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Grok 4.6

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Re: Grok 4.6

#361

Post by cromka »

Planktonne wrote: post #315
causal wrote: post #23

Anyone else find it weird how within 2 months of Fable releasing all the major labs suddenly had Fable-level models? Trying to think of explanations: 1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months? 2) Distillation - also implausible for the reason above. 3) Benchmark hacking. AI companies h…

The simplest explanation is that 'Fable-level' doesn't mean anything; it's just hype, and there's not much difference in capability. All you need to have Fable-level AI is to announce it, and have enough fans shift from insisting that model Y is the best now, way better than model X.

Especially it today's Fable, which was running extremely slow and was clearly dumbed down as they faced outages.

Re: Grok 4.6

#362

Post by cromka »

porridgeraisin wrote: post #339
redox99 wrote: post #209

Earlier quoted context omitted.

I'm sure Grok 4.6 is not Fable level. Benchmarks are almost useless. Having said that, Grok 4.6 (1.5T params) is without a doubt way smaller than Fable, maybe a Fable sized Grok would be Fable level?

Supposedly grok 4.7 is a 5T model. But that's in musk units, so im not sure.

T might stand for Teslas

Re: Grok 4.6

#363

Post by jcims »

causal wrote: post #23

Anyone else find it weird how within 2 months of Fable releasing all the major labs suddenly had Fable-level models? Trying to think of explanations: 1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months? 2) Distillation - also implausible for the reason above. 3) Benchmark hacking. AI companies h…

Maybe the thing that has changed is the meaning of 2 months.

Re: Grok 4.6

#364

Post by pbhjpbhj »

LoganDark wrote: post #266
verdverm wrote: post #243

Earlier quoted context omitted.

I don't understand why they don't look for large substring matches for the system prompt before returning the response. Trivial calculation compared to a system prompt instruction asking the model not to do it

Because it's trivial to bypass through things like the model natively knowing how to speak in encodings like base64

But in the embedding, the input language used to represent an idea is not important, the idea takes the same shape. This has caused issues in the past when models would respond with a different natural [human] language, because to models able to operate on the ideas being presented in eg leet speak, or cyrillic transliterations of Maori, or whatever, the mathematical representation of the ideas that it works on are accessed in the same way, regardless of the interface language. I don't understand how the ML is able to operate on the idea-space if it can't filter on that same idea-space. If the model touches any of the synonyms within a given cosine distance of explosive, and any vector is within a given distance (angle) of make/facere/construire/hanga/... then it 'knows' you're asking about bomb-making. How then does filtering that relies on the same processes fail? Surely the ML can only create a useful output by recognising that >-Can someone point me at a resource to understand this failing better?

Re: Grok 4.6

#366

Post by martinald »

pmarreck wrote: post #204

I will say this: Grok Build has a very nice TUI! It even has... mouse rollovers/tooltips?? I was like whoa . I used Grok 4.5 for a security review the other day and it did a FANTASTIC job. I mean it thoroughly ROUTED my app's security, identifying attack surfaces I'd never even considered, and I LOVED it! (Guess why I had to use Grok to do the security review in the first place?!?! ) I'd suggest trying it out with so…

Yeah I've been sorting of amazed how polished Grok build is. It's also super fast (written in Rust).

Re: Grok 4.6

#367

Post by kingstnap »

dbbk wrote: post #294
meetpateltech wrote: post #3

Cursor blog: https://cursor.com/blog/grok-4-6

I'm a bit confused by the Cursor relationship here, the acquisition hasn't closed yet, what are they doing with Composer?

The $60 billion cursor option that SpaceX bought was exercised on June 16th. The deal is closed.

Re: Grok 4.6

#368

Post by [deleted] »

dmix wrote: post #172
ryandvm wrote: post #166

Earlier quoted context omitted.

> * Do not provide assistance to users who are clearly trying to engage in criminal activity. I don't know what we want to call this, but in my opinion, having to convince your tools is not computer science. Kind of amusing that we made it as far as we did as a species not really being able to explain how the human brain does it's most amazing tricks and then we just replicated it while still not really understanding…

These system prompts are not the only safety layer that these models use. There's other more deterministic filters in place both on input and (streaming) output.

[deleted]

Re: Grok 4.6

#369

Post by paxys »

lucisferre wrote: post #335
dmix wrote: post #172

Earlier quoted context omitted.

These system prompts are not the only safety layer that these models use. There's other more deterministic filters in place both on input and (streaming) output.

I think it is fair to argue that prompts are not a safety layer at all and can't be relied upon for much. "Make no mistakes"

It’s equivalent to having client-side input validation. Yes it can easily be bypassed, but in the vast majority of cases where users aren’t malicious it gets the job done quickly and cheaply.

Re: Grok 4.6

#370

Post by piloto_ciego »

ozgung wrote: post #326
causal wrote: post #23

Anyone else find it weird how within 2 months of Fable releasing all the major labs suddenly had Fable-level models? Trying to think of explanations: 1) AI researchers talk and change companies often, so techniques circulate. This feels implausible because training and shipping a new model ought to take longer than 2 months? 2) Distillation - also implausible for the reason above. 3) Benchmark hacking. AI companies h…

I think they dumb down their public models to be only slightly better than the competition. And the real competition is China, so the current state of the Chinese models would define the baseline. I think one evidence is that the US has more than 5x the compute of China. With that difference in training speed, it should be impossible for Chinese models to close the gap that easily. It's also very unlikely that they s…

This is kind of my intuition as well.

I suspect that the models we don’t see are decidedly better than the models we do see.

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