Musk is a genius creating really exciting ideas. No doubt about that.
But as they say,"the devil is in the details"
- Can Starship transport people from London to Sydney safely economically, compared to Boom, which is working on a supersonic passenger aircraft ?
-Why can the boring machine dig tunnel at much lower cost than it's competitors? Maybe it's because the everyone else tries to dig tunnels for trains, which have a much larger diameter than Musk's boring machine, which only fits his "Teslas at a tunnel" concept?
And it might be a good idea. Worth a try. But be honest about it.
-Sure, data centers in space probably have some great uses, and I'm happy he's trying, but will they ever be more economical than deploying servers on the ocean? On countries with very cool climate?, powered by new energy technologies?
I'm not sure I understand. From a quick google search it seems like they are designing and manufacturing it themselves (with a few partners). Am I missing something, or is your information out of date?
The industrial bases of entire nations military aviation have been taxed for years/decades to produce supersonic capable engines simply for high maintenance fighters, now do that for affordable maintenance low headcount passenger jets. I'm not going to say impossible, but it will take more than VC money and anonymous 'partners' to convince me its likely.
For it to have a chance the US gov. needs to do IP transfer and pair them with NASA for test as they did with SpaceX, more realistically simply twist Pratt&Whitneys arm a bit...
Boom is planning to operate at Mach 1.7 (approx. twice that of current aircraft) with a range of about 4250 nautical miles (4900 miles, 7900 km). Over land they're only going to fly at Mach 1.3 to reduce sonic boom effects.
That's not enough range to do London - Sydney, it's not enough to do Los Angeles to Sydney either, or Los Angeles to Tokyo, it's basically a replacement for trans-Atlantic flights only because even US cross-continental Mach 1.3 is only about 50% faster than a 737 (3h vs. 5h)... It's pretty much geared to the prestige market only.
Under an hour to anywhere on the planet, meanwhile, is absolutely someone would be a premium for -- and they'll do it for most/all long haul flights if it was available.
Starship isn't a proven manned transport vessel yet. And Boom was founded in 2014.
If I was to hazard a guess, the BFS concept is 2035 at the earliest, most likely 2040 -- and it'll be at a much smaller scale than previously advertised.
If the end goal is that only regulated US companies can use Fable, that is a pretty good outcome for Amazon, and also for Jeff Bezos's new startup which aims to use AI to monopolize large industries that depend on advanced engineering in the physical world.
>If the end goal is that only regulated US companies can use Fable, that is a pretty good outcome for Amazon
It's a terrible outcome for Amazon because it destroys Anthropic's revenue. Roughly half of Anthropic's customers are foreigners, and they wouldn't use Anthropic if its next generation model was banned while other providers' next generation models aren't. And if the US follows through and bans all Mythos-level models for foreigners, then in 6-12 months the entire global market will be overtaken by China when its models catch up, and Amazon will lose money on its investment in OpenAI too.
Immediate revenue impact is basically 0 - nobody cancels their Claude sub because Fable isn’t why they got it in the first place (by nobody I mean like 1% of total users and they’re likely net neutral tokenmaxxers for revenue).
Signal to OpenAI and Google is clear: can’t release too smart models or they get controlled. It follows there is no danger to revenue since other providers are forced to plateau at the same level.
…which puts the whole train the next model business idea a risky proposition since the training can’t ever pay for itself - but USG really wants you to keep training, so guess what happens?
Oh and re China - if you think they’ll release an open Mythos-class model, I have a bridge to sell.
Seems like estimates are that 70-85% of their revenue comes from API usage/pricing, so some users switching from Opus to Fable for that would've had a big impact
Then there's people switching from GPT 5.5 or upgrading their subscriptions, and Fable being scheduled for removal from subscriptions on the 23rd
Maybe one possible path(to make weaker models highly capable) is making the job of the llm as easy as possible.
I wonder if part of the solution is building/finding the right libraries, with the right documentation/language/API(one that plays well with LLM's) and maybe creating some synthetic data around them - to make it very easy for the llm.
And maybe there could be a business model around creating those libraries.
So in my limited experience: The smaller the model, the bigger the harness. The biggest issue becomes the context window. For big models you can kind of just give it bash access and let it run... while with the smaller ones you need to fully manage the context in each LLM call.
If you can ask the model for a specific function; with a spec design (typed languages help too) then the small models are great! I have had good progress with generating small python modules for example, but you need verification rounds to catch issues.
So test driven design + a good spec sheet + a very detailed todo.md (or even better if its todo.json because then the LLM does not need to manage it, you do from the harness) is your best bet for small models.
I think as well there might be "algorithms" that can work with local LLMs. With local LLMs there is a small context window, but not that much cost per token. So perhaps there is a way to do lots of small prompts that work in a sequence to produce a result.
Like perhaps you could produce 5 versions of a piece of code, and then compare them to choose the best.
Also if the local LLMs can call tools, maybe you can use static analysis tools to catch errors and try again in a loop or process of some sort.
There also might be certain languages that work better because those languages have better static checks.
Current state of the art in guitar emulations are Neural Amp Modeler Core A2 plugins, which are dramatically better than Line6 amp emulations. (See the results of large scale listening tests in the following page that compare NAM A2 against current-generation Line 6 amp emulations).
Guitarix plugins actually use the technique I'm chasing (circuit diagram based simulation). I'm honestly not sure how Guitarix emulations stack up against Line 6 emulations, or whether Lin6 uses a similar approach. To my ears they seem to be of comparable quality. But NAM A2 is dramatically better than both.
I'm actually chasing this line of research as part of an effort to write a realtime-capable accurate emulation of a Dyna Comp compressor for inclusion in the ToobAmp collection of plugins that uses a hybrid approach (circuit simulation for the envelope generator, which NAM modeling struggles with, and a nano NAM model for the Operational Transconductance Amplifier at the core of the original effect, which is computationally expensive when using circuit emulation. Too early to tell whether that's a sound approach atm. Finding a good open-source library of Spice components (for branded diodes, transistors, op amps, &c) may prevent my circuit simulation project from reaching a publicly releasable state.
Disclosure of conflict of interest: My own open-source project (PiPedal, search for it if you're interested) relies heavily on NAM A2 models.
I think the parent was referring to the Variax, which models guitars, not amps. That line has been discontinued, sadly for me who plays one. I hadn't thought of using AI to reverse engineer the modeling, implemented in firmware in the guitar. That could be interesting.
... and to answer your question directly. No. I don't think claude could do it unless you guide it very carefully through the process. You need to have a pretty good idea of what needs to be done.
In short, as far as I can remember: evolutionary, it makes sense to understand other humans, to feel what they feel(empathy - the mirror neurons system), and simulate their thinking and feelings.
And once we have those systems, we can also use those on ourselves. And that's consciousness.
Edit:And I wonder if this is a testable hypothesis, in a simulation.
This way of thinking can only explain externally-visible parts of consciousness. It does nothing to address internal experience of being conscious and qualia. I don't think the internal experience has any bearing on physical reality (P-zombies would act the same externally) which makes this something outside of the realm of currently understood physics.
The internal experience has bearing on physical reality right here, because without it you wouldn’t have written about it and caused these words to appear on my screen in physical reality. It affects your thinking, and hence your actions and utterances in the physical word.
For reasons like that, I don’t think that P-zombies are possible.
Having internal mental experiences causes my brain to send physical signals to my fingers in order to type the words "I have internal mental experiences". A philosophical zombie would type those same words, but they would be caused by something else since by definition it lacks those experiences. That would be rather surprising, and it would be even more surprising that the words that the zombie emits coincidentally correspond exactly to the experiences that the non-zombie has.
As the article says the alternatives (that the author seems to favor instead) boil down to "there's some physics we missed" and probably that's the point where we differ. I find that implausible, what would that be? Consciousness quantum field? Consciousness boson? If it's going to be interacting with matter it has to have a way to do that.
Internal experience is an input to your mind (that’s how you know about it), and what your mind perceives affects what it does. The better question is: how can what you experience possibly not affect your actions?
The need arises when you consider the complex social systems humans leverage for survival — our ability to navigate interpersonal conflicts and engage in cooperation relies on theory of mind and our tendency to perceive ourselves as individual free agents empathizing with separate free agents.
By definition, internal experience is something you perceive, and what you perceive informs how you act. Therefore internal experience affects outward physical action.
Qualia are the inside view of sensory data and reward signals.
Think about it from an evolutionary perspective:
Animals that step into a lava flow or forest fire don't reproduce. Eventually some evolve the ability to detect intense heat from a distance, and pain as soon as tissue destruction is imminent. They do not have nor need a general understanding of the dangers of heat, or even conscious awareness that they've stepped on a hot coal.
The pain signal compels them, but that is very low level machinery. It had to continue compelling beings that developed larger and more sophisticated brains that are capable of abstract thought and reasoning. Feeling pain is one of the lowest level parts of the brain telling the higher parts exactly what its going to do in terms that permit no disagreement.
Internal to what? The brain is not a monolithic thing, it is different parts communicating and interconnecting. When the connection between the halves is cut, the person objectively becomes two people, but still experiences and presents themselves as one. Observing ourselves is just one part of the brain responding to another, or theorizing on past behavior. There is probably no actual introspection going on inside of the human brain, only the perception of one.
Internal as in that which is feeling things. In this context the physical brain is what is responsible for what you do and feel, but it is not physically different from other matter and it requires no "internal observer" do do its thing.
Not sure about taking it down to the level of consciousness, but makes sense regarding the sense of self, the conceptual experiencer, the perceived center of experience. It agrees well with the observation I have made again and again they my sense of self is much stronger when I'm around people, and stronger still when I'm in a context where I don't know people and/or am uncertain in social rules.
This can be as immediate as dancing in a club, and closing my eyes I feel open, free, still, the body just flowing, then opening my eyes and feeling the cage of categorization of the world, relating my self to other people as a major function, coming right back.
Also being alone in nature for me makes the sense of self drop. Without intention, spending even just a few hours alone in a forest seems to quiet down the part modeling my self in relation to the world so much. There's no need for it there. I'm not a person in a forest; I become the trees, the birds, the rustling of the leaves, the sun shining through the canopy.
I agree about the forest part. and your comment was interesting.
I know that the part of the brain responsible for the self thoughts is called the "default mode network". and meditation can reduce it's activity, i.e. the internal monologue stops, but also it can be measured via FMRI.
So i wondered: are the mirror neurons part of the "default mode network"? I asked claude that, he said no, they are two different systems.
So maybe the mirror neurons, those responsible for empathy, "to feel as someone else" are also responsible for becoming the trees, the birds and the rushing of the leaves?
I'm not saying that they don't have some internal self model that helps them model the internal states of others, quite the opposite. I am saying this specific explanation seems to lean on a biological mechanism that (at least by the phrasing of the linked article) is only present in "hominids".
Musk of course used twitter so Trump could get elected.
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