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Quantum Logic Gates: The Next Frontier in Computing Technology

Quantum logic gates, the fundamental building blocks of quantum computing, are poised to revolutionize the field of computing technology. As the world becomes increasingly reliant on digital information and the processing power of computers, the need for more advanced computing systems has become evident. Classical computers, which operate using binary bits that represent either a 0 or a 1, have limitations in their ability to solve complex problems and perform calculations at high speeds. Quantum computing, on the other hand, leverages the principles of quantum mechanics to process information in a fundamentally different way, opening up new possibilities for solving problems that were previously considered intractable.

At the heart of quantum computing are quantum bits, or qubits, which can exist in multiple states simultaneously, thanks to a phenomenon known as superposition. This allows quantum computers to perform multiple calculations at once, vastly increasing their processing power compared to classical computers. Additionally, qubits can be entangled, a unique property that allows them to be correlated with one another in such a way that the state of one qubit can instantly affect the state of another, regardless of the distance between them. This phenomenon, known as quantum entanglement, is another key aspect of quantum computing that enables it to outperform classical computing systems.

Quantum logic gates are the devices that manipulate the states of qubits, allowing them to perform operations and calculations. These gates are analogous to classical logic gates, which perform operations on binary bits in classical computers. However, quantum logic gates operate on qubits and take advantage of their unique properties, such as superposition and entanglement, to perform operations that are not possible with classical logic gates. As a result, quantum logic gates have the potential to unlock a new frontier in computing technology, enabling the development of quantum computers that can solve problems and perform calculations at speeds and scales that were previously unimaginable.

One of the most significant applications of quantum computing technology is in the field of cryptography. Modern encryption methods, which are used to secure digital information and communications, rely on the difficulty of factoring large numbers into their prime components a task that is incredibly time-consuming and resource-intensive for classical computers. However, quantum computers, with their vastly superior processing power, could potentially crack these encryption methods in a fraction of the time, rendering current cryptographic techniques obsolete. This has led to a race among researchers and technology companies to develop new encryption methods that can withstand the power of quantum computing.

Another promising application of quantum computing is in the field of artificial intelligence and machine learning. The ability of quantum computers to process vast amounts of data simultaneously could significantly accelerate the development of more advanced AI algorithms and enable the creation of more sophisticated machine learning models. This, in turn, could lead to breakthroughs in fields such as natural language processing, computer vision, and autonomous systems.

Despite the immense potential of quantum computing, there are still numerous challenges that must be overcome before this technology can be fully realized. One of the most significant obstacles is the issue of error correction, as quantum systems are highly susceptible to errors due to their delicate nature and sensitivity to external factors. Researchers are actively working on developing error-correcting codes and fault-tolerant quantum computing architectures to address this issue.

In conclusion, quantum logic gates represent the next frontier in computing technology, with the potential to revolutionize fields such as cryptography, artificial intelligence, and many others. As researchers continue to make progress in overcoming the challenges associated with quantum computing, we can expect to see a new era of technological advancements that will reshape the way we process and interact with digital information.

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Quantum Logic Gates: The Next Frontier in Computing Technology - CityLife

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Barely a week passes without another dramatic report about humanity and the planet reaching a climate change tipping point. The latest reports were a heart-stopping analysis from the World Meteorological Organization and arresting criticism from the UN Secretary-General. Both were shared in the final days of April.

Artificial Intelligence will determine whether we blow through the tipping point or row back from the brink.

AI is one of the significant tools left in the fight against climate change. AI has turned its hand to risk prediction, the prevention of damaging weather events, such as wildfires and carbon offsets. It has been described as vital to ensuring that companies meet their ESG targets.

Yet, its also an accelerant. AI requires vast computing power, which churns through energy when designing algorithms and training models. And just as software ate the world, AI is set to follow.

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AI will contribute as much as $15.7 trillion to the global economy by 2030, which is greater than the GDP of Japan, Germany, India and the UK. Thats a lot of people using AI as ubiquitously as the internet, from using ChatGPT to craft emails and write code to using text-to-image platforms to make art.

The power that AI uses has been increasing for years now. For example, the power required to train the largest AI models doubled roughly every 3.4 months, increasing 300,000 times between 2012 and 2018.

This expansion brings opportunities to solve major real-world problems in everything from security and medicine to hunger and farming. It will also have a punitive impact on climate change.

Computing goes hand-in-hand with high energy costs and a larger carbon footprint, which tap the accelerator pedal on the worlds climate change.

This is especially true for AI. The huge number of GPUs running machine learning algorithms get hot and need to be cooled; otherwise, they melt. Training even one large language model (LLM) requires an eye-watering amount of energy with a large carbon footprint.

For example:

As we move into the GPT4 era and the models get larger, the energy needed to train them grows. GPT-3 was 100 times larger than its predecessor GPT, and GPT-4 was ten times the size of GPT-3. All the while, larger models are being released quicker. GPT-4 arrived in March 2023, nearly four months after ChatGPT (powered by GPT-3.5) was released at the end of November 2022.

For balance, we shouldnt assume that as new models and companies emerge in the space AIs carbon footprint will continue growing. Geeta Chauhan, an AI engineer at Meta, is using open-source software to reduce the operational carbon footprint of LLMs. Her latest work shows a 24-fold reduction in carbon emissions compared with GPT-3.

However, AIs popularity and its exponential power undermine much of the climate action in force today and call into question its potential to be part of the solution.

We need a solution that allows AI to flourish while arresting its carbon footprint. So, what do we do?

As always, technology will drag us out of this predicament.

For the explosion of AI to be sustainable, advanced computing must come to the fore and do the heavy lifting for many tasks that are currently performed by AI. The good news is that we already have advanced computing technologies that are primed to execute these tasks more efficiently and quickly than AI, with the added benefit of using much, much less energy.

In short, advanced computing is the most effective tool we have to temper AIs carbon addiction. With it, we can slow the creep of climate change.

There are a number of different technologies in advanced computing emerging that can solve some of the problems AI is currently tackling.

For example, quantum computing is superior to AI in drug discovery. As humans live longer, they are encountering, in ever greater numbers, new diseases that are complex and untreatable. This is called the better than The Beatles problem, where new drugs have modest improvements on already successful therapeutics.

So far, drug development has focused on rare events within a dataset and making educated guesses to design the right drugs to target and bind to the proteins that cause disease. LLMs can be efficiently used to help with this task.

LLMs are remarkably good at predicting which words in our vocabulary can best fit a sentence to accurately convey meaning. Drug discovery isnt wildly dissimilar as the problem is identifying the best fit, or configuration, of molecules in a compound to get a therapeutic result.

However,molecules are quantum elements, so quantum computing is much better at tackling this problem. Quantum computing has the capacity to quickly simulate vast numbers of binding sites in medicines to create the right configuration for treating currently incurable diseases.

Quantums capabilities mean that these can be solved much faster and with much less energy usage.

Another development with a real possibility to be an enhancement to AI is photonics, or so-called optical computing, which uses laser-produced light instead of electricity to send information.

Some companies are building computers that use this technology, which is much more energy-efficient than most other computing technologies and is being recognized increasingly as a route to achieving Net Zero.

Elsewhere, we have neuromorphic computers. This is a type of computer engineering where elements of the computer system are modeled on those in the human brain and nervous system. They perform computations to replicate the analog nature of our neural system. Trials of this technology include projects by Mythic and Semron. Neuromorphic is another greener option that needs further investment. Its hardware has the potential to run large deep learning networks that are more energy-efficient than comparable classical computing systems.

For example, processing information through its hundred billion neurons consumes only 20 watts, similar to an energy-saving light bulb in a home.

Developing and applying these innovations are imperative if we are to apply the brakes on climate change.

There are many startups (and investors) around the world obsessed with advanced computing but there are just a handful of companies that are focusing on so-called impact areas like healthcare, the environment and climate change.

Within quantum computing, the most-exciting companies that are developing use cases for energy and drug discovery are Pasqal (its cofounder was awarded the Nobel Prize in Physics 2022), Qubit Pharmaceutical and IBM. When it comes to photonics, we view the leaders with global impact as Lightmatter and Luminous, while in neuromorphic computing, we are tracking the progress of Groq, Semron and Intel.

Advanced computing is vital for achieving the energy efficiency we need to fight climate change. It simply takes too long and is too energy-intensive to run artificial neural networks on a GPU.

By adopting advanced computing methods as alternatives to AI, businesses can greatly alleviate the impact that AI has on the environment while still ensuring its vast power can mitigate some of the impacts of climate change, like anticipating wildfires or extreme weather.

The existential endpoint is approaching for our environment. But the situation is not hopeless.

The deployment of advanced computing is one credible and powerful resource to counteract the problem. We need to invest in these technologies now to solve the greatest challenge facing humanity.

Francesco Ricciuti is a VC at Runa Capital.

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Energy in the Quantum World: Understanding the Requirements of Quantum Computers

Quantum computing has been a hot topic in the world of technology for quite some time now. The potential of quantum computers to revolutionize industries such as cryptography, drug discovery, and artificial intelligence has led to a surge in research and development in this field. However, one aspect that is often overlooked is the energy requirements of these powerful machines. As we delve deeper into the quantum world, it is crucial to understand the energy needs of quantum computers and the challenges that lie ahead in making them a reality.

Quantum computers operate on the principles of quantum mechanics, which is fundamentally different from classical physics. In classical computing, information is stored and processed in bits, which can be either a 0 or a 1. Quantum computers, on the other hand, use qubits, which can be both 0 and 1 simultaneously, thanks to a phenomenon known as superposition. This allows quantum computers to perform complex calculations at an exponentially faster rate than classical computers.

However, the power of quantum computing comes at a cost. The delicate nature of qubits requires them to be maintained in a highly controlled environment, isolated from any external disturbances. This is because qubits are extremely susceptible to decoherence, a process in which the quantum state of a qubit is lost due to interactions with its surroundings. To prevent decoherence, quantum computers need to be cooled to temperatures close to absolute zero (-273.15 degrees Celsius), which requires a significant amount of energy.

In addition to cooling, quantum computers also require energy for error correction. Due to the inherent instability of qubits, quantum computers are prone to errors, which can significantly impact the accuracy of their calculations. To overcome this challenge, researchers have developed various error correction techniques that require additional qubits and energy resources. As the number of qubits in a quantum computer increases, so does the need for error correction, leading to a higher energy demand.

The energy requirements of quantum computers pose a significant challenge to their large-scale implementation. While research is ongoing to develop more energy-efficient quantum computing technologies, it is essential to consider the environmental impact of these powerful machines. The energy consumption of data centers, which house classical computers, already accounts for about 1% of global electricity use, and this number is expected to grow as our reliance on technology increases. If quantum computers were to replace classical computers, the energy demand could potentially skyrocket, putting immense pressure on our already strained energy resources.

One possible solution to the energy challenge in quantum computing is the development of hybrid systems that combine the best of both classical and quantum computing. These systems would use quantum computers for specific tasks that require their unique capabilities, while relying on classical computers for other tasks. This approach could help minimize the energy consumption of quantum computers while still harnessing their immense computational power.

Another avenue of research is focused on developing new materials and technologies that can support quantum computing at higher temperatures. This would reduce the need for extreme cooling and potentially make quantum computers more energy-efficient. However, this research is still in its early stages, and it remains to be seen whether it will yield practical solutions.

In conclusion, the energy requirements of quantum computers are a critical aspect that needs to be addressed as we move closer to realizing their potential. While the challenges are significant, ongoing research and development in this field hold the promise of finding innovative solutions to make quantum computing more energy-efficient and environmentally sustainable. As we continue to explore the quantum world, it is essential to keep in mind the energy implications of this groundbreaking technology and strive to develop solutions that balance both performance and sustainability.

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Energy in the Quantum World: Understanding the Requirements of ... - EnergyPortal.eu

Bitcoin Gold has unique features that make it an intriguing platform for smart contract applications. In this article, we delve into the exciting world of Bitcoin Gold and its potential synergy with smart contracts. Try Immediate Fortune if you really want considerable profits from this market in a short time.

One of the main advantages of integrating smart contracts on the Bitcoin Gold network is the enhanced security it offers. Bitcoin Gold utilizes the Equihash algorithm, which is resistant to specialized mining hardware known as ASICs. This characteristic ensures a more decentralized mining process and reduces the risk of centralization, enhancing the security of smart contracts executed on the network.

Additionally, Bitcoin Gold's robust and well-established infrastructure provides a solid foundation for the implementation of smart contracts. Its active and dedicated developer community continually works to improve the platform and expand its capabilities. Leveraging this existing infrastructure, and integrating smart contracts becomes a natural progression, enabling developers to leverage the security and reliability of Bitcoin Gold while exploring new possibilities.

Another crucial aspect to consider is the potential for interoperability between Bitcoin Gold and other blockchain networks. Cross-chain interoperability allows smart contracts executed on Bitcoin Gold to interact with other blockchain platforms, enabling a seamless exchange of assets and data. This interoperability can open up a wide range of applications, including decentralized finance (DeFi) protocols, decentralized exchanges, and cross-border transactions.

Furthermore, integrating smart contracts on the Bitcoin Gold network can unlock opportunities for the tokenization of real-world assets. By creating digital representations of physical assets, such as real estate or commodities, on the Bitcoin Gold blockchain, these assets can be easily traded, fractionalized, and managed in a transparent and secure manner.

However, it is important to acknowledge that implementing smart contracts on Bitcoin Gold also comes with certain challenges. Bitcoin Gold's primary focus has been on being a store of value and a medium of exchange, rather than a smart contract platform. As a result, modifications and upgrades to the Bitcoin Gold protocol may be necessary to fully support the complexities of smart contract execution.

One crucial aspect is the development of a specialized programming language and development framework for smart contracts on Bitcoin Gold. Ethereum, for example, uses Solidity as its primary programming language. Similarly, Bitcoin Gold would require a language specifically designed for writing smart contracts that can run on its network. This language should be user-friendly, secure, and efficient to facilitate the widespread adoption and development of smart contracts on the platform.

Additionally, the availability of development tools and documentation plays a vital role in enabling developers to create, deploy, and test smart contracts on Bitcoin Gold. A comprehensive development toolkit, including integrated development environments (IDEs), debugging tools, and deployment frameworks, would simplify the process and attract more developers to build on the platform. Clear and extensive documentation, along with code examples and tutorials, would further enhance the accessibility and understanding of smart contract development on Bitcoin Gold.

Interoperability with other blockchain networks is another critical consideration. Smart contracts executed on Bitcoin Gold should be able to interact seamlessly with contracts and protocols on other blockchain platforms. This requires the establishment of standardized communication protocols and cross-chain bridges that enable the transfer of assets, data, and instructions between different blockchain networks. Interoperability opens up opportunities for cross-chain decentralized applications (DApps) and broader ecosystem integration.

Scalability is a fundamental concern when it comes to executing smart contracts on any blockchain network, including Bitcoin Gold. As smart contracts typically involve multiple computations and interactions, the network must handle a significant number of transactions simultaneously. To address scalability challenges, Bitcoin Gold may need to implement solutions like layer-two scaling techniques, such as state channels or sidechains, which can offload some of the computational burdens from the main chain while maintaining security and decentralization.

Another critical aspect is security. Smart contracts are subject to vulnerabilities, such as coding errors or malicious attacks, which can result in financial losses or exploitation of the network. Bitcoin Gold should prioritize security measures, including rigorous auditing, testing frameworks, and best practices for secure smart contract development. Implementing formal verification methods, which mathematically prove the correctness of smart contract code, can further enhance security and mitigate potential risks.

Integrating smart contracts onto the Bitcoin Gold network presents a promising frontier for blockchain technology. With enhanced security, existing infrastructure, interoperability, and potential for asset tokenization, Bitcoin Gold offers unique possibilities for decentralized applications. While technical considerations and challenges exist, exploring smart contracts on Bitcoin Gold can shape a future where programmable money and innovative applications thrive.

(Disclaimer: Devdiscourse's journalists were not involved in the production of this article. The facts and opinions appearing in the article do not reflect the views of Devdiscourse and Devdiscourse does not claim any responsibility for the same.)

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Unraveling the Potential of Smart Contracts in Bitcoin Gold - Devdiscourse

The Bitcoin blockchain is a complex system of varying protocols. Two protocols, Stacks and Ordinals, are often mistaken for one another or lumped in as the same thing. However, there are some key differences between Stacks and Ordinals that you should be aware of.

Smart contracts are a key component of decentralized finance (DeFi). These programs can automatically execute an agreement so long as a specific set of pre-written conditions are fulfilled. Smart contracts remove the need for third parties or intermediaries and add to DeFi's trustless model.

Smart contracts began on Ethereum but have since been adopted by many other blockchains, including Solana, Stellar, and Waves. And now, even the crypto industry's biggest player, Bitcoin, has delved into this useful technology through Stacks.

Stacks (formerly known as Blockstack) is a Layer-2 solution implemented on the Bitcoin blockchain in 2018. Since then, it has undergone its second mainnet launch, giving way to the Stacks we know today.

Stacks is linked to the Bitcoin blockchain via its proof of work consensus mechanism. While Ethereum is often known as the prime place for using smart contracts, Stacks brings a similar capability to Bitcoin.

The official Stacks whitepaper states it "enables smart contracts and decentralized applications to trustlessly use Bitcoin as an asset and settle transactions on the blockchain." Put simply; Stacks lets you use smart contracts and decentralized applications (DApps), features that were not previously present on the Bitcoin blockchain.

Many DeFi applications, such as automatic market makers (MMs) and liquidity pools, need smart contracts to function. So, without such capabilities, Bitcoin remains very limited in what it can offer. With Stacks, and therefore smart contracts, many doors are opened.

While Stacks is a Bitcoin Layer-2 solution, it does not use the proof of work mechanism. Rather, it uses something known as proof of transfer. Proof of transfer is a modified version of proof of burn. By burning their STX tokens (which we'll discuss later), miners can mine on the Stacks blockchain.

The Stacks whitepaper also reveals that the name "Stacks" is an acronym. Here's what each letter stands for:

As you can see, the Stacks solution focuses on several elements, including security, scalability, and trust. The protocol's Clarity smart contracts protects users from bugs and exploits.

Stacks does not allow the creation of Bitcoin-based NFTs, as it is a Layer-2 solution. However, its smart contract abilities can be used in NFT trades. Stacks also has its own NFT marketplace, wherein all products are priced with STX.

The Stacks protocol also comes with its own crypto asset, STX. We briefly mentioned this crypto previously, but it's important to understand its purpose and functionality within the Stacks ecosystem.

STX is used to pay network fees, conduct payments within Stacks-based DApps, and reward miners for securing the blockchain.

The Stacks protocol has its own network of important contributors, including miners. Miners must burn their STX tokens to mine via the proof of transfer mechanism. However, for a Stacks block to be mined, a Bitcoin transaction must first take place on the original blockchain. For each Stacks block, there must be a Bitcoin block it is linked to.

Throughout early and mid-2023, Bitcoin Ordinals became a very hot crypto topic.

Many choose Ethereum over Bitcoin simply because the former blockchain offers so much more. Ethereum has long since been known as the prime blockchain for NFT creation, minting, and sales, whereas the Bitcoin blockchain serves as the ledger used for Bitcoin transactions. In short, Bitcoin wasn't very versatile.

However, many Bitcoin enthusiasts have been eager to tackle this versatility issue with some useful blockchain solutions, including Stacks and Ordinals. We already know what Stacks is, but Ordinals brings a whole new element to the game: Bitcoin NFTs.

The Bitcoin Ordinals protocol launched in January 2023. This is a Layer-1 protocol used for numbering satoshis. Like Stacks, Ordinals gives the Bitcoin blockchain extra capabilities, but the two are not one and the same.

Bitcoin NFTs, or Bitcoin Ordinals, are made using satoshis. Satoshis are tiny fractions of single BTC coins, with one Bitcoin containing 100,000,000 satoshis. Though minuscule, satoshis can transfer data, which can then be tracked.

This is done by inscribing data onto the satoshi, a process made possible by the Ordinals protocol. By attaching extra data to an individual satoshi, such as comments or messages, a non-fungible token (NFT) is effectively made. For instance, a satoshi could be inscribed with information on a digital file's location, making it an NFT.

However, because the Bitcoin blockchain does not use smart contracts, neither do Ordinals. This separates Bitcoin NFTs and other well-known NFT-capable blockchains like Ethereum, Solana, and Cardano.

Though Ordinals is a 2023 phenomenon, it was made possible via the 2021 Bitcoin Taproot update, which enabled satoshi inscription.

It's easy to confuse Stacks and Ordinals due to their similarities, but both protocols have different applications. So, when should you use either of these Bitcoin solutions?

If you want to utilize smart contracts using Bitcoin, Stacks is your solution.

Say, for example, you want to create, mint, or trade Stacks-based NFTs or secure your NFTs using Bitcoin's protection. Via the Stacks protocol, this is all possible. Additionally, you can use Stacks to create decentralized apps, which isn't directly possible on the Bitcoin blockchain.

If, on the other hand, you want to create or trade Bitcoin-based NFTs, the Ordinals protocol will serve you well. Because Ordinals is a Layer-1 solution rather than Layer-2, it allows for the generation of non-fungible tokens directly on the Bitcoin blockchain, not a separate chain like Stacks.

Though Stacks and Ordinals have different natures and purposes, it is undeniable that both solutions offer their own great perks. If you love Bitcoin but also want to reap the benefits of DeFi and all its versatility, both of these protocols may serve you well.

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Bitcoin Stacks vs. Ordinals: What's the Difference? - MUO - MakeUseOf