Oh this sounds like Macgyvering. The Real Life section in the TV tropes article on it has some interesting examples and lists some other cultural takes on it: desenrascanço, débrouillard, Jugaad. It's a skill clever poor people are more likely to have opportunities to hone.
Renewables are indeed vital. At the same time, it feels counterproductive that every discussion on nuclear or renewables ends up casting things as an either or proposition. Nuclear as baseload remains very useful. What's more, we don't just seek to replace current capacity but also to quickly increase generation.
While costs of transmission infrastructure required for country scale (larger distances for lower correlation) energy dispatch are recognized, its more abstract challenges are less well acknowledged. Dispatch at this level is not just about developments in grid integration or hardware like solid state "transformers", it also has a complex routing coordination aspect requiring research in control and even game theory [1].
A lack in wind and solar can sometimes occur simultaneously. Analysis of German wind turbines data observed that experiencing a stretch of almost a week with generation as low as 10% installed capacity was likely within a given year [2]. Surprising/extreme weather events like Europe's recent "wind drought" are rare but there remains a large amount of uncertainty in how changes in climate will affect the tail of this distribution. Tools such as coordinating distributed generation and improvements in storage tech will surely help smooth generation, nuclear is another powerful tool in that toolbox.
> Nuclear as baseload remains very useful. What's more, we don't just seek to replace current capacity but also to quickly increase generation.
The problem is that Nuclear may not be economical if it is only used when both solar and wind run out. Nuclear has large fixed costs. And almost zero marginal costs. So the average costs -- what needs to be charged in order to avoid bankruptcy, increase as you use it less.
That means every solar panel you add makes the nuclear power a bit more expensive. And that incentivizes adding more solar. Up until you drive the nuclear out of business, and then suddenly you don't have reliable power anymore.
Then you are faced with a situation of
a) only having nuclear power which can provide for all of your needs, in which case adding solar is an unnecessary expense
b) only having solar+wind and an unreliable grid, which means you need to add batteries to cover solar+wind. And the price of those batteries may be more than the price of the nuclear plant.
c) having nuclear and solar both, with enough subsidies given to the nuclear plant to keep it in business so that the total solution is more costly than just going with nuclear.
So yeah, there really is a tension between nuclear and solar.
This is not the situation, however, with solar and coal. Because coal plants are damn cheap, and they have higher marginal costs. Thus solar can coexist with coal or with gas much better than with nuclear.
Therefore the economics is such that as people promote solar the result is a decrease in nuclear and an increase in coal and gas.
Your model is overly simplified. Nuclear runs into the exact same issues in the other direction as you try to scale it to take over more of the grid. Frances nuclear reactors where at 70% capacity factors vs 90% in the US even with France exporting and importing vast amounts of electricity with the rest of Europe. It’s really not Nuclear vs Solar it’s simply Nuclear’s high cost and thus inflexibility that’s at issue.
Current electricity demand is heavily biased to daytime use even with cheap nighttime prices causing people to shift demand to use that. Start to ramp up solar to the point where daytime demand is higher and a great deal of nighttime demand drops off.
Grid storage isn’t cheap enough to store energy at current nighttime rates, but it’s cheap enough to have a balanced grid backed by hydro, wind, and solar even with zero fossil fuels. The tipping point to cheap daytime rates and expensive nighttime rates isn’t inherently better or worse, it just reflecting the future economic reality.
You are correct that my model is simplified. I ignore the issue that demand isn't really stable, and you need some peaker plants.
The problem is that Solar isn't really a good solution for peaker plants, because those need to be reliable. So I don't think this simplification undermines the tradeoffs I was describing, although I agree that in the space of peaker plants, there can be some combination of solar and gas to handle peaks when it is sunny and also when it is not sunny. Just be prepared that you need enough gas and coal to cover all the generating capacity you are getting from solar and wind, which is again very expensive.
> grid backed by hydro, wind, and solar even with zero fossil fuels
This requires a lot of hydro, more than most nations have together with really punitive electric rates when there is an absence of wind or solar. I mean, massively punitive rates, because demand for electricity is highly price inelastic. So be prepared for rates to go up 10x or 20x or even 100x when there is a stretch of windless days with weak sun. I think there is a reason why no nation has gone this route except oddballs like Iceland with their reliable geothermal.
Solar is the economic equivalent of base load power in that it’s cheap, and doesn’t follow the demand curve. Batteries then fill the role of peaking power plants as long as they can be filled cheaply. How you get from there to a balanced grid isn’t to have exactly as much generation on average as you need. Instead you install about twice as much as you need on average because it’s just that cheap vs any other source that even half of all generated solar is wasted it’s still cheaper than any other alternative.
At that point you are still going to get multiple day stretches where wind and solar only cover ~1/2 of daily demand but hydro can make up the difference on such occasions even if it’s only supplying 6.6% of annual US demand. Basically you get 1-2% hydro on most days and on 5% of days you a lot of energy stored.
As to high costs, because of the excess solar you’re generally filling batteries with nearly free electricity. Average nighttime wholesale prices therefore end up at ~10c/kWh or whatever the battery storage costs settle on, but daytime rates when most demand actually takes place are going to tank. That’s a net reduction in average prices. Trying to make a grid from Nuclear + batteries on the other hand means your paying Nuclear prices at night, but nuclear + battery prices in the daytime which is the opposite of what you want. Nuclear + fossil fuels on the other hand simply doesn’t go far enough.
Now in a mostly solar world a very low percentage of electricity may end up generated by fossil fuels, but a 99.X% solution is success by any reasonable metric.
PS: As a sanity check you can look at what people are paying when their off grid and then realize that’s very much a worst case.
Lack of wind and solar can happen but at scale there is plenty of hydro energy stored to cover significant edge cases. Rivers can handle significantly more flow than current hydro releases without causing flooding, we just need to retro fit existing dams and then reduce their generation most of the time to reserve that capacity for when it’s needed. Aka averaging 6.6% over 365 days a year ~= 80% for 30 days.
Also, be careful when looking at wind and solar minimal percentages. It’s the difference between median output and minimum output that matters not maximum output. Long term it’s likely something like 30 to 50% of all solar generation is going to be wasted simply because it’s just that cheap.
Dams don’t release CO2, they can produce trivial amounts of methane but that breaks down fairly rapidly in the atmosphere. It’s only when vast amounts of methane are released at the same time or the source is continuous that methane is an issue.
In terms of fish, large dams are needed for flood control and water. But rivers and streams often have huge numbers of small dams that are equally problematic and far less useful.
I've never met a coherent definition of symbolic AI so I'll just focus on what it contained: some type of search or inference algorithm (iterative deepening, depth first search being major ones) often combined with heuristics written in a programming language like prolog or lisp. Specification + Inference ≊ Specification + Control flow. That means Probabilistic models written in a language like Stan, which is Inference + Specification, fit neatly into so called symbolic AI (which is basically just programming with search/inference).
These search and sampling algorithms still play key roles in game playing AI (chess, poker, Go) and natural language generation. It is the human knowledge, specification and heuristics, part that tends to be more readily replaceable. A lot of control flow and data-structures that powered old AI approaches can be found in databases, compilers, type inference, computer algebra and even the autodiff libraries neural nets are written in.
Video game AI, constraint solving and business rules engines are probably closest to still using the full symbolic approach rather than merely extracting the control flow and structures portion.
We can therefore make a compact prediction: learned approaches replace human written computer programs (specifications, rules systems or heuristics) whenever human contribution is not valuable or is somehow harmful to robustness/generalization.
Portia spiders do demonstrate trial and error learning, quoting the abstract of [1]:
> All species from the jumping spider genus Portia appear to be predators that specialize at preying on other spiders by invading webs and, through aggressive mimicry gaining dynamic fine control over the resident spider’s behavior. There is evidence that P. fimbriata, P. labiata and P. schultzi derive signals by trial and error. Here, we demonstrate that P. africana is another species that uses a trial and error, or generate and test, algorithm when deriving the aggressive-mimicry signals that will be appropriate in different predator–prey encounters.
It turns out that the species with more variation in encountered prey types are more likely to rely on search, varying over possible patterns until a response is received. Other papers show their ability to learn generalizes beyond mimicry of vibrational patterns. They are also capable of deriving and maintaining situation specific attack routes and plans.
I'll also argue that a fully instinctual repertoire, even without learning, should count as intelligence if flexibly deployed. Consider: despite an inability to learn or adjust, a Nash equilibrium approximating poker bot or an Alpha Zero neural network can be described as encompassing a deep instinct of the game that enables intelligent action selection.
Sociality is not the only (and probably not an initial) driver of the evolution of intelligence in animals. Ecological and particularly foraging competency in less predictable environments is another and likely more primary stimulator for intelligence.
Coordinating complex movements is another one that appears to drive intelligence.
Vulnerability in a hostile environment. Together with foraging and coordinating complex movement plans, it is hypothesized that predation pressure when combined with the loss of their shell drove cephalopod intelligence. Trading defense for agility and int would also have provided a competitive advantage when competing for prey.
Fredkin's contribution were to reversible computation and since Quantum computers are a kind of reversible computer, many ideas and gate notions carried over.
I guess you can ask, can someone be a significant contributor to a field they don't believe in? Didn't Einstein contribute to Quantum Mechanics, while simultaneously harboring grave misgivings? (God doesn't play dice etc)
An in-between option that is relatively simple and a rather fast (though not as fast as the automata) optimization to levenstein distance and based on Tries is: http://stevehanov.ca/blog/?id=114.
Differential forms are a particular kind of tensor and tensors can be defined in terms of multilinear maps. As spekcular says, the standard curriculum covers differential forms, tensors and vectors. This entails becoming familiar with multivectors, the wedge product and multilinear algebra, making geometric algebra a relatively small delta to pick up.
On the other hand, the standard course will also prepare you for mathematical topics like lie derivatives, differential geometry and de Rham cohomology.
Other than physics, the standard approach equips you with the mathematical machinery underlying many topics in machine learning and statistics like Hamiltonian monte carlo, automatic differentiation, information geometry and geometric deep learning.
The central advantage of geometric algebra over the standard approach isn't that it's better or more general, it's that pedagogical material for it is generally leagues and magnitudes better than those for the standard course.
> As spekcular says, the standard curriculum covers differential forms, tensors and vectors... making geometric algebra a relatively small delta to pick up.
Could you be a bit more specific about which "standard curriculum"/"standard approach" you're talking about?
For example, in my formal education (high school; masters with physics major, comp. sci. minor; 4 years of a comp. sci. PhD (abandoned)), I did not encounter differential forms, tensors, multivectors, the wedge product or multilinear algebra (or quaternions, lie derivatives, differential geometry, (co)homology, etc.).
Maybe you're talking about a "standard approach" for a pure mathematics curriculum, or perhaps physics/math grad school?
All I can say is that high school and undergraduate physics (in the UK, circa the late naughties) (a) does not standardise on those topics, (b) is filled with tricky operations which are easy to mix up or perform the wrong way around (e.g. cross products, matrix multiplication, pseudovectors), and (c) many of those annoyances would simplify-away under GA.
It's a cliche that physicists (certainly when teaching) cherry-pick the parts of mathematics they find useful. All of those concepts would certainly be useful in a physics course, but would perhaps be too much to fit in; yet there's certainly enough scope to cherry-pick GA (since we can drop Gibbs-style vector algebra[0] to make room). Perhaps something else, like differential forms, might be even better; I honestly don't know (maybe I'll do some reading about it).
[0] By "Gibbs-style" I mean the 'cross product and dot product ought to be enough for anyone' approach that permeated my undergraduate learning.
By standard approach I mean the typical material covered for someone studying vector calculus properly. This will be stuff like differential forms and the basics of tensors, manifolds and multilinear maps at the undergrad level. Differential geometry and cohomology are examples of courses which build on them.
I agree with you that pseudovectors, cross products and vector calculus are a terribly adhoc way to teach this stuff but a course covering linear algebra with differential forms elegantly unifies, corrects and generalizes them. Standard is also in contrast to the geometric algebra/calculus alternate path.
If you can’t invert vectors, you aren’t studying vector calculus properly. ;-)
Differential forms are a half-baked formalism.
Unfortunately I don’t know of any great undergraduate level geometric calculus textbooks. Ideally there would be something like Hubbard & Hubbard’s book (http://matrixeditions.com/5thUnifiedApproach.html) written using GA as a formalism.
From my view, it goes both ways: geometric algebra/calculus is a more transparent version of the standard approach and the translation back to it is also a relatively small delta to pick up.
Either way of going about what is in essence the same material entails becoming familiar with multivectors, the wedge product, and multilinear algebra, whether you do it through geometric algebra or the standard approach.
That makes sense but my argument is since further material (some examples which I listed) assumes and builds upon the standard approach, you'll likely be better off taking that path.
I've played many of the author's games and consider them to have better stories than most. I’d have to reach for the likes of Planescape or Disco Elysium to find something I’d consider more compelling.
As you imply, there are many games whose brief summary might sound weird, cheesy or cliche but are actually very well crafted story experiences when played. For me, some would be: Life is Strange, Soma, Deus Ex, Human Revolution, Alpha Centauri, Alan Wake, Control, Quantum Break and Detroit Become Human.
Then there are the Soul Reaver games with middling stories but whose written dialogue and delivery easily put them at the level of great literature for me.
Storywise, some of the author's games would not be out of place if ranked highly amongst such a list. It's like Berkson's paradox, his studio has had staying power but you certainly couldn't point to graphics or unique game mechanics as explanations for why.
>This article seems like a self-congratulating piece
I'd go as far as to argue the author undersells his abilities. His RPG world building and stories are a great deal more entertaining if compared to many fantasy books.
> That doesn't mean AAA studios can't make a good game story,
They could but rarely do. Meanwhile, the majority of those few attempts get workshopped to death (it's easy to tell when a game with potential got derailed in this way). The author isn't saying good game stories don't exist, only that they're rare and most often from smaller studios.
I don't think it's a stupid question, just oddly phrased (more on that later). I think there are two stable interpretations. "When did grass evolve" or "when were grass lawns invented".
Later:
Why isn't it an obviously stupid question? Because I think the accompanying "who (or what) invented grass" is validly answered as "by evolution". I feel the act of invention requires no intentionality and is simply the output of learning processes where generated artifacts have material and dynamic properties embodying deep knowledge of physical laws and help achieve some goal relative to an environment. Evolution learns in the sense that the mathematics of natural selection mirror that of bayesian filters.
https://tvtropes.org/pmwiki/pmwiki.php/Main/MacGyvering