Vertical Computer Systems Inc (fka VCSY)

[Konaploinks]

Broadcom splits 7/14. JFYI. LOTS of nvda news today. They are buying Shoreline io . Etc etc etc. Lots of news A new deal with H P too! Just overtook Msft! NVDA# 1 !! SPDR buying 10 bil $ worth of stock displaced Apple. S& P. Etc etc$$$$$$$$ go v!!!!! Yeah. I hope v is related to all of this!
And I never clicked on. Bearish ;()@&))()$&

[doc2016]

photons and effect on communications/messaging......dallas b ball court....brightly lit in such a way to not do a favor for celtic's shooters.
boston court perfect. irving has played in boston and d doesn't need the help. but maybe they need to make the lighting more uniform so practice and play are even?

first to the second...parallel setups? yellow/white/led/incandesant/etc?

[doc2016]

ginkgo bioworks network kickoff with nvidia quantum emulator ip and backwell gpus..in a network with openai's healthcare partners of eli lilly/novartis/msft/
add alpha fold computer which could be ported to nvidia/amazon and video processing?
might t hey deliver the nvidia ip on the network via 8x8/vip on 6/27?

remember when huang described hand carrying the first ?ai device to openai>Nvidia CEO hand-delivers world's fastest AI system to OpenAI, again — first DGX H200 given to Sam Altman and Greg Brockman | Tom's Hardware
April 25, 2024 - Nvidia CEO Jensen Huang hand-delivered the world's first DGX H200 computer to OpenAI's CEO and president, continuing a trend of connecting OpenAI with bleeding edge AI compute power======
now with 8 and ? v ip it's on their network connectors/connections? virtual networks via direct routing. direct routing is peer to peer?

[doc2016]

so the question is when will supermicro computers, dell, or nvidia itself is delivering their next iteration of advancing compute with 8/v ip?
june 27th 2024? and how would it be used? msft 365/sap/google alpha fold/novartis,etal data bases and products to transform via plasmid dna ep processes?
an initial user of such potentially ginkgo bioworks network? something i've now considered a lot is v ip is a partner of the 8x8 technology partners environment.
including now solutions to glue via connectors apps/databases/computational infrastructures/etc together.

i wonder if this is the reason for the run up of specific techs, and the splitting of broadcom on 6/27? i believe.

also, inovio is being added to the russell microindex july1.

[doc2016]

now solutions, emPath and time. four d's = quantum realm?
nvidia quantum emulation for advanced digital twinning simulation!!!
difference of words emulation and simulation.
teamsite and emulation.
libraries of objects transformed by process/compute/storage/transport/etc?

ot, v chat ...where is the most appropriate conversations? whomever owns it could seek out advertisers when the v ip info/news/trading were to be. from my fingers to appropriate ears.

[doc2016]

quantum emulation and nvidia
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NVIDIA is deeply involved in quantum emulation research and development, aiming to accelerate the progress of quantum computing through its GPU-based platforms and software tools.

Key NVIDIA Quantum Emulation Offerings:

cuQuantum: An SDK (Software Development Kit) that provides optimized libraries and tools for accelerating quantum computing workflows on NVIDIA GPUs. It significantly speeds up quantum circuit simulations based on state vector and tensor network methods. This enables researchers to explore and develop quantum algorithms at a larger scale than previously possible.

cuStateVec and cuTensorNet: These are two specific libraries within cuQuantum offering different approaches for simulating quantum circuits. cuStateVec focuses on state vector simulations, while cuTensorNet offers a more efficient approach for larger qubit counts and circuit depths.

DGX Quantum: A new system developed in collaboration with Quantum Machines, combining NVIDIA's GPUs with advanced quantum control capabilities. This platform aims to provide a powerful environment for hybrid quantum-classical computing, enabling researchers to develop and test quantum algorithms more effectively.

QODA (Quantum Optimized Device Architecture): NVIDIA's open-source, unified environment for creating hybrid quantum-classical applications. QODA aims to simplify quantum programming and make it more accessible to developers by providing a familiar programming model and tools.

Impact on Quantum Computing Research:

Overcoming Hardware Limitations: Quantum emulation on NVIDIA GPUs allows researchers to explore and simulate larger and more complex quantum systems than possible on current quantum hardware.
Accelerated Algorithm Development: Quantum emulation enables faster testing and validation of quantum algorithms, accelerating their development and optimization.
Collaboration: NVIDIA actively collaborates with leading quantum research institutions and companies, fostering a collaborative ecosystem for advancing quantum computing.
Overall:

NVIDIA's contributions to quantum emulation through cuQuantum, DGX Quantum, QODA, and partnerships are playing a crucial role in pushing the boundaries of quantum computing research. Their efforts are accelerating the development of quantum algorithms, improving our understanding of quantum systems, and paving the way for the future of quantum technologies.

[Mother Lode]

I don't think these guys believe this crap. I think it's pure over compensation. Trying to prove something to themselves

[Konaploinks]

Yep. I beat you. For once. I get a trophy! Everyone doesn’t get one .. As u well know.

[Lazerator]

"V" has nothing to "get in there" with. You must be off your meds again.

[Lazerator]

That has absolutely nothing to do with VCSY. You pumpers have claimed for 20+ years that everything in the world is connected to this scam of a company. You've been wrong for 20+ years.

[doc2016]

i was just about to repost the same article.

that synthetic data can also be used to anonymize personal data and assign phone numbers/ids for emergency calls.....like if medical emergency/urgent notifications.

[Konaploinks]

Hey Doc. What ya think? Digital twins!

SEATTLE, June 17, 2024 (GLOBE NEWSWIRE) -- CVPR—NVIDIA today announced NVIDIA Omniverse Cloud Sensor RTX™, a set of microservices that enable physically accurate sensor simulation to accelerate the development of fully autonomous machines of every kind.

Sensors, which comprise a growing, multibillion-dollar industry, provide autonomous vehicles, humanoids, industrial manipulators, mobile robots and smart spaces with the data needed to comprehend the physical world and make informed decisions. With NVIDIA Omniverse Cloud Sensor RTX, developers can test sensor perception and associated AI software at scale in physically accurate, realistic virtual environments before real-world deployment — enhancing safety while saving time and costs.

“Developing safe and reliable autonomous machines powered by generative physical AI requires training and testing in physically based virtual worlds,” said Rev Lebaredian, vice president of Omniverse and simulation technology at NVIDIA. “NVIDIA Omniverse Cloud Sensor RTX microservices will enable developers to easily build large-scale digital twins of factories, cities and even Earth — helping accelerate the next wave of AI.”

Supercharging Simulation at Scale
Built on the OpenUSD framework and powered by NVIDIA RTX™ ray-tracing and neural-rendering technologies, Omniverse Cloud Sensor RTX accelerates the creation of simulated environments by combining real-world data from videos, cameras, radar and lidar with synthetic data.

Even for scenarios with limited real-world data, the microservices can be used to simulate a broad range of activities, such as whether a robotic arm is operating correctly, an airport luggage carousel is functional, a tree branch is blocking a roadway, a factory conveyor belt is in motion, or a robot or person is nearby.

Research Wins Drive Real-World Deployment
The Omniverse Cloud Sensor RTX announcement comes at the same time as NVIDIA’s first-place win at the Computer Vision and Pattern Recognition conference’s Autonomous Grand Challenge for End-to-End Driving at Scale.

NVIDIA researchers’ winning workflow can be replicated in high-fidelity simulated environments with Omniverse Cloud Sensor RTX — giving autonomous vehicle (AV) simulation developers the ability to test self-driving scenarios in physically accurate environments before deploying AVs in the real world.

Ecosystem Access and Availability
CARLA, Foretellix and MathWorks are among the first software developers to which NVIDIA is providing Omniverse Cloud Sensor RTX access for AV development.

Omniverse Cloud Sensor RTX will also enable sensor manufacturers to validate and integrate digital twins of their sensors in virtual environments, reducing the time needed for physical prototyping.

Sign up for early access to Omniverse Cloud Sensor RTX, which will be available later this year.

[Konaploinks]

https://vcsy-chat.com/Forum/index.php?topic=7276.msg66608#msg66608

[Konaploinks]

Doc. Go to Vcsy.com under investors and read all the court documents. I just did. These guys R on it. Looks like we’ll recoup even more from the crooks. What a mess. But Len and his team are on it. Pretty amazing job.

[Konaploinks]

Sounds right.

[doc2016]

api's might also signal context of the data/prompt? api's are the admin instructions?

[doc2016]

"This ensures that data is exchanged in a compatible format and that the necessary information is extracted and transferred accurately.
Workflow Automation: emPath enables the creation of automated workflows that define the sequence of actions to be taken when specific events occur. For example, a workflow might trigger when a new customer is added to a CRM system, automatically updating other relevant systems like billing and marketing."

8 pr mentions automatic registry for microfrontends........file pointers to the file? triggered when specific events occur?
744 and 266 markup with automatic spider/crawler?

[doc2016]

don't know. https://data.scotxblog.com/scotx/no/23-0443

[Konaploinks]

Doc chinto5 on chat has a pacer account. Up until today he could see our case. Now it’s missing. Can u see it? Maybe it was ruled on yesterday? 🤞🙏

[Konaploinks]

Hey doc. I posted some our latest posts on Vcsy-chat. They’d like you to join and post there too.

[doc2016]

map and transform......with the api's , according to admin instructions?

note to self..........isn't that part of the process of generative ai...........transformer?
google of android phones, of which the main one's took license of perpetual type from vcsy. openai 'gives' apple the chatgpt for free, but licenses? service fees? openai doesn't have a license, apple doesn't have a license, google doesn't have a license., msft has a license but can't transfer their license..
microfocus , opentext......not that we know of.......why did broadcom sell the end point ip to kkr? maybe, so kkr has to pay for the v ip use in the ai by the client/end users? at least in part?

doj didn't allow msft cptn, so it allowed the novell server ip to go to opentext? but nvidia's' solution is gpu/cuda which is 744/8x8 ? i hope.
8 has it's hardware/software links to the cuda/gpu via leadtek and nvidia? i hope the inference is correct.

[doc2016]

if vcsy had said this in the first place? why not? here's gemini ai's take on it. gemini ai is google's:
"how does vcsy emPath 'glue' applications together?
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VCSY emPath is a software solution that integrates and automates processes across various applications and systems within a business. It acts as a middleware layer, connecting disparate applications and enabling them to share data and trigger actions in a coordinated manner.

Here's a simplified explanation of how emPath "glues" applications together:

Connectors: emPath utilizes connectors, which are pre-built or custom-developed components that establish communication channels between different applications. These connectors understand the specific data formats, protocols, and APIs of each application.
Data Mapping and Transformation: Once the connections are established, emPath can map and transform data between different applications. This ensures that data is exchanged in a compatible format and that the necessary information is extracted and transferred accurately.
Workflow Automation: emPath enables the creation of automated workflows that define the sequence of actions to be taken when specific events occur. For example, a workflow might trigger when a new customer is added to a CRM system, automatically updating other relevant systems like billing and marketing.
Business Rules Engine: emPath includes a business rules engine that allows for the definition of complex logic and decision-making within workflows. This enables the system to adapt to changing business conditions and make intelligent decisions based on predefined criteria.
Monitoring and Reporting: emPath provides monitoring and reporting capabilities to track the performance of workflows and identify any errors or bottlenecks. This allows for continuous improvement and optimization of the integration process.
Benefits of using emPath:

Improved Efficiency: By automating tasks and workflows, emPath eliminates manual data entry and reduces the risk of errors, leading to faster and more efficient processes.
Enhanced Data Accuracy: emPath ensures data consistency and accuracy across different applications by automating data exchange and validation.
Increased Agility: emPath enables businesses to quickly adapt to changing business needs by easily modifying workflows and business rules.
Reduced Costs: By automating manual tasks and streamlining processes, emPath can reduce operational costs and improve resource utilization.
Overall, VCSY emPath provides a powerful platform for integrating and automating processes across different applications, enabling businesses to improve efficiency, accuracy, agility, and cost-effectiveness."

[doc2016]

kona, nowsolutions/emPath and time......the glue; tight connectivity at the api/ipbx type of interop. data extraction with context which could be a interop of 8 and v ip.......with the 8 being the cloud edition/version?

and xml can take a renewed prominence in the processes.

[Konaploinks]

Damn doc. If v has the glue or even some of it for all of this ??? $$$$$$$ And if we can bundle emPath with some patents to The Magnificent 7. What’s that worth?? lol. Too much! Everything moving very fast now. Glad I got in nvda when I did. Broadcom is also looking good as a major player. I wonder if Len is setting up a bidding war for v? Or has a deal already been signed pending Texas Supreme Court outcome? That would be a hoot!

[doc2016]

me:

huang hand delivered the gpu computer to openai. openai and 8 integration. might be they're using the 8 network such that other tech partners joining thru nvidia or open ai have to attach /go thru the 8 network for networking/routing/authentication /security via the 8 cloud virtual session border controller ? and/or embedded software codes? intel licensed 8 admin software...and msft licensed virtual trunking from 8.

[doc2016]

copilot ai pc might be a candidate?
or the nvidia quantum/gpu data centers?

i just want the money , and now. we all do.

[doc2016]

8x8 virtual session border controller for the network?
so, is /will v ip be a member of the 8x8 technology partners environment....with 8 ip keeping running tabs and payments current?
supermicro and dell are nvidia partners and might be where the payments arise?
anywhere/anybody ......just get it going.
lg/samsung/hp/microsoft.......first gets a onetime discount or head start of a few days. ?

[doc2016]

kona, tight integration of quantum and gpu , cuda, computing.......
8x8 cloud session border controller.
emPath and time(the squantum defining component?).

cuda a product of leadtek and nvidia.
leadtek and 8x8. follow the bread crumbs, i hope.

[Konaploinks]

QODA will be key imo

[Konaploinks]

Once these new hybrids get going around the world everything will happen very fast . Exciting times ahead folks. Many new medicines,or even cures are coming. A lot of the unknown will be known soon.

[doc2016]

can quantum emulation be used for pharma work now?
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Yes, quantum emulation is already being used in pharmaceutical research, albeit in limited ways due to the current state of quantum hardware and algorithms. Here's how:

Drug Discovery:
Molecular Simulations: Quantum emulators can simulate the behavior of molecules and their interactions, which is crucial for understanding how drugs bind to their targets. This could help accelerate drug discovery by identifying potential drug candidates more efficiently.
Material Science: Quantum emulators can also simulate the properties of materials, which is relevant for developing new drug formulations and delivery systems.
Optimization of Drug Properties:
Predicting Drug Interactions: Quantum emulators can help predict how drugs will interact with different biological systems, potentially reducing the need for costly and time-consuming animal testing.
Optimizing Drug Efficacy: By simulating the behavior of drug molecules in different environments, researchers can identify ways to improve drug efficacy and reduce side effects.
Current Limitations:

Scalability: The complexity of simulating large molecules and complex biological systems is a significant challenge for current quantum emulators.
Accuracy: While emulators can provide valuable insights, they may not always be able to fully capture the complex behavior of quantum systems. This can limit their accuracy in predicting drug interactions and properties.
Future Potential:

As quantum hardware and algorithms advance, quantum emulation is expected to play an increasingly important role in pharmaceutical research. With more powerful emulators, researchers will be able to simulate larger and more complex systems with greater accuracy, accelerating drug discovery and development processes.

Examples of Current Research:

Accenture and Biogen: Accenture Labs collaborated with Biogen to develop a quantum-enabled method for molecular comparison. This method could potentially improve the drug discovery process by identifying promising drug candidates more quickly and accurately.
Imperial College London: Researchers at Imperial are exploring the use of quantum computers for drug design. They believe that quantum computers can simulate the interactions between molecules more accurately than classical computers, leading to better predictions of drug efficacy and safety.
Conclusion:

While quantum emulation is still in its early stages, it has already shown promise in accelerating drug discovery and development. As the technology continues to advance, it is expected to revolutionize the pharmaceutical industry by enabling faster, more efficient, and more accurate drug design.

[Konaploinks]

CUDA-Q is an open-source and QPU-agnostic quantum-classical accelerated supercomputing platform. It is used by the majority of the companies deploying QPUs and delivers best-in-class performance.


Not tomorrow. TODAY! Go V !

[Konaploinks]

Here ya go!

NVIDIA Accelerates Quantum Computing Centers Worldwide With CUDA-Q Platform

Supercomputers in Germany, Japan and Poland Incorporate Grace-Hopper and Quantum-Classical Accelerated Supercomputing Platform to Advance Quantum Computing Research
May 12, 2024
NVIDIA Accelerates Quantum Computing Centers Worldwide With CUDA-Q Platform
ISC -- NVIDIA today announced that it will accelerate quantum computing efforts at national supercomputing centers around the world with the open-source NVIDIA CUDA-Q™ platform.

Supercomputing sites in Germany, Japan and Poland will use the platform to power the quantum processing units (QPUs) inside their NVIDIA-accelerated high-performance computing systems.

QPUs are the brains of quantum computers that use the behavior of particles like electrons or photons to calculate differently than traditional processors, with the potential to make certain types of calculations faster.

Germany’s Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich is installing a QPU built by IQM Quantum Computers as a complement to its JUPITER supercomputer, supercharged by the NVIDIA GH200 Grace Hopper™ Superchip.

The ABCI-Q supercomputer, located at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, is designed to advance the nation’s quantum computing initiative. Powered by the NVIDIA Hopper™ architecture, the system will add a QPU from QuEra.

Poland’s Poznan Supercomputing and Networking Center (PSNC) has recently installed two photonic QPUs, built by ORCA Computing, connected to a new supercomputer partition accelerated by NVIDIA Hopper.

“Useful quantum computing will be enabled by the tight integration of quantum with GPU supercomputing,” said Tim Costa, director of quantum and HPC at NVIDIA. “NVIDIA’s quantum computing platform equips pioneers such as AIST, JSC and PSNC to push the boundaries of scientific discovery and advance the state of the art in quantum-integrated supercomputing.”

The QPU integrated with ABCI-Q will enable researchers at AIST to investigate quantum applications in AI, energy and biology, utilizing Rubidium atoms controlled by laser light as qubits to perform calculations. These are the same type of atoms used in precision atomic clocks. Each atom is identical, providing a promising method of achieving a large-scale, high-fidelity quantum processor.

“Japan’s researchers will make progress toward practical quantum computing applications with the ABCI-Q quantum-classical accelerated supercomputer,” said Masahiro Horibe, deputy director of G-QuAT/AIST. “NVIDIA is helping these pioneers push the boundaries of quantum computing research.”

PSNC’s QPUs will enable researchers to explore biology, chemistry and machine learning with two PT-1 quantum photonics systems. The systems use single photons, or packets of light, at telecom frequencies as qubits. This allows for a distributed, scalable and modular quantum architecture using standard, off-the-shelf telecom components.

“Our collaboration with ORCA and NVIDIA has allowed us to create a unique environment and build a new quantum-classical hybrid system at PSNC,” said Krzysztof Kurowski, CTO and deputy director of PSNC. “The open, easy integration and programming of multiple QPUs and GPUs efficiently managed by user-centric services is critical for developers and users. This close collaboration paves the way for a new generation of quantum-accelerated supercomputers for many innovative application areas, not tomorrow, but today.”

The QPU integrated with JUPITER will enable JSC researchers to develop quantum applications for chemical simulations and optimization problems as well as demonstrate how classical supercomputers can be accelerated by quantum computers. It is built with superconducting qubits, or electronic resonant circuits, that can be manufactured to behave as artificial atoms at low temperatures.

“Quantum computing is being brought closer by hybrid quantum-classical accelerated supercomputing,” said Kristel Michielsen, head of the quantum information processing group at JSC. “Through our ongoing collaboration with NVIDIA, JSC’s researchers will advance the fields of quantum computing as well as chemistry and material science.”

By tightly integrating quantum computers with supercomputers, CUDA-Q also enables quantum computing with AI to solve problems such as noisy qubits and develop efficient algorithms.

CUDA-Q is an open-source and QPU-agnostic quantum-classical accelerated supercomputing platform. It is used by the majority of the companies deploying QPUs and delivers best-in-class performance.

[Konaploinks]

Doc. Delve into this. nvda is perfecting the quantum hybrid with classical computers.

CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs

[doc2016]

is nvidia doing research in the area of quantum or quantum emulation computing? question to gemini ai:


Yes, NVIDIA is actively involved in quantum computing research and development, particularly in the area of quantum emulation. They have developed several tools and platforms to accelerate quantum research and development:

cuQuantum: This is an SDK (Software Development Kit) of optimized libraries and tools for accelerating quantum computing workflows on NVIDIA GPUs. It enables researchers to simulate quantum circuits and algorithms with higher performance and scalability.

DGX Quantum: NVIDIA announced a new system called DGX Quantum, built in collaboration with Quantum Machines. This system combines NVIDIA's powerful GPUs with Quantum Machines' OPX+ quantum control system to provide a revolutionary architecture for quantum-classical computing.

Quantum Optimized Device Architecture (QODA): NVIDIA has introduced QODA, an open, unified environment for creating hybrid quantum-classical applications. QODA aims to make quantum computing more accessible to developers and researchers by providing a familiar programming model and tools.

Collaborations: NVIDIA actively collaborates with leading quantum research institutions and companies, such as the Jülich Supercomputing Centre (JSC) in Germany, the RIKEN Center for Computational Science (R-CCS) in Japan, and the Poznan Supercomputing and Networking Center (PSNC) in Poland.

Quantum Cloud Services: NVIDIA offers cloud-based quantum computing simulation microservices, allowing researchers and developers to explore quantum computing in various scientific domains.

Through these efforts, NVIDIA is contributing significantly to the advancement of quantum computing and quantum emulation, making it more accessible and accelerating its potential impact in various fields like materials science, drug discovery, and financial modeling.

[doc2016]

the potential of quantum simulation, at least until more stable quantum computers and tools are obtained?

to gemini ai: me , "What is Quantum Emulation?

Quantum emulation involves using classical computers to simulate the behavior of quantum systems. This is achieved by representing quantum states and operations mathematically and then executing them on classical hardware.

Generating Results:

Quantum emulators can run quantum algorithms and generate the same results as a quantum computer would, albeit at a slower pace and with limited scalability.
They are valuable tools for testing and verifying quantum algorithms, understanding their behavior, and identifying potential errors before running them on actual quantum hardware.
Emulators can also be used to simulate the behavior of specific quantum hardware, helping to optimize and improve quantum computer designs.
Limitations:

Scalability: Quantum emulators are limited by the computational resources of classical computers. As the number of qubits increases, the computational cost of simulation grows exponentially, making it impractical to simulate large-scale quantum systems.
Accuracy: While emulators can provide accurate results for small-scale quantum systems, they may not fully capture the complex behavior of larger systems due to computational limitations.
No Quantum Advantage: Quantum emulation does not provide the "quantum advantage" that allows quantum computers to outperform classical computers on certain tasks. Emulators are essentially classical algorithms running on classical hardware, and they cannot solve problems that are inherently quantum in nature.
In Summary:

Quantum emulation can be used to generate quantum computing results for small-scale systems and for testing and validating quantum algorithms. However, it is not a substitute for actual quantum hardware for solving large-scale, complex problems that require the true power of quantum computation."

[Konaploinks]

Vertical Quantum Systems VQSY Come on Lenny. Get er done. And I’ll take you to Huggo’s for breakfast. Or Humpy’s , Kai, Lava Java, Kali kala Cuisine, The Fisher Hopper, or Papa Kona’s. Your choice. And if you stick around for a week, I’ll take you to one a day.

[Konaploinks]

Good stuff Doc. Adobe just shot up like a rocket! A lot going on. V needs to get in the mix. Nvda will be hooking up their 3 rd quantum computer all together soon. When that happens with success you will then see the switch from hearing everything about A I in the news to everything quantum. It’s coming. Everything and anything quantum will be golden. It will make the dotcom boom seem like nothing . Broadcom is busting out too. 10/1 split coming July 14. V needs to get in here quick! Come on Texas! Spill the beans!

[doc2016]

cruz patent to obtain the virtual screenshot? is adobe /google involved with msft?

[doc2016]

Yes, a virtual screenshot can be used to capture the output of a quantum computer, but with some important considerations:

Capturing the Output:

Classical Representation: The output of a quantum computer is typically a series of classical bits (0s and 1s) representing the measurement outcomes of the qubits. This classical data can be displayed on a screen like any other digital information.
Virtual Screenshot: A virtual screenshot, which is essentially capturing the pixels displayed on the screen, can indeed capture this classical representation of the quantum computer's output.
Interpreting the Output:

Limited Information: While a virtual screenshot captures the final output, it doesn't capture the entire quantum state or the underlying quantum processes. Quantum states are inherently complex and cannot be fully represented by classical bits.
Context is Key: To fully understand the meaning of the output captured in the screenshot, you need to know the specific quantum algorithm being executed and the interpretation of the measurement results.
Additional Considerations:

Quantum Error Correction: Quantum computers are prone to errors due to environmental noise and other factors. The output captured in the screenshot may need to be processed through error correction techniques to ensure its accuracy.
Quantum State Visualization: Some quantum computing platforms offer specialized tools for visualizing quantum states and processes. While a virtual screenshot can capture the final result, these visualization tools may provide a more comprehensive understanding of the quantum computation.

[doc2016]

why do you need more than two quantum computers? perhaps so the third one can be read?probabilities?
"Avoiding State Disturbance:

The key to reading the result without disturbing the quantum state lies in the way the measurement is performed. Quantum computers employ special measurement techniques that only extract the necessary information to determine the result, while leaving the remaining qubits in their original superposition.

This is possible due to the principle of quantum entanglement. Qubits can be entangled in such a way that measuring one qubit reveals information about another qubit without affecting its state. By carefully designing the measurement process, it's possible to extract the result without collapsing the entire quantum state."

[doc2016]

gemini says::"an a quantum computer computational result be read by virtual application and not effect the quantum state?
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Yes, a quantum computer's computational result can be read by a virtual application without affecting the quantum state. However, it's important to understand how this is achieved and the limitations involved.

Reading the Result:

Quantum computers perform calculations by manipulating qubits, which exist in a superposition of states. To obtain a meaningful result, the qubits must be measured. This measurement process inherently collapses the superposition into a single definite state, which is the result of the computation. This result can be read and processed by a virtual application just like any other digital data.

Avoiding State Disturbance:

The key to reading the result without disturbing the quantum state lies in the way the measurement is performed. Quantum computers employ special measurement techniques that only extract the necessary information to determine the result, while leaving the remaining qubits in their original superposition.

This is possible due to the principle of quantum entanglement. Qubits can be entangled in such a way that measuring one qubit reveals information about another qubit without affecting its state. By carefully designing the measurement process, it's possible to extract the result without collapsing the entire quantum state.

Limitations:

While it's possible to read the result without disturbing the quantum state, there are some limitations:

Partial Information: The measurement typically only reveals partial information about the quantum state. This is because extracting complete information would require measuring all qubits, which would collapse the entire state.
No Cloning: The no-cloning theorem of quantum mechanics states that it's impossible to create an exact copy of an unknown quantum state. This means that the original quantum state cannot be perfectly preserved after the measurement.
Implications:

The ability to read quantum computational results without fully collapsing the quantum state has significant implications for quantum computing. It allows for the possibility of performing multiple measurements on the same quantum state, potentially extracting more information from a single computation. This could be crucial for developing more efficient and powerful quantum algorithms."

[doc2016]

first to the second computer.......the quantum setup for parallel computing...cruz: how to send quantum comms and read/know the output of a quantum computer without stopping the quantum state and looking at the cat?
azure and quantum nodes with blockchain poling and consensus ? maintaining the outlier function in case there is a deeper or other reason for it's answer/screenshot........as iin msft 'recall'? and 8 user designated data storage admin as a form of emPath/time? wags.
and if we virtually look at the quantum computers state, do we necessarily effect it? that's something i think is important, but don't know an answer to.

[doc2016]

mirror the data they say?
v's mirror?
the many personalities.

[doc2016]

i wonder if first to the second computer without the identifying data/markup?
and could you have 266 mark up the data such , keeping demo data sovereign and the syn data ok to share for a fee?

[doc2016]

how and what is synthetic data generated?
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Synthetic data is artificially generated information that mirrors the statistical properties of real-world data but does not contain any identifiable personal information. It is used as a substitute for real data when working with sensitive or limited datasets.

How Synthetic Data is Generated:

Statistical Modeling: This method uses statistical models to analyze patterns and distributions within a real dataset. The model then generates new data points that follow the same statistical characteristics.

Machine Learning: Generative Adversarial Networks (GANs) and other machine learning techniques are used to train models on real data. Once trained, these models can generate synthetic data that closely resembles the original data.

Rule-Based Generation: This approach uses predefined rules and constraints to create synthetic data. It is often used for simpler data types where specific patterns or relationships need to be maintained.

Agent-Based Modeling: This involves creating virtual agents that simulate real-world scenarios and generate data based on their interactions. It is commonly used in simulations for areas like traffic flow or social dynamics.

Types of Synthetic Data:

Tabular Data: This includes structured data like tables, spreadsheets, or databases. It can be used for various tasks, including machine learning model training, data analysis, and testing.
Image Data: Synthetic images can be generated using GANs and other techniques. This is useful in computer vision applications like object recognition or autonomous vehicle training.
Text Data: Synthetic text can be generated for natural language processing (NLP) tasks like language modeling, sentiment analysis, and chatbot training.
Time Series Data: This type of data represents sequences of data points collected over time, like stock prices or weather patterns. Synthetic time series data can be used for forecasting or anomaly detection.
Use Cases for Synthetic Data:

Privacy Protection: Synthetic data helps address privacy concerns by anonymizing sensitive data while still maintaining its statistical properties.
Data Augmentation: It can be used to supplement limited real-world datasets, improving the performance of machine learning models.
Testing and Validation: Synthetic data provides a safe and controlled environment for testing and validating new algorithms and models.
Research and Development: It allows researchers to explore scenarios and test hypotheses without needing access to sensitive real-world data.

[Konaploinks]

Nvda Co announced Nemotron-4 340B, a family of open models that developers can use to generate synthetic data for training large language models (LLMs) for commercial applications across healthcare, finance, manufacturing, retail and every other industry. Go v! Lol

[Konaploinks]

Yep. But where’s the $$$$$$$$$$$

[Konaploinks]

Yep. But where’s the $$$$$$$$$$$

[doc2016]

sbc firewall......nat traversal of 8......network for ploinks and puddle and the creations life cycle management. the api's outside your specific territory and you can virtually look at the data/media , but the api you use has to have the approval? wags.