They are because they can, because it serves as social proof, which convinces their customers that they are doing something of deeper value. Then in reality they will use it to develop channels preparing to use their customers (and the data customers trust them with) as the product in the future.
That signals the reverse that they might jack up prices at any time for their 10x returns for the investors. How does that instil any confidence at all?
As I see the perspective of a typical vp champion/customer/middle manager at a large org that buys their services: if my vendor increases their prices that is usually an indication they have something of value and things are going well. It is a negotiation, buy or build business choices, not embarrassing. If my vendor doesn’t raise, and then they cease to exist, or become so weak that a competitor of mine can buy them out, then I am actually in an embarrassing place.
My main job in this conception is to not be in an embarrassing place, and grow my budgets and headcount. Prices rising can even help with this, perversely.
I agree with much of what you’ve written but think you are missing the correct alignment of the mobile data timeline — mobile data had standards because it was forced to. It was forced to early because it was not a fundamental innovation, telecom itself was the fundamental innovation, mobile was a constraint relaxation. Intelligence might be forced to have standards as well, we will see what form the regulations take when prices reflect costs and healthy margins and become existential threats for many businesses.
I agree with that as a premise, but again it seems to
me you are selectively jumping way into the end game. There were early networks that did not standardize, and these nonstandard networks had advantages, and some of those advantages were sacrificed in market-driven standardization.
Intelligence must have interfaces, and those can be standardized. Businesses will try to remain provider agnostic, which will also drive standardization via standard sales and marketing methods.
Separately, we are doing our best to standardize performances on benchmarks.
I don’t disagree that right now transport of standardized mobile data vs emulation of human intelligence is qualitatively different, but perhaps primarily because it is early in development, and our vantage point this time is relatively from within the network, instead of outside it.
This argument sounds nice at a surface level, but seems deeply incoherent and wrong in a way I haven’t yet put my finger on precisely. How can you say this:
> We have souls. We have an inner self. We can treat ourselves as transcendental subjects in the Kantian sense. We have emotions and spiritual life; we experience qualia. These entities are not obtained by addition to a physical state, but by subtraction from a complete physical account. Mental processes are physical processes described in a way that captures only their salient characteristics.
followed by this:
> The reason why this picture is more credible than any dualism is not that “science explains everything” — it doesn’t — or because “physics explains everything” — it does so even less. It is because of the hundreds of years of astonishing and unexpected success of the sciences that have convincingly shown that apparent metaphysical gaps are never such.
followed by this:
> Earth is not metaphysically different from the heavens, living beings are not metaphysically different from inanimate matter, humans are not metaphysically different from other animals. The soul is not metaphysically different from the body. We are all parts of nature, like anything else in this sweet world.
So it isn’t describable by physics but it is only physics? And there are no closures or gaps? Ok sure in one sense we can say everything is connected, but this article seems to me to demonstrate effectively that without these divisions, pursuing understanding of it is essentially intractable.
He seems to be describing the dissolution of some construct in his worldview that I am having a difficult time relating to. Anyone have a different take?
I think there is a gap, but it's not what they think it is - it is the gap between description and execution. Chalmers wants a description level explanation for the properties of execution, which is not possible. He wants to get for free what is an irreducible recursion between cost and action. The gap is not ontological, it is epistemic.
It just means we can't know without paying the price, walking the path of the process, step by step. No jumping ahead. We can't even predict a 3 body system far ahead. We can't tell the properties of a code without executing it. We can't compress most processes, their execution is the shortest description. Chalmers wants 3p to eat for free at the table of 1p.
This is essentially where the field is going, started with predictive processing by Friston with his free energy principle, combined into Hofstadter’s “I am
a strange loop” and then the continuing thrust with applying the FEP as well as Rosenthal’s higher order theories and Graziano’s attention schema theory.
Putting info into a spreadsheet is a higher level of abstraction that doesn't require thinking. There are many concrete representations like that.
LLMs don't use them much. This is a lack.
Can you point a LLM at a body of code, and tell it "give me a concise UML chart of what this does"? I'm not advocating humans writing UML, but some representation like that may be useful to AIs. Except that they don't really do graphs very well. We may need a specification language intended to be read and written by AIs, readable by humans but seldom written by them. Going directly from natural language specifications to code causes the LLM blithering problem to generate too much code.
I’m not sure you and the parent are talking about the same thing.
I think they were making a joke about us getting dumber that I am confused about the premise of.
You seem to be suggesting we are going to fill spreadsheets (which claude already does pretty well) and that spatial reasoning is an insurmountable problem instead of just something that doesn’t emerge naturally from training on text/code corpi.
The entire point of abstraction layers is that they require less thinking most of the time (and, usually as a tradeoff, more thinking a minority of the time).
I don't think I think less when writing Clojure or Rust than I would writing raw assembly code, I just broaden the scope of my projects to fill up my thinking capacity.
The accurate version of the result would be something like: “if you model lifespan as aging + i.i.d. noise and dial the noise to zero, heritability of the aging component is ~40-50% in our model.” Which is barely a finding, since by construction reducing i.i.d. noise has to increase heritability of whatever non-noise remains.
This would require an accurate definition of ageing. What is ageing? How is it related to life span? Because in theory, there can be definitions of ageing that are not tied to life span. For instance, do bacteria age? Does this affect life span? What is the life span of a bacterium anyway? Does hydra age? (For those who don't know much about biology: literally everything ages, if you define ageing as functional decline over time. Even viruses would age, if you define it as functional infections possible plotted over time. Does DNA and RNA age? The definitions become blurry; almost no molecule is immune to changes and modifications, so just about anything would age. So it really depends on the definition, and we need to read the definition before we can accept assumptions based on it. Thus: what is ageing and how does it relate to lifespan, as definition?)
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