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Di Alex (del 27/04/2024 @ 17:56:44, in Universo Apple, letto 535 volte)
Differenze principali tra Mac Mini M1 e M2:
CPU e GPU:
M1: CPU 8-core (4 performance e 4 efficiency) e GPU 7-core.
M2: CPU 8-core (4 performance e 4 efficiency) e GPU 10-core.
Prestazioni:
M2: Fino al 18% più veloce in CPU single-core e fino al 35% più veloce in GPU rispetto all'M1.
M2 Pro: Fino a 1,9 volte più veloce in CPU e fino a 2,4 volte più veloce in GPU rispetto all'M1.
Memoria:
M1: Supporta fino a 16GB di memoria unificata.
M2: Supporta fino a 24GB di memoria unificata.
Media Engine:
M2: Un media engine più potente per la gestione di video ProRes, H.264 e HEVC, con supporto a flussi multipli fino a 8K.
Connettività:
M1: Wi-Fi 6 e Bluetooth 5.0. M2: Wi-Fi 6E e Bluetooth 5.3.
Altre differenze:
M2: Supporta un display esterno aggiuntivo fino a 8K (M1 supporta fino a 6K). M2: Porta Gigabit Ethernet integrata da 10Gb (M1 ha una porta Gigabit Ethernet).
Benchmark:
Nei test, il Mac Mini M2 con chip base ha mostrato un miglioramento medio del 12% rispetto all'M1 nei test single-core e fino al 20% nei test multi-core.
Le prestazioni per attività specifiche come la transcodifica video ProRes in Final Cut Pro sono fino a 2,4 volte più veloci su M2 Pro rispetto all'M1.
Le prestazioni in Adobe Photoshop sono fino al 50% più veloci su M2 Pro rispetto all'M1.
In generale, il Mac Mini M2 offre prestazioni migliori in CPU, GPU e media engine rispetto all'M1. Ha anche una migliore connettività e supporta più memoria e display esterni. Il Mac Mini M2 Pro offre prestazioni ancora migliori, ma a un prezzo più alto.
Quale Mac Mini scegliere dipende dalle tue esigenze e dal tuo budget.
Se ti serve un computer desktop base per attività quotidiane come la navigazione web, l'email e l'elaborazione di testi, l'M1 è un'ottima scelta. Se hai bisogno di più potenza per attività come l'editing video o fotografico, il rendering 3D o il gaming, l'M2 o l'M2 Pro sono una scelta migliore.
[Fonte: Macrumors]
Ottima videorecensione di HDBlog.it!
Di Alex (del 01/01/2024 @ 00:00:01, in Giochi intelligenti, letto 18221 volte)
ProteusSF-Aureo closed PRIVATE betatester program is completed!
Please don't ask it even as betatester, I'll release it under GPLv3 once the AI-modules will be ready!
OFFERING only PC, Mac M1|Intel & Android compilation of Stockfish and all open sources engines. ASK ME TO DO THE JOB FOR YOU FOR 10€!!
ProteusSF FREE DEMO public release ProteusSF-Piranha 15.1 (with GPLv3 source)
updated to last Stockfish 15.1 + Polybook support
I'm developing next-gen ProteusSF with Artificial Intelligence
After 3 months of developing in C++ I'm starting my first tests of ProteusSFX-AI !!! First implementation: A supervisor asks to Bard and ChatGPT APIs the best strategy according to the opening when out of the book, then ProteusSF applies some pre-configuted patterns. Eg It doesn't try to win against C67 with White. No learning anymore, contestual analysis in real time that is much faster! Like some leading chess programs, such as AlphaZero and Leela Chess Zero, that already use LLM to improve their performance. LLM can be used to improve chess programs in a number of ways. First, LLM can be used to generate new game ideas. This can be done by using LLM to analyze a wide range of chess positions and identify possible moves that could lead to an advantage. Second, LLM can be used to evaluate the strength of a chess position. This can be done by using LLM to analyze the possible moves of both sides and determine which position is more advantageous. Third, LLM can be used to learn from chess games played by humans. This can be done by using LLM to analyze the games and identify the strategies and tactics that were used to win. Some of the specific ways in which LLM can be used to improve chess programs include: Move generator: LLM can be used to generate new game ideas that might not have been considered by a traditional chess engine. Position evaluation: LLM can be used to evaluate the strength of a chess position more accurately than a traditional chess engine can. Learning from chess games: LLM can be used to learn from chess games played by humans more efficiently than a traditional chess engine can. Chess programs that use LLM have been shown to be able to beat traditional chess programs. For example, AlphaZero beat Stockfish, which was considered the best chess engine in the world at the time, in a series of games. It is likely that LLM will continue to improve the performance of chess programs. As LLM technology continues to develop, chess programs that use LLM will become even stronger. Additional information: LLM stands for "large language model". It is a type of artificial intelligence (AI) that is trained on a massive dataset of text and code. LLMs can be used for a variety of tasks, including generating text, translating languages, writing different kinds of creative content, and answering questions in an informative way.
Update February 28, 2023: LATEST BUILD 23.5 ProteusSF-Sunrise including an optimized ProteusSF-Sunrise.exp is ready for internal tests!!
Stockfish-dev derivative plus Polybook .bin, MCTS support and Learning. Stronger than ever, holds Stockfish and every derivative. Choice
Contempt, Pure|Hybrid|Classical no NNUE, Positional or Materialistic style!
CLOSED BETA For Microsmeta.com internal PRIVATE TESTERS only!
(GPLv3 PS-23.5 DIRTY source *Linrock architecture still MISSING*)
Very good performance online on Playchess.com running on PCs with only 4 cores against Core i7, Ryzen 7, Ryzen 9, Xeon on ThreadRipper boosted engines up to 128 threads ...beyond AI and Zeus 50.3, Corchess 4, LC0, ShashChess and BrainLearn, Crystal 6, Stockfish 16-dev, Dragon 3.2, Eman 9.40, Charisma, Hypnos, Dark Sister, SF PB and ToreroX3Pro!!!
December 16 2022 - Christmas GIFT: ProteusSF-Piranha 15.1 (with GPLv3 source)
updated to last Stockfish 15.1 + Polybook support
-->CROWDFUNDING FREE COMMUNITY EDITION 221216 RELEASE:
Since October ProteusSF-Piranha-221016 & Sunrise will be private
I have no budget for free developing & hosting server costs Microsmeta.com private testers will still receive last closed betas via email
- Stockfish-Polybook 15.1
- CorChess3.0-Polybook
- Crystal-Polybook 5 KWK 221106
and my custom compilations of your desired engines...Donating only 10 Euro for each one and specifying in the donation comment for which operating system and version (PC avx2, bmi2, sse41, sse3 or oldPC | Android ARMv8, ARMv7 or Intel | Mac M1 or Intel ) you need to be compiled for you! You will receive it quickly on your email
VISIT BanksiaGui ProteusSF dev Forum with all development news and tests (ENGLISH ONLY) featuring TCEC 2022 (Most reliable chess engines tournament worldwide)
& |
PAID HOSTING COSTS UP TO 12/2023 THANKS TO DONATIONS