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In 2028 BYD sells B100 performant laptop? (Re: Could ISAMORE anti-unification help?)

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Hi,

AI Laptops are technically evolving so much,
the operating systems cannot evolve fast enough.
Its like the cars in Bali geting bigger and bigger,

but the streets are still narrow or bad. Quite
a stunner was the RTX sparc announcement May 2026
that might put 1 PETA OPS AI Inferencing, or will

it be machine learning, into your hands for $2000 ?
There are a lot of things going on, like ARM SME2
unlocking even Apple Silicon for everybody, and

Nvidia countering Apple Silicon with its own unified
memory convential memory. What will be the future? I
guess we might see Laptops having high bandwidth memory:

TSMC’s CoWoS (Chip-on-Wafer-on-Substrate) is
an advanced 2.5D packaging technology that
vertically and horizontally integrates multiple
distinct silicon dies
https://www.nomadsemi.com/p/tsmcs-cowos-capacity

But did you know that BYD started as a battery
company and has now a semincoductor branch, already
operating a 4nm? BYD electronics spinning off a laptop?

MidAmerican Energy Holdings, a subsidiary of Warren
Buffett's Berkshire Hathaway Inc, invested about
US$230 million for a 9.89% share of BYD
at HK$8 per share.
https://www.nomadsemi.com/p/byd-semiconductor-deep-dive

Bye

Mild Shock schrieb:
> Hi,
> 
> One challenge is that the example has
> not only anti-unification, like the c*d\=d*c,
> the Mc Cune style model finder implementation
> 
> makes also heavy use of backtracking. So
> I even don’t know whether ISAMORE papers
> with saturation would help:
> 
> Finding Reusable Instructions via E-Graph Anti-Unification
> Youwei Xiao et al. - ASPLOS ’26
> https://github.com/pku-liang/ISAMORE
> 
> But I guess ISAMORE also delivers
> rewriting challenges. But their subject
> matter in the above paper is LLVM/GEM5 (*),
> 
> so maybe so maybe I rather buy a new Mac
> Neo (only $500) and enjoy local AI.
> 
> Bye
> 
> (*)
> https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms#Level_3
> 
> Mild Shock schrieb:
>> Hi,
>>
>> Now toying around with a model finder,
>> for some rewritng problems. Not bad, I
>> didn't see that before on my computer:
>>
>> ?- time(mccune([e*X=X,X^(-1)*X=e,X*(Y*Z)=(X*Y)*Z, c*d\=d*c], 6, _)).
>> % Zeit 166.140 ms, GC 0.000 ms, Lips 18616 k
>> true
>>
>> ?- mccune([e*X=X,X^(-1)*X=e,X*(Y*Z)=(X*Y)*Z, c*d\=d*c], 6, R).
>> R = [d-2, c-1, 5*2-3, 5*5-4, 4*3-2, 3*5-2, 3*2-5, 4*4-5, 2*4-3,
>> 2*3-4, 3*4-1, 3*1-4, 5*3-1, 4*1-3, 1*5-3, 1*3-5, 2*1-5, 2*5-1,
>> 5*1-2, 4*2-1, 1*4-2, 1*2-4, 5*0-5, 4*0-4, 4*5-0, 5^ -1-4, 5*4-0,
>> 4^ -1-5, 3*0-3, 3*3-0, 3^ -1-3, 2*0-2, 2*2-0, 2^ -1-2, 1*0-1,
>> 1*1-0, 1^ -1-1, 0^ -1-0, 0*5-5, 0*4-4, 0*3-3, 0*2-2,
>> 0*1-1, 0*0-0, e-0]
>>
>> But still not as good as Mc Cune, wo reported
>> 0.010 seconds , so 10 ms (*). I guess I need to
>> explore more heuristics. But will it include
>>
>> union find? The payback of union find in such
>> search examples is so low. If |D| = n is the
>> domain size, then although |D x D| has size n^2,
>>
>> the diagonal E_D, namely E_D = { (x,y) | x e D,
>> y e D, x = y } has only size n. So the probability
>> of a pair in certain problem domains, is around 1/n,
>>
>> getting smaller and smaller with larger and larger n.
>>
>> Bye
>>
>> (*)
>> https://www.mcs.anl.gov/research/projects/AR/mace4/July-2005/doc/mace4.pdf 
>>
>>
>> Mild Shock schrieb:
>>> Hi,
>>>
>>> This is a nice example how the young generation
>>> doesn't understand systems that were developed
>>> 30 years ago:
>>>
>>> Example 1:
>>> No clue that SWI-Prolog does have JIT indexes,
>>> which explain mysterious differene between
>>> cold and warm run.
>>> https://arxiv.org/pdf/2511.13600
>>>
>>> Example 2:
>>> No clue that subsumption could make a difference,
>>> claims left recursion is fastest, with referene
>>> to [TL10] and a bogus node argument.
>>> https://arxiv.org/abs/2504.21291
>>>
>>> Maybe the Prolog eduction group should organize
>>> a summer school about tabling?
>>>
>>> Sad news: It will not help to keep up with
>>> the AI boom. Whats behind the AI boom and
>>> computing transitive closures?
>>>
>>> Bye
>>>
>>> Mild Shock schrieb:
>>>> Hi,
>>>>
>>>> Ok, thats noice:
>>>>
>>>> "On a GPU cluster, the ratio of high computing
>>>> power to communication bandwidth makes scaling
>>>> breadth-first search (BFS) on a scale-free
>>>> graph extremely challenging."
>>>>
>>>> Scalable Breadth-First Search on a GPU Cluster
>>>> Yuechao Pan, Roger Pearce, John D. Owens
>>>> 2018 - Lawrence Livermore National Laboratory
>>>> https://arxiv.org/abs/1803.03922
>>>>
>>>> Sniff, still passed the deadline Q1 2026 for
>>>> my GigaLIPS Prolog. There were so many other
>>>> improvements , more low hanging fruits to cover.
>>>>
>>>> Bye
>>>>
>>>> P.S.: Wanna rent some GPUs?
>>>>
>>>> Cloud GPU Index
>>>> Compare 2,542 GPU prices across 57 cloud providers
>>>> https://getdeploying.com/gpus
>>>>
>>>> Mild Shock schrieb:
>>>>> Well its called "artificial" intelligence.
>>>>> Like "atificial" flowers made from plastic
>>>>> try to share the look and feel of natural flowers,
>>>>>
>>>>> articial intelligence tries to share the
>>>>> look and feel of natural intelligence.
>>>>> AI is not really genetic engineering of
>>>>>
>>>>> bioforms, right? However, there is a research
>>>>> frontier sometimes called biocomputing or
>>>>> synthetic biology AI.
>>>>>
>>>>> Kunstblumen
>>>>> https://www.xxxlutz.ch/kunstblumen-C22C8C1
>>>>>
>>>>> The convergence of AI and synthetic biology: the looming deluge
>>>>> https://www.nature.com/articles/s44385-025-00021-1
>>>>>
>>>>> x schrieb:
>>>>>> On 3/7/26 03:08, Mild Shock wrote:
>>>>>>> Hi,
>>>>>>>
>>>>>>> Resolution of Erd˝os Problem #728
>>>>>>> We provide a writeup of a resolution of Erd˝os
>>>>>>> Problem #728; this is the first Erd˝os problem
>>>>>>> (a problem proposed by Paul Erd˝os which has
>>>>>>> been collected in the Erd˝os Problems website [3])
>>>>>>> regarded as fully resolved autonomously by an AI
>>>>>>> system. The system in question is a combination of
>>>>>>> GPT-5.2 Pro by OpenAI and Aristotle by Harmonic,
>>>>>>
>>>>>> I guess there is something called 'logic' and then
>>>>>> there is something called 'semantics'.
>>>>>>
>>>>>> Does it matter if words have meaning?  If the
>>>>>> answer is no - then of course you can generate
>>>>>> the look and feel of meaning through 'AI'.
>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
> 

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In 2028 BYD sells B100 performant laptop? (Re: Could ISAMORE anti-unification help?) Mild Shock <janburse@fastmail.fm> - 2026-06-09 20:13 +0800

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