Today we’ll talk about Trouble at ITER, robots that build robots, air pollution, AI that classifies supernovae, a small asteroid that hit Canada, Super GPS, a new supercomputer simulation of the sun, a quantum thermometer. And of course, the telephone will ring.
Transcript, references, and discussion on Patreon.
[This is a transcript of the video embedded below. Some of the explanations may not make sense without the animations in the video.]
Forget war, forget climate change, recessions, pandemics. Today we’ll talk about a real crisis. The decrease of testosterone levels. Just look at all those headlines. There must be something going on. But what? Are testosterone levels really falling? If so, why? And how much of a crisis is it? That’s what we’ll talk about today.
The probably most prominent advocate for boosting your testosterone levels is Tucker Carlson, an American TV host. He’s seriously worried about the supposed decline of manliness and, among other things, suggests that men tan their balls to increase their testosterone levels. This is what his vision of the future man looks like.
So I made a PhD in physics and somehow ended up on YouTube talking about people tanning their balls. How do I explain this to my mom?
Apparently the idea started with a paper from 1939 by researchers from the Psychiatric Unit of the Boston State Hospital. The irradiated five patients with a mercury lamp in different body parts and found that the largest increase of testosterone levels happened when the target was the scrotum.
I don’t know want to know what else happened at that place. But even leaving aside the somewhat questionable circumstances, 5 patients in a psychiatric unit are not a representative sample for half the world population. There’s no evidence that irradiating your family jewels will do your testosterone levels any good. And the US Food and Drug Administration cautions against the use of testosterone unless there’s an underlying medical condition. They say that the benefits and safety of testosterone supplements have not been established.
But let’s step back from the testosterone craze for a moment and talk about the scientific basic. Testosterone and estrogen are the most important human sex hormones. We all have both, but men have higher testosterone levels, while women have higher estrogen levels. Testosterone in men is, among other things, responsible for changes during puberty, muscle mass and strength, hair growth, and sperm production.
Men with low testosterone levels may suffer from fatigue, depression, and sexual dysfunction. But too high testosterone levels also aren’t good. One of the consequences is muscle growth, which is why the stuff’s used for doping. But the side-effects are mood swings, aggressive and risk-taking behavior, skin problems, hair loss, and elevated cholesterol levels. Also, if the testosterone level is too high, the body tries to produce less of it, which leads to a reduced sperm count and shrinking of the testicles. And since the body converts part of the testosterone to a form of estrogen, high testosterone levels can, among other things, lead to breast development. So, more isn’t always better.
All of which brings up the question how much testosterone is normal? This question is surprisingly difficult to answer.
To begin with, testosterone levels change during the day, especially in young men, where they peak in the early morning. That’s why testosterone levels are measured in the morning, and another reason why early-morning classes should be illegal.
But that’s not the only reason testosterone levels vary. According to a 2020 study testosterone levels change with the seasons and are higher in summer. They are also known to change with partnership status. According to a Harvard University study published in 2002, married men have lower levels of testosterone than single men, and the more time they spend with family, the lower the testosterone level. Other studies have shown that men’s testosterone levels drop when holding an infant, or even a baby doll, and that the level goes up again after divorce.
That’s all very interesting, but these are all quite small effects. What we want to know is what’s a normal average level?
In 2014, a group of researchers did a meta-analysis to find out. They collected the data of 13 previously published studies and found that testosterone blood levels in men peak at about 19 years of age with a mean value of 15 point 4 nanomoles per liter. They then fall slightly to about 13 point 0 by age 40. Be careful, this plot has a log scale on the vertical axis. The authors found no evidence for a further drop in mean testosterone with age, although the variation increases as men get older.
Medical guidelines in the United States currently say everything above 11 point 1 nanomoles per liter is normal, below 6 point 9 is too low, and in between there’s a grey area where they send you from one doctor to another until one can decide what to do with you. In Europe they think men should have a little more testosterone and the guidelines are 12 and 8 nanomoles per liter, respectively.
Now that we know what we’re talking about, what’s the deal with the falling testosterone levels? First off – the headlines are right. Testosterone levels really are falling. This has been backed up by several independent studies. And it isn’t even news.
One of the best-known papers about this was published by researchers from the US in 2007. They tracked three groups of randomly selected men from Boston, during the 1980’s, 1990’s and 2000’s.
They found that the later-born men had lower testosterone levels at the same age as the earlier born ones. You can see this in this graph, where the solid lines are the mean values, and the dotted lines are the 95 percent confidence levels.
Don’t get confused about the numbers on the vertical axis. This graph uses different units than the ones we had before, but even so you can clearly see that indeed testosterone levels are falling. For example, a 70-year old man in the first study group from the 1980s had a higher total testosterone level than the youngest man in the second group. They found that the average levels declined by about 1 percent per year, so men born 15 years later would have 15 percent lower testosterone levels at the same age.
In case you think something odd is going on in Boston in particular, similar studies have found the same elsewhere in the US and also in Europe. For example, a Finnish study from 2013 found that older generations of men had higher testosterone levels at any given age range compared to younger generations. It’s not a small difference.
For example, for men aged 60-69 years born in between 1913 and 1922, testosterone levels were 21 point 9 nanomoles per liter, but for those born between 1942 and 51, it was only 13 point 8. Finnish men born during the 1910’s had more testosterone in their sixties than men born in the 1970’s when they were in their twenties.
It's not just testosterone, and it’s not just men. Strength levels seem to be decreasing in general. A 2016 study measured the grip strength of about 250 healthy full-time students aged 20 to 34 at Universities in North Carolina. They compared the results to measurements from 1985 and found that grip strength had significantly increased both for men and for women. It seems firm handshakes really are going out of style.
Okay, so we’re all getting weaker and slower and spend our days watching YouTube. But why? The brief answer is that no one really knows, there’s just speculation, so let’s have a look at the speculations. First of all, the changes happen too quickly to be genetic adaptations.
But one suspect factor is food. According to a recent meta-analysis done by researchers from the UK eating too much protein can significantly decrease testosterone levels. They found that diets with more than 35 percent protein decreased testosterone levels by 37 percent. 35 percent protein is a lot. The average person in the developed world eats less than half of that, so it doesn’t explain the observed trend. But if you only eat meat, it quite possibly has consequences.
A related issue is the increasing number of obese people, which we just talked about some weeks ago. We know that in men, a high body mass index is correlated with lower testosterone levels. And according to a 2014 paper by researchers from Australia, the causation goes both ways. That is low testosterone can cause weight gain, and weight gain lowers testosterone levels, which can create a self‐perpetuating cycle of metabolic complications. However, the studies that documented the fall in testosterone levels found it even for men with normal body mass index, so this doesn’t explain it either.
Another factor might be smoking, or rather, the lack thereof. That’s because some chemicals contained in tobacco prevent testosterone from converting to other hormones, which can increase the mean testosterone level. A meta analysis from 2016 found that men who smoked had higher mean testosterone levels than non-smokers with the difference being about 1 point 5 nanomoles per liter. In women the difference wasn’t statistically significant. So, the overall decline in smoking might have had an impact on the overall decline in testosterone levels. But again, that alone doesn’t explain it.
What are we to make of this? It seems plausible to me that several factors are at play. As we have seen, testosterone levels change with living circumstances. The world is a more comfortable place today than 50 years ago, so maybe testosterone just isn’t needed as much as it used to. And then the changes in diet and smoking add on top of that. Is that enough to explain it? I don’t know. As scientists like to say “more work is needed”.
Is it something to worry about? Well, that depends on what you want the world to be. Carl Sagan once referred to testosterone as a poison that causes conflict. He said “Why is the half of humanity with a special sensitivity to the preciousness of life, the half untainted by testosterone poisoning, almost wholly unrepresented in defense establishments and peace negotiations worldwide?” However, he then continued, “Testosterone also causes the kind of aggression needed to defend against predators, and without it, we’d all be dead. [...] Testosterone is there for a reason. It’s not an evolutionary mistake.”
Personally I see the decrease of testosterone levels more as a reaction to our changing environment than reason for concern. The world changes and we change with it. We study tree rings to find out which years were good years and which years were bad years for the trees. And maybe in ten thousand years from now, scientists will study testosterone levels to find out which times were good times and which times were bad times for us.
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[This is a transcript of the video embedded below. Some of the explanations may not make sense without the animations in the video.]
Quantum technology current attracts a lot of attention and money, which might explain why they’re missing on my end. But it’s not just governments who think quantum everything is where your taxes should go, business investors and companies are willing to putting in big money, too. This has had a dramatic impact on quantum physics research in the past decade. It’s also created a lot of hype, especially around quantum computing. But if so much of quantum computing is hype then why are companies like Google and IBM pouring so much money into it, what’ll happen when the investment bubble bursts, what’s the “quantum winter”, and what does it mean for all of us? That’s what we’ll talk about today.
There are several different quantum technologies, and as a rule of thumb, the fewer headlines they make, the more promising they are. Take for example, quantum metrology. That’s not a mispronunciation of meteorology, that’s making better measurements with quantum effects. You basically never read anything about this. But it’s really promising and already being used by scientists to improve their own experiments. You can learn more about this in my earlier video.
On the other hand, you have those quantum things that you read a lot about but that no one needs or wants, like the quantum internet. And then there is quantum computing which according to countless headlines is going to revolutionize the world. Quantum computers are promising technology, yes, but the same can be said about nuclear fusion and look how that worked out.
A lot of physicists, me included, have warned that quantum computing is being oversold. It’s not going to change the world, it’ll have some niche applications at best, and it’s going to take much longer than many start-ups want you to believe.
Though I admire the optimism of the quantum computing believers and also the vocabulary. For example, there’s a startup called “multiverse” that is “Working with customers in more than 10 verticals”. Some of them don’t find the way back from the bathroom.
Or here’s one called “universal quantum” which has a “fault tolerant team” that “embraces entanglement” and helps everyone find a “super position”. If you look at them, do they collapse?
This company also recently published a blogpost titled “Six reasons Liz Truss needs a quantum computer” which explains for example, “Quantum computers are suited to modelling complex systems, making them better at forecasting both near-term weather patterns and the long-term effects of climate change.”
Last time I looked, no one had any idea how to do a weather forecast on a quantum computer. It’s not just that no one has done it, no one knows if it’s even possible, because weather is a non-linear system whereas quantum mechanics is a linear theory.
Here is an example of some recent quantum hype, from a website called “Investors Chronicle” in an article titled “Quantum computing: a new industrial revolution”. After creating a lot of fog about superpositions and interference, they explain that quantum computers are close to showing “quantum advantage” and that “Quantum advantage, therefore, can be interpreted as being when problem-solving power can be applied to real world issues, which makes it much more interesting for investors.”
That’s just wrong. Quantum advantage has indeed been demonstrated for some quantum computers but that just means the quantum computer did something faster than a conventional computer, not that this was of any use for real world issues. They just produced a random distribution that would take a really long time to calculate by any other means. It’s like this this guy stapling 5 M&M. That’s a world record, hurray, but what are you going to do with it?
Problem is, a lot of CEOs in industry and the financial sector can’t tell a bra from a ket and believe that quantum computing is actually going to be relevant for their business, and that it’s going to be relevant soon. For example, at a recent Quantum Computing conference in London, the managing director of research at Bank of America said that quantum computing will be “bigger than fire”. The only way in I can see this coming true is that it’ll produce more carbon emissions.
This bubble of inflated promises will eventually burst. It’s just a matter of time. This’ll cause a sudden decline of investment in quantum tech overall and be the start of a difficult time for research and development. This scenario has been dubbed the “quantum winter”. And winter is coming. But before we get to the quantum winter, let me briefly summarize how quantum computers work and what their problems are.
A conventional computer works with bits that take on one of two discrete values. A quantum computer instead uses qubits that can be in arbitrary *superpositions of two states. A quantum computer then works by entangling the qubits and shifting this entanglement around. Entanglement is a type of correlation, but it has no analogy in conventional computers. This is why quantum computers can do things that standard computers can’t do.
For some mathematical problems, a quantum computer can give you an answer much faster than any conventional computer possibly could. This is called “quantum advantage”. Those problems include things like factorizing large numbers into prime factors. But also calculating properties of molecules and materials without having to chemically synthesize them first. Putting these questions on a quantum computer could speed up material design and drug discovery. Quantum computers can also solve certain logistic problems or optimize financial systems. This is why, if you’re Bank of America, you think it's bigger than fire.
And like fire, quantum computing is not magic, it’s an application of standard quantum mechanics. There is no speculative new physics involved. It’s rather to the contrary. Claims that quantum computers will *not work rest on speculative new physics. But it’s one thing to say if you could build them, they’d be useful. It’s another thing entirely to actually build them.
So what does it take to build a quantum computer? First of all you need qubits. Then you have to find a way of entangling many of those qubits. And, like a conventional computer, a quantum computer needs an algorithm, that tells it how to move the entanglement around. Eventually, you make a measurement which collapses the wave-function and you read out the final state. This final state should be one that answers your question correctly with high probability. This means most importantly, a quantum computer isn’t a stand-alone device, it needs other devices for the programming and the readout. The quantum part is really just a small piece of the whole thing.
Now let’s talk about the problems. First there’s the qubits. Producing them is not the problem, indeed there are many different ways to produce qubits. I went through the advantages and disadvantages of each approach in an earlier video, so check this out if you want to know more. But a general problem with qubits is decoherence, which means they lose their quantum properties quickly.
The currently most widely developed systems are superconducting qubits and ion traps. Superconducting qbits are used for example by IBM and Google. For them to work, they have to be cooled to 10-20 milli Kelvin, that’s colder than outer space. Even so, they decoherence within 10s of micro-seconds.
Ion traps are used for example by IonQ and Honeywell. They must “only” be cooled to a few Kelvin above absolute zero. They have much longer coherence times, up to some minutes, but they’re also much slower to react to operations, so it’s not a priori clear which approach is better. I’d say they’re both equally bad. The cooling isn’t only expensive and energy-intensive, it requires a lot of equipment and it’s difficult to scale to larger quantum computers. It seems that IBM is trying to do it by breaking world records in building large cryogenic containers. I guess if the thing with quantum computing doesn’t work out, they can rent them out for people to have their heads frozen.
There are some qubits that operate at room temperature, the most promising ones of those are currently nitrogen vacancy systems and photonics on a chip. However, for both of those, no working quantum computer exists to date and it’s unclear even what the challenges may be, let alone how to overcome them.
The next biggest problem is combining these qubits. Again, the issue is that quantum effects are fragile, so the quantum computer is extremely sensitive to noise. The noise brings in errors. You can correct for those to some extent, but this error correction requires more qubits.
More qubits bring problems by themselves, for example, they tend to be not as independent as they should be, an issue known as “crosstalk”. It’s kind of like if you’re trying to write while moving your feet in circles. It gets really difficult. The qubits states are also drifting if you leave them unattended. Indeed it’s somewhat of a mystery at the moment what a quantum computer does if you don’t calculate with it. It’s like it’s difficult to calculate what a big quantum system does. Maybe we can put it on a quantum computer?
And finally there’s the issue of the algorithms: Few algorithms for quantum computers are known, an issue that goes often unmentioned because everyone is focused on the technology. Wikipedia helpfully has a list of quantum algorithms. It’s short. Several of those algorithms don’t compute anything of practical use, and for some it's not known if they lead to any speedup.
As this brief summary makes clear, the challenges are enormous. But how far along is the technology? The largest current quantum computers have somewhere between 50 and 100 qubits, though IBM has a roadmap saying they want to make it to a thousand next year. Two different approaches have demonstrated a “quantum advantage”, that is, they have performed a calculation faster than the currently fastest conventional computer could have done. However in those demonstrations of quantum advantage, the devices were executing algorithms that did not calculate anything of use.
The record breaking “useful” calculation for quantum computers is the prime-number factorization of 21. That’s the number, not the number of digits. Yes, the answer is 3 times 7, but if you do it on a quantum computer you can publish it in Nature. In case you are impressed by this achievement, please allow me to clarify that doing this calculation with the standard algorithm and error correction is way beyond the capacity of current quantum computers. They actually used a simplified algorithm that works for this number in particular.
To be fair, there have been some cute applications of quantum algorithms for simple examples in quantum chemistry and machine learning, but none of this is anywhere even close to being commercially interesting.
How many qubits do you need for a quantum computer to do something commercially interesting? Current estimates say it’s several hundred thousand to a few millions qubits, depending on what you want to calculate and how large your tolerance for errors is.
A lot of quantum computing enthusiasts claim that we’ll get there quickly because of Moore’s law. Unfortunately, I have to inform you that Moore’s law isn’t a law of nature. It worked for conventional computers because those could be miniaturized. However, you can’t miniaturize ions or the Compton wavelength of electrons. They’re already as small as it gets. Nature’s a bitch sometimes.
In the past years there’s been some noise around Noisy intermediate scale quantum computers, or NISQs for short. Those are small quantum computers in which you just accept the noise, kind of like YouTube comment sections. But no one seems to have found anything useful to do with them and the hype around them has noticeably died down recently.
I guess you understand now why I am extremely skeptical that we are anywhere close to commercially relevant applications of quantum computers. But let’s hear what some other people say.
There is for example Mikhail Dyakonov, a physics prof who has worked on quantum things much longer than I have. He’s written a book that was published in 2020 under the title “Will We Ever Have a Quantum Computer?” It has only 49 pages which is what happens if you agree to write a book but then notice half through you’d rather do something else. He finishes by answering his own question:
“No, we will never have a quantum computer. Instead, we might have some special-task (and outrageously expensive) quantum devices operating at millikelvin temperatures. The saga of quantum computing is waiting for a profound sociological analysis, and some lessons for the future should be learnt from this fascinating adventure.”
The brevity of Dyakonov’s book is balanced by another book “Law and Policy for the Quantum Age” by Chris Hoofnagle and Simson Garfinkle, who make it to a whooping 602 pages. Their book was just published earlier this year, it’s freely available online, and it has an adorable cat pic on the cover, so definitely go check it out. Hoofnagle is a professor for law and Garfinkle is a data scientist, but their book has been heavily informed by people who work in quantum computing. They look at the possible future scenarios. The most likely scenario, they say, is the “Quantum Winter” which they describe as follows:
“In this scenario (call it “Quantum Winter”), quantum computing devices remain noisy and never scale to a meaningful quantum advantage… After a tremendous amount of public and private monies are spent pursuing quantum technologies, businesses in the field are limited to research applications or simply fail, and career paths wither. If that happens, funding eventually dries up for quantum computing. Academics and scientists in the field either retool and shift, or simply appear irrelevant, even embarrassing.”
Then there is Victor Galitski, Professor at the Joint Quantum Institute at the University of Maryland who wrote in a 2021 post on LinkedIn:
“The number of known quantum algorithms, which promise advantage over classical computation, is just a few (and none of them will "solve global warming" for sure). More importantly, exactly zero such algorithms have been demonstrated in practice so far and the gap between what’s needed to realize them and the currently available hardware is huge, and it's not just a question of numbers. There are qualitative challenges with scaling up, which will likely take decades to resolve (if ever).”
“As more money flowed [into quantum computing], the field grew, and it became progressively more tempting for scientists to oversell their results… After a few years of this, a highly exaggerated perspective on the promise of quantum computing reached the mainstream, leading to… the formation of a classical bubble.”
He then points out that no quantum computing company is currently making profit and that:
“The little revenue they generate mostly comes from consulting missions aimed at teaching other companies about “how quantum computers will help their business”.”
I have to disagree on the final point because big companies have another way to make money from quantum computers, namely by renting them out to universities. And since governments are pouring money into research, that’s quite a promising way to funnel tax money into your business. Imagine the LHC was owned by Google and particle physicists had to pay to use it.
That’s how I think it’ll go with quantum computing: First all the smaller startups will falter because they don’t reach their milestones, venture capital will evaporate, and all the overeducated quantum computists in academia will use grant money to pay a few large companies who own the only workable devices. And while those devices are interesting research objects, they’ll not be useful for commercial applications.
I might be totally wrong of course. Maybe one of those start-ups will actually come up with a scalable quantum computing platform. I don’t know, I’m guessing as much as everyone else.
But if quantum winter is coming, what does it mean for you and me? Well, some people will lose a lot of money but that just means they had too much of it to begin with, so can’t say it bothers me all that much. There’ll also be fewer headlines about how quantum computing is supposedly going to revolutionize something or other, which I’d say is a good development. And we’ll see many people who worked in quantum computing going into other professions. Chances are in ten years you can have a nice chat about the finer details of multi-particle entanglement with your taxi driver. I don’t know about you, but I’m looking forward to quantum winter.
