Mostafavi and his colleagues tested more than 8 million common mutations, and found two that seemed to become less prevalent with age
I don't understand this: only two of the 8 million common mutations affect longevity?
The only thing that makes sense to me is if the number "two" refers to late-acting mutations that become less prevalent with age.
A little while later, when that rat is sitting around, its brain sometimes re-creates a nearly identical pattern of electrical impulses zipping between the same set of neurons
This is like what we see in the mind's eye after hours of playing the same video game.
Whenever we choose a model with low complexity (like a linear model) and thus low variance, we’re also choosing a model with high bias. If we try to increase the complexity of our model, such as a quadratic model, we sacrifice low variance in exchange for low bias at the cost of high variance
It's interesting to think how the terms "complexity", "bias", and "variance" could also apply to people's beliefs. You could make an analogy that less sophisticated thinkers (low complexity) are highly biased and don't sufficiently adapt their beliefs (low variance) depending on the situation (data).
But interestingly, as the xkcd comic demonstrates, it's also common for people to over-generalize (overfit) based one or two instances of experience (few data points). We tend to call these people "biased" because they often seem to have prejudices that don't fit all the data that's actually out there. But from their point of view, with limited experience/data, they actually are fitting perfectly and would consider themselves "unbiased". So "bias" is a matter of perspective (a matter of which dataset you have).
A broader distribution of value means that you’re probably more likely to create a $B+ company in enterprise than in consumer. The top five enterprise companies account for 11% of total value creation, whereas the top five consumer companies account for over 3X that amount, or 36% of total value creation.
The markets for consumer startups are more "winner-take-all"
Now that we are able to adjust the road, we can dig into our hypothesis that the trajectories "reflect" off the edge of the road at the same angle that they hit it. Is this exactly true, or an approximation? By examining many examples, can you understand why a fixed turning rate leads to this behavior?
I don't see why. Why wouldn't the author just tell us?
We stepped up a level of abstraction to see a high-level pattern, and then stepped down to discover the explanation for that pattern. I believe that this dance is where the deepest insights are born — not at any one level of abstraction, but in the transitions between them. This is why it is crucial that our representations provide both a step up and a step back down.
Key assertion. Very profound. I will have to keep an eye out for this to see if I find that to be true.
count in counter IP
this should probably be "c"
Then the cancer cells cloak themselves in a protective layer of platelets to hide from the patrolling sentries of the immune system.
I find it interesting that the author anthropomorphizes the cancer cells by writing "to hide"--as if they had intent--rather than "which hides them". It's almost as if survivorship bias is a key element of narrative and the sense of free will.
gaff
Spelling correction: gaffe
poor implementations of the model-view-controller pattern can also cause this to happen. What happens is the controller (= application layer), takes on far too much responsibility, leaving the model (= domain layer) to become anaemic
This Massive (View-)Controller problem is why the CLEAN Architecture (and thus VIPER and RIB) splits the controller into 3 parts: Controller (a much smaller kind of Controller), Presenter and Interactor.
The Interactor is in the Use Cases Layer, aka Application Layer (where application-specific business rules reside).
The Presenter is in the Interface Layer. So is the new Controller, which I believe is really what we know as ViewController in IOS MVC.
One downside of the layered architecture is that it suggests a linear stacking of dependencies, from the presentation layer all the way down to the infrastructure layer. However, we may want to support different implementations within both the presentation and infrastructure layer
This is the same argument that Uncle Bob makes in CLEAN Archiecture, where he groups the view and persistence layers in an Interface Adapters circle.
The fact that the Strategy pattern makes use of polymorphism does not mean that the pattern cannot be used in a good functional language[4].
Critique: that isn't the claim. The claim is that the pattern is so obvious in a functional language that it doesn't even need a name.
The overriding difference between a functional language and a non-functional language is that functional languages don’t have assignment statements.[1]
What about Elixir? It's functional but it allows assignment/binding? Clearer would have been to say "re-assignment"
model interpretability is a serious legal mandate in the regulated verticals of banking, insurance, and other industries. Business analysts, doctors, and industry researchers simply must understand and trust their models and modeling results
Reaction: interesting that there's a "legal mandate".
Research distillation is the opposite of research debt
Term definition: "research distillation"
Research debt is the accumulation of missing interpretive labor
Term definition: "Research debt"
ability as web developers to extend it with new features.
Clarification: "web developers" as opposed to "standard bodies" and "browser vendors"
Fuel is about a third of the cost of operating a long-haul truck, and while drivers are capable of wringing maximum miles per gallon from their trucks, many are too heavy-footed on the pedals. (Berdinis says the best drivers are 30 percent more fuel-efficient than the worst ones.) Otto’s equipment is programmed to keep trucks pegged to optimal speeds and acceleration
Drivers are legally restricted to 11 hours of driving a day and 60 hours a week. Given that a new big rig goes for about $150,000, and taking into account the vast delays that pulling over to rest injects into the movement of goods, trucks that can cruise nearly 24/7 could dramatically lower freight costs.
Key points:
As a social species, we have two tendencies: the need for competition and the need for collaboration. Our collaboration on forming opinions leads to persistent, baseless judgments, and the competitive priority to win arguments disincentivizes us from correcting them. This evolutionary adaptation is reinforced by a dopamine rush when we encounter supporting information. Scientific facts don’t correct extreme, baseless opinions. But one potential paradoxical solution is to appeal to emotions. And another is to somehow force people to think deeply about how realistic their opinions are.
Providing people with accurate information doesn’t seem to help; they simply discount it. Appealing to their emotions may work better, but doing so is obviously antithetical to the goal of promoting sound science.
It's paradoxical that the most effective way to fight fire is with fire, but maybe that's the only practical solution, as long as science fails as a fire retardant.
And here our dependence on other minds reinforces the problem
Clarification: In other words, not only do we base our judgment on other's opinions but seeing many others around us sharing the same opinion makes us more confident in our own, no mattter how baseless it is.
If we all now dismiss as unconvincing any information that contradicts our opinion, you get, well, the Trump Administration.
Critique: this statement begs the question: does the author of this article herself suffer from confirmation bias when assessing the Trump Administration's depth of understanding?
So well do we collaborate, Sloman and Fernbach argue, that we can hardly tell where our own understanding ends and others’ begins.
Interesting rationalization for "illusion of explanatory depth" but this snippet isn't convincing. I could easily imagine the rationale being that people confuse "few moving parts" with "simple mechanism". In other words, it's easy to be ignorant of the toilet's siphon mechanism because there's no obvious connection to the short list of parts.
book, “The Enigma of Reason” (Harvard)
https://www.amazon.com/Enigma-Reason-Hugo-Mercier/dp/0674368304
Rarely has this insight seemed more relevant than it does right now.
A subtle reference to the zeitgeist of the Trump era