Quantum Computing

     AI is still at the top of my list of technologies which will change the world, and it is already beginning to happen. Another transformative technology further out but which is beginning to get press coverage is quantum computing. Quantum computers promise to revolutionize industries ranging from artificial intelligence to drug discovery. The terminology and techniques used in quantum computing is extremely complex but, in this blog post, I will summarize the key aspects of quantum computing, what it is, who are the key players in the field, the timeline for availability, and its potential benefits.

At its core, quantum computing is quite different than the binary framework of classical computers. Classical systems process information using bits, which exist in one of two states: 0 or 1. Quantum computers, on the other hand, use qubits (quantum bits), which can use a superposition of states, which means qubits can represent both 0 and 1 or both simultaneously. This allows quantum computers to perform multiple calculations at once, exponentially increasing their computational power compared to classical systems.

Quantum entanglement further enhances this capability by linking qubits in such a way that the state of one qubit directly influences the state of another, no matter the distance between them. This interconnectedness enables quantum computers to solve problems involving vast datasets or intricate simulations which would take classical computers millions of years to compute. Mind boggling?

The race to develop practical quantum computing technology has attracted a mix of tech giants and startups. Here are some of the key players:

  1. IBM is widely regarded as a leader in quantum computing. It has developed advanced systems like the 1,121-qubit Condor processor and aims to build a 100,000-qubit system by 2033. IBM also provides access to its quantum machines through the IBM Quantum Cloud platform and supports algorithm development with its open-source Qiskit framework.
  2. Google made headlines in 2019 by claiming “quantum supremacy” with its Sycamore processor. The company continues to push boundaries with plans to develop a million-qubit system within a decade.
  3. Microsoft is pursuing topological qubits through its Azure Quantum platform, aiming for fault-tolerant systems capable of performing millions of operations per second.
  4. Amazon is offering cloud-based access to various quantum hardware platforms while investing heavily in research and development.
  5. D-Wave specializes in quantum annealing, a method particularly suited for optimization problems.
  6. Formed by merging Cambridge Quantum Computing and Honeywell Quantum Solutions, Quantinuum focuses on applications in fields like chemistry and artificial intelligence.
  7. Known for its superconducting qubit technology, Rigetti offers a cloud platform called Forest for developing quantum algorithms.
  8. Xanadu, a Canadian company, focuses on photonic quantum computing and provides cloud-based tools for researchers and developers.

These companies are complemented by government initiatives across the globe. For example, China and the European Union have collectively invested billions into quantum research, while the United States has committed significant funding through initiatives like the National Quantum Initiative Act.

The timeline for widespread adoption of quantum computing remains uncertain but is progressing faster than many experts anticipated. Early-stage applications are already emerging in fields such as material modeling and optimization problems. For instance, IBM demonstrated a 127-qubit system could outperform classical computers in specific tasks like simulating molecular interactions.

Despite the huge investments, achieving fully scalable and fault-tolerant systems, capable of solving real-world problems at scale, may take another decade or more. IBM projects that its 100,000-qubit system could be operational by 2033, marking a significant milestone for the industry. Other estimates suggest practical large-scale systems might not arrive until closer to 2040 due to engineering challenges like error correction and qubit stability. In the meantime, hybrid approaches combining classical and quantum systems are being explored to deliver incremental benefits while full-scale quantum capabilities are developed.

Quantum computing has the potential to revolutionize numerous industries by addressing challenges previously unsolvable or computationally prohibitive. Here are some key benefits:

  1. Quantum computers can process large datasets more efficiently than classical machines, enabling faster training of AI models and more sophisticated algorithms for applications like natural language processing and image recognition.
  2. By simulating molecular interactions at an atomic level, quantum computers could accelerate drug discovery processes, leading to breakthroughs in treating diseases and developing new medicines.
  3. Financial institutions could use quantum computing for portfolio optimization, risk analysis, and fraud detection by processing complex datasets with unprecedented speed and accuracy.
  4. While quantum computers pose risks to current encryption methods, they also offer opportunities to develop new cryptographic techniques resistant to quantum attacks.
  5. Quantum simulations could improve our understanding of climate systems by analyzing intricate variables at scales impossible for classical supercomputers.
  6. Advances in material science enabled by quantum computing could lead to more efficient batteries for electric vehicles and renewable energy storage solutions.
  7. Businesses could optimize logistics networks and streamline supply chains more effectively using quantum algorithms tailored for large-scale optimization problems.
  8. The synergy between Internet of Things (IoT) devices and quantum computing could enable real-time data analysis for applications like smart cities or predictive maintenance in industrial settings.

Despite its immense promise, several obstacles remain before quantum computing can achieve mainstream adoption. The key challenges are reducing error rates, building systems with thousands or millions of qubits requires overcoming significant engineering challenges, developing and maintaining quantum hardware is very expensive, the field requires specialized expertise which is currently limited, and the ability of quantum computers to break existing encryption methods raises concerns about data security and privacy.

Quantum computing represents one of the most exciting frontiers in technology today. While practical applications are still emerging, progress is accelerating thanks to investments from industry leaders like IBM, Google, Microsoft, Amazon, and others. As these companies continue to push technological boundaries, we can expect transformative impacts across industries ranging from healthcare to finance and beyond within the next two decades.

In conclusion, though challenges remain, the potential benefits make it clear why governments and private enterprises alike are investing heavily in this groundbreaking field. By unlocking new possibilities for computation at an unprecedented scale, quantum computing has the potential not only to change how we solve problems but also how we understand our world itself.

Read more about technology at johnpatrick.com.

Note: I use Perplexity, ChatGPT, and Gemini AI chatbots as my research assistants. AI can boost productivity for anyone who creates content. Sometimes I get incorrect data from AI, and when something looks suspicious, I dig deeper. Sometimes the data varies by sources where AI finds it. I take responsibility for my posts and if anyone spots an error, I will appreciate knowing it, and will correct it.

In this section, I share what I am up to, pictures of the week, what is new in AI and crypto, and more.

Had very productive meetings with Dr. Wright et al at Nuvance Health Neuroscience Institute. We discussed use of ElliQ table top robot for those suffering from loneliness.  Also discussed use of AI for cognitive therapy.

Pizza oven from Italy at Fire in the Bricks restaurant in Palm Coast, FL

American Pizza with onions and mushrooms

Several notable developments in AI have occurred this week:

OpenAI Partnership with BNY:
US banking giant BNY has entered a multi-year partnership with OpenAI to enhance its proprietary AI platform, Eliza. This collaboration aims to integrate OpenAI’s advanced reasoning model and fine-tuning capabilities into BNY’s AI-powered solutions, potentially revolutionizing the bank’s global operations[7].

Anaconda’s Lumen AI:
Anaconda has announced Lumen AI, a new tool designed to make AI-powered analytics more intuitive and accessible. Lumen allows users to generate SQL queries, analyze datasets, and build interactive dashboards without writing code, streamlining data science workflows[3].

CTGT’s Venture Capital Funding:
CTGT has secured $7.2 million in venture capital funding for enterprise AI compute technology. This investment addresses the growing demand for AI compute power as enterprises move from proof-of-concept to production-scale AI projects[3].

Google’s AI Co-scientist:
Google has launched a new AI system called AI co-scientist, designed to assist experts in gathering research and refining their work. The tool aims to enhance the scientific process rather than automate it entirely[3].

NVIDIA’s AI Sign Language Tool:
NVIDIA has introduced a new AI tool for sign language learning. The system analyzes users’ signs and provides feedback, with a goal of expanding its database to 400,000 video clips representing 1,000 signed words[3].

Fortanix GenAI Data Security Report:
Fortanix has released its 2025 GenAI Data Security Report, highlighting that 97% of companies plan to implement GenAI solutions for business process automation or new revenue streams. However, 87% of security executives reported a breach in the past 12 months, emphasizing the need for robust data security measures[3].

GoDaddy’s AI Impact Study:
GoDaddy, in partnership with UCLA Anderson Forecast, has released a study quantifying the economic impact of AI on small businesses. The report aims to provide insights into AI’s present-day effects and implications for 2025[3].

These developments showcase the rapid advancements and diverse applications of AI across various sectors, from finance and research to accessibility and small business operations.

Several notable developments have occurred in the crypto market this week:

Bullish Market Sentiment:
On February 27, 2025, crypto analyst Altcoin Gordon predicted a bullish crypto market for the year. However, things are looking weak at the moment:

As of February 27, 2025, at 11:49 AM EST:
Bitcoin (BTC) price: $84,922.99

Ethereum (ETH) price: $2,310.50

Altcoin Performance:
Solana (SOL) and Cardano (ADA) experienced substantial growth, with SOL rising to $220 (up 7.3%) and ADA to $1.50 (up 5.5%) by 10:00 AM UTC on February 27[3].

AI-Driven Trading Impact:
The AI token SingularityNET (AGIX) experienced a 12% increase in trading volume to $200 million at 10:30 AM UTC on February 27, following the release of a new AI trading bot by the company. This surge indicates heightened investor interest in AI-driven projects[3].

New Cryptocurrency Launches:
Several new cryptocurrencies were launched recently, including B3 (Base), a Layer 3 gaming ecosystem; Wall Street Pepe (WEPE), a meme coin with trading signals; DIAM, a quantum-resistant blockchain; and Stool Prisondente (JAILSTOOL), a viral meme coin[4].

Regulatory Developments:
Iran’s government is considering imposing new levels of control and oversight on crypto amid deteriorating economic conditions. The Central Bank of Iran is proposing measures such as high levels of access to customer data and daily caps on cryptocurrency price fluctuations in rials[5].

Banking Sector Developments:
JPMorgan Chase announced plans to implement restrictions on Zelle payments due to scam risks. Starting March 23, the bank will request additional information on payments it believes originated through contact on social media platforms and may decline or block those payments[6].

These developments highlight the dynamic nature of the crypto market, with significant price movements, new project launches, regulatory challenges, and increasing integration of AI technologies in the crypto space.