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@triplepoints understandable tbh! i’ll be buying it used myself probably
personally i really love SuMo and USUM and let’s go is charming even if it’s a remake, but regardless the crunch to sync up game and merch/anime release is so obvious at this point and it’s a shame because so much creativity and work is stifled and rushed in favor of releasing on a quick date
Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
Free to watch • No registration required • HD streaming
I didn't know Dagoth was like an elder scrolls thing I just thought you just came up with a great occult aesthetic and decided that the baby's names icon was the perfect vessel for some demon glamour
hahahah no i just love the house dagoth aesthetic and i love the baby’s names buge so i fused them. at least you didn’t confuse my icon for the art angel’s creature like some people on here do.
triplepoints replied to your post: man i’ve been busy. hoo. im sorry also in personal...
Congrats! I know driving has been a source of anxiety for you so I’m sure this is a big step!
thanks!!!! yeah i'm learning to do it regularly just in case, mainly for my own wellbeing if somewhere doesn't have accessible or reliable public transport. also trying to be more independent I suppose.... hoo. thank you!
triplepoints replied to your post: ok another thing im disappointed w/ abt new...
What??? That’s like… a really big deal. Are we sure they don’t just mean until you beat the game/get national dex?
"Pokémon HOME can only transfer Pokémon to Sword & Shield if they appear in the Galar Pokédex." were there words. I assume maybe a future game will allow them but, as of now, only galar regional mons will be transferrable.
either that or, temporarily, you wont be able to transfer some mons until an eventual update or something. idk
triplepoints replied to your post: triplepoints replied to your post: ok another...
That’s potentially a dealbreaker for me. Like, I thought the upgrade in hardware would allow for less limitations on the number of pokemon. Not being able to transfer specific ones over kind of ruins the appeal.
what i'm super duper hoping for is that, maybe, it's just a temporary thing (like how pokebank was unavailable for like a month after XY released) until they update servers or systems. we can only hope at this point... I do hope for that
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triplepoints replied to your post “triplepoints replied to your post: Author you...”
fates came out chronologically directly after awakening. The series's issues didn't start with fates but they were certainly emphasized. Heroes is what made me drop the series ESPECIALLY after an in game event that made a 13 year old character from por and rd a "bride" as a class/title.
TRACS: The Future of Quantum Dot Calibration and Control
A Revolutionary AI Quantum Dot Control Method Scalable quantum computers require precise qubit manipulation, especially in semiconductor quantum dot systems. The laborious and complicated process of manually adjusting these devices has hampered our effort. This approach becomes impractical as qubits increase, causing a scaling constraint. Scientists have developed TRACS, a machine learning method that promises to autonomously, precisely, and adaptably tune quantum dots.
Fixing Quantum Dot Control Bottleneck Charge stability diagrams track electron behaviour in quantum dots, a potential spin-based quantum computing architecture. These diagrams must be accurately interpreted to manipulate qubits, quantum computer components. Conventional methods sometimes require multiple processing stages and have problems generalising across device types, making them unsuitable for future quantum processors. Due to the need for automated tuning and characterisation, machine learning, especially deep learning, has been extensively studied to optimise quantum dot device operating points. A New Transformer-Based End-to-End Paradigm
TRACS is a breakthrough machine learning technology that improves automatic interpretation of charge stability diagrams. Unlike other systems, TRACS is a single, end-to-end learning system, simplifying and increasing its applicability. TRACS relies on the transformer-based paradigm, first designed for natural language processing but now employed for visual object detection. This innovative model automatically identifies “triple points” and their linkages in charge stability diagrams. TRACS is a hardware-software quantum dot control approach that prioritises scalability. This end-to-end learning system directly addresses a major bottleneck in quantum dot manufacturing and control utilising object detection transformers, enabling more reliable and scalable quantum computer architectures. Determine Qubit Control Precision: Triple Points and Connectivity Finding “triple points” and how they relate in charge stability diagrams is not just a technical marvel, but it is also crucial for several critical qubit control tasks. These operations include: For precise voltage management, virtual gates must be calibrated.
Initialising charge states: Qubits start in a known state.
Adjusting for drift: Maintaining stability.
Control pulse sequencing: Quantum precision. Identifying these properties improves quantum device control efficiency and accuracy, enabling larger and more complex quantum processors. By abstracting charge stability diagrams into connection graphs, TRACS improves device characterisation and control and simplifies algorithm tweaking. Best Performance and Generalisation Across Architectures A highlight of TRACS is its unmatched performance and generalisation. Data from silicon, germanium, and silicon-germanium heterostructure quantum dot devices shows that it routinely beats well-known convolutional neural networks. TRACS is highly generalisable since it performs better without retraining for different device materials or topologies. TRACS efficiently locates triple spots with 3% voltage scan range accuracy. TRACS inference times are sometimes one to three orders of magnitude faster than CNNs. This breakthrough in precision, speed, and architecture-agnostic capability promises more dependable and scalable quantum dot control. Facilitating Quantum Computing Scalability This research supports the development of more reliable and efficient quantum dot-based computers. TRACS can automate and improve charge stability diagram analysis to speed up the construction of larger and more powerful quantum processors, ushering in the next wave of the Quantum Revolution. The system's simple, end-to-end learning method and suppleness in managing different device types help scale quantum computing technologies. Transfer learning may reduce the data needed for machine learning model training, which is important in quantum dot studies. The wider body of research suggests investigating this technique. Cutting-edge machine learning, complicated modelling tools, and cryogenic electronics are creating a vibrant and rapidly emerging market for scalable and programmable quantum dot devices.
The triple point of cyclohexane ⚗️ In thermodynamics, the triple point of a substance is the temperature and pressure at which the three phases of that substance coexist in thermodynamic equilibrium. That means, the substance exists as a liquid, solid and gas at the same time! . . Credits: @reactionchamber . . . . #sciencevideo #sciencevideos #scienceisawesome #triplepoints #interestingvideos #amazingvideos #chemistryexperiment #chemistryexperiments #chemistrylaboratory #cyclohexane #chemistrylovers #chemistryclass #chemistryteacher #chemistryteachers #chemicals #chemistry https://www.instagram.com/p/CBGN5y6jQGd/?igshid=k2o3pxdbrvuu
