On Tue, Apr 2, 2024, 7:18 PM '[email protected]' via Everything List <
[email protected]> wrote:

> Opinion on what occurs when we load, not an LLM, but a LLM + a Neural  Net
> on a low-error, high entanglement, quantum computer. Will this create a
> mind?
>


If you're not careful, you could create 2^N minds. Where N is the number of
qubits.

Jason


> On Saturday, March 30, 2024 at 08:31:25 AM EDT, John Clark <
> [email protected]> wrote:
>
>
> On Fri, Mar 29, 2024 at 10:28 PM Russell Standish <[email protected]>
> wrote:
>
>
> * >"There is a big difference between the way transistors are wired in
> a CPU and the way neurons are wired up in a brain."*
>
>
> Yes, but modern chips made by companies like NVIDIA, Cerebras and Groq
> don't make CPUs or even GPUs, they make Tensor Processing Units, or in
> Groq's case Language Processing Units, chips that have been optimized to do
> best not in floating point operations but in large neural networks that all
> current AI programs are. In the recent press conference where Nvidia
> introduced their new 208 billion transistor Blackwell B200 tensor chip,
> they pointed out that when used for neural nets, AIs chips have increased
> their performance by a factor of 1 million over the last 10 years. That's
> far faster than Moore's Law, and that was possible because Moore's Law is
> about transistor density, but they were talking about AI workloads, and
> doing well at AI is what NVIDIA's chips are specialized to do. I also found
> it interesting that their new Blackwell chip, when used for AI, needed 25
> times less energy than the current AI chip champion,  NVIDIA's Hopper chip,
> which the company introduced just 2 years ago.  And I do not think it's a
> coincidence that this huge increase in hardware capability coincided with
> the current explosion in AI improvement.
>
>
>
> *> "In the future, I would expect we'd have dedicate neural processing
> units, based on memristors"*
>
>
> If memristor technology ever becomes practical that would speed things up
> even more, but it's not necessary to achieve superhuman performance in an
> AI in the very near future.
>
>
>
> > *"**The comparing synapses with ANN parameters is only relevant for
> the statement "we can simulate a human brain sized ANN by X date"."*
>
>
> I don't see how comparing the two things can produce anything useful
> because one is concerned with software and the other is concerned with
> hardware. Comparing transistors to synapses may not be perfect but it's a
> much better analogy than comparing program parameters with brain synapses,
> at least transistors and synapses are both hardware. Comparing hardware
> with software will only produce a muddle.
>
>
>
> > *"**he [Kurzweil] said human intelligence parity (which I supose could
> be taken to be avergae intelligence, or an IQ of 100) [...]*
>
>
>
> *AI passes 100 IQ for first time, with release of Claude-3
> <https://secretive-tarsal-fe8.notion.site/AIs-ranked-by-IQ-AI-passes-100-IQ-for-first-time-with-release-of-Claude-3-f67219c7ccb44e4da1707d54ef1df8f1>
>  *
>
>
>  John K Clark    See what's on my new list at  Extropolis
> <https://groups.google.com/g/extropolis>
> lnm
>
>
>
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