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If you ever worked in IT consultancy you would know its not a stunt, but its not impressive either.

F500 companies software is like switz cheese when it comes to security.

It was often a strategic decision to „release anything fast now, worry later”.

Ppl abusing AI will find those holes now but we all know there will be „zero” actions taken on it. Too many managers, CEOs, CTOs, higher-ups would be forced to take responsibility. This will simply not happen.

It did not happen, wont happen now and most likely wont happen in the future.


Haven't worked in consultancy specifically, but I've seen enough "internal use" corpo software to echo your "swiss cheese" sentiment. That a solid cybersecurity AI can find exploitable holes in it just isn't surprising.

People who never worked with corporate software written by underqualified, underpaid and overworked developers often have some incredibly inflated code quality expectations. An average open source project has code that's ten times as neat and a hundred times as battle tested as what's common in tooling inside corporate perimeters.

As a rule of thumb for this kind of corporate code: assume the software was written by a drunk developer at 3am, and you wouldn't be too far off.

All the more reason to mock the braindead "it's all marketing". There's no magic in a year 2026 agentic AI being able to traverse poorly secured corporate networks.


GPT6 level model and astronomous amount of money to run it to do it.

Ppl always say that like its „just run it on your laptop” thing.

No its not and very few are even given right to be able to do it.


Reality is- Anthropic is a tokens dealer. If they can hook you up for bigger spend -> they will.

We already know company is not making any profit. To break even they need ppl to use a lot more tokens AND pay for them premium price.

We also know LLMs dont give such a huge productivity boost do warrant spending of THAT size.

At this point you only wait for more and more shady plays.


CC isnt instrumental to use Anthropic LLMs. Yet here we are.

Apple Watch with 1TB of vram with the size of well.. a watch.

Amazing story. If we make such leap in semiconductor field, it will be bigger than anything we have done till now. And all of that in 10years!


No, it won't. We moved about order of magnitude that from 1990 to 2000.

The thing is, it needs demand to drive it. Laptops have been roughly the same spec for the last 10 years because we don't need them to be bigger; there's no demand for a 16Tb RAM laptop because we don't have anything that could possible need that much RAM. Until LLMs came along, and we all want to run them locally, and so now there is a market for 16Tb laptops. So we'll invent the tech to make that happen.


Right but 2000 to 2010 didn't have similar progress, and especially 2010 to 2020 didn't. Sure, things have gotten better but not as much as the 1990 to 2000 leaps.

And yes, laptop specs haven't changed much and this is partially because the need for spec changes wasn't present, but also during the last 20 years there has been tremendous pressure for efficiency in datacenters.

Despite that, dennard scaling is dead since 20 years. There are physical limits. Already now, the wear effect of electrons jumping is present, and it will only get worse as things scale towards smaller sizes.

There are some benefits to be had, e.g. one can etch models into chips directly so you can pack them more closely, and run more inference on Tensor like chips, but that gives you maybe one order of magnitude improvement in total, at most. Also, of course nobody does that when each 2-6 months a new model comes out.


The thing that we did in 1990-2000 was adopt new standards as the old ones became blocks on progress.

I had a friend working in optical computing back in the late 80's that would wax lyrical about how optical computing was vastly superior to silicon back then. But it never took over because silicon worked well enough.

If we've hit the limits of silicon then there are other options. We would need to reinvent huge chunks of our tech stack, and that is incredibly expensive, but if the demand is there, we'll do it. The demand has never been there.


The original claim from the parent comment was running a Fable-level comment within a decade. Even if you're right about whether it's possible that another model could support that level physically, do you really think that we'll figure it out and ramp up the infrastructure to profitably sell on come consumer hardware anywhere close to that soon?

Well, we did do similar stuff back then. All it takes is money ;)

You're talking about going from a single gigabyte to 16 terabytes in a low-power consumer form factor, which is 1600x. A generous estimate of the factor of the RAM sizes for low-power consumer devices between 1990 and 2000 would still be a few orders of magnitude short, if I'm doing my math right.

Examples of what exactly you're claiming is precedent for this would be helpful.


This went down a rabbit-hole, which was fascinating, so thanks for the push :)

Not sure where the 1Gb number comes from? A standard laptop now is ~16Gb of RAM, so 1000x (and 1Gb -> 16Tb would be 16000x not 1600x). We went from Kb to Mb and then Mb to Gb of memory roughly every ten years from ~1990 -> ~2010. Each of those jumps is 1000x

Talking this over with claude, though, it pointed out that the need in dealing with LLMs is bandwidth and read-only storage, since the weights aren't dynamic. So we're not necessarily looking at 1Tb of RAM, we could be looking at 256Gb of faster RAM, and multi-TB of (much cheaper) flash storage, with extensive caching built in at OS level. This is all technically do-able with current tech, so it'll be interesting to see if it happens.


If it happens, that’ll be proof enough for me that LLM assisted science is giving economic returns!

Till its used in prod for few years and polished, I wont touch that.

Too many things tests wont catch.


Yea, like France or Germany or Belgium

You know Im right


This is a permissions scope misconfiguration by OP.

It has nothing to do with GitHub and giving it a name is hilarious.

“Look I shoot myself in the foot and now its bleeding. ITS THE GUN MANUFACTURER FAULT”


So ppl will do the same thing engineers in my country do.

They dont add into it was done by AI.

Works like a charm and Goverment has no issues with it.


And there is Asmongold doing a video of him watching someone else making a video with commentary like “absolutely”, “outrageous”, “bold” and having it all monetized with literally ZERO effort.

So yea.. it takes a lot of effort -> if you are nobody.

For eatablished streamers just slapping something from stream on ytb is enough.


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