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Paul Tarau versus Mr. Taskmanager, who would win? [A PDP-11 Humunkulus from 1979]

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  Paul Tarau versus Mr. Taskmanager, who would win? [A PDP-11 Humunkulus from 1979] Mild Shock <janburse@fastmail.fm> - 2026-04-24 02:46 +0200
    AI dooms day escape: Güttinger Wald (Re: Paul Tarau versus Mr. Taskmanager, who would win?) Mild Shock <janburse@fastmail.fm> - 2026-04-25 14:06 +0200
      Elmos Fascist Dreams of a 365 Prolog (Was: AI dooms day escape: Güttinger Wald) Mild Shock <janburse@fastmail.fm> - 2026-05-09 12:52 +0200
        Even the Buddos are clueless [Did Tarau see Liliputians?] (Re: Elmos Fascist Dreams of a 365 Prolog) Mild Shock <janburse@fastmail.fm> - 2026-05-09 15:19 +0200
          Halfing the AI Laptop Budget: Ne-Meow sold out! (Re: Even the Buddos are clueless [Did Tarau see Liliputians?]) Mild Shock <janburse@fastmail.fm> - 2026-05-10 09:09 +0200
      Prolog Expert Ginis (PEGs) on a Keychain (Re: AI dooms day escape: Güttinger Wald) Mild Shock <janburse@fastmail.fm> - 2026-06-20 13:04 +0800
        Chatbot Classified as a Weapon (Re: Prolog Expert Ginis (PEGs) on a Keychain) Mild Shock <janburse@fastmail.fm> - 2026-06-21 05:39 +0800
        Introduction to AI Accelerator Prolog [π-WAM of Dogelog] (Re: Prolog Expert Ginis (PEGs) on a Keychain) Mild Shock <janburse@fastmail.fm> - 2026-07-17 11:16 +0200
          Not praying to the god of lambda calculus [π beats α] (Re: Introduction to AI Accelerator Prolog [π-WAM of Dogelog]) Mild Shock <janburse@fastmail.fm> - 2026-07-17 11:17 +0200
          Re: Introduction to AI Accelerator Prolog [π-WAM of Dogelog] (Re: Prolog Expert Ginis (PEGs) on a Keychain) "Chris M. Thomasson" <chris.m.thomasson.1@gmail.com> - 2026-07-17 13:03 -0700
            pi in pi-WAM refers to pi-calculus (Was: Introduction to AI Accelerator Prolog [π-WAM of Dogelog] ) Mild Shock <janburse@fastmail.fm> - 2026-07-18 01:16 +0200
              Milners fickle() in pi-WAM [For fun and profit] (Re: pi in pi-WAM refers to pi-calculus) Mild Shock <janburse@fastmail.fm> - 2026-07-18 01:50 +0200
                Re: Milners fickle() in pi-WAM [For fun and profit] (Re: pi in pi-WAM refers to pi-calculus) Ross Finlayson <ross.a.finlayson@gmail.com> - 2026-07-18 01:34 -0700
                  Robin Milners pi calculus is typeless (Was: Milners fickle() in pi-WAM [For fun and profit]) Mild Shock <janburse@fastmail.fm> - 2026-07-18 10:57 +0200
                    Can the Church Turing hypotheses be refuted? [TLo @ FOM] (Was: Robin Milners pi calculus is typeless) Mild Shock <janburse@fastmail.fm> - 2026-07-18 11:08 +0200
      AI Laptops are just strange novel xBoxes (Was: AI dooms day escape: Güttinger Wald) Mild Shock <janburse@fastmail.fm> - 2026-07-08 20:44 +0200
        Re: AI Laptops are just strange novel xBoxes (Was: AI dooms day escape: Güttinger Wald) "Chris M. Thomasson" <chris.m.thomasson.1@gmail.com> - 2026-07-08 15:22 -0700
          TDR solutions --> work slicing (Was: AI Laptops are just strange novel xBoxes) Mild Shock <janburse@fastmail.fm> - 2026-07-09 09:47 +0200
            Thinking of Chris M. Thomasson: From shadertoys to computetoys? (Re: TDR solutions --> work slicing) Mild Shock <janburse@fastmail.fm> - 2026-07-09 09:52 +0200
      FYI: Unified Memory Architecture (UMA) (Re: Implementing Gas for a Compute Shader [Avoid TDR]) Mild Shock <janburse@fastmail.fm> - 2026-07-09 19:43 +0200
        The Wider von Neumann Neck (Re: FYI: Unified Memory Architecture (UMA)) Mild Shock <janburse@fastmail.fm> - 2026-07-10 07:51 +0200
          The new MIMD Warp is the cherry on top (Re: The Wider von Neumann Neck) Mild Shock <janburse@fastmail.fm> - 2026-07-10 08:08 +0200
          Dumbwit, just run it on your RTX 5070 trash (Re: The Wider von Neumann Neck) Mild Shock <janburse@fastmail.fm> - 2026-07-10 15:49 +0200
            We are still waiting for results! [Confused Dumbwit] (Re: We are waiting Dumbwit: 1 Month, 3 Months, .. [node.js dawn]) Mild Shock <janburse@fastmail.fm> - 2026-07-10 22:45 +0200
              404 Brain not Found [GPU saturation] (Re: We are still waiting for results! [Confused Dumbwit]) Mild Shock <janburse@fastmail.fm> - 2026-07-10 23:40 +0200
                I nowhere talked about 10GB/s (Re: 404 Brain not Found [GPU saturation]) Mild Shock <janburse@fastmail.fm> - 2026-07-10 23:41 +0200
                  I nowhere said something about AI (Re: I nowhere talked about 10GB/s) Mild Shock <janburse@fastmail.fm> - 2026-07-10 23:52 +0200
                    What do you not understand in "budget"? (Re: I nowhere said something about AI) Mild Shock <janburse@fastmail.fm> - 2026-07-11 00:08 +0200
                      SWI makes only MLips not GLips (Re: What do you not understand in "budget"?) Mild Shock <janburse@fastmail.fm> - 2026-07-11 00:09 +0200
                        micro penis got hurt by "budget" (Re: SWI makes only MLips not GLips) Mild Shock <janburse@fastmail.fm> - 2026-07-12 19:20 +0200
    Micro Penis Nemesis: Shoe String Budget π-WAM (Was: Paul Tarau versus Mr. Taskmanager, who would win?) Mild Shock <janburse@fastmail.fm> - 2026-07-12 19:26 +0200
      micro penis struggels with mobile grade GPU concept [Redmi Note 14 Pro+ Results] (Re: Micro Penis Nemesis: Shoe String Budget π-WAM) Mild Shock <janburse@fastmail.fm> - 2026-07-12 21:32 +0200
        Micro Penis Existential Crisis: DeepSeek on a Mobile GPU (Re: micro penis struggels with mobile grade GPU concept [Redmi Note 14 Pro+ Results]) Mild Shock <janburse@fastmail.fm> - 2026-07-12 21:47 +0200
          Micro Penis is worse than Sleepy Joe (Re: Micro Penis Existential Crisis: DeepSeek on a Mobile GPU) Mild Shock <janburse@fastmail.fm> - 2026-07-12 23:00 +0200
            Maybe change your pampers? (Was: Micro Penis is worse than Sleepy Joe) Mild Shock <janburse@fastmail.fm> - 2026-07-12 23:01 +0200
              herpes blister rossy boy is confused (Re: Maybe change your pampers?) Mild Shock <janburse@fastmail.fm> - 2026-07-13 06:54 +0200
                nothing gets blocked except your brain [LPDDR5X-RAM] (Re: herpes blister rossy boy is confused) Mild Shock <janburse@fastmail.fm> - 2026-07-13 13:21 +0200
                  flogging a dead horse PCI VRAM graphic cards (Re: nothing gets blocked except your brain [LPDDR5X-RAM]) Mild Shock <janburse@fastmail.fm> - 2026-07-13 13:52 +0200

Page 1 of 2  [1] 2  Next page →

#345657 — Paul Tarau versus Mr. Taskmanager, who would win? [A PDP-11 Humunkulus from 1979]

Hi,

Ok I was looking at this learning challenge,
producing vector (y1,y2,y3,y4) from a vector
(x1,x2,x3,x4), System R can do it via least square?

| 0 0 0 1 |   | x1 |     | x4 |
| 0 0 1 0 |   | x2 |  =  | x3 |
| 0 1 0 0 |   | x3 |     | x2 |
| 1 0 0 0 |   | x4 |     | x1 |

How it started:

"multiplicative RNNs arises naturally from a
proof-theoretic interpretation of next-token
prediction as nested intuitionistic implication"
Paul Tarau - 2026
https://arxiv.org/abs/2601.19915

How its going:

"Dave uses a PDP-11 to train a real Neural
Network complete with Transformers and
Attention so you can see them at their most basic."
Mr. Taskmanager - 2026
https://www.youtube.com/watch?v=OUE3FSIk46g

We see Doctor Frankstein in action from
the Bronze Age of Computing, producing
a Humunkulus, the progenitor of todays

Bulgakov Shuriks in the Hyperscale Age!

Bye

P.S.: My impression neither cut to the core, that
this incredible transformer most likely
produced this deterministic attention:

| -1 | * | k | + | 5 | = | k' |

Or differently expressed y_k = x_{5-k}.

How did the transformer do it? It produced
a neural network with 1216 parameters, but
didn't use embeddings or polar encoding

of positions. But if we strip the noise
and denoise from the position encoding,
the denoise is done via softmax. We somehow

must get the above, right? I still need to
verify my claim! BTW: The PDP-11 assembly
from 1979 uses wider example not with n=4

but with n=8.

[toc] | [next] | [standalone]

#345678 — AI dooms day escape: Güttinger Wald (Re: Paul Tarau versus Mr. Taskmanager, who would win?)

Hi,

You just escaped AI dooms day. Humanity has
reset all internet and computers as a last resort
to prevent AGI developing, by an electromagnetic

pulse. You are stuck in Güttinger Wald and hunted
down a deer by your bare hands, the deer still
confused and tame because tourists were feeding it.

Now you have no knife, what do you do:

Chimpanzees Have Entered The Stone Age
https://www.youtube.com/watch?v=wPXX2I_uYjc

So we are just apes with internet.

Bye

Mild Shock schrieb:
> Hi,
> 
> Ok I was looking at this learning challenge,
> producing vector (y1,y2,y3,y4) from a vector
> (x1,x2,x3,x4), System R can do it via least square?
> 
> | 0 0 0 1 |   | x1 |     | x4 |
> | 0 0 1 0 |   | x2 |  =  | x3 |
> | 0 1 0 0 |   | x3 |     | x2 |
> | 1 0 0 0 |   | x4 |     | x1 |
> 
> How it started:
> 
> "multiplicative RNNs arises naturally from a
> proof-theoretic interpretation of next-token
> prediction as nested intuitionistic implication"
> Paul Tarau - 2026
> https://arxiv.org/abs/2601.19915
> 
> How its going:
> 
> "Dave uses a PDP-11 to train a real Neural
> Network complete with Transformers and
> Attention so you can see them at their most basic."
> Mr. Taskmanager - 2026
> https://www.youtube.com/watch?v=OUE3FSIk46g
> 
> We see Doctor Frankstein in action from
> the Bronze Age of Computing, producing
> a Humunkulus, the progenitor of todays
> 
> Bulgakov Shuriks in the Hyperscale Age!
> 
> Bye
> 
> P.S.: My impression neither cut to the core, that
> this incredible transformer most likely
> produced this deterministic attention:
> 
> | -1 | * | k | + | 5 | = | k' |
> 
> Or differently expressed y_k = x_{5-k}.
> 
> How did the transformer do it? It produced
> a neural network with 1216 parameters, but
> didn't use embeddings or polar encoding
> 
> of positions. But if we strip the noise
> and denoise from the position encoding,
> the denoise is done via softmax. We somehow
> 
> must get the above, right? I still need to
> verify my claim! BTW: The PDP-11 assembly
> from 1979 uses wider example not with n=4
> 
> but with n=8.

[toc] | [prev] | [next] | [standalone]

#345869 — Elmos Fascist Dreams of a 365 Prolog (Was: AI dooms day escape: Güttinger Wald)

Hi,

Lets get emotional! While Varoufakis painted
the picture of cloud capital. That might have
mobilized "The Internationale", or another

more defensive less motolotov throwing song:

Pink Floyd - Run Like Hell (Live)
https://www.youtube.com/watch?v=lKgOe1Rl8YY

Now since Athropic is teaming with xAI, we
might ask do we see the next OneDrive of Prolog
on the horizon. Even a tame Erlang dream:

populate the Web with clever Prolog agents!
https://trinity.elfenbenstornet.se/

Might have a nasty Prolog as SaaS aspect!
As long as we talk about services and not
assets, we might miss something. Who owns

the present and future LLMs/LRMs?

Bye

Mild Shock schrieb:
> Hi,
> 
> You just escaped AI dooms day. Humanity has
> reset all internet and computers as a last resort
> to prevent AGI developing, by an electromagnetic
> 
> pulse. You are stuck in Güttinger Wald and hunted
> down a deer by your bare hands, the deer still
> confused and tame because tourists were feeding it.
> 
> Now you have no knife, what do you do:
> 
> Chimpanzees Have Entered The Stone Age
> https://www.youtube.com/watch?v=wPXX2I_uYjc
> 
> So we are just apes with internet.
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Ok I was looking at this learning challenge,
>> producing vector (y1,y2,y3,y4) from a vector
>> (x1,x2,x3,x4), System R can do it via least square?
>>
>> | 0 0 0 1 |   | x1 |     | x4 |
>> | 0 0 1 0 |   | x2 |  =  | x3 |
>> | 0 1 0 0 |   | x3 |     | x2 |
>> | 1 0 0 0 |   | x4 |     | x1 |
>>
>> How it started:
>>
>> "multiplicative RNNs arises naturally from a
>> proof-theoretic interpretation of next-token
>> prediction as nested intuitionistic implication"
>> Paul Tarau - 2026
>> https://arxiv.org/abs/2601.19915
>>
>> How its going:
>>
>> "Dave uses a PDP-11 to train a real Neural
>> Network complete with Transformers and
>> Attention so you can see them at their most basic."
>> Mr. Taskmanager - 2026
>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>
>> We see Doctor Frankstein in action from
>> the Bronze Age of Computing, producing
>> a Humunkulus, the progenitor of todays
>>
>> Bulgakov Shuriks in the Hyperscale Age!
>>
>> Bye
>>
>> P.S.: My impression neither cut to the core, that
>> this incredible transformer most likely
>> produced this deterministic attention:
>>
>> | -1 | * | k | + | 5 | = | k' |
>>
>> Or differently expressed y_k = x_{5-k}.
>>
>> How did the transformer do it? It produced
>> a neural network with 1216 parameters, but
>> didn't use embeddings or polar encoding
>>
>> of positions. But if we strip the noise
>> and denoise from the position encoding,
>> the denoise is done via softmax. We somehow
>>
>> must get the above, right? I still need to
>> verify my claim! BTW: The PDP-11 assembly
>> from 1979 uses wider example not with n=4
>>
>> but with n=8.
> 

[toc] | [prev] | [next] | [standalone]

#345871 — Even the Buddos are clueless [Did Tarau see Liliputians?] (Re: Elmos Fascist Dreams of a 365 Prolog)

Hi,

Even the Buddos are cluless, while Tarau might
indeed appear in the anals of the Borg, as a
notable human being, seeing connections.

While the Buddos are the man mountains of
Janathan Swists Gulliver's Travel, creating
huge egg montains, replaying some rewriting

school inventions. They might nevertheless be
strapped down by Liliputians:

Gulliver captzured by the Liliputians
https://www.lookandlearn.com/history-images/M301092/Scene-from-Gullivers-Travels

But who are these Liliputians? Well just
toying around with a deep seek v4 derivate in
LM Studio, a model that came out 9 days ago.

Etc.. etc.. it shows more text, all generated
on a laptop that was even only $1000 since
end of year 2025, there were some discounts.

The laptop has the Windows Copilot+ specs.
The secrete sauce? Some general matrix
multiplications (GEMM) tucked in your iGPU:

What is Xe Matrix eXtensions (XMX)?
https://www.intel.com/content/www/us/en/support/articles/000091112/graphics.html

Bye

Mild Shock schrieb:
> Hi,
> 
> Lets get emotional! While Varoufakis painted
> the picture of cloud capital. That might have
> mobilized "The Internationale", or another
> 
> more defensive less motolotov throwing song:
> 
> Pink Floyd - Run Like Hell (Live)
> https://www.youtube.com/watch?v=lKgOe1Rl8YY
> 
> Now since Athropic is teaming with xAI, we
> might ask do we see the next OneDrive of Prolog
> on the horizon. Even a tame Erlang dream:
> 
> populate the Web with clever Prolog agents!
> https://trinity.elfenbenstornet.se/
> 
> Might have a nasty Prolog as SaaS aspect!
> As long as we talk about services and not
> assets, we might miss something. Who owns
> 
> the present and future LLMs/LRMs?
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> You just escaped AI dooms day. Humanity has
>> reset all internet and computers as a last resort
>> to prevent AGI developing, by an electromagnetic
>>
>> pulse. You are stuck in Güttinger Wald and hunted
>> down a deer by your bare hands, the deer still
>> confused and tame because tourists were feeding it.
>>
>> Now you have no knife, what do you do:
>>
>> Chimpanzees Have Entered The Stone Age
>> https://www.youtube.com/watch?v=wPXX2I_uYjc
>>
>> So we are just apes with internet.
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> Ok I was looking at this learning challenge,
>>> producing vector (y1,y2,y3,y4) from a vector
>>> (x1,x2,x3,x4), System R can do it via least square?
>>>
>>> | 0 0 0 1 |   | x1 |     | x4 |
>>> | 0 0 1 0 |   | x2 |  =  | x3 |
>>> | 0 1 0 0 |   | x3 |     | x2 |
>>> | 1 0 0 0 |   | x4 |     | x1 |
>>>
>>> How it started:
>>>
>>> "multiplicative RNNs arises naturally from a
>>> proof-theoretic interpretation of next-token
>>> prediction as nested intuitionistic implication"
>>> Paul Tarau - 2026
>>> https://arxiv.org/abs/2601.19915
>>>
>>> How its going:
>>>
>>> "Dave uses a PDP-11 to train a real Neural
>>> Network complete with Transformers and
>>> Attention so you can see them at their most basic."
>>> Mr. Taskmanager - 2026
>>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>>
>>> We see Doctor Frankstein in action from
>>> the Bronze Age of Computing, producing
>>> a Humunkulus, the progenitor of todays
>>>
>>> Bulgakov Shuriks in the Hyperscale Age!
>>>
>>> Bye
>>>
>>> P.S.: My impression neither cut to the core, that
>>> this incredible transformer most likely
>>> produced this deterministic attention:
>>>
>>> | -1 | * | k | + | 5 | = | k' |
>>>
>>> Or differently expressed y_k = x_{5-k}.
>>>
>>> How did the transformer do it? It produced
>>> a neural network with 1216 parameters, but
>>> didn't use embeddings or polar encoding
>>>
>>> of positions. But if we strip the noise
>>> and denoise from the position encoding,
>>> the denoise is done via softmax. We somehow
>>>
>>> must get the above, right? I still need to
>>> verify my claim! BTW: The PDP-11 assembly
>>> from 1979 uses wider example not with n=4
>>>
>>> but with n=8.
>>
> 

[toc] | [prev] | [next] | [standalone]

#345874 — Halfing the AI Laptop Budget: Ne-Meow sold out! (Re: Even the Buddos are clueless [Did Tarau see Liliputians?])

Hi,

Interesting, the Copilot+ minimal
requirement is 40 TOPS. Now Wiki is
mumbling something of 35 TOPS + 15%,

for the new A18 chip, that is found
in iPhones and the new Mac Neo. The
new Mac Neo is only $500 , half of

my discount AI laptop, and is selling
like hotcakes. I should try it, see
what AI workloads it can do locally.

Bye

P.S.: The Mac Neo is jokingly called
Ne-Meow in this hands on video by Bijan
Bowen, showing some vibe web coding:

MacBook Neo Local AI Test
https://www.youtube.com/watch?v=75PFpW9SOL0

Mild Shock schrieb:
> Hi,
> 
> Even the Buddos are cluless, while Tarau might
> indeed appear in the anals of the Borg, as a
> notable human being, seeing connections.
> 
> While the Buddos are the man mountains of
> Janathan Swists Gulliver's Travel, creating
> huge egg montains, replaying some rewriting
> 
> school inventions. They might nevertheless be
> strapped down by Liliputians:
> 
> Gulliver captzured by the Liliputians
> https://www.lookandlearn.com/history-images/M301092/Scene-from-Gullivers-Travels 
> 
> 
> But who are these Liliputians? Well just
> toying around with a deep seek v4 derivate in
> LM Studio, a model that came out 9 days ago.
> 
> Etc.. etc.. it shows more text, all generated
> on a laptop that was even only $1000 since
> end of year 2025, there were some discounts.
> 
> The laptop has the Windows Copilot+ specs.
> The secrete sauce? Some general matrix
> multiplications (GEMM) tucked in your iGPU:
> 
> What is Xe Matrix eXtensions (XMX)?
> https://www.intel.com/content/www/us/en/support/articles/000091112/graphics.html 
> 
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Lets get emotional! While Varoufakis painted
>> the picture of cloud capital. That might have
>> mobilized "The Internationale", or another
>>
>> more defensive less motolotov throwing song:
>>
>> Pink Floyd - Run Like Hell (Live)
>> https://www.youtube.com/watch?v=lKgOe1Rl8YY
>>
>> Now since Athropic is teaming with xAI, we
>> might ask do we see the next OneDrive of Prolog
>> on the horizon. Even a tame Erlang dream:
>>
>> populate the Web with clever Prolog agents!
>> https://trinity.elfenbenstornet.se/
>>
>> Might have a nasty Prolog as SaaS aspect!
>> As long as we talk about services and not
>> assets, we might miss something. Who owns
>>
>> the present and future LLMs/LRMs?
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> You just escaped AI dooms day. Humanity has
>>> reset all internet and computers as a last resort
>>> to prevent AGI developing, by an electromagnetic
>>>
>>> pulse. You are stuck in Güttinger Wald and hunted
>>> down a deer by your bare hands, the deer still
>>> confused and tame because tourists were feeding it.
>>>
>>> Now you have no knife, what do you do:
>>>
>>> Chimpanzees Have Entered The Stone Age
>>> https://www.youtube.com/watch?v=wPXX2I_uYjc
>>>
>>> So we are just apes with internet.
>>>
>>> Bye
>>>
>>> Mild Shock schrieb:
>>>> Hi,
>>>>
>>>> Ok I was looking at this learning challenge,
>>>> producing vector (y1,y2,y3,y4) from a vector
>>>> (x1,x2,x3,x4), System R can do it via least square?
>>>>
>>>> | 0 0 0 1 |   | x1 |     | x4 |
>>>> | 0 0 1 0 |   | x2 |  =  | x3 |
>>>> | 0 1 0 0 |   | x3 |     | x2 |
>>>> | 1 0 0 0 |   | x4 |     | x1 |
>>>>
>>>> How it started:
>>>>
>>>> "multiplicative RNNs arises naturally from a
>>>> proof-theoretic interpretation of next-token
>>>> prediction as nested intuitionistic implication"
>>>> Paul Tarau - 2026
>>>> https://arxiv.org/abs/2601.19915
>>>>
>>>> How its going:
>>>>
>>>> "Dave uses a PDP-11 to train a real Neural
>>>> Network complete with Transformers and
>>>> Attention so you can see them at their most basic."
>>>> Mr. Taskmanager - 2026
>>>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>>>
>>>> We see Doctor Frankstein in action from
>>>> the Bronze Age of Computing, producing
>>>> a Humunkulus, the progenitor of todays
>>>>
>>>> Bulgakov Shuriks in the Hyperscale Age!
>>>>
>>>> Bye
>>>>
>>>> P.S.: My impression neither cut to the core, that
>>>> this incredible transformer most likely
>>>> produced this deterministic attention:
>>>>
>>>> | -1 | * | k | + | 5 | = | k' |
>>>>
>>>> Or differently expressed y_k = x_{5-k}.
>>>>
>>>> How did the transformer do it? It produced
>>>> a neural network with 1216 parameters, but
>>>> didn't use embeddings or polar encoding
>>>>
>>>> of positions. But if we strip the noise
>>>> and denoise from the position encoding,
>>>> the denoise is done via softmax. We somehow
>>>>
>>>> must get the above, right? I still need to
>>>> verify my claim! BTW: The PDP-11 assembly
>>>> from 1979 uses wider example not with n=4
>>>>
>>>> but with n=8.
>>>
>>
> 

[toc] | [prev] | [next] | [standalone]

#346751 — Prolog Expert Ginis (PEGs) on a Keychain (Re: AI dooms day escape: Güttinger Wald)

Hi,

NVIDIA has just release RTX 3080 Mini.
Only the size of space bar, it easily
fits into a keyboard:

Nvidia RTX 3080 Mini! The Future of GPUs!
https://www.instagram.com/p/C3gbuA8P0eE/

The association of logic programming has
coorperated with Morbid AI Inc. and used
a local GPT builder to bring Prolog

Expert Ginis on a keychain. You can now
easily carry around in your pocket:

Mini Hakan: Ask it anything about
constraint programming, contains the
wealth of CLP examples written in
different CLP dialect.

Mini Paul: Ask it anything about Jini
Prolog VMs. The complete hitchhiker guide
to engineering fabulous sequential
Prolog engines.

Mini Jan: Ask it anything about XPCE
and SWI. More than a manual , rather
a language monument. Fancy easter egg,
contains a complete GUI tracer.

Stay tuned, more to come...

Bye

Mild Shock schrieb:
> Hi,
> 
> You just escaped AI dooms day. Humanity has
> reset all internet and computers as a last resort
> to prevent AGI developing, by an electromagnetic
> 
> pulse. You are stuck in Güttinger Wald and hunted
> down a deer by your bare hands, the deer still
> confused and tame because tourists were feeding it.
> 
> Now you have no knife, what do you do:
> 
> Chimpanzees Have Entered The Stone Age
> https://www.youtube.com/watch?v=wPXX2I_uYjc
> 
> So we are just apes with internet.
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Ok I was looking at this learning challenge,
>> producing vector (y1,y2,y3,y4) from a vector
>> (x1,x2,x3,x4), System R can do it via least square?
>>
>> | 0 0 0 1 |   | x1 |     | x4 |
>> | 0 0 1 0 |   | x2 |  =  | x3 |
>> | 0 1 0 0 |   | x3 |     | x2 |
>> | 1 0 0 0 |   | x4 |     | x1 |
>>
>> How it started:
>>
>> "multiplicative RNNs arises naturally from a
>> proof-theoretic interpretation of next-token
>> prediction as nested intuitionistic implication"
>> Paul Tarau - 2026
>> https://arxiv.org/abs/2601.19915
>>
>> How its going:
>>
>> "Dave uses a PDP-11 to train a real Neural
>> Network complete with Transformers and
>> Attention so you can see them at their most basic."
>> Mr. Taskmanager - 2026
>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>
>> We see Doctor Frankstein in action from
>> the Bronze Age of Computing, producing
>> a Humunkulus, the progenitor of todays
>>
>> Bulgakov Shuriks in the Hyperscale Age!
>>
>> Bye
>>
>> P.S.: My impression neither cut to the core, that
>> this incredible transformer most likely
>> produced this deterministic attention:
>>
>> | -1 | * | k | + | 5 | = | k' |
>>
>> Or differently expressed y_k = x_{5-k}.
>>
>> How did the transformer do it? It produced
>> a neural network with 1216 parameters, but
>> didn't use embeddings or polar encoding
>>
>> of positions. But if we strip the noise
>> and denoise from the position encoding,
>> the denoise is done via softmax. We somehow
>>
>> must get the above, right? I still need to
>> verify my claim! BTW: The PDP-11 assembly
>> from 1979 uses wider example not with n=4
>>
>> but with n=8.
> 

[toc] | [prev] | [next] | [standalone]

#346806 — Chatbot Classified as a Weapon (Re: Prolog Expert Ginis (PEGs) on a Keychain)

Hi,

Statement on the US government
https://www.anthropic.com/news/fable-mythos-access

The Government Classified a Chatbot as a Weapon
https://www.youtube.com/watch?v=0RxMj0L0-fY

Ha Ha, AI leaders learning that they are
treated as Yuri Orlov, since their models
now do easily recursive self improvement?

But look at the bright size, you don't
need HK staff, which are also a security
risk, if your models are self-improving

anyways. But hey who cares, China has
already countered with Z.ai from Zhipu,
announcing as well at 5:21 pm, that

they will make it open source.

Bye

P.S.: BTW, anybody already using WPS
Office? It has a Copilot, is this
terrifying Microsoft?

Mild Shock schrieb:
> Hi,
> 
> NVIDIA has just release RTX 3080 Mini.
> Only the size of space bar, it easily
> fits into a keyboard:
> 
> Nvidia RTX 3080 Mini! The Future of GPUs!
> https://www.instagram.com/p/C3gbuA8P0eE/
> 
> The association of logic programming has
> coorperated with Morbid AI Inc. and used
> a local GPT builder to bring Prolog
> 
> Expert Ginis on a keychain. You can now
> easily carry around in your pocket:
> 
> Mini Hakan: Ask it anything about
> constraint programming, contains the
> wealth of CLP examples written in
> different CLP dialect.
> 
> Mini Paul: Ask it anything about Jini
> Prolog VMs. The complete hitchhiker guide
> to engineering fabulous sequential
> Prolog engines.
> 
> Mini Jan: Ask it anything about XPCE
> and SWI. More than a manual , rather
> a language monument. Fancy easter egg,
> contains a complete GUI tracer.
> 
> Stay tuned, more to come...
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> You just escaped AI dooms day. Humanity has
>> reset all internet and computers as a last resort
>> to prevent AGI developing, by an electromagnetic
>>
>> pulse. You are stuck in Güttinger Wald and hunted
>> down a deer by your bare hands, the deer still
>> confused and tame because tourists were feeding it.
>>
>> Now you have no knife, what do you do:
>>
>> Chimpanzees Have Entered The Stone Age
>> https://www.youtube.com/watch?v=wPXX2I_uYjc
>>
>> So we are just apes with internet.
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> Ok I was looking at this learning challenge,
>>> producing vector (y1,y2,y3,y4) from a vector
>>> (x1,x2,x3,x4), System R can do it via least square?
>>>
>>> | 0 0 0 1 |   | x1 |     | x4 |
>>> | 0 0 1 0 |   | x2 |  =  | x3 |
>>> | 0 1 0 0 |   | x3 |     | x2 |
>>> | 1 0 0 0 |   | x4 |     | x1 |
>>>
>>> How it started:
>>>
>>> "multiplicative RNNs arises naturally from a
>>> proof-theoretic interpretation of next-token
>>> prediction as nested intuitionistic implication"
>>> Paul Tarau - 2026
>>> https://arxiv.org/abs/2601.19915
>>>
>>> How its going:
>>>
>>> "Dave uses a PDP-11 to train a real Neural
>>> Network complete with Transformers and
>>> Attention so you can see them at their most basic."
>>> Mr. Taskmanager - 2026
>>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>>
>>> We see Doctor Frankstein in action from
>>> the Bronze Age of Computing, producing
>>> a Humunkulus, the progenitor of todays
>>>
>>> Bulgakov Shuriks in the Hyperscale Age!
>>>
>>> Bye
>>>
>>> P.S.: My impression neither cut to the core, that
>>> this incredible transformer most likely
>>> produced this deterministic attention:
>>>
>>> | -1 | * | k | + | 5 | = | k' |
>>>
>>> Or differently expressed y_k = x_{5-k}.
>>>
>>> How did the transformer do it? It produced
>>> a neural network with 1216 parameters, but
>>> didn't use embeddings or polar encoding
>>>
>>> of positions. But if we strip the noise
>>> and denoise from the position encoding,
>>> the denoise is done via softmax. We somehow
>>>
>>> must get the above, right? I still need to
>>> verify my claim! BTW: The PDP-11 assembly
>>> from 1979 uses wider example not with n=4
>>>
>>> but with n=8.
>>
> 

[toc] | [prev] | [next] | [standalone]

#348118 — Introduction to AI Accelerator Prolog [π-WAM of Dogelog] (Re: Prolog Expert Ginis (PEGs) on a Keychain)

Hi,

Maybe I should write a blog post, titled
Introduction to AI Accelerator Prolog:

- specialized jobs π-WAM (currently integerish stuff)
- π-WAM uses no atomics, only comms
- π-WAM uses warp, 30-40% more speed
- π-WAM runs on GPU and CPU
- π-WAM runs from within JavaScript, Python and Java

Feels like reinventing FGCS concurrent
logic programming.

LoL

Bye

Mild Shock schrieb:
> Hi,
> 
> NVIDIA has just release RTX 3080 Mini.
> Only the size of space bar, it easily
> fits into a keyboard:
> 
> Nvidia RTX 3080 Mini! The Future of GPUs!
> https://www.instagram.com/p/C3gbuA8P0eE/
> 
> The association of logic programming has
> coorperated with Morbid AI Inc. and used
> a local GPT builder to bring Prolog
> 
> Expert Ginis on a keychain. You can now
> easily carry around in your pocket:
> 
> Mini Hakan: Ask it anything about
> constraint programming, contains the
> wealth of CLP examples written in
> different CLP dialect.
> 
> Mini Paul: Ask it anything about Jini
> Prolog VMs. The complete hitchhiker guide
> to engineering fabulous sequential
> Prolog engines.
> 
> Mini Jan: Ask it anything about XPCE
> and SWI. More than a manual , rather
> a language monument. Fancy easter egg,
> contains a complete GUI tracer.
> 
> Stay tuned, more to come...
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> You just escaped AI dooms day. Humanity has
>> reset all internet and computers as a last resort
>> to prevent AGI developing, by an electromagnetic
>>
>> pulse. You are stuck in Güttinger Wald and hunted
>> down a deer by your bare hands, the deer still
>> confused and tame because tourists were feeding it.
>>
>> Now you have no knife, what do you do:
>>
>> Chimpanzees Have Entered The Stone Age
>> https://www.youtube.com/watch?v=wPXX2I_uYjc
>>
>> So we are just apes with internet.
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> Ok I was looking at this learning challenge,
>>> producing vector (y1,y2,y3,y4) from a vector
>>> (x1,x2,x3,x4), System R can do it via least square?
>>>
>>> | 0 0 0 1 |   | x1 |     | x4 |
>>> | 0 0 1 0 |   | x2 |  =  | x3 |
>>> | 0 1 0 0 |   | x3 |     | x2 |
>>> | 1 0 0 0 |   | x4 |     | x1 |
>>>
>>> How it started:
>>>
>>> "multiplicative RNNs arises naturally from a
>>> proof-theoretic interpretation of next-token
>>> prediction as nested intuitionistic implication"
>>> Paul Tarau - 2026
>>> https://arxiv.org/abs/2601.19915
>>>
>>> How its going:
>>>
>>> "Dave uses a PDP-11 to train a real Neural
>>> Network complete with Transformers and
>>> Attention so you can see them at their most basic."
>>> Mr. Taskmanager - 2026
>>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>>
>>> We see Doctor Frankstein in action from
>>> the Bronze Age of Computing, producing
>>> a Humunkulus, the progenitor of todays
>>>
>>> Bulgakov Shuriks in the Hyperscale Age!
>>>
>>> Bye
>>>
>>> P.S.: My impression neither cut to the core, that
>>> this incredible transformer most likely
>>> produced this deterministic attention:
>>>
>>> | -1 | * | k | + | 5 | = | k' |
>>>
>>> Or differently expressed y_k = x_{5-k}.
>>>
>>> How did the transformer do it? It produced
>>> a neural network with 1216 parameters, but
>>> didn't use embeddings or polar encoding
>>>
>>> of positions. But if we strip the noise
>>> and denoise from the position encoding,
>>> the denoise is done via softmax. We somehow
>>>
>>> must get the above, right? I still need to
>>> verify my claim! BTW: The PDP-11 assembly
>>> from 1979 uses wider example not with n=4
>>>
>>> but with n=8.
>>
> 

[toc] | [prev] | [next] | [standalone]

#348119 — Not praying to the god of lambda calculus [π beats α] (Re: Introduction to AI Accelerator Prolog [π-WAM of Dogelog])

Hi,

Somebody tasked the logic programming community
to make an α-Prolog, i.e. have some alpha
conversion whatever builtin, plus maybe nominal
logic fresh variables whatever.

But who reads such nonsense in 2026:

Lifting E-Graphs: A Function Isn't a Constant
https://arxiv.org/abs/2606.22734

So you see where I am aiming with π-WAM, surely
not α-Prolog . I wouldn't care less about  α-Prolog.
π is more fun than α, and working on WAM is more
fun then creating some silly prototype of a

REPL of a homunkulus of a Prolog. π beats α:

- α = abstract, academic, awkward
- π = parallelism, performance, practical

Bye

Mild Shock schrieb:
> Hi,
> 
> Maybe I should write a blog post, titled
> Introduction to AI Accelerator Prolog:
> 
> - specialized jobs π-WAM (currently integerish stuff)
> - π-WAM uses no atomics, only comms
> - π-WAM uses warp, 30-40% more speed
> - π-WAM runs on GPU and CPU
> - π-WAM runs from within JavaScript, Python and Java
> 
> Feels like reinventing FGCS concurrent
> logic programming.
> 
> LoL
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> NVIDIA has just release RTX 3080 Mini.
>> Only the size of space bar, it easily
>> fits into a keyboard:
>>
>> Nvidia RTX 3080 Mini! The Future of GPUs!
>> https://www.instagram.com/p/C3gbuA8P0eE/
>>
>> The association of logic programming has
>> coorperated with Morbid AI Inc. and used
>> a local GPT builder to bring Prolog
>>
>> Expert Ginis on a keychain. You can now
>> easily carry around in your pocket:
>>
>> Mini Hakan: Ask it anything about
>> constraint programming, contains the
>> wealth of CLP examples written in
>> different CLP dialect.
>>
>> Mini Paul: Ask it anything about Jini
>> Prolog VMs. The complete hitchhiker guide
>> to engineering fabulous sequential
>> Prolog engines.
>>
>> Mini Jan: Ask it anything about XPCE
>> and SWI. More than a manual , rather
>> a language monument. Fancy easter egg,
>> contains a complete GUI tracer.
>>
>> Stay tuned, more to come...
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> You just escaped AI dooms day. Humanity has
>>> reset all internet and computers as a last resort
>>> to prevent AGI developing, by an electromagnetic
>>>
>>> pulse. You are stuck in Güttinger Wald and hunted
>>> down a deer by your bare hands, the deer still
>>> confused and tame because tourists were feeding it.
>>>
>>> Now you have no knife, what do you do:
>>>
>>> Chimpanzees Have Entered The Stone Age
>>> https://www.youtube.com/watch?v=wPXX2I_uYjc
>>>
>>> So we are just apes with internet.
>>>
>>> Bye
>>>
>>> Mild Shock schrieb:
>>>> Hi,
>>>>
>>>> Ok I was looking at this learning challenge,
>>>> producing vector (y1,y2,y3,y4) from a vector
>>>> (x1,x2,x3,x4), System R can do it via least square?
>>>>
>>>> | 0 0 0 1 |   | x1 |     | x4 |
>>>> | 0 0 1 0 |   | x2 |  =  | x3 |
>>>> | 0 1 0 0 |   | x3 |     | x2 |
>>>> | 1 0 0 0 |   | x4 |     | x1 |
>>>>
>>>> How it started:
>>>>
>>>> "multiplicative RNNs arises naturally from a
>>>> proof-theoretic interpretation of next-token
>>>> prediction as nested intuitionistic implication"
>>>> Paul Tarau - 2026
>>>> https://arxiv.org/abs/2601.19915
>>>>
>>>> How its going:
>>>>
>>>> "Dave uses a PDP-11 to train a real Neural
>>>> Network complete with Transformers and
>>>> Attention so you can see them at their most basic."
>>>> Mr. Taskmanager - 2026
>>>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>>>
>>>> We see Doctor Frankstein in action from
>>>> the Bronze Age of Computing, producing
>>>> a Humunkulus, the progenitor of todays
>>>>
>>>> Bulgakov Shuriks in the Hyperscale Age!
>>>>
>>>> Bye
>>>>
>>>> P.S.: My impression neither cut to the core, that
>>>> this incredible transformer most likely
>>>> produced this deterministic attention:
>>>>
>>>> | -1 | * | k | + | 5 | = | k' |
>>>>
>>>> Or differently expressed y_k = x_{5-k}.
>>>>
>>>> How did the transformer do it? It produced
>>>> a neural network with 1216 parameters, but
>>>> didn't use embeddings or polar encoding
>>>>
>>>> of positions. But if we strip the noise
>>>> and denoise from the position encoding,
>>>> the denoise is done via softmax. We somehow
>>>>
>>>> must get the above, right? I still need to
>>>> verify my claim! BTW: The PDP-11 assembly
>>>> from 1979 uses wider example not with n=4
>>>>
>>>> but with n=8.
>>>
>>
> 

[toc] | [prev] | [next] | [standalone]

#348122 — Re: Introduction to AI Accelerator Prolog [π-WAM of Dogelog] (Re: Prolog Expert Ginis (PEGs) on a Keychain)

On 7/17/2026 2:16 AM, Mild Shock wrote:
> Hi,
> 
> Maybe I should write a blog post, titled
> Introduction to AI Accelerator Prolog:
> 
> - specialized jobs π-WAM (currently integerish stuff)
> - π-WAM uses no atomics, only comms
> - π-WAM uses warp, 30-40% more speed
> - π-WAM runs on GPU and CPU
> - π-WAM runs from within JavaScript, Python and Java

[...]

No atomic fetch-and-add?

[toc] | [prev] | [next] | [standalone]

#348123 — pi in pi-WAM refers to pi-calculus (Was: Introduction to AI Accelerator Prolog [π-WAM of Dogelog] )

Hi,

The pi in pi-WAM refers to pi-calculus.
pi-calculus has not atomic(i32).

The π-calculus is a universal model of computation.
This was first observed by Milner in his paper
"Functions as Processes",[10] in which he presents
two encodings of the lambda-calculus in the π-calculus.
https://en.wikipedia.org/wiki/%CE%A0-calculus

LoL

Bye

Chris M. Thomasson schrieb:
> On 7/17/2026 2:16 AM, Mild Shock wrote:
>> Hi,
>>
>> Maybe I should write a blog post, titled
>> Introduction to AI Accelerator Prolog:
>>
>> - specialized jobs π-WAM (currently integerish stuff)
>> - π-WAM uses no atomics, only comms
>> - π-WAM uses warp, 30-40% more speed
>> - π-WAM runs on GPU and CPU
>> - π-WAM runs from within JavaScript, Python and Java
> 
> [...]
> 
> No atomic fetch-and-add?

[toc] | [prev] | [next] | [standalone]

#348124 — Milners fickle() in pi-WAM [For fun and profit] (Re: pi in pi-WAM refers to pi-calculus)

Hi,

Milners fickle() is here:

Functions as processes
https://inria.hal.science/inria-00075405

After Theorem 7.7:

So in P we construct a fickle ‘function’ which
behaves differently on successive calls.

Here is a pi-WAM run in Dogelog Player, using the emulator:

Dogelog Spieler 2.2.4, Oracle Corporation, Java 26.0.1
(c) 1985-2026, XLOG Technologies AG, Schweiz
?- ensure_loaded(library(edge/brainfog)).
true.
?- emulate((between(1,2,Y),in(X),out(Y))).
: 0
1
: 0
2
fail.

The emulator is portable, can be run every Prolog
system. But it is only 1 process. So its better
to use the n process backends for CPU or GPU.

Which are less portable, not anymore pure Prolog,
a great deal of thread start and join infrastructure
as well, and a native Hack VM.

The comms across process is not yet implemented.
But the in/1 and out/1 instructions are already
there. But they currently go to stdin/stdout.

Bye

Mild Shock schrieb:
> Hi,
> 
> The pi in pi-WAM refers to pi-calculus.
> pi-calculus has not atomic(i32).
> 
> The π-calculus is a universal model of computation.
> This was first observed by Milner in his paper
> "Functions as Processes",[10] in which he presents
> two encodings of the lambda-calculus in the π-calculus.
> https://en.wikipedia.org/wiki/%CE%A0-calculus
> 
> LoL
> 
> Bye
> 
> Chris M. Thomasson schrieb:
>> On 7/17/2026 2:16 AM, Mild Shock wrote:
>>> Hi,
>>>
>>> Maybe I should write a blog post, titled
>>> Introduction to AI Accelerator Prolog:
>>>
>>> - specialized jobs π-WAM (currently integerish stuff)
>>> - π-WAM uses no atomics, only comms
>>> - π-WAM uses warp, 30-40% more speed
>>> - π-WAM runs on GPU and CPU
>>> - π-WAM runs from within JavaScript, Python and Java
>>
>> [...]
>>
>> No atomic fetch-and-add?
> 

[toc] | [prev] | [next] | [standalone]

#348125 — Re: Milners fickle() in pi-WAM [For fun and profit] (Re: pi in pi-WAM refers to pi-calculus)

On 07/17/2026 04:50 PM, Mild Shock wrote:
> Hi,
>
> Milners fickle() is here:
>
> Functions as processes
> https://inria.hal.science/inria-00075405
>
> After Theorem 7.7:
>
> So in P we construct a fickle ‘function’ which
> behaves differently on successive calls.
>
> Here is a pi-WAM run in Dogelog Player, using the emulator:
>
> Dogelog Spieler 2.2.4, Oracle Corporation, Java 26.0.1
> (c) 1985-2026, XLOG Technologies AG, Schweiz
> ?- ensure_loaded(library(edge/brainfog)).
> true.
> ?- emulate((between(1,2,Y),in(X),out(Y))).
> : 0
> 1
> : 0
> 2
> fail.
>
> The emulator is portable, can be run every Prolog
> system. But it is only 1 process. So its better
> to use the n process backends for CPU or GPU.
>
> Which are less portable, not anymore pure Prolog,
> a great deal of thread start and join infrastructure
> as well, and a native Hack VM.
>
> The comms across process is not yet implemented.
> But the in/1 and out/1 instructions are already
> there. But they currently go to stdin/stdout.
>
> Bye
>
> Mild Shock schrieb:
>> Hi,
>>
>> The pi in pi-WAM refers to pi-calculus.
>> pi-calculus has not atomic(i32).
>>
>> The π-calculus is a universal model of computation.
>> This was first observed by Milner in his paper
>> "Functions as Processes",[10] in which he presents
>> two encodings of the lambda-calculus in the π-calculus.
>> https://en.wikipedia.org/wiki/%CE%A0-calculus
>>
>> LoL
>>
>> Bye
>>
>> Chris M. Thomasson schrieb:
>>> On 7/17/2026 2:16 AM, Mild Shock wrote:
>>>> Hi,
>>>>
>>>> Maybe I should write a blog post, titled
>>>> Introduction to AI Accelerator Prolog:
>>>>
>>>> - specialized jobs π-WAM (currently integerish stuff)
>>>> - π-WAM uses no atomics, only comms
>>>> - π-WAM uses warp, 30-40% more speed
>>>> - π-WAM runs on GPU and CPU
>>>> - π-WAM runs from within JavaScript, Python and Java
>>>
>>> [...]
>>>
>>> No atomic fetch-and-add?
>>
>

So he partial-computes his alpha to alpha_alpha
in his Futamura projection, yet, that's partial computation,
why not make Minsky counter-machines using the bottom-up
approach of making arithmetizations and DFA's.


Of course the lambda-calculus and pi-calculus are great
things for models of types and communicating sequential processes.

Roberto di Cosmo has a great book on types, and more than one.

https://books.google.com/books/about/Isomorphisms_of_Types.html?id=cdJZRjIxavwC

[toc] | [prev] | [next] | [standalone]

#348126 — Robin Milners pi calculus is typeless (Was: Milners fickle() in pi-WAM [For fun and profit])

Hi,

Mild Shock schrieb:
 > The π-calculus is a universal model of computation.
 > This was first observed by Milner in his paper
 > "Functions as Processes",[10] in which he presents
 > two encodings of the lambda-calculus in the π-calculus.
 > https://en.wikipedia.org/wiki/%CE%A0-calculus

Ross Finlayson schrieb:
 > Of course the lambda-calculus and pi-calculus
 > are great things for models of types and communicating
 > sequential processes.
 >
 > Roberto di Cosmo has a great book on types,
 > and more than one.
 >
 > 
https://books.google.com/books/about/Isomorphisms_of_Types.html?id=cdJZRjIxavwC 


When a 1970s paper claims a relation ship between
pi-calculus and lambda calculus, then both calculi
refer to a typeless calculi.

Types are a later invention. The original lambda
calculus was typeless. Church encodings came later,
but for example the Church Turing hypotheses is

formulated along typeless lambda calculus.

Bye

P.S.: Prolog is also typeless. I do not intend to
add any types to pi-WAM either.

Ross Finlayson schrieb:
> On 07/17/2026 04:50 PM, Mild Shock wrote:
>> Hi,
>>
>> Milners fickle() is here:
>>
>> Functions as processes
>> https://inria.hal.science/inria-00075405
>>
>> After Theorem 7.7:
>>
>> So in P we construct a fickle ‘function’ which
>> behaves differently on successive calls.
>>
>> Here is a pi-WAM run in Dogelog Player, using the emulator:
>>
>> Dogelog Spieler 2.2.4, Oracle Corporation, Java 26.0.1
>> (c) 1985-2026, XLOG Technologies AG, Schweiz
>> ?- ensure_loaded(library(edge/brainfog)).
>> true.
>> ?- emulate((between(1,2,Y),in(X),out(Y))).
>> : 0
>> 1
>> : 0
>> 2
>> fail.
>>
>> The emulator is portable, can be run every Prolog
>> system. But it is only 1 process. So its better
>> to use the n process backends for CPU or GPU.
>>
>> Which are less portable, not anymore pure Prolog,
>> a great deal of thread start and join infrastructure
>> as well, and a native Hack VM.
>>
>> The comms across process is not yet implemented.
>> But the in/1 and out/1 instructions are already
>> there. But they currently go to stdin/stdout.
>>
>> Bye
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> The pi in pi-WAM refers to pi-calculus.
>>> pi-calculus has not atomic(i32).
>>>
>>> The π-calculus is a universal model of computation.
>>> This was first observed by Milner in his paper
>>> "Functions as Processes",[10] in which he presents
>>> two encodings of the lambda-calculus in the π-calculus.
>>> https://en.wikipedia.org/wiki/%CE%A0-calculus
>>>
>>> LoL
>>>
>>> Bye
>>>
>>> Chris M. Thomasson schrieb:
>>>> On 7/17/2026 2:16 AM, Mild Shock wrote:
>>>>> Hi,
>>>>>
>>>>> Maybe I should write a blog post, titled
>>>>> Introduction to AI Accelerator Prolog:
>>>>>
>>>>> - specialized jobs π-WAM (currently integerish stuff)
>>>>> - π-WAM uses no atomics, only comms
>>>>> - π-WAM uses warp, 30-40% more speed
>>>>> - π-WAM runs on GPU and CPU
>>>>> - π-WAM runs from within JavaScript, Python and Java
>>>>
>>>> [...]
>>>>
>>>> No atomic fetch-and-add?
>>>
>>
> 
> So he partial-computes his alpha to alpha_alpha
> in his Futamura projection, yet, that's partial computation,
> why not make Minsky counter-machines using the bottom-up
> approach of making arithmetizations and DFA's.
> 
> 
> Of course the lambda-calculus and pi-calculus are great
> things for models of types and communicating sequential processes.
> 
> Roberto di Cosmo has a great book on types, and more than one.
> 
> https://books.google.com/books/about/Isomorphisms_of_Types.html?id=cdJZRjIxavwC 
> 
> 
> 

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#348127 — Can the Church Turing hypotheses be refuted? [TLo @ FOM] (Was: Robin Milners pi calculus is typeless)

Hi,

Ha Ha, TLo @ FOM schrieb:
 > Lastly--there is the Church-Turing-thesis itself.
 > I cannot imagine what form a proof could have. But at
 > least a refutation is conceivable, if extremely far-fetched.

Can the Church Turing hypotheses be refuted? Well
since it is stricly speaking only a hypothesis and
not a thesis, it cannot be that much refuted,

since it is a kind of exhaustion argument defining
a category by examples. The history goes as follows:

> In 1935–36,[7] Alonzo Church formalized the 
 > concept of effectively calculable functions by proposing
 > that they are general recursive functions, or,
 > equivalently, λ-definable functions.
https://en.wikipedia.org/wiki/Church%E2%80%93Turing_thesis

Does his λ-definable include types? Nope. Do
we need large cardinal axioms? It depends.
Church λ-computable was syntactically defined,

it didn't have a semantic referent. The search
for a semantic referent gave rise to certain
additional problems of set theory and type theory.

Have Fun!

Bye

Mild Shock schrieb:
> Hi,
> 
> Mild Shock schrieb:
>  > The π-calculus is a universal model of computation.
>  > This was first observed by Milner in his paper
>  > "Functions as Processes",[10] in which he presents
>  > two encodings of the lambda-calculus in the π-calculus.
>  > https://en.wikipedia.org/wiki/%CE%A0-calculus
> 
> Ross Finlayson schrieb:
>  > Of course the lambda-calculus and pi-calculus
>  > are great things for models of types and communicating
>  > sequential processes.
>  >
>  > Roberto di Cosmo has a great book on types,
>  > and more than one.
>  >
>  > 
> https://books.google.com/books/about/Isomorphisms_of_Types.html?id=cdJZRjIxavwC 
> 
> 
> When a 1970s paper claims a relation ship between
> pi-calculus and lambda calculus, then both calculi
> refer to a typeless calculi.
> 
> Types are a later invention. The original lambda
> calculus was typeless. Church encodings came later,
> but for example the Church Turing hypotheses is
> 
> formulated along typeless lambda calculus.
> 
> Bye
> 
> P.S.: Prolog is also typeless. I do not intend to
> add any types to pi-WAM either.
> 
> Ross Finlayson schrieb:
>> On 07/17/2026 04:50 PM, Mild Shock wrote:
>>> Hi,
>>>
>>> Milners fickle() is here:
>>>
>>> Functions as processes
>>> https://inria.hal.science/inria-00075405
>>>
>>> After Theorem 7.7:
>>>
>>> So in P we construct a fickle ‘function’ which
>>> behaves differently on successive calls.
>>>
>>> Here is a pi-WAM run in Dogelog Player, using the emulator:
>>>
>>> Dogelog Spieler 2.2.4, Oracle Corporation, Java 26.0.1
>>> (c) 1985-2026, XLOG Technologies AG, Schweiz
>>> ?- ensure_loaded(library(edge/brainfog)).
>>> true.
>>> ?- emulate((between(1,2,Y),in(X),out(Y))).
>>> : 0
>>> 1
>>> : 0
>>> 2
>>> fail.
>>>
>>> The emulator is portable, can be run every Prolog
>>> system. But it is only 1 process. So its better
>>> to use the n process backends for CPU or GPU.
>>>
>>> Which are less portable, not anymore pure Prolog,
>>> a great deal of thread start and join infrastructure
>>> as well, and a native Hack VM.
>>>
>>> The comms across process is not yet implemented.
>>> But the in/1 and out/1 instructions are already
>>> there. But they currently go to stdin/stdout.
>>>
>>> Bye
>>>
>>> Mild Shock schrieb:
>>>> Hi,
>>>>
>>>> The pi in pi-WAM refers to pi-calculus.
>>>> pi-calculus has not atomic(i32).
>>>>
>>>> The π-calculus is a universal model of computation.
>>>> This was first observed by Milner in his paper
>>>> "Functions as Processes",[10] in which he presents
>>>> two encodings of the lambda-calculus in the π-calculus.
>>>> https://en.wikipedia.org/wiki/%CE%A0-calculus
>>>>
>>>> LoL
>>>>
>>>> Bye
>>>>
>>>> Chris M. Thomasson schrieb:
>>>>> On 7/17/2026 2:16 AM, Mild Shock wrote:
>>>>>> Hi,
>>>>>>
>>>>>> Maybe I should write a blog post, titled
>>>>>> Introduction to AI Accelerator Prolog:
>>>>>>
>>>>>> - specialized jobs π-WAM (currently integerish stuff)
>>>>>> - π-WAM uses no atomics, only comms
>>>>>> - π-WAM uses warp, 30-40% more speed
>>>>>> - π-WAM runs on GPU and CPU
>>>>>> - π-WAM runs from within JavaScript, Python and Java
>>>>>
>>>>> [...]
>>>>>
>>>>> No atomic fetch-and-add?
>>>>
>>>
>>
>> So he partial-computes his alpha to alpha_alpha
>> in his Futamura projection, yet, that's partial computation,
>> why not make Minsky counter-machines using the bottom-up
>> approach of making arithmetizations and DFA's.
>>
>>
>> Of course the lambda-calculus and pi-calculus are great
>> things for models of types and communicating sequential processes.
>>
>> Roberto di Cosmo has a great book on types, and more than one.
>>
>> https://books.google.com/books/about/Isomorphisms_of_Types.html?id=cdJZRjIxavwC 
>>
>>
>>
> 

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#347703 — AI Laptops are just strange novel xBoxes (Was: AI dooms day escape: Güttinger Wald)

Hi,

We can thank the gamers, that GPUs developed muscles:

The global video game industry contributes hundreds
of billions to worldwide GDP, generating over $500
billion in total market volume. The global software
and services market alone accounts for an estimated
$255 billion, easily surpassing the film and recorded
music industries combined.

How it started:

URP Cookbook: Compute shaders - Part 1: Particle fun
https://www.youtube.com/watch?v=omZap7XHxKc

How its going:

Dogelog Player: 11.4 Giga Lips with a Budget Laptop
https://medium.com/2989/899b0d5c027b

Bye

Mild Shock schrieb:
> Hi,
> 
> You just escaped AI dooms day. Humanity has
> reset all internet and computers as a last resort
> to prevent AGI developing, by an electromagnetic
> 
> pulse. You are stuck in Güttinger Wald and hunted
> down a deer by your bare hands, the deer still
> confused and tame because tourists were feeding it.
> 
> Now you have no knife, what do you do:
> 
> Chimpanzees Have Entered The Stone Age
> https://www.youtube.com/watch?v=wPXX2I_uYjc
> 
> So we are just apes with internet.
> 
> Bye
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Ok I was looking at this learning challenge,
>> producing vector (y1,y2,y3,y4) from a vector
>> (x1,x2,x3,x4), System R can do it via least square?
>>
>> | 0 0 0 1 |   | x1 |     | x4 |
>> | 0 0 1 0 |   | x2 |  =  | x3 |
>> | 0 1 0 0 |   | x3 |     | x2 |
>> | 1 0 0 0 |   | x4 |     | x1 |
>>
>> How it started:
>>
>> "multiplicative RNNs arises naturally from a
>> proof-theoretic interpretation of next-token
>> prediction as nested intuitionistic implication"
>> Paul Tarau - 2026
>> https://arxiv.org/abs/2601.19915
>>
>> How its going:
>>
>> "Dave uses a PDP-11 to train a real Neural
>> Network complete with Transformers and
>> Attention so you can see them at their most basic."
>> Mr. Taskmanager - 2026
>> https://www.youtube.com/watch?v=OUE3FSIk46g
>>
>> We see Doctor Frankstein in action from
>> the Bronze Age of Computing, producing
>> a Humunkulus, the progenitor of todays
>>
>> Bulgakov Shuriks in the Hyperscale Age!
>>
>> Bye
>>
>> P.S.: My impression neither cut to the core, that
>> this incredible transformer most likely
>> produced this deterministic attention:
>>
>> | -1 | * | k | + | 5 | = | k' |
>>
>> Or differently expressed y_k = x_{5-k}.
>>
>> How did the transformer do it? It produced
>> a neural network with 1216 parameters, but
>> didn't use embeddings or polar encoding
>>
>> of positions. But if we strip the noise
>> and denoise from the position encoding,
>> the denoise is done via softmax. We somehow
>>
>> must get the above, right? I still need to
>> verify my claim! BTW: The PDP-11 assembly
>> from 1979 uses wider example not with n=4
>>
>> but with n=8.
> 

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#347707 — Re: AI Laptops are just strange novel xBoxes (Was: AI dooms day escape: Güttinger Wald)

On 7/8/2026 11:44 AM, Mild Shock wrote:
> Hi,
> 
> We can thank the gamers, that GPUs developed muscles:
> 
> The global video game industry contributes hundreds
> of billions to worldwide GDP, generating over $500
> billion in total market volume. The global software
> and services market alone accounts for an estimated
> $255 billion, easily surpassing the film and recorded
> music industries combined.
> 
> How it started:
> 
> URP Cookbook: Compute shaders - Part 1: Particle fun
> https://www.youtube.com/watch?v=omZap7XHxKc
[...]

Compute shaders are pretty nice. Except then the damn os can cancel them 
because they took too long! God damn windows! ;^)

I have ported my field to compute shaders and geometry shaders. They 
work great! A compute shader can take a field from say 30 seconds on a 
high performance multi-threaded cpu version down to around 3 seconds. 
The compute shader is using atomic operations for thread, or warp sync.

The geometry shader makes my field in real time.

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#347719 — TDR solutions --> work slicing (Was: AI Laptops are just strange novel xBoxes)

Hi,

Current workaround, for workloads which take
longer, regedit TdrDelay and TdrDdiDelay:

GPU drivers crash with long computations (TDR crash)
https://experienceleague.adobe.com/en/docs/substance-3d-painter/using/technical-support/technical-issues/gpu-issues/gpu-drivers-crash-with-long-computations-tdr-crash

Future solution is work slicing. Make the
GPU inferencing granular. Since I am using

a Hack virtual machine, adding a "Heartbeat"
should be possible, Dogelog Player has

already some auto-yield (*). Mostlikely this will
then prevent the OS from killing the GPU.

Will see! WebLLM etc.. can also do it.

Bye

(*) A browser does also kill a long runnning
JavaScript, it was a similar issue.

Chris M. Thomasson schrieb:
> On 7/8/2026 11:44 AM, Mild Shock wrote:
>> Hi,
>>
>> We can thank the gamers, that GPUs developed muscles:
>>
>> The global video game industry contributes hundreds
>> of billions to worldwide GDP, generating over $500
>> billion in total market volume. The global software
>> and services market alone accounts for an estimated
>> $255 billion, easily surpassing the film and recorded
>> music industries combined.
>>
>> How it started:
>>
>> URP Cookbook: Compute shaders - Part 1: Particle fun
>> https://www.youtube.com/watch?v=omZap7XHxKc
> [...]
> 
> Compute shaders are pretty nice. Except then the damn os can cancel them 
> because they took too long! God damn windows! ;^)
> 
> I have ported my field to compute shaders and geometry shaders. They 
> work great! A compute shader can take a field from say 30 seconds on a 
> high performance multi-threaded cpu version down to around 3 seconds. 
> The compute shader is using atomic operations for thread, or warp sync.
> 
> The geometry shader makes my field in real time.
> 

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#347722 — Thinking of Chris M. Thomasson: From shadertoys to computetoys? (Re: TDR solutions --> work slicing)

Hi,

Over the recent days was often thinking
about Chris M. Thomasson. I am somehow
familiar with his work on sci.math etc..

even back in times before there was the
gexit (Google Groups Exit) and AP (Archimedes
Plutonium) was enriching the forums.

So whats the evolution here?

Well we had shadertoys:

https://www.shadertoy.com/

Now have computetoys:

https://compute.toys/

The https://compute.toys/view/3138 (Spinning
Terrain) example drives my GPU on the Ryzen
up to 91 degree, normally it has 44 degree

temperature or something.

LoL

Bye

Mild Shock schrieb:
> Hi,
> 
> Current workaround, for workloads which take
> longer, regedit TdrDelay and TdrDdiDelay:
> 
> GPU drivers crash with long computations (TDR crash)
> https://experienceleague.adobe.com/en/docs/substance-3d-painter/using/technical-support/technical-issues/gpu-issues/gpu-drivers-crash-with-long-computations-tdr-crash 
> 
> 
> Future solution is work slicing. Make the
> GPU inferencing granular. Since I am using
> 
> a Hack virtual machine, adding a "Heartbeat"
> should be possible, Dogelog Player has
> 
> already some auto-yield (*). Mostlikely this will
> then prevent the OS from killing the GPU.
> 
> Will see! WebLLM etc.. can also do it.
> 
> Bye
> 
> (*) A browser does also kill a long runnning
> JavaScript, it was a similar issue.
> 
> Chris M. Thomasson schrieb:
>> On 7/8/2026 11:44 AM, Mild Shock wrote:
>>> Hi,
>>>
>>> We can thank the gamers, that GPUs developed muscles:
>>>
>>> The global video game industry contributes hundreds
>>> of billions to worldwide GDP, generating over $500
>>> billion in total market volume. The global software
>>> and services market alone accounts for an estimated
>>> $255 billion, easily surpassing the film and recorded
>>> music industries combined.
>>>
>>> How it started:
>>>
>>> URP Cookbook: Compute shaders - Part 1: Particle fun
>>> https://www.youtube.com/watch?v=omZap7XHxKc
>> [...]
>>
>> Compute shaders are pretty nice. Except then the damn os can cancel 
>> them because they took too long! God damn windows! ;^)
>>
>> I have ported my field to compute shaders and geometry shaders. They 
>> work great! A compute shader can take a field from say 30 seconds on a 
>> high performance multi-threaded cpu version down to around 3 seconds. 
>> The compute shader is using atomic operations for thread, or warp sync.
>>
>> The geometry shader makes my field in real time.
>>
> 

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#347739 — FYI: Unified Memory Architecture (UMA) (Re: Implementing Gas for a Compute Shader [Avoid TDR])

Hi,

These novel GPUs , that are part of AI Laptops,
feature Unified Memory Architecture (UMA).
In the case of my Ryzen the main memory is 32 GB,

and the GPU can access 16 GB. It is a design where
CPUs and GPUs share a single coherent memory space,
eliminating the need for separate host and

accelerator memory. Nevertheless the WebGPU API,
works with some copy and synchronization semantics
and buffer abstractions, which is not a big loss.

But all buffers reside in the same AI Lapop
RAM. And the MIMD architecture allows instructions
where seperate threads access the same

memory location, either for read or for write.
There is also a data type atomic(T), which
features operation such as AtomicAdd() etc.. etc..

BTW, I made a GitHub project of my exploration:

11.4 Giga Lips with a Budget Laptop
https://github.com/Jean-Luc-Picard-2021/gigabudget

BTW, pi-WAM is nevertheless optimized to have
no memory contention. On the other hand pi-WAM
is happy to access large memory areas.

Bye

BTW: The grandmother of these novel GPUs
is NVIDIAs Volta which already appeared in
2017, meanwhile we have 2026.

See also:

Starting with the NVIDIA Volta architecture,
Independent Thread Scheduling allows full
concurrency between threads, regardless of warp.
https://forums.developer.nvidia.com/t/back-to-simd/311983

The AMD Radeon 860M is an integrated graphics
processor that does not have its own dedicated
VRAM. Instead, it dynamically shares up to 50%
of your total system RAM with the CPU in a
standard Windows configuration.
https://www.amd.com/en/blogs/2025/faqs-amd-variable-graphics-memory-vram-ai-model-sizes-quantization-mcp-more.html

Ryann Likunov schrieb:
 > Mild Shock wrote:
 >
 >> Hi,
 >>
 >> I guess, you can read off how to do it here,
 >> i.e. avoid TDR (DXGI_ERROR_DEVICE_HUNG 0x887A0006). The below compute
 >> toys example has a similar
 >>
 >> approach, just like my π-WAM and Hack GPU backend,
 >> that is based on a Instruction Set Architecture (ISA):
 >
 > how come they are not able to map the local RAM
 > as gpu arrays for using them as local AI resource
 >

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