From Newsgroup: comp.lang.prolog

Hi,

With their stupid fixation on Emacs Prolog
missed a Billion Dollar Business Model.

Now people will start paying 4'000 USD per
Year and GPU to Red Hat to have some AI
model deployment and training enviroment:

DGX Spark Arrives at SpaceX
https://www.youtube.com/watch?v=peaIkB0NzS0

But these environments are nothing then
Python virtual environments. Can Prolog not
also push some evaluation graphs to

a GPU or NPU? Well it seems with its current
philosophy only if there is a spare Key
Combination in Emacs for it.

Bye
--- Synchronet 3.21a-Linux NewsLink 1.2

From Newsgroup: comp.lang.prolog

Hi,

Prolog has become the Useful Fool.
Over the years it was trained that
constraints are importanter than

anything else. Even this talk blends
out natural language processing:

Manuel Hermenehgildo - 50 Years of Prolog and Beyond https://prologyear.logicprogramming.org/videos/PrologDay_Session_1_talk.mp4

And if you give them some IBM Roadrunner
precursor, all they can do, is play
some stupid constraint games:

Parallel local search for solving Constraint Problems on the Cell
Broadband Engine (Preliminary Results) https://www.researchgate.net/publication/220481722

And mentioning in passing how useless
blunt constraint solving is as implemented
by most CLP(X), can't even solve

magic square of 10 x 10.

Bye

Mild Shock schrieb:

Hi,

With their stupid fixation on Emacs Prolog
missed a Billion Dollar Business Model.

Now people will start paying 4'000 USD per
Year and GPU to Red Hat to have some AI
model deployment and training enviroment:

DGX Spark Arrives at SpaceX
https://www.youtube.com/watch?v=peaIkB0NzS0

But these environments are nothing then
Python virtual environments. Can Prolog not
also push some evaluation graphs to

a GPU or NPU? Well it seems with its current
philosophy only if there is a spare Key
Combination in Emacs for it.

Bye

--- Synchronet 3.21a-Linux NewsLink 1.2

From Newsgroup: comp.lang.prolog

Hi,

On small clusters, a failed GPU process
usually crashes visibly. On large TPU systems,
you can get “silent” or “partial” failures
where a chip is alive but unhealthy —

producing NaNs, stalling on the interconnect,
or returning corrupted data that’s
not immediately flagged.

At hyperscale, training becomes a kind of
“distributed computer architecture problem,”
and engineers do end up inventing their own
“parity-check”–like systems — not for

individual bits (as in DRAM ECC), but for
entire tensors, gradients, and replicas.

See also:

Gemini 2.5: Pushing the Frontier
https://arxiv.org/abs/2507.06261

Bye

Mild Shock schrieb:

Hi,

Prolog has become the Useful Fool.
Over the years it was trained that
constraints are importanter than

anything else. Even this talk blends
out natural language processing:

Manuel Hermenehgildo - 50 Years of Prolog and Beyond https://prologyear.logicprogramming.org/videos/PrologDay_Session_1_talk.mp4

And if you give them some IBM Roadrunner
precursor, all they can do, is play
some stupid constraint games:

Parallel local search for solving Constraint Problems on the Cell
Broadband Engine (Preliminary Results) https://www.researchgate.net/publication/220481722

And mentioning in passing how useless
blunt constraint solving is as implemented
by most CLP(X), can't even solve

magic square of 10 x 10.

Bye

Mild Shock schrieb:

Hi,

With their stupid fixation on Emacs Prolog
missed a Billion Dollar Business Model.

Now people will start paying 4'000 USD per
Year and GPU to Red Hat to have some AI
model deployment and training enviroment:

DGX Spark Arrives at SpaceX
https://www.youtube.com/watch?v=peaIkB0NzS0

But these environments are nothing then
Python virtual environments. Can Prolog not
also push some evaluation graphs to

a GPU or NPU? Well it seems with its current
philosophy only if there is a spare Key
Combination in Emacs for it.

Bye

--- Synchronet 3.21a-Linux NewsLink 1.2