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The Dataome: The Energy Intensity of the Digital World
Key takeaways:
• The generation and usage of digital data requires a significant amount of energy and resources.
• Silicon chip production is an energy-intensive process due to the creation of ordered structures from disordered material.
• Efforts to generate electric power for the current informational world are hindered by the fight against entropy.
• The energy requirements for computation, data storage, and data transmission are increasing exponentially.
• Without significant improvements in efficiency, the energy needed to run our digital data homes may soon match the global civilization's total energy usage.
Transcript:
Speaker 1
Its everything, right? It's this conversation in recording to yr bits. It's the information that went to and from your phone when you picked it up in the morning. It's the video you made. It's all the financial transactions, it's all the scientific computation. And that, of course, all takes energy. It takes the construction of te technology. In the first instance, making silican chips is an extraordinarily energy intensive thing, because you're making these exquisitely ordered structures out of very disordered material. And so there too, we go back to simo dynamics. And you're fighting, in this sense, against entropines. In a local fashion, we're having to generate electric to power current informational world, that piece of the data. And the rather sobering thing is that already, the amount of energy and resources that we're putting into this, it's about the same as the total metabolic utilization of around 700 Million human and if you look at the trend in energy requirements for computation, for data storage and data transmission, the trends all upwards. Its an expedential curve. And they suggest that perhaps, even if we have some improvements in efficiency, unless those improvements are then in a few decades time, we may be at a point where the amount of energy, Just electrical energy, required to run our digital data home, is roughly the same as the total amount of electrical energy we utilize as a global civilization at this time.
Speaker 3
The
Caleb Scharf on the Ascent of Information — Life in the Human Dataome
COMPLEXITY: Physics of Life
How Measurability/Mathematical Bias Limits the Scope of Scientific Inquiry and Human Discovery
Transcript:
Speaker 1
So there's this old paper from the, I think, 1960s by Eugene Vigner, the Nobel Prize physicist. It's called something like, on the unreasonable effectiveness of mathematics. The fun paper, and he's like, there's no good reason why mathematics should work as well as it does. And there's no good reason why there should be a tool that allows humans to predict things as well as math does. There's no good reason. It's kind of nuts. And we should all just be grateful. And he says some other things, but he's basically just kind of being all about how great mathematics is and how there's no good reason why it should be. And it's pretty cool that it does work so well. I think that there's a counter to that, which is that not everything is that easily described that mathematics. And there's lots of things for which mathematics is not that effective at describing. And it's actually just the things that were well described or easily described by mathematics are the things that were discovered using mathematical tools. They're the things that lend themselves that were amenable to mathematical inquiry. And a lot of the things that we're interested in terms of social science and cognitive science and the related philosophical inquiry are things that are much less tangible in terms Of this kind of specification. And you can see it like in a physics equation, right, a physical theory, whether it's about mass or electricity or something else, right, you have a theory about how things work. And then you can write out equations. And all the terms in the equations have units. And they are all directly related to the things that are measurable. The theories are directly about relationships between things that are measured. And in social theories and cognitive theories, so often our theories are about relating constructs. And then we have proxy measurements, but the theory isn't about the relationship between the proxy measures. The theory is about the constructs and the relationships between the constructs that are social in nature, that are cognitive in nature, but aren't the things that are being measured. And so there's this gap. And I don't know the extent to which that gap can be overcome.
Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale
COMPLEXITY: Physics of Life
The tension between the ambiguity of individuals' goals and large scale collective organization
Transcript:
Speaker 2
Here's the pessimistic nightmare. It is really good and healthy for human beings to live in an ambiguous environment with a pluralistic set of goals, many of which are in Kuwait. That is an essential tension with the methods of large scale collective organization. If it's true that for an organization to cohere, it needs to have clear policies so it can act coherently, then we should not expect that kind of ambiguity to survive at scale. And I think what you're describing, so I tend to think about since I'm a philosopher like what makes something constitutively coherent. And what you're describing is a kind of evolutionary process. You know, some organizations are going to be more coherent than others and some people are more interested in coherence. And the people that are more interested in following the strict outcome are going to arise in the organization. And the organizations that have clear outcomes are going to be better at achieving those outcomes. And so our world is going to be full of large organizations staffed with people that have very, very clear specifications of outcomes. And there's something inhumane and bad about that for individuals. But that's what happens when we need to organize in large scale collectives.
Paul Smaldino & C. Thi Nguyen on Problems With Value Metrics & Governance at Scale
COMPLEXITY: Physics of Life
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