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Groups > comp.lang.prolog > #14922
| From | Mild Shock <janburse@fastmail.fm> |
|---|---|
| Newsgroups | comp.lang.prolog |
| Subject | Eat Tteokbokki before SkyNet kills you [$100 ChatGPT] (Was: Ask Phind: AI inflection point right now [End 2025]) |
| Date | 2025-10-18 15:57 +0200 |
| Message-ID | <10d06ch$17p4u$1@solani.org> (permalink) |
| References | <107t0fi$6bgl$1@solani.org> <10cmqea$s93$1@solani.org> <10cn157$10qq$1@solani.org> <10co9kp$12u6u$1@solani.org> <10coa13$12ucf$1@solani.org> |
Hi, Thinks are definitively accelerating. I really would like to use an AI that knows about all the News of today. This bloody cut date is so annoying. Further indicative that AI is accelerating: In August 2025, Sam Altman dropped a bombshell: *months, not years: Rushing GPT-6* In August 2025, Sam Altman dropped a bombshell: GPT-6 is already in development and coming sooner than you think. Not in two years, but potentially in months. https://www.youtube.com/watch?v=44mJb5sKji0 Karpathy, coined vibe coding, released in October 2025: *nanochat: The best ChatGPT that $100 can buy* This repo is a full-stack implementation of an LLM like ChatGPT in a single, clean, minimal, hackable, dependency-lite codebase. nanochat is designed to run on a single 8XH100 node via scripts like speedrun.sh, that run the entire pipeline start to end. https://github.com/karpathy/nanochat Bye Mild Shock schrieb: > Hi, > > But not only Mobie AI and Desktop AI are making > a broader imprint now. We might also experience > Workstation AI, with a 3'000.- USD price tag: > > > You Can't Buy This... Yet! The NVIDIA GB10 from Dell > > The New Superchip that Terrifies the Cloud! > > https://www.youtube.com/watch?v=x1qViw4xyVo > > So whats going on? I was asking Phind, which is > driven by a 70B model tailored towards developers: > > Q: Is there an AI inflection point right now , > with NPUs in mobile, desktop and workstation > > A: Evidence of the Inflection Point > > - Mobile Leadership > NPUs originated in smartphones > Now becoming ubiquitous across all device types > Enabling sophisticated AI features at consumer price points > > - Desktop Revolution > Major manufacturers implementing NPUs across product lines > Apple's Neural Engine integrated into M-series chips > Qualcomm, Intel, and AMD incorporating AI accelerators > > - Workstation Transformation > Professional-grade NPUs in mobile workstations > Demonstrated superior performance for AI-specific tasks > Enabling local processing of previously cloud-dependent workloads > > https://www.phind.com/search/cmgs1s6jv00023h67g5z2aaa0 > > Bye > > Mild Shock schrieb: >> Hi, >> >> It seems I am having problems pacing with >> all the new fancy toys. Wasn't able to really >> benchmark my NPU from a Desktop AI machine, >> >> picked the wrong driver. Need to try again. >> What worked was benchmarking Mobile AI machines. >> I just grabbed Geekbench AI and some devices: >> >> USA Fab, M4: >> >> sANN hANN qANN >> iPad CPU 4848 7947 6353 >> iPad GPU 9752 11383 10051 >> iPad NPU 4873 36544 *51634* >> >> China Fab, Snapdragon: >> >> sANN hANN qANN >> Redmi CPU 1044 950 1723 >> Redmi GPU 480 905 737 >> Redmi NNAPI 205 205 469 >> Redmi QNN 226 226 *10221* >> >> Speed-Up via NPU is factor 10x. See the column >> qANN which means quantizised artificial neural >> networks, when NPU or QNN is picked. >> >> The mobile AI NPUs are optimized using >> mimimal amounts of energy, and minimal amounts >> of space squeezing (distilling) everything >> >> into INT8 and INT4. >> >> Bye >> >> Mild Shock schrieb: >>> Hi, >>> >>> The change from 378 ms to 286 ms is around 25-30% >>> is insane. But I did both tests on a novel AI CPU. >>> To be precise on a AMD Ryzen AI 7 350. >>> >>> But somehow I picked up rumors that AI CPUs now >>> might do Neural Network Branch Prediction. The >>> idea seems to exist in hardware at least since (2012): >>> >>> Machine learning and artificial intelligence are >>> the current hype (again). In their new Ryzen >>> processors, AMD advertises the Neural Net >>> Prediction. It turns out this is was already >>> used in their older (2012) Piledriver architecture >>> used for example in the AMD A10-4600M. It is also >>> present in recent Samsung processors such as the >>> one powering the Galaxy S7. What is it really? >>> https://chasethedevil.github.io/post/the_neural_network_in_your_cpu/ >>> >>> It can be done with Convoluted Neural Networks (CNN): >>> >>> BranchNet: A Convolutional Neural Network to >>> Predict Hard-To-Predict Branches >>> To this end, Tarsa et al. proposed using convolutional >>> neural networks (CNNs) that are trained at >>> compiletime to accurately predict branches that >>> TAGE cannot. Given enough profiling coverage, CNNs >>> learn input-independent branch correlations. >>> https://microarch.org/micro53/papers/738300a118.pdf >>> >>> Interstingly the above shows cases a PGO based >>> Machine Learning for Branch Predictors. No clue >>> how they construct the CPU, that they can feed >>> >>> it with offline constructed neural neutworks for >>> their own execution. Maybe an optimizer uses it? >>> But I guess a more modern solutions would not only >>> >>> use CNN, but also an Attention Mechanism. >>> >>> Bye >>> >>> Mild Shock schrieb: >>>> Hi, >>>> >>>> I spent some time thinking about my primes.pl >>>> test. And came to the conclusion that it >>>> mainly tests the Prolog ALU. Things like >>>> >>>> integer successor or integer modulo. Then >>>> I found that Java has Math.floorMod() which >>>> I wasn't using yet. And peng results are better: >>>> >>>> /* Dogelog Player 2.1.2 for Java, today */ >>>> ?- time(test). >>>> % Zeit 286 ms, GC 1 ms, Lips 26302430, Uhr 15.10.2025 02:31 >>>> true. >>>> >>>> Maybe the Java backend picks a CPU instruction >>>> for Math.floorMod() instead of executing the >>>> longer code sequence that is needed to correct >>>> >>>> rem/2 into mod/2. Who knows. I also reorganized >>>> the code a little bit, and eliminated an extra >>>> method call in all arithmetic functions, by >>>> >>>> inlining the arithmetic function body in the >>>> evaluable predicate definition code. Comparison >>>> to old measurements and some measurements of >>>> >>>> other Prolog systems: >>>> >>>> /* Dogelog Player 2.1.2 for Java, weeks ago */ >>>> ?- time(test). >>>> % Zeit 378 ms, GC 1 ms, Lips 19900780, Uhr 28.08.2025 17:44 >>>> true. >>>> >>>> /* SWI-Prolog 9.0.4 */ >>>> ?- time(test). >>>> % 7,506,639 inferences, 0.363 CPU in 0.362 seconds >>>> (100% CPU, 20693560 Lips) >>>> true. >>>> >>>> /* Scryer Prolog 0.9.4-639 */ >>>> ?- time(test). >>>> % CPU time: 0.365s, 7_517_613 inferences >>>> true. >>>> >>>> /* Trealla Prolog 2.82.23-3 */ >>>> ?- time(test). >>>> % Time elapsed 0.868s, 11263917 Inferences, 12.983 MLips >>>> true. >>>> >>>> Bye >>>> >>>> P.S.: The code uses the hated mathematical mod/2, >>>> and not the cheaper rem/2 that CPUs usually have: >>>> >>>> test :- >>>> len(L, 1000), >>>> primes(L, _). >>>> >>>> primes([], 1). >>>> primes([J|L], J) :- >>>> primes(L, I), >>>> K is I+1, >>>> search(L, K, J). >>>> >>>> search(L, I, J) :- >>>> mem(X, L), >>>> I mod X =:= 0, !, >>>> K is I+1, >>>> search(L, K, J). >>>> search(_, I, I). >>>> >>>> mem(X, [X|_]). >>>> mem(X, [_|Y]) :- >>>> mem(X, Y). >>>> >>>> len([], 0) :- !. >>>> len([_|L], N) :- >>>> N > 0, >>>> M is N-1, >>>> len(L, M). >>>> >>>> Mild Shock schrieb: >>>>> Hi, >>>>> >>>>> WebPL is already outdated I guess. It doesn't >>>>> show the versions of the other Prolog systems >>>>> it is using. While I had these results for >>>>> >>>>> the primes example in the WebPL playground: >>>>> >>>>> /* Trealla Prolog WASM */ >>>>> (23568.9ms) >>>>> >>>>> When I run the example here: >>>>> >>>>> https://php.energy/trealla.html >>>>> >>>>> I get better results: >>>>> >>>>> /* trealla-js 0.27.1 */ >>>>> >>>>> ?- time(test). >>>>> % Time elapsed 9.907s, 11263917 Inferences, 1.137 MLips >>>>> >>>>> Bye >>>> >>> >> >
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WebPL is already outdated Mild Shock <janburse@fastmail.fm> - 2025-08-17 18:37 +0200
Heap/Stack versus WAM resp. ZIP (Was: WebPL is already outdated) Mild Shock <janburse@fastmail.fm> - 2025-08-18 14:52 +0200
Trealla knows Program Sharing (PS) Tricks ? (Was: Heap/Stack versus WAM resp. ZIP) Mild Shock <janburse@fastmail.fm> - 2025-08-18 15:06 +0200
Smarter Partial Strings would use Program Sharing ['$append'/3] (Was: Trealla knows Program Sharing (PS) Tricks ?) Mild Shock <janburse@fastmail.fm> - 2025-08-18 15:42 +0200
Static Shunting is even better [Dogelog Player] (Was: Smarter Partial Strings would use Program Sharing ['$append'/3]) Mild Shock <janburse@fastmail.fm> - 2025-08-18 15:49 +0200
The Artificial Intelligence Flip: Acer Swift Go! (Was: WebPL is already outdated) Mild Shock <janburse@fastmail.fm> - 2025-08-31 23:56 +0200
2025 will be last year we hear of Python (Re: The Artificial Intelligence Flip: Acer Swift Go!) Mild Shock <janburse@fastmail.fm> - 2025-09-01 00:45 +0200
Apertus: With love, from Switzerland [02 Sept 2025] (Re: 2025 will be last year we hear of Python) Mild Shock <janburse@fastmail.fm> - 2025-09-05 00:36 +0100
Don't try this (Was: Apertus: With love, from Switzerland [02 Sept 2025] ) Mild Shock <janburse@fastmail.fm> - 2025-09-05 01:03 +0100
AI means ambracing Non-Linearity (Was: 2025 will be last year we hear of Python) Mild Shock <janburse@fastmail.fm> - 2025-09-19 10:01 +0200
AI soaked PCs: Is there a Copilot+ Prolog? (Was: AI means ambracing Non-Linearity) Mild Shock <janburse@fastmail.fm> - 2025-09-19 10:10 +0200
The morning coffee incident [Prolog Community] (Was: AI soaked PCs: Is there a Copilot+ Prolog?) Mild Shock <janburse@fastmail.fm> - 2025-09-19 14:38 +0200
Root Cause Prediction for Your Brain (Was: The morning coffee incident [Prolog Community]) Mild Shock <janburse@fastmail.fm> - 2025-09-19 18:22 +0200
Please delete my account and all my posts on SWI-Prolog discourse (Re: Root Cause Prediction for Your Brain) Mild Shock <janburse@fastmail.fm> - 2025-09-19 18:38 +0200
I will consult a Lawyer of mine (Was: Please delete my account and all my posts on SWI-Prolog discourse) Mild Shock <janburse@fastmail.fm> - 2025-09-19 18:42 +0200
Scryer Prolog unify_with_occurs_check/2 doesn't scale (Was: WebPL is already outdated) Mild Shock <janburse@fastmail.fm> - 2025-09-19 16:08 +0200
How bad is Rust, can JavaScript beat it? (Was: Scryer Prolog unify_with_occurs_check/2 doesn't scale) Mild Shock <janburse@fastmail.fm> - 2025-09-19 16:18 +0200
unify_with_occurs_check/2 might have been fixed (Was: Scryer Prolog unify_with_occurs_check/2 doesn't scale) Mild Shock <janburse@fastmail.fm> - 2025-09-25 01:50 +0200
Had to Rollback my Jaffar Unification (Was: unify_with_occurs_check/2 might have been fixed) Mild Shock <janburse@fastmail.fm> - 2025-09-25 01:59 +0200
Trealla Prolog might apply "frozeness" to cyclic terms (Was: Had to Rollback my Jaffar Unification) Mild Shock <janburse@fastmail.fm> - 2025-09-25 02:06 +0200
Non-intrusive through "frozen" subcategories (Was: Trealla Prolog might apply "frozeness" to cyclic terms) Mild Shock <janburse@fastmail.fm> - 2025-09-25 02:21 +0200
Scryer Prolog occurs check cannot do hydra (Was: Scryer Prolog unify_with_occurs_check/2 doesn't scale) Mild Shock <janburse@fastmail.fm> - 2025-09-26 12:19 +0200
WebPL and Scryer Prolog are bad examples (Was: WebPL is already outdated) Mild Shock <janburse@fastmail.fm> - 2025-10-13 09:49 +0200
Who will win Shift-Reduce or Tabled DCG? [AI Boom] (Was: WebPL and Scryer Prolog are bad examples) Mild Shock <janburse@fastmail.fm> - 2025-10-13 15:09 +0200
primes.pl mainly tests the Prolog ALU [mod/2 vs rem/2] (Was: WebPL is already outdated) Mild Shock <janburse@fastmail.fm> - 2025-10-15 02:38 +0200
25-30% is insane, Neural Network Branch Prediction? (Was: primes.pl mainly tests the Prolog ALU) Mild Shock <janburse@fastmail.fm> - 2025-10-15 04:33 +0200
NPUs (Neural Processing Units) are the new normal (Was: 25-30% is insane, Neural Network Branch Prediction?) Mild Shock <janburse@fastmail.fm> - 2025-10-15 16:04 +0200
Ask Phind: AI inflection point right now [End 2025] (Was: NPUs (Neural Processing Units) are the new normal) Mild Shock <janburse@fastmail.fm> - 2025-10-15 16:10 +0200
Eat Tteokbokki before SkyNet kills you [$100 ChatGPT] (Was: Ask Phind: AI inflection point right now [End 2025]) Mild Shock <janburse@fastmail.fm> - 2025-10-18 15:57 +0200
Give Julio Di Egidio the bloody money [3 RMB¥ MiniMind] (Re: Eat Tteokbokki before SkyNet kills you [$100 ChatGPT]) Mild Shock <janburse@fastmail.fm> - 2025-10-18 16:19 +0200
Vertex AI Training is more expensive? (Was: Give Julio Di Egidio the bloody money [3 RMB¥ MiniMind]) Mild Shock <janburse@fastmail.fm> - 2025-10-21 00:32 +0200
The Love Affair: OpenAI and AMD (Was: NPUs (Neural Processing Units) are the new normal) Mild Shock <janburse@fastmail.fm> - 2025-10-18 18:59 +0200
The NPU in your Browser [WebNN by W3C] (Was: NPUs (Neural Processing Units) are the new normal) Mild Shock <janburse@fastmail.fm> - 2025-10-26 08:39 +0100
Fuzzy Alert: Boris the Loris on the Dancefloor (Was: The NPU in your Browser [WebNN by W3C]) Mild Shock <janburse@fastmail.fm> - 2025-10-26 11:33 +0100
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