Quantum Computing and Cryptocurrency
Previous articles have discussed the impact of quantum computing and potential security vulnerabilities in the future. One area of consideration is cryptocurrency. Encryption is fundamental to cryptocurrencies because it secures the private and public key relationship within the blockchain. Quantum computing is not yet powerful enough for malicious actors to exploit, but implications for cryptocurrency mining are worth considering.
Theoretically, quantum computers could mine coins much faster, reducing the time and work needed. This could potentially decrease the value of the coin. To mitigate this risk, the coin might adopt quantum-resistant encryption. Assuming quantum-resistant encryption is implemented, the comparison between Proof of Work (PoW) and Proof of Stake (PoS) becomes relevant.
Proof of Work involves significant computational effort to validate transactions and add new blocks to the blockchain. This method provides robust security but requires more energy and is slower.
Proof of Stake allows users with a small amount of cryptocurrency to participate in staking. In PoS, the more cryptocurrency a user holds and is willing to stake for network security, the higher their chances of validating transactions. This method is faster and less energy-intensive than PoW but may result in centralization by those who own the most coins.
Both methods have advantages and disadvantages. Although quantum computing is still developing, its future impact on cryptocurrency over the next decade is an important consideration.
AI doesn't truly 'learn'
Once the model is finalized and deployed, its 'learning' ceases, maintaining a static knowledge base until reconstructed with fresh data, incurring significant costs. Explore more insights in the article linked below:
"AI doesn't really learn and knowing why will help you use it more responsibly."
Read more at: https://lnkd.in/ghuriMtr
Exciting News: Amazon Introduces Alexa+ š
Amazon has unveiled Alexa+, a new and improved version of its voice assistant, designed to offer a more human-like interaction by utilizing advanced generative AI technology. This enhancement aims to make Alexa+ smarter and more intuitive, capable of seamlessly processing complex requests with its suite of large language models. Initially available in English, Alexa+ will launch early access next month, with Amazon Prime subscribers enjoying free access during this period. The system will be compatible with Echo smart devices, offering a smarter and more approachable AI experience that can stream music, recognize surroundings, and assist with everyday tasks. Alexa+ will start rolling out in the United States in the coming weeks, expanding accessibility to various regions over time.
What are your thoughts on this new development? Do you think Alexa+ will change the way we interact with AI assistants? š¤
Microsoft recently announced the development of their new quantum computing chip, Majorana 1. Advances in this field are occurring with increasing frequency, prompting discussions regarding its implications for AI models, cryptography, and financial modeling.
Quantum computing offers significantly greater speed compared to current silicon-based technology utilized in large data centers. With enhanced speed and parallel processing capabilities, it is possible to process larger and more complex models, thereby driving advancements in areas such as drug research and material science.
Companies are substantially investing to become leaders in AI technology, leveraging developments in quantum computing. Additionally, other nations are making substantial progress in both AI and quantum computing. This competitive landscape may present security risks if a nation succeeds in developing a quantum computer capable of compromising existing encryption technologies such as AES, SSL, digital signatures, and blockchain.
It is imperative that new encryption methods be developed and swiftly implemented to safeguard critical systems from vulnerabilities. To date, NIST has approved four ciphers that are resistant to quantum computing. It is essential for these quantum-resistant ciphers to be integrated into all equipment along the data stream. Historically, upgrading ciphers has been feasible; for example, IT teams globally have deprecated TLS 1.0 and transitioned to updated standards.
The emergence of quantum computing raises several significant questions: Is this new technology merely an impetus for another cipher upgrade? Will there be a necessity for new hardware? Furthermore, will these advancements be available before quantum computing becomes a practical reality? I invite you to share your perspectives and thoughts on these matters
Thoughts on the human impact on AI
Artificial Intelligence (AI) has garnered significant attention recently, prompting several important questions. As an IT professional, it is imperative to examine AI not only from a technical standpoint but also to understand its social implications to make informed decisions regarding its implementation and usage.
As with many technological advancements, there is a strong drive to dominate the market for financial gain and power. This competition often leads to consumers having to choose between rival products. While competition can spur innovation, it does not always result in benefits for consumers. Ideally, the most functional and effective product would prevail, but we do not live in a perfect world. Instead, various shades of gray affect outcomes. Opinions and preferences frequently influence facts, and disinformation has significantly infiltrated our daily information consumption. Factors such as emotion, perceived intangible value, status symbols, and political views contribute to the formation of opinions that may be erroneously regarded as facts. Advertisements permeate every aspect of our lives, further complicating our judgments and decisions.
Given these considerations, can AI truly be unbiased? Regrettably, achieving complete impartiality seems unlikely. Even if data is sourced openly, human tendencies can still obscure clarity. Therefore, I believe that AI can never be fully autonomous. Human intervention and oversight will be necessary to maintain checks and balances, presenting an interesting paradox.
In light of these observations, what are your thoughts on the unfolding developments in AI?