and greenhouse gas emissions per unit for different energy sources including coal, oil, natural gas, biomass, hydropower, wind, nuclear power, and solar.
Death rates from fossil fuels and biomass are based on state-of-the art plants with pollution control in Europe and are based on older models of the impacts of air pollution on health. This means these death rates are likely to be very conservative. For further discussion see our article: OurWorldinData.org/safest-sources-of-energy. Electricity shares are given for 2021. Data sources: Markandya & Wilkinson (2007); UNSCEAR (2008: 2018); Sovacol et al. (2016); IPCC AR5 (2014); UNECE (2022); Ember Energy (2001). OurWorldinData.org – Research and data to make progress against the world’s largest problems. Licensed under CC-BY by the authors Hannah Ritchie and Max Roser. Citation : Hannah Ritchie (2020) – “What are the safest and cleanest sources of energy?” Published online at OurWorldinData.org. Retrieved from: ‘https://archive.ourworldindata.org/20260202-100556/safest-sources-of-energy.html’ [Online Resource] (archived on February 2, 2026).

As you can see wind power is safe and emits very little greenhouse gases over its lifetime. In addition, there is no water impact associated with the operation of wind turbines, but a relatively small amount is used in manufacturing. There are other issues with land use, sounds, rare earth mining, waste, and effects on wildlife particularly birds.

However, these issues are in general smaller than depicted must be compared to issues with the fossil fuels they replace. For example, 15 billion tons of fossil fuels (including 9 billion tons of coal) are mined every year and burned whilst the annual mining for all clean energy technologies is around 7 million tons (2,000 times less). More about birds in the next section. Overall wind energy is a clean, renewable, and a sustainable power source. You can read more about this here, here, here, or here.

I am referring to this fact as a super fact because, it is true, an important topic, and yet it’s a fact that is difficult for many people to believe. Too much misinformation has been spread about wind power. I expect some people to dismiss this fact out of hand. But that is the point of super facts, they are true but hard to believe for many, or surprising, and perhaps even shocking.

Wind power saves a lot more birds than it kills

It may come as a surprise to some, but wind power is not a major cause of bird death. Wind farms are estimated to be responsible for losing less than 0.4 birds per gigawatt-hour (GWh) of electricity generated, compared to over 5 birds per GWh for fossil fueled power stations. This means that replacing fossil fuels with wind power saves a lot more birds than wind power turbines take. In addition, cats, windows, cars, poison and powerlines are examples of things that kill a lot more birds than wind power does. Cats kill thousands of times more birds than wind power does, and this usually does not bother us. Note I love both dogs and cats.

It is difficult to make exact estimates of bird deaths but below are some interesting graphs from reputable sources, confirmed by many other studies and analysis, such as this overview from MIT and this analysis by Hannah Richie. The numbers aren’t the same, but they make the same point. You can read more about this here.

The graph shows that Wind Turbines kill 328,000 birds per year in the US, Electrocutions kill 6,250,000 birds, Collisions with powerlines kill 32,500,000 birds, Poison kills 72,000,000 birds, Vehicle collisions kill 214,500,000 birds, Collisions with glass kill 676,500,000 birds, and cats kill 1,850,700,000 birds per year in the US.
From Wikipedia: Universiteit van Nederland, CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons
Bar graph showing cats killing an estimated 2,400 million birds per year, buildings killing an estimated 599 million birds per year, automobiles killing an estimated 200 million birds per year, pesticides killing an estimated 67 million birds per year, powerlines killing an estimated 28 million birds per year, communication towers killing an estimated 6.6 million birds per year, and wind turbines killing an estimated 1.2 million birds per year. | Wind Energy is Indeed Clean Energy
An alternative graph taken from Hannah Richie / Our World in Data, using alternative sources essentially showing the same thing. Sources: Loss et al. (2015), (2013), US Fish and Wildlife Service; Subramnayan et al. (2012), American Bird Conservancy (2021).

That does not mean we shouldn’t do our best to reduce bird deaths from wind power stations. However, don’t fall for the misinformation that is trying to paint it is a big problem specifically for wind power.

Wind power turbines by the seashore. The sun is setting. | Wind Energy is Indeed Clean Energy
Photo from pexels.com

Wind Power is Inexpensive

Finally, a bit of a deviation from the main topic. In addition to being a relatively clean, renewable, and sustainable power source, wind power is now relatively cheap, which explains its recent success around the world. I am bringing this up because another widespread myth about wind power is that it is expensive and wouldn’t survive without subsidies.

Practically all energy sources are subsidized, and fossil fuels have a long history of government subsidies. Below is the average unsubsidized levelized cost of energy according to Lazard. Levelized means that construction costs, land rent, and other costs not directly caused by electricity generation are taken into consideration. Notice how cheap wind is (blue line). This graph is for the United States.

The image shows 8 graphs representing the price of Nuclear, Gas (peaker), Thermal Solar, Coal, Geothermal, Natural Gas, Solar Panels, and Wind. Today Wind is the cheapest.
Average unsubsidized levelized cost of energy. Notice that the light blue line indicates that wind power is pretty cheap. Mir-445511, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons.

Windpower is not only relatively cheap. Wind power is one of the most efficient and sustainable energy sources available. The energy required to manufacture, install, and maintain wind turbines is small compared to the energy they produce over their lifespan. This is known as their energy return on investment (EROI), which is quite favorable for wind energy. The Institute of Environmental Management and Assessment (IEMA) states that the average wind farm will pay back the energy that was used in its manufacture within 3-5 months of operation. This article in the journal Renewable Energy found that the average windfarm produces 20-25 times more energy during its operational life than was used to construct and install its turbines. It included data from 119 turbines across 50 sites going back 30 years.

It is important to be aware that there are many false claims floating around about wind power. The sound from wind power stations does not cause cancer, it does not use any other energy sources while operating; it solely harnesses the kinetic energy from the wind to generate electricity, meaning it only relies on wind to function as its primary energy source. Windpower is not a major cause if bird deaths. To read more about false claims about wind power click here.

Conclusion

There are positive and negative aspects of wind power, like any other source of energy. One issue with wind power (and solar) is that it is an intermittent source of energy. When the wind is not blowing you need other sources of energy (until there is sufficient energy storage). This is less of a problem when you have a mix of energy sources and in practice it has not been a big problem so far. However, what we know is that Wind Energy is indeed clean energy, much cleaner than the fossil fuels they potentially replace, and also relatively cheap, even without subsidies.

Other Posts by Me Related to Wind Power

To see the Other Super Facts click here

The Evolution of Whales is No Longer a Mystery

Super fact 85 : Scientists recognized that whales descended from land animals already in the 19th century. However, it was not until the 1980’s that intermediate fossils for whale evolution were found. In addition, molecular and genetic / DNA studies showed that Hippopotamus and whales were closely related. Until then the evolution of whales was a bit of a mystery and creationists frequently mocked the lack of intermediate fossils for whale evolution.

This graph shows pictures of a sperm whale, gray whale and hippopotamus on the right, and two whale ancestors at the top and they are connected via lines ultimately showing the common connection point on the far left. | 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. Just like humans and chimpanzees have a common ancestor 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). All pictures are shown below.
The picture shows a mother and calf sperm whale swimming in the ocean.
Sperm whales from Wikimedia commons. A mother sperm whale and her calf off the coast of Mauritius. The calf has remoras attached to its body.
The picture shows a gray whale in water. | The Evolution of Whales is No Longer a Mystery
A gray whale in captivity. Marine Mammal Commission, Public domain, via Wikimedia Commons.
Portrait of a Hippopotamus in water in Saadani National Park. Muhammad Mahdi Karim, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0&gt;, via Wikimedia Commons.

Scientists realized hundreds of years ago that whales were a lot more like mammals than fish, in fact they were mammals. However, the fact that no intermediate fossils between land dwelling mammals and whales had been found presented a mystery and attracted the mockery by creationists. It was said that there was a missing link. Then intermediate fossils were found, and then a lot more of them.

In addition, DNA analysis of modern whales and hippopotamus showed that they were related and had a common ancestor. Just like chimpanzees and humans have a common ancestor, but chimpanzees are not an ancestor to humans, hippopotamus and whales have a common ancestor, but whales did not evolve from hippopotamus. To read more about the evolution of whales click here, or here, or here, or here, or here, or here, or here.

The thing with gaps in the fossil record or so called missing links is that as they are filled out new gaps are created, smaller gaps. Therefore, you can always claim that there are gaps. So be careful when you hear creationists speaking of missing links or gaps in the fossil record. Instead focus on the intermediate fossils that we have found and keep finding.

The fact that we’ve found a lot of intermediate fossils for the evolution of whales and that DNA tells us that Hippos and Whales are related and have a common ancestor probably comes as a surprise to many. It was certainly a surprise to me when I heard it the first time. It is true and kind of important to know. Therefore, I consider this a super fact.

Evolution of Whales – Intermediate Fossils

The first intermediate fossil found between land mammals and whales was Pakicetus found in Pakistan in 1983. You may wonder how we know that Pakicetus was related to whales. This evidence includes its fossilized ear bone (auditory bulla), which possesses a unique, thickened shape called an involucrum that is found only in cetaceans. Pakicetus also shares whale-like teeth, an ankle bone and a skull structure similar to other early whale like creaturs. Since the discovery of Pakicetus a lot more whale ancestors (intermediate fossils) have been found. Below is a list with illustrations of the various intermediate fossils.

Pakicetus: The illustration shows a four legged carnivorous mammal with a tail and an elongated snout.
Pakicetus inachus, a whale ancestor from the Early Eocene of Pakistan, after Nummelai et al., (2006), pencil drawing, digital coloring. It lived 48-49 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Indohyus: The illustration shows a four legged carnivorous mammal with a tail and an elongated snout. | The Evolution of Whales is No Longer a Mystery
Indohyus major, a herbivorous whale ancestor from the Middle Eocene of Kashmir, pencil drawing, digital coloring. It lived 48-49 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Ambulocetus: The illustration shows a four legged carnivorous mammal with a tail and an elongated snout.
Ambulocetus natans, a primitive whale from the Early Eocene of Pakistan, pencil drawing, digital coloring. It lived 48-49 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
Kutchicetus: The illustration shows a carnivorous mammal with short legs, a tail and an elongated snout. It is swimming in the ocean.
Kutchicetus minimus, an early whale from the middle Eocene of India. Pencil drawing, digital coloring. It lived 48 million years ago. Nobu Tamura, CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
Remingtonocetus: The illustration shows a carnivorous mammal with short legs, a tail and an elongated snout. It is swimming in the ocean.
Remingtonocetus harudiniensis, an archaeocete whale from the Middle Eocene of India, pencil drawing, digital coloring. It lived 48 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
Maiacetus. It lived 47.5 million years ago. | The Evolution of Whales is No Longer a Mystery
Maiacetus. It lived 47.5 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons.
Rodhocetus: The illustration shows a mammal with short legs swimming in the ocean. It has flat feet, a tail and an elongated snout. It looks even more like a sea creature now.
Rodhocetus kasrani, an archaeoceti whale from the late Eocene of Pakistan, digital. It lived 45 million years ago. Nobu Tamura, CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Dorudon: The illustration shows a mammal with fins swimming in the ocean. It has flat feet, a tail and an elongated snout. It looks even more like a sea creature now.
Dorudon atrox, an ancestral whale from the Late Eocene of Egypt, pencil drawing, digital coloring. It lived 35 million years ago. Nobu Tamura, CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
Aetiocetu: The illustration shows a fish or whale looking creature swimming in the ocean.
Aetiocetus cotylalveus, an early baleen whale from the Late Oligocene of Oregon, pencil drawing, digital coloring. It lived 27 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
Squalodon: The illustration shows a fish or dolphin looking creature swimming in the ocean. | The Evolution of Whales is No Longer a Mystery
Squalodon calvertensis, a toothed whale from the Late Miocene of North America, pencil drawing, digital coloring. It lived 25 million years ago. Nobu Tamura, CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Janjucetus: The illustration shows a fish or whale looking creature swimming in the ocean.
Janjucetus hunderi, a Mysticeti whale from the Oligocene of Australia, digital work. It lived 25 million years ago.  Nobu Tamura   email:nobu.tamura@yahoo.com   http://www.palaeocritti.comderivative work: Niusereset, CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Kentriodon: The illustration shows a dolphin looking creature swimming in the ocean.
Kentriodon pernix, an odontocete dolphin-like whale from the Miocene, pencil drawing, digital coloring. It lived 20 million years ago. Nobu Tamura (http://spinops.blogspot.com/2012/06/kentriodon-pernix.html?q=Kentriodon), CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
Aulophyseter: The illustration shows a creature that looks a bit like a sperm whale swimming in the ocean. | The Evolution of Whales is No Longer a Mystery
Aulophyseter morricei, a sperm whale from the Middle Miocene of California. It lived 20 million years ago. Nobu Tamura, CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Cetotherium: The illustration shows a creature that looks like a modern gray whale swimming in the ocean.
Cetotherium furlongi, a baleen whale from the mid-Late Miocene of Europe, Russia and North America, digital. It lived 18 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 <https://creativecommons.org/licenses/by/3.0&gt;, via Wikimedia Commons.
Brygmophyseter: The illustration shows a creature that looks like a sperm whale swimming in the ocean.
Brygmophyseter shigensis (aka as Nagacetus shigensis), a sperm whale from the Mid Miocene of Japan. Digital. It lived 15 million years ago. Nobu Tamura (http://spinops.blogspot.com), CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons.
To see the other Super Facts click here

Humans and Chimpanzees Have a Common Ancestor

Super fact 81 : Humans are not descended from chimpanzees, or monkeys, or any other primate living today. However, humans and chimpanzees share a common ancestor that lived roughly 5 to 7 million years ago. The two species evolved separately to become modern humans and chimpanzees. Humans and chimpanzees are closely related and share approximately 98.8% of their DNA. Studying the DNA, it is possible to determine how long ago this ancestor lived despite not having any fossils from this ancestor.

Chimpanzee genome sequencing and the sequencing of human DNA has led to the realization that human and chimpanzee DNA is very similar and that humans and chimpanzees share an ancestor. The fact that the great apes have 48 (24 pairs) chromosomes while humans have 46 (23 pairs) is not an issue. What happened was that the ancestral chromosomes corresponding to modern chimpanzee chromosomes 2A and 2B fused to create human chromosome 2. We can see that the genes in 2A and 2B line up with chromosome 2 and we can also see where the 2A and 2B merge in the human chromosome 2 (see picture below).

The picture is a graph that shows that gorillas, chimpanzees and humans share a common ancestor with orangutans. In turn bonobos, chimpanzees and humans share a common ancestor with gorillas and finally chimpanzees and bonobos share a common ancestor with humans. | Humans and Chimpanzees Have a Common Ancestor
Evolution of humans via phylogenetics and differentiation between humans, chimpanzees, and other primates. Shutterstock Asset id: 2448150743 by kanyanat wongsa

The graph above shows that gorillas, chimpanzees and humans share a common ancestor with orangutans. At the next level bonobos, chimpanzees and humans share a common ancestor with gorillas and finally chimpanzees and bonobos share a common ancestor with humans. We can deduct these things from DNA without needing fossils. We have found millions of fossils corresponding to more than 250,000 species. However, the best evidence for so called “macro evolution” and the best tool for determining relationships between species may not be the fossil record but DNA.

It should be noted that the terms “macro-evolution” and “micro-evolution” are terms that creationists like to use but that scientists do not like to use. Creationists like to say that microevolution is possible (it is observed) but not macroevolution. However, macroevolution is the result of repeated microevolution, so you cannot claim that microevolution is possible but not macroevolution. In addition, speciation is relative. 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.  The border between microevolution and macroevolution is fuzzy.

The fact that we can determine evolutionary ancestry by sequencing DNA of living creatures may come as a surprise to many people. In addition, we can also determine how long ago a common ancestor lived. It may also come as an additional surprise to many that we are not descended from the great apes but share a common ancestor. Super fact 81 is a super fact because we know it is true, it is surprising to many, and important to know.

Identifying a common ancestor using DNA Sequencing

Below is a very high-level image of human and chimpanzee chromosomes referred to as a Karyotype. A karyotype is a laboratory-produced image or visual profile of an individual’s complete set of chromosomes, arranged in pairs by size, shape, and number.

The pictures show the set of the human 46 chromosomes on the left and the set of the chimpanzee 48 chromosomes on the right. The chromosomes look very similar between the two species, except human chromosome 2 which is split into chromosome 2A and 2B in the chimpanzee.
Comparison between human and chimpanzee karyotypes isolated on background. Shutterstock Asset id: 2432966649 by kanyanat wongsa

Based on the similarity in transposons, or jumping genes, pseudo genes, and genes in general (all of the genome) we know that the closest related living animals to humans are chimpanzees and bonobos. You can read more about this in the book Relics of Eden by Daniel Fairbanks, a book I highly recommend. According to the author the latest and perhaps best evidence for evolution as well as the fact that humans and chimpanzees have a common ancestor comes from so called junk-DNA. DNA that is not currently used but contains scientifically informative remnants of our evolutionary ancestry trapped in our DNA. The author refers to these remnants as relics.

Hominini species

Another interesting fact derived from DNA research is that chimpanzees and humans are more closely related than chimpanzees than to the other great apes. Based on the genetic record chimpanzees are no longer classified as great apes but as Hominini together with humans. The fact that there are three Hominini species (homo sapies – us humans, chimpanzees and bonobos) could maybe be another super fact.

Homo skull changes of hominids from Wikipedia<>. SimplisticReps, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons.

Speaking about hominini species, we have found more than 6,000 hominin fossils corresponding to dozens of species including Australopithecus, Paranthropus, Homo Habilis, Homo Erectus, Homo Heidelbergensis, Homo Neanderthalis, and Homo Sapiens. This link features a cool phylogenetic tree that includes Homo Sapiens (us), Neanderthals, as well as chimpanzees and bonobos.

Other Evolution Related Super Facts

To see the other Super Facts click here

Conic Sections are the Shapes that Shape Our World

Super fact 80 : A conic section is a shape formed by slicing a cone with a plane. There are four such shapes, circle, ellipse, parabola, and hyperbola. The conic sections universally describe motion under gravity. The orbits of planets around their stars are circles or ellipses, comets fly around space in elliptical orbits, or parabolic or hyperbolic paths. Objects thrown up in the air follow parabolic paths. They are the basis for a huge amount of engineering applications.

Esther’s writing prompt: January 21 : Shapes

Click here or here  to join in.

Four cones each shown with a plane section forming a specific conic section. | Conic Sections are the Shapes that Shape Our World
Types of conic sections : circle , ellipse , parabola , hyperbola Shutterstock Asset id: 2377159367 by ProfDesigner

The four conic sections, circle, ellipse, parabola and hyperbola are fundamental and very useful shapes in mathematics, physics and engineering. Well, a circle is a special case of an ellipse, so it is really only three conic sections. The motion of the planets and other stellar objects are described by the conic shapes. Isaac Newton derived his law of gravitation from Kepler’s laws, which describe planetary orbits as ellipses.

The conic sections are all described by second degree equations (quadratic equations) and are in that sense the simplest shapes aside from points and lines. It is important to understand that there is an infinite amount of shapes that are almost conic sections and look like conic sections, but it is the exact mathematical properties of the four conic sections that make them so common in physics, mathematics, nature and engineering.

The picture shows a cone with four planes slicing the cone in four ways. The resulting shapes are circle (red), ellipse (green), parabola (blue), hyperbola (orange).
The black boundaries of the colored regions are conic sections. Not shown is the other half of the hyperbola, which is on the unshown other half of the double cone. by Magister Mathematicae, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=18556148

It may not come as a surprise that the circle is a fundamental and important shape, but I believe that the fact that the other conic sections are also fundamental in mathematics, physics and engineering come as a surprise to people outside of the STEM fields. It is a true and an important fact regarding how our world works.

Conic Sections

As mentioned, the conic sections are fundamental shapes that appear in a lot of places in STEM. Below are a few examples.

Parabola

Math function parabola graphics illustration with a dark background. | Conic Sections are the Shapes that Shape Our World
Math function parabola. Shutterstock Asset id: 1628916337 by EleonoraDesigner

A parabola is formed when a plane cuts a cone, so the plane is parallel to a side of the cone. Parabolas are shapes that are roughly U-shaped and described by the equation y = x^2 or more generally by y = ax^2 + bx + c. Parabolas have a so called focus point. See the picture below. If you throw a ball, or any object, up in the air its trajectory will be a parabola (ignoring distortions caused by friction and wind). I should say the parabola you get in this case is upside down. The parabola is important when you design any kind of projectile.

U-shaped parabola with the focus shown. The pciture has an x-axis and a y-axis.
Part of a parabola (blue), with various features (other colours). The complete parabola has no endpoints. In this orientation, it extends infinitely to the left, right, and upward. Picture is from Wikipedia Melikamp, CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons.

Antennas shaped like parabolas (in 3D) will direct incoming radiation and waves towards their focus point. If the surface is reflective a light located at the focus point will reflect to create a straight beam. Parabolas are used for radio telescopes, satellite dishes, car headlights, flashlights, solar cookers, solar power plants, water fountains, suspension bridges, business modelling and thousands of engineering applications. Parabolas like circles and the other conic sections shape our modern world (pun intended).

A parabola dish with equipment located at the focus.
Würzburg-Riese radar built by Germany in WW2 had a 7.4 meter (24 foot) dish. From this page. Alan Wilson from Stilton, Peterborough, Cambs, UK, CC BY-SA 2.0 https://creativecommons.org/licenses/by-sa/2.0, via Wikimedia Commons

Ellipse and circle

As mentioned, a circle and an ellipse are conic sections formed by intersecting a plane with a cone. You get a circle when the cuts perpendicular to the cone’s axis (see pictures above) and an ellipse form when the plane intersects the cone at a slant but not slanted so much that it becomes a parabola or a hyperbola. An alternative for an ellipse is that the sum of the distances from any point on the curve to two fixed points (called the foci) is a constant. See the picture below. The two definitions are identical. For a circle the two foci are merged into one point at the center.

The picture shows an ellipse and its two foci points. From the foci points there are lines going to a point P on the ellipse. The length of the two lines are added together and is the sum “2a” no matter where on the ellipse the point P is located. | Conic Sections are the Shapes that Shape Our World
Ellipse: definition by sum of distances to foci. Ag2gaeh, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons

There are a lot of real world examples of ellipses. Planets orbit the Sun in elliptical paths. The sun is in one of the foci points. The orbits of other stellar objects and satellites are also elliptical. Charged particles follow elliptical paths within magnetic fields.  Elliptical patterns are observed in the rotation of ocean currents, elliptical models and algorithms are used in medical imaging, computer science and encryption. Also whispering galleries.

Hyperbola

Comets and spacecraft that are not orbiting another body, in other words, they have enough speed to escape the gravitational pull and continue into deep space, will travel along a hyperbola. The boundary of a shockwave from a supersonic jet (a sonic boom) creates a hyperbolic curve on the ground as it moves. The intersection of two sets of concentric ripples in water makes a hyperbola. The light beam from a lamp or flashlight makes an ellipse or an hyperbola on a plane depending on the angle.

Newton’s Law of Gravitation

Johannes was an early 17th century German mathematician who derived three laws that describe how planetary bodies orbit the Sun using the observational data collected by the Danish astronomer Tycho Brahe. The three laws are the following:

  • Planets move in elliptical orbits with the Sun as a focus.
  • A planet covers the same area of space in the same amount of time no matter where it is in its orbit.
  • A planet’s orbital period is proportional to the size of its orbit (its semi-major axis).
Kepler’s three laws are illustrated in a diagram for two planets.
Illustration of Kepler’s laws with two planetary orbits.
The orbits are ellipses, with foci F1 and F2 for Planet 1, and F1 and F3 for Planet 2. The Sun is at F1.
The shaded areas A1 and A2 are equal and are swept out in equal times by Planet 1’s orbit.
The ratio of Planet 1’s orbit time to Planet 2’s is (a1/a2)^3/2
Hankwang, CC BY-SA 3.0 <http://creativecommons.org/licenses/by-sa/3.0/&gt;, via Wikimedia Commons

Later Isaac Netwon would use Kepler’s three laws to derive his law of gravity. Newton showed that an inverse-square force (gravity) directed toward the sun was necessary to explain the orbits.

My Other Responses to Esther’s Prompts

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