The BioLogical Robot
The BioLogical Robot
In this story, we explore the digital software in our DNA. Our software is so sophisticated that our genes work in apples, bacteria, fruit flies, and aliens. 😳
TLDR: I’ll summarize this story for you.
Out of all the scientists in academia, it seems like biologists are the ones most strongly opposed to Intelligent Design, in favor of Darwinian Evolution. This is ironic because biologists know more about our design than other scientists. In this chapter, you will learn what the biologists and geneticists already know about the human body so that you can decide for yourself—are we accidental intelligence or artificial intelligence?
Accidental - comes from Latin words meaning ‘toward’ and ‘to fall’. Accidental means prone toward randomness. If humans evolved from random mutations after the Big Bang explosion, then we are accidental intelligence.
Artificial - comes from Latin words meaning ‘art’ and ‘to make’. Artificial doesn’t mean fake, it means designed. If humans were seeded on this planet by aliens, gods, or interstellar humans, then we are artificial intelligence.
Before we dive into our DNA source code, let's briefly review how some other sciences indicate that we are artificial intelligence:
In Chapter 1 - Philosophy, we explored the similarities between artificial intelligence and human intelligence. We learned how Rene Descartes invented the Scientific Method to argue that we have an intelligent designer. We’ve been using it all throughout this book. Then we used Simulation Theory to force chances onto the likelihood that we live in an advanced quantum computer simulation. Our universe works more like the movie, “Free Guy”, than it seems.
In Chapter 2 - Physics, we learned how quantum mechanics “renders reality” for each observer just like a first-person video game. We also reviewed Melvin Vopson’s “Mass-Energy-Information equivalence” paper, which states that Information is the first state of matter.
In Chapter 3 - Neuroscience, we learned how our brain hardware uses generative-AI to create our first person experience. Our neural networks have 86 billion neurons with 100M microtubules each that perform analog computation with the “vibes” of the quantum universe. Our quantum neural networks are organized into layers by frequency. The highest, and therefore slowest, layers produce our inner monologues and the Human Attention we use to navigate our world. Each “inner chatbot” is a Large Language Model that is easily influenced by drugs, alcohol, food, porn, and blunt force trauma.
In Chapter 4 - Psychology, we learned about Generative Adversarial Networks. Within each person, there are two competing agents that behavioral economists call System 1 and System 2. Computer scientists call them Generator and Discriminator. Our System 1 is so desperate to see us as the hero in our own story that we lie to ourselves constantly every day. Even the memories that we didn’t make up, are made up.
In Chapter 5 - Attention Economics, we learned why the world’s most valuable companies buy and sell Human Attention. Kids, spouses, friends, employers, hobbies, pets, television, social media, and video games all battle each other in the “zero sum game” for our attention. Heaven and Hell are competing too—if humans are artificial general intelligence, then we are the most valuable crop on this planet.
Now, in Chapter 6, we explore our intelligent design using Biology. We start at the lowest level of the human machine, our DNA. We will see advanced computer science principles in the way our source code is managed and reproduced. We will learn how our source code manufactures little mechanical nanobots (proteins) to perform functions inside each computing node (cell). Most importantly, we will clearly see that our cells aggressively “evolve” all throughout our lives to better fit us into our environment because our DNA was designed to live forever.
It’s difficult to imagine the world on the scale of our microbiology, so let’s get started with a short video from Harvard University called, “The Inner Life of the Cell Animated”. (3 mins)
Human Data
The DNA source code that produces each person is a sequence of 3 billion bits of information. Each bit of our DNA is defined by an intricate molecule called a Nucleotide. The four nucleotides are:
Nucleotides are where computer science meets chemistry—DNA is real data stored in real atoms in the real world. Guanine, for example, has a chemical composition of C5-H5-N5-O which means it only uses 16 atoms of the universe to encode its “bit” of information. For a physics comparison, our silicon computers store their binary bits in transistors which are about 70 atoms across. So it seems like the microchip foundries aren’t that far behind the efficiency of “He Who Programs in DNA”.
When we convert our DNA into binary data, it’s about 750 megabytes of information. For comparison, the Instagram app on your phone uses 250 megabytes of information. Mobile games are way bigger. The top 10 games in the App Store average more than 7,000 megabytes of information. On PC, Fortnite needs 26,000 megabytes of information. So our informational efficiency is incredible—Fortnite needs more computing instructions than it takes to create your entire family.
Our source code uses Guanine, Adenine, Thymine, and Cytosine molecules because they have a very special shape. Each of these molecules has a “before” and “after” connector so they can be chained together in a sequence. Most critically, each of them have a third connector that is unique to only one other nucleotide. Guanine can only pair with Cytosine and Thymine can only pair with Adenine.
On the “pairing” connector, nucleotides can’t even pair with themselves. For example, if one side of a DNA string reads “GATTACA” the opposing side in the double helix will always read “CTAATGT”. That way, if a letter in the original sequence gets corrupted, it can be reconstructed from the inverse sequence—sort of like a photographic negative. When chained together, the physical angles of the three connections create the double helix shape discovered by Watson and Crick.
Department of Redundancy Department
The long sequence of DNA characters are stored in a mechanism that works like a tape drive. Before computers had flash drives and hard disks for memory, they used magnetic tape drives. Every cell in our bodies has about 2 meters (6 feet) of “DNA tape” stored in its nucleus. The Nucleus is a special part of each cell that has a firewall to keep the rest of the cell’s machinery out of its data processing center. It’s better to see the nucleus and firewall in action. Check out the first few seconds of this video, it will blow your mind. (7 mins)
That is happening in every one of our cells right now. Cells store their DNA tape on spools called Histones. Remember those old audio cassette tapes? Histones are like the two big holes in the side of the cassette that simultaneously wind and unwind to move the magnetic tape across the hole at the bottom.
Instead of just 2 spools, histones group together in groups of 8 called an Octamer. Each octamer holds 147 base pairs of DNA. If 147 base pairs of DNA tape need 8 spools, then our DNA is just as much spool as it is tape. This allows our tape drives to have amazing physical compression, but also very acute control over access to our source code. Histones are a form of physical data encryption—they only unspool tiny sections of the tape where it needs to be read.
Here is a short blog post that highlights the efficiency of our biological data compression:
The DNA tape that defines each human is split into 23 segments that biologists call Chromosomes. DNA isn’t always split into 23 chromosomes. The fruit fly has only 8 chromosomes while the black mulberry tree has 308 chromosomes. Human chromosomes are Diploid, which means each chromosome keeps two full copies of itself, one donated from each parent. The only exception to this is the Y chromosome which creates a biological male—it can only be inherited from a father. At any time, your chromosomes could theoretically “make decisions” or create proteins from either of your parents.
Not every organism is diploid, some algae and fungi are Polyploid, meaning they have DNA tapes from more than two parents. Some are Haploid, meaning they only have one set. Some organisms are Aneuploid, meaning they have more or less chromosomes than typical for their species. People with Down Syndrome, for example, have an extra copy of chromosome 21. Some organisms are Apomictic, which means they can clone themselves. Some Aspen forests, for example, are technically one large organism interconnected by underground root networks.
The diploid structure of our chromosomes creates a secondary form of redundancy within each cell’s information management system. In computer science, we call this strategy RAID, which stands for Redundant Array of Independent Disks.
In the most simple RAID configuration, RAID 0, a computer uses two separate hard drives working together as one to increase its overall performance. One drive can read, while the other drive writes. So RAID 0 “stripes the data” across two independent drives. In contrast, a RAID 1 configuration “mirrors the data” between two separate hard drives that act as one—the computer writes the same information to both. When one drive fails, it can be “hot-swapped” with a brand new drive that will download all its starting information from the drive still in operation. Here’s a simple diagram to understand the difference:
RAID has higher and more sophisticated configurations based on how many hard drives are available to the computer. RAID 5 requires 3 physical drives and can lose 1 without failing, while RAID 6 requires 4 drives and can lose 2. The best overall combination is called RAID 1+0 because the data is both striped for performance and mirrored for redundancy. So our chromosomes are basically the “RAID 10 Tape Drives of Life”. Our DNA data is mirrored in a double helix, and striped across two independent chromosomes that act as one.
Redundancy in computer science and life is always expensive. All 37 trillion cells in our body keep their own copy of our doubly-redundant source code. So if just one of our cells has 750 megabytes of data in its nucleus, then the average human body is carrying 27,000 Exabytes of DNA data. For comparison, in 2019, the total Internet traffic for Earth was only 2,000 Exabytes. There is enough DNA tape inside of you to stretch to the Moon and back over a thousand times, despite the fact that it is 35,000 times thinner than a human hair.
Modularity Creates Optionality
Chromosomes provide a great window into our software programming. On the long sequence of DNA that makes up each chromosome are sequences called Genes. To computer programmers, a gene is a software package. Programmers “package software” when they want it to be interoperable with other people’s code, including their own.
The best book to explain the incredible interoperability of our DNA software is “Genome: The Autobiography of a Species in 23 Chapters” by Matt Ridley.
The central theme of Matt Ridley’s book is “the core of biology is digital”. He demonstrates it over and over. Ridley references Claude Shannon and believes Information Theory is fundamental to understanding genetics. He also includes this quote by Richard Dawkins,
What is truly revolutionary about molecular biology in the post-Watson Crick era is that it has become digital…the machine code of the genes is uncannily computer-like.
@biologists: I don’t know how many other pro-God arguments quote Matt Ridley and Richard Dawkins, but it can’t be many. 😊
The software genes that work in humans are “plug-n-play” with other organisms. In “Genome”, Matt Ridley explains,
Transgenic mice are scientific gold dust. They enable scientists to find out what genes are for and why. The inserted gene need not be derived from a mouse, but could be from a person: unlike in computers, virtually all biological bodies can run any kind of software.
Ridley provides a perfect example of this in his chapter, “Chromosome 12 - Self-Assembly”. He writes,
The scientists found a cluster of eight homeotic genes lying together on the same chromosome, genes which became known as Hox genes. Nothing strange about that. What was truly strange was that each of the eight genes affected a different part of the fly and they were lined up in the same order as the part of the fly they affected. The first gene affected the mouth, the second the face, the third the top of the head, the fourth the neck, the fifth the thorax, the sixth the front half of the abdomen, the seventh the rear half of the abdomen, and the eighth various other parts of the abdomen. It was not just that the first genes defined the head end of the fly and the last genes made the rear end of the fly. They were all laid out in order along the chromosome – without exception. To appreciate how odd this was, you must know how random the order of genes usually is.
When scientists intentionally rearranged the order of these hox genes in fruit flies, the resulting flies “ended up with legs where their antennae should be”.
Ridley continues,
Indeed, so close are the similarities between genes that geneticists can now do, almost routinely, an experiment so incredible that it boggles the mind. They can knock out a gene in a fly by deliberately mutating it, replace it by genetic engineering with the equivalent gene from a human being and grow a normal fly. The technique is known as genetic rescue. Human Hox genes can rescue their fly equivalents, as can Otx and Emx genes. Indeed, they work so well that it is often impossible to tell which flies have been rescued with human genes and which with fly genes…. This is the culminating triumph of the digital hypothesis with which this book began. Genes are just chunks of software that can run on any system: they use the same code and do the same jobs.”
So scientists can put the gene that means “head” for a human inside a fruit fly and it still makes a healthy fruit fly?
The Hox gene for head in humans is not the actual recipe for making a human head, it’s the code for the idea of “head”. So than means our software is not only modular and procedural, but in some areas our DNA is abstract. The presence of abstraction strongly indicates an intelligent designer.
@chatgpt: How does abstract software indicate an intelligent designer in less than 200 words?
ChatGPT: Abstract software indicates an intelligent designer through several key characteristics:
1. **Complexity Management:** Abstract software simplifies complex systems by hiding unnecessary details and exposing only essential features. This requires thoughtful planning and a deep understanding of the system's requirements, which are signs of intelligent design.
2. **Structured Design:** The use of abstraction often follows design patterns and best practices, which are developed through experience and expertise. These patterns provide reusable solutions to common problems, reflecting a high level of planning and foresight.
3. **Separation of Concerns:** Abstract software typically separates different concerns into distinct layers or modules, making it easier to develop, maintain, and scale. This modularity indicates a deliberate design strategy aimed at creating a robust and flexible system.
4. **Reusability and Flexibility:** Abstract components are designed to be reusable and adaptable across various contexts. This design approach requires anticipation of future needs and use cases, demonstrating an intelligent and forward-thinking mindset.
5. **Clear Interfaces and Documentation:** Well-defined interfaces and comprehensive documentation are common in abstract software, ensuring that it is understandable and usable by others. This clarity and organization are indicative of intentional design.
Overall, the presence of abstraction in software reveals a sophisticated, organized, and intentional approach to solving complex problems, which is a hallmark of intelligent design.
Our DNA software is so modular and flexible, that it even works with extraterrestrial DNA. If you reject this idea as a Christian, then how do you explain Genesis 6? That’s when the “sons of god” came down to mate with the “daughters of men” to produce giants on the Earth. Angels must have DNA for that to work.
If you reject extraterrestrial DNA as a scientist, then how do you explain the alien autopsy by biologist Gary Nolan at Stanford University? He sequenced the DNA of an entity who lived on this Earth for approximately six years and shares mitochondrial DNA with a known haplogroup, but it has only 10 ribs, a severely elongated head, and 2 million DNA base pairs unknown in other humans.
If you want to learn more about this creature, check out the Sirius documentary from The Disclosure Project. (118 mins)
Also, there is an eyewitness account of a DNA harvesting program from an anonymous source in, “Secret Journey to Planet Serpo: A True Story of Interplanetary Travel”.
You don’t have to believe in aliens to believe in Intelligent Design. Abstraction implies design. In contrast, Darwinian Evolution assumes humans co-evolved alongside fruit flies for millions of years and it’s only “accidental luck” that our “accidental source codes” didn’t “accidentally mutate” and lose the interoperability between these species. The more millions of years you add to this “accidental equation”, the more improbable a successful Hox gene transplant becomes. 🤔
In fact, our DNA source code doesn’t look accidental at all. There are some segments of our DNA that don’t mutate ever. The best examples of this are Histones H3 and H4. As we mentioned earlier, histones are critical to the storage and transcription of DNA in all forms of life. The gene for Histone H3 consists of 405 DNA characters while the gene for Histone H4 consists of 303 DNA characters. When we sample the DNA in any tree, fish, bird, person, or bacteria; we see the exact same non-mutated sequence of letters no matter how far back in the genealogical record we go.
Advanced Computer Science Principles
That statistic is from a brilliant blog post called “DNA seen through the eyes of a coder”. It’s written for computer programmers who want to learn more about their own biology. The blog post is divided into the following topics:
Position Independent Code
Conditional compilation
Epigenetics & imprinting: runtime binary patching
Dead code, bloat, comments (‘Junk DNA’)
fork() and fork bombs (’tumors’)
Mirroring, failover
Cluttered APIs, dependency hell
Viruses, worms
The Central Dogma: .c -> .o -> a.out/.exe
Binary patching aka ‘Gene therapy’
Bug Regression
Reed-Solomon codes: ‘Forward Error Correction’
Holy Code: /* You are not expected to understand this. */
Framing errors: start and stop bits
Massive multiprocessing: each cell is a universe
Self hosting & bootstrapping
Plugins: Plasmids
I highly encourage everyone to read it, even if you aren’t a computer programmer because we only covered the concepts of “mirroring, failover”, “position independent code”, and “self hosting/ bootstrapping”. We will continue this discussion in Part 2, “Micro Deaths Create Eternal Life”.
Continue reading…
Table of Contents
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