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Was That Script Written By A Human Or An AI? Here’s How To Spot The Difference.

If you spent time on social media today, you probably came across that script for an Olive Garden commercial allegedly written by an artificial intelligence algorithm. The commercial is a hilarious trip into the absurd in which patrons enjoy classic staples of the kind of Italian dining we’ve come to expect from America’s 15th favorite chain restaurant, such as “warm and defeated pasta nachos,” secret soup, Italian citizens, and “unlimited stick.”

The commercial was also, unfortunately, likely not written by AI at all. Instead, it was probably just a boring old human who claimed to have used a neural net for some sweet, sweet social media fame.

Last night, engineer Janelle Shane took to Twitter to lay out some of the telltale giveaways that the script was written by a person pretending to be an AI algorithm for kicks. You may recognize Shane as the person who trains neural nets to create jokes that devolve into nonsense or paint colors that almost sound real after being trained on thousands of actual examples. Yes, the AI-generated results are absurd, but they also highlight one key fact — the neural nets have no clue what the hell they’re talking about.

So how do you spot something written by an AI, anyhow?

“I’d say the clearest giveaways are a really short memory (maybe just a couple of sentences long) and a lack of understanding of meaning and context,” Shane told Futurism. “One characteristic of neural net text is it’ll tend to mimic the surface appearance of things without really getting the meaning behind them.

The fun parts of these bot-written passages are the parts where it creates impossibly-surreal scenarios, but one tell-tale sign that something was actually written by a person is when those individual images still fit together. For instance, the cast of the Olive Garden commercial remains consistent; if an actual neural net had been the author, characters would have been introduced and abandoned willy-nilly.

A neural net trained just on commercials wouldn’t understand how to put together a cohesive narrative, but a human writer would keep an eye out for these things.

Take, for example, this example of a recipe that was written by a neural net trained on recipes:

The instructions, you notice, have absolutely nothing to do with the ingredients listed.

Right now, artificial intelligence excels at incredibly-narrow tasks. It can generate cohesive grammar at the sentence level, but something like a script is still too complex.

“For many years yet, it will be the case that if you see a well-written story with a coherent plot and clever wordplay, it will be because a human did most of the work,” Shane said.

AI-written text will continue to grow in sophistication and prevalence, even if it’s mostly a source of humor today, Shane added. And that means it can grow to be more misleading. Today we’re just talking about who or what wrote a funny commercial online, but as artificial intelligence becomes more sophisticated, it could be used to write misinformation like convincing (but fake news) articles. That could have very real consequences for people who fall for it.

Now, based on what Shane told us, we’ve come up with a list of tell-tale signs to look for if you want to know whether a particular text was penned by human or a bot.

  1. Did it make sense? If something looks like it matches a classic joke convention but the content seems totally garbled, it likely wasn’t written by a person.
  2. How’s their attention span? If the author seems to have forgotten what they were talking about part of the way through, then you’re likely witnessing a neural net’s inherently-short attention span. Meanwhile, if the text seems sophisticated and clever or it seems as though someone actually put care into the structure of their sentences, then you’re looking at signs of a human’s touch.
  3. Did they show their work? As Shane pointed out, whoever managed to write an Olive Garden commercial with nothing but an AI algorithm would be gloating about it much more — we’d see a whole lot more about how they trained their neural net and how they managed to make everything come together. The fact that no one is geeking out about the technical side of this neural net suggests that it doesn’t exist.

The truth at the bottom of all this? We need to know what AI is actually capable of. Because how can we appreciate a parody if we don’t understand what it’s mimicking?

“There’s definitely a place for parodies of AI-generated text,” added Shane, “but the parodies only work if you know what the real stuff is like.”

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Science & Technology

20 scientific predictions for the next 10 years

We are lucky to be born and live in an incredible time of development of science and technology. We know the approximate rate of development of both, but we have no idea what this rate will be by the end of our life. Things that have long been considered science fiction are becoming components of our lives every day. In the next ten years, the world may present us with gifts that cannot be refused.

The amazing thing about all these scientific discoveries is that they give rise to technologies that further accelerate technological progress. Our ability to innovate grows exponentially as the years go by. 

To give you an idea of ​​the significance of this progression, here are 20 scientific predictions that should occur by 2030.

1. Artificial intelligence (AI) will pass the Turing test, or in other words, the machine will prove that it can think independently.

2. Hyperloop (Elon Musk’s vacuum train project) will start passenger transportation.

3. Biosensors will go on sale, which will call an ambulance if the wearer suddenly becomes ill. In addition, they will remind you to take certain medications, assessing the current state of the body.

4. The level of air pollution will rise, but scientists will come closer to an effective solution to this global problem.

5. Self-driving car will remain a luxury.

6. The world average cost of solar panels will drop sharply, the transition to solar energy will be very rapid.

7. People will return to the moon and begin its consistent colonization.

8. Robots-killers (drones with weapons) will appear. Crime will reach a fundamentally new level. Investigations will come to a standstill.

9. In developed countries, life expectancy will rise sharply. Cancer will cease to be a fatal problem.

10. NASA’s James Webb Space Telescope will be launched, which will help discover hundreds of new earth-like planets and partially learn the chemical composition of their atmospheres.

11. Rapid development of the multi-billion dollar space tourism industry.

12. In the public domain there will be “sources” for printing clothes on a 3D printer. Tens of millions of workers from poor countries will be left without even this low-paying job.

13. If breast cancer is detected on time, the chance of cure will be 100%.

14. The United States will actively grow organs from stem cells from patients themselves. The donation will in fact be liquidated.

15. We will not find extraterrestrial life on Mars. We will probably find it on the moons of Jupiter or Saturn.

16. SpaceX regularly brings people into lunar orbit in preparation for a manned mission to Mars.

17. Global warming will release the oldest viruses. The Chinese coronavirus will seem like a childish joke.

18. The Internet will completely replace television and print media.

19. Tesla cars will become the world’s best-selling cars.

20. Mass DNA editing experiments will begin. Thanks to this, children will be born with “built-in” protection against a huge number of diseases.

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Science & Technology

Designer has created a concept for the electric bike of the future

Futuristic motorcycles have become part of popular culture, associated with the concepts of the near future. They appeared in the film ” Tron: Legacy”, the anime “Akira” and in many video games from the “cyberpunk” genre. Recently, Russian designer Roman Dolzhenko presented his version of the bike of the future.

Russian designer has created a concept for the electric bike of the

MIMIC eBike – the concept of an electric superbike – originally existed as a sketch on a paper napkin. Later, the designer made the idea more realistic by rendering in 3DS max.

Minimalism prevails in motorcycle design. It lacks straight lines and protrusions. The dashboard of the bike is completely digital, and consists of a solid display showing basic information (speed and battery charge status).


There are very few details about the superbike. Social network users are most often concerned about the question: how to turn the steering wheel with this design? The front wheel fairing and handlebar structure appear to be inactive. In an interview for InceptiveMind, Dolzhenko answered this question: the front of the motorcycle turns completely, but at a slight angle.


There is no information on the cost of transport, capacity and production, which is not surprising. MIMIC eBike is just an extremely realistic concept art of the motorcycle of the future. Perhaps in a couple of years, some Elon Musk will adapt the MIMIC design for a real electric superbike.

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Genes work differently in men and women

All of our cells have the same genes. They can have mutations, however, both in the muscle cell and in the neuron there is a gene for the globin protein, an insulin gene, an acetylcholinesterase gene, etc. But is it worth reminding that a muscle cell is not like a nerve cell? The point is that genes work differently in different cells.

… although these differences should not be exaggerated – even the end sections of chromosomes, which determine biological age, look the same in men and women.

More than ten years ago, a large international team of researchers launched the GTEx (Genotype-Tissue Expression) project, the goal of which was to determine the activity of all genes in all human tissues and organs. Samples of 49 tissues were taken from 838 donors – dead healthy people, mostly elderly. First of all, the DNA was read from each of the donors. Second, the amount of different RNA was analyzed in each tissue. As you know, genetic information from genes in DNA is first read into the messenger RNA (mRNA) molecule, and then proteins are already synthesized on the mRNA molecule (for simplicity, we are not talking about a large class of RNAs that do not encode proteins and which themselves perform various important functions in the cell). The more active a gene is, the more mRNA is read from it. Therefore, by the level of different mRNAs, one can understand where which genes are more active,

The activity of a gene depends on special regulatory sequences, which are also recorded in the DNA – that is, some sections of DNA affect others. By comparing the genetic text in DNA with the amount of different RNAs in different people, one can understand which regulatory regions in DNA affect a particular gene. Such regions (or loci) in DNA are called eQTL, expression quantitative trait loci, which can be roughly translated as loci that determine the level of activity.

As a result of the work, a whole bundle of fifteen articles was recently published in Science , Science Advances , Cell and other journals. Now, using the map of tissue genetic activity for each gene, you can check how it should work in a particular organ or part of it (because several samples were taken from each organ). On the other hand, by looking for a regulatory region (eQTL) in a person’s genome, one can estimate how certain genes will work. It’s genes – because each regulatory eQTL affects more than two genes.

Another important result concerns telomeres, the ends of chromosomes that shorten with each cell division. Telomeres are often used to assess biological age: the shorter they are, the older the body is. But usually blood cells are taken to measure telomeres. What if different fabrics age differently?

The researchers estimated the length of the end sections of chromosomes in 23 tissues, and came to the conclusion that blood does indeed provide an indication of age in general: telomeres in blood cells shorten in proportion to telomeres in other tissues. At the same time, earlier studies were not confirmed, in which female telomeres were on average longer than male ones – that is, neither women nor men have telomere advantages. Which is curious in its own way, since it is believed that women generally live longer than men . This is probably because telomeres are a significant, but not the only indicator of age. In addition, it was not possible to see a strong shortening of telomeres in smokers (here it is worth noting that lung cancer can occur without telomere shortening).

By the way, about women and men. Gender differences are hard to ignore, and we all know that men and women have different sex chromosomes and that men and women have different hormones. Obviously, this should affect the work of genes. Indeed, researchers have found that 37% of our genes work differently in men and women in at least one tissue. Moreover, some genes, relatively speaking, “work” only in one sex. For example, men with different DPYSL4 gene variants will have different body fat percentages. But in women, the DPYSL4 gene does not affect body fat – this does not mean that the gene does not work, just the amount of adipose tissue depends on other genes. Similarly, in men with different variants of the CLDN7 genethere will be different birth weights. In women, birth weight is linked to another gene, HKDC1 .

Many genes, whose activity depends on sex, are associated with diseases, but their “sex” differences were still unknown. Obviously, this information is useful in personalized therapy, when the patient is being treated according to his individual genetic characteristics. However, the authors of the work note that although a lot of “sex-dependent” genes were found, their activity itself does not change very much. In general, the gender genetic differences between men and women are not very large. We emphasize that this is precisely if we take it as a whole – because the genes on which, say, primary and secondary sexual characteristics depend, work in men and women in very different ways.

What else affects gene activity? For example, age – but here there is a gap in the received data. Above we said that the samples were taken mostly from people in years; in addition, more material is needed to analyze age differences across the entire genome. (By the way, it is possible that sex differences are manifested in different ways at different ages.) Some experts, according to The Scientist portal , generally strongly doubt the reliability of the results, because samples were taken from the dead, and not from living people. On the other hand, where can we find healthy volunteers who would allow them to take a piece of tissue from the bowels of their own brain? Subsequent studies are likely to greatly adjust this map of tissue gene activity, but, one way or another, the new data will have something to compare with.

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