Some terms created for science fiction eventually are adopted when the technology they anticipate comes to pass. In this case, we can thank The Six Million Dollar Man for popularizing the term “bionic” which was originally coined by Jack E. Steele in August 1958. The term is a portmanteau of biological and electronic, plus it just sounds cools and does roll off the tongue, so it’s a keeper. So while there are more technical terms for an artificial electronic eye, such as “biomimetic”, the press has almost entirely used the term “bionic”.

The current state of the art is nowhere near Geordi’s visor from Star Trek TNG. In terms of approved devices actually in use, we have the Argus II, which is a device that include an external camera mounted on glasses and connected to a processor. These send information to a retinal implant that connects to ganglion cells which send the signals to the brain. In a healthy eye the light-sensing cells in the retina will connect to the ganglion cells, but there are many conditions that prevent this and cause blindness. The photoreceptors my degenerate, for example, or corneal damage does not allow light to get to the photoreceptors. As long as there are surviving ganglion cells this device can work.

Currently the Argus II contains 60 pixels (6 columns of 10) in black and white. This is incredibly low resolution, but it can be far better than nothing at all. For those with complete blindness, being able to sense light and shapes can greatly enhance the ability to interact with the environment. They would still need to use their normal assistive device while walking (cane, guide dog or human), but would help them identify items in their environment, such as a door. Now that this device is approved and it functions, incremental improvements should come steadily. One firmware update allows for the perception of color, which is not directly senses but inferred from the pattern of signals.

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It’s all about money, and infrastructure. We can talk about what’s best for the environment, but when it comes to individual purchasing decisions, the decisive factors are going to be expense and functionality – how much bang do you get for the buck. This is especially true when it comes to industry. Things like fashion and trendiness don’t really matter on the factory floor, only efficiency, ROI, cost effectiveness.

In our conversion to a green economy, the low carbon options have to be cost effective if we want wide adoption (short of mandates). For electric cars, we are already there. According to the Natural Resources Defense Council:

Over the anticipated 15-year life span of a vehicle, the electricity required to run a battery-powered electric car can be as much as $14,480 cheaper than fueling up an internal combustion vehicle.

That, however, is the best case depending on electricity and gasoline costs. In areas with the highest electricity costs and lowest gasoline prices there can be a small advantage to gas. But there is an overall cost advantage to electric cars. Also, according to Consumer Reports:

Consumers who purchase an electric car can expect to save an average of $4,600 in repair and maintenance costs over the life of the vehicle compared with a gasoline-powered car, CR’s study shows.

A 2018 study combines these factors and takes average value and concludes:

The average cost to operate an EV in the United States is $485 per year, while the average for a gasoline-powered vehicle is $1,117.

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There are many times as a skeptic that I wish I were wrong. I really want to detect an alien artifact, and would love free energy, cold fusion, and a cure for cancer. I completely understand why these ideas have endless allure and the temptation to engage in a small bit of motivated reasoning to see the science from a particular, if odd, angle. But science does not progress this way. It progresses through the cold and heartless removal of error, by brutally smashing the pillars of our own vanity, fear, and desires, and by controlling for our own biases and shortcomings. I often refer to the peer-review process as a meat-grinder – it chews up and spits out ideas, but there is a product at the end – and that goes right back into the meat-grinder for another round.

One more really tempting idea now bites the dust – the EM Drive. I first wrote about this almost seven years ago. The idea is to create propellantless propulsion. This would revolutionize space travel, and could potentially even create that flying car we always wanted. Now, in the world of physics, in order to accelerate something there needs to be a force acting on it. If you want a rocket to go up, then you need to throw some mass from the rocket down so that the mass and velocities match (equal and opposite). So rockets need propellant, something to throw out their back. Ideally this is something very light that gets accelerated to really high speeds to produce the maximal thrust to the rocket.

While this concept works just fine, it is also extremely limiting, by something known as the rocket equation. The rocket needs to carry enough fuel to accelerate the entire rocket, including all the fuel it is carrying. So it needs fuel to carry the fuel to carry the fuel… This means there is a geometric rather than linear relationship between speed and range and how big a rocket and its fuel has to be. For many chemical rockets the fuel is the propellant; when you ignite it the fuel rapidly heats and expands and gets pushed out the exhaust. Other rocket designs may have a separate energy source and propellant. Ion drives, for example, create energy to power magnets which accelerate charged particles to extreme velocities.

But what if you did not need propellant? What if all you needed was energy, and could somehow use that energy to create thrust without having to throw any matter out the back end? That would drastically alter the rocket equation. This would reduce the cost of space travel and open up the solar system. It might even make it practical to get to nearby stars – in a hundred years we might have a fusion powered ship that can zip around the galaxy at a constant 1G acceleration.

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Humans are simply not adapted to space. We evolved in 1G, the amount of gravity near the surface of the Earth, and are well suited to that environment. Spending a lot of time in microgravity, such as aboard the ISS, has a number of physiological effects. Now that some astronauts have been spending long periods of time aboard the ISS, researchers have been better able to understand these effects.

One recent study involved astronaut Scott Kelly, who spent 340 days in the microgravity of ISS. This study involved heart function – the hypothesis was that spending lots of time in orbit would reduce the strain on the heart, because it would no longer have to pump blood against gravity. Over time this would weaken the heart. That is, in fact, what they found. Kelly’s heart lost about 27% of its mass over the 340 days. However, it then regained that mass after months back in normal gravity, readapting to 1G.

What remains to be seen is if there are any long term consequences of losing and then regaining so much heart mass. One concern is that this may change the overall shape and ratio of the atria to the ventricles, and may predispose to atrial fibrillation, an abnormal conduction in the heart.

As an interesting aside, the same study also looked at swimmer Benoît Lecomte who spent 159 days swimming an average of 5.8 hours per day in the Pacific. He also experienced a 25% loss of heart mass. This was due to spending so much time horizontal and floating. This shows that swimming can be a good physiological marker for microgravity, at least for heart function. The study also shows that in both men exercise did not prevent this effect. Astronauts aboard the ISS have a rigorous exercise program to reduce bone and muscle loss, but apparently this did not prevent heart muscle mass loss.

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Perhaps the biggest scientific, political, and practical challenge facing the world today is how to rapidly decarbonize our energy infrastructure. The goal is to do it fast enough to avoid total global warming in excess of 1.5 degrees Celsius, which we will probably fail to do. At the very least we want to avoid going over 2.0 degrees Celsius, which is more realistic but will still be a challenge. We are not on a path to achieving either goal right now. We are currently at about 1 degree increase over pre-industrial average surface temperature.

There is a lot of healthy debate about what is the best path to net-zero carbon energy, and it’s fascinating to watch. I personally think we should do everything. We don’t want to put our chips down on one answer and find out in 30 years it was the wrong choice. We really have just one shot left to avoid 2.0 C, so we should spread out bets out as much as possible. Also, we should use each source where optimal, rather than try to have one or a few energy sources fit all circumstances. This means investing in renewables, many forms of grid storage, carbon capture, nuclear power, nuclear isotope batteries, artificial leaf technology to make hydrogen, maybe even some biofuel, and improved energy efficiency. One thing is certain – we need to get off fossil fuels as quickly as possible. This also means the transportation sector needs to wean off fossil fuels.

In this debate there are many solar advocates. I, too, am a fan of solar, I just don’t think we should count on solar alone (which would require grid storage we don’t currently have). Solar is currently a cost-effective option, and is only getting better as the technology continuously incrementally improves. The problem is, as we try to push intermittent renewable energy further and further, that cost effectiveness goes away. This is because you need overproduction and/or grid storage, plus significant grid upgrades, to handle the intermittent and distributed nature of sources like solar.

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Right now there are about 3,000 active satellites in Earth orbit. About 1,000 of those satellites are part of the Starlink project to provide internet access everywhere on the planet, with a planned 42,000 total when complete. that is a massive increase in the number of active satellites. At the same time there another 3,000 defunct satellites that are no longer operational but remain in orbit. There is about 9,000 tonnes of total orbital debris, and we are tracking 30,000 objects of 10 cm or larger. But estimates are that there are millions of smaller objects in orbit.

In other words – usable Earth orbit is becoming crowded and hazardous. This is a risk to operational satellites, space stations, and any spacecraft hoping to get off Earth. Much of this debris is moving very fast relative to other objects with intersecting orbits. A lost bolt could destroy a satellite or punch a hole in the International Space Station (ISS). There is a concern that a serious collision, say between two satellites, would generate enough debris to cause a cascading event of further collisions.

There are now international agreements that make states responsible for anything they put into orbit for its lifetime. Companies and nations are supposed to arrange for the deorbiting of anything they put into orbit within 25 years of the end of its functional lifetime. However, the agreements have little teeth and compliance is low. This is just another example of allowing entities to externalize the costs of their own waste or downstream effects. It is also another example of how the assumption that natural resources are so gigantic we don’t have to worry about sustaining them. Space is really big, so who cares if we leave a lot of junk up there? Well, it took only a few decades for us to clutter low Earth orbit with enough debris to be a serious hazard.

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In 1970 robotics professor Masahiro Mori observed, “Bbukimi no tani genshō,” which was later translated into “uncanny valley”. This refers to an observed phenomenon (first in robots, but also applies to digital recreations) that the more human-like the robot the greater the emotional affinity of people. However, as imitation approaches complete imitation it takes a sharp dip where people actually become uneasy and even revulsed by the not-quite-human face, before going up again as perfection is achieved. That dip in emotional affinity for near human imitation is the uncanny valley. Both roboticists and digital artists have been trying to break through that valley every since it was identified.

Perhaps the most notorious example of this phenomenon in modern popular culture is the CG portrayal of Tom Hanks in the movie Polar Express.  There is something dead about his eyes, which gives him the eerie appearance of an animated corpse. Even the most advanced current CG does not quite break through, but it’s getting damn close.

There are two neurological phenomena at work here. The first, as I have discussed before, is agency detection. Our brains divide the world into things with agency (the ability to act of their own will) and things without. Our brains are wired to then network our perception of things with agency to the limbic system and assign some emotional significance to them. This is why we feel something about our pets but not about a rock. Of course this is an oversimplification, because our brains are massive parallel processors with many circuits all working at the same time. But this is definitely a fundamental component that explains a lot about our reaction to certain things. This concept has even been pushed to the limits – in 1944 researchers made a video of simple two-dimensional shapes interacting with each other on a screen. Subjects spontaneously imbued these shapes with agency and provided elaborate interpretations of their actions and motivations. (A triangle is about as far away from the uncanny valley in the other direction as you can get.)

Neurologically we can see why we have no problem identifying with cartoon characters, responding to their personality, and even getting invested in their story. Added to this is the brain wiring behind seeing faces and reading emotion. This too can be stripped down to basic components – which is why we can interpret emoji’s. Cartoonists learn how to convey a range of emotions with a few lines. This in turn is partly due tot he fact that we have a large area of our visual cortex dedicated to processing information about human faces. Even infants will prefer to look at a human face over other stimuli. We also have a tendency to construct visual stimuli as a face – which is why we can see faces everywhere, such as in low-res images from the surface of Mars, or in the bark of a tree.

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I have been following the development of virtual and augmented reality (VR and AR), writing about it here occasionally. I have a VR headset and use it regularly (I am currently playing Myst VR – very nice). I don’t use it exclusively not even for gaming, some games are better on a usual screen and some are better in VR. My only gaming experience with AR is Pokemon on my cellphone (probably like most people). It was fun for a short period but the novelty wore off fast. This is not a knock against AR, I just think the cellphone version is limited.

Now Microsoft is pushing their Mesh network on their Hololens device, which represents “mixed” reality – what’s that? The term “mixed reality” was coined in a 1994 paper about a range of technologies including VR and AR. MR, essentially exists along a spectrum including physical and virtual elements, and the ability to interact with those virtual elements and project yourself into the virtual world.

For background, VR involves total immersion, wearing a headset that occupies your entire vision so you only see the virtual world. AR, rather, overlays digital elements onto the real world, which you still see. The Pokemon version I referenced uses your cellphone’s camera to take realtime video of the world and places digital elements within them – so you only see the Pokemon critters on your screen, like looking through a lens at the virtual world. The far better version of AR would be wearing transparent glasses that display the virtual elements so you see the virtual world overlaid on top of the real world.

Mixed reality, like the Mesh network, can accommodate VR, AR, and regular screen use at the same time. We are at the very beginning of this technology with lots of people making predictions about how they will be used, and that’s what I want to talk about. Currently the Holo lens costs almost $5k, so this is just dipping into the prosumer market. The general consumer market for high-tech devices is generally considered to be sub-$1,000, so we have a ways to go. One of the primary “killer apps” for mixed reality is collaboration, so how widespread the adoption is matters. That’s why it is common now for virtual spaces to be accessible on regular flat monitors, as a bridge to MR adoption.

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I have been tracking the research in brain-machine interface (BMI), specifically with an eye towards studies that claim to interpret brain data. Typically I find that such studies are overhyped, at least in the press release and subsequent reporting. The question I always ask myself is – what exactly are they measuring and interpreting? A new study, using BMI and a form of AI called Generative adversarial neural networks (GANs), claims to read brain data to determine what faces subjects find attractive. What are the researchers doing, and what are they not doing?

The ultimate goal of BMI research (or at least one goal) is to figure out how to interpret brain activity so well that it is essentially mind-reading. For example, you might think of the word “cromulent” and a machine reading the resulting brain activity will be able to interpret it so well that it can generate the word “cromulent”. This would make possible a fully functional digitial-neural interface, like in The Matrix. To be clear – we are no where near this goal.

We have picked some of the low-hanging fruit, which are those areas of the brain that function through some form of somatotopic mapping. Vision is the most obvious example – if you are looking at the letter “F”, neurons in the visual cortex in the literal shape of an “F” will become active. Visual processing is much more complex than this, but at some level there is this bitmap level of representation. The motor and sensory parts of the brain also follow somatotopic mapping (the so-called homonculus for each). There is likely also a map for auditory processing, but more complex and we don’t fully understand it.

The big question is – what are the conceptual maps? Physical maps representing space, images, even sound frequencies, are easy to understand. What are the neural map for words, feelings, or abstract concepts? Related to this is the concept of embodied cognition – that our reasoning derives ultimately from our understanding of the physical world. We use physical metaphors to represent abstract concepts. For example, an argument can be “strong” or “weak”, your boss is hierarchically “above” you, you may have “gone too far” with a wild idea that is a “stretch”. This may just be how languages evolved, but the idea of embodied cognition is that the language represents something deeper about how our brains work. Perhaps even abstract concepts are physically mapped in the brain, anchoring even our abstract thoughts to a physical reality. Perhaps embodied cognition is not absolute, but more of a bridge between the physical and the abstract, or a scaffold on which fully abstract ideas can be cortically mapped. We are a long way from sorting all this out.

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We are approaching 8 billion people on this planet, and so anything that a lot of people do is likely to have a significant impact. This includes things that we previously considered to be essentially resource free, or at least insignificant, including digital activity. This may be a bit of a generational thing – those of us who lived through the explosion of computer use, the adoption of the web and social media, and the general shift from analog to digital technology grew up with the idea that doing things digitally was resource efficient.

For example, there was a huge push to transform to a “paperless office” because that would save trees. It is much better to shuffle electrons around than pieces of paper. This transition took a lot longer than anyone thought, and in fact – it hasn’t really happened yet. Here we are, 40 years later, and office paper use is still increasing. No one would have predicted that.

Because of the pandemic meetings and many services shifted from in-person to online, over Zoom, for example. This is much more efficient than people traveling to the same physical location for the meeting. But this does not mean we can ignore the electricity use, and therefore carbon footprint, of the digital meeting. A recent study, for example, found that simply turning off the video when not needed can reduce that footprint by 96%. This is small individually, but huge in the aggregate:

Turning off a camera for 15 hour-long meetings every week would reduce carbon dioxide emissions by 9.4 kilograms (20.7 pounds) per month. If one million Zoom users did this, they would save 9,000 tons of CO2, the equivalent of coal-powered energy used by a city of 36,000 in that same month.

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