Scientist worked out how to transfer data between two machines using quantum teleportation - Related to using, saudi, discuss, data, board
(PR) IBM & Lenovo Expand Strategic AI Technology Partnership in Saudi Arabia
IBM and Lenovo today revealed at LEAP 2025 a planned expansion of their strategic technology partnership designed to help scale the impact of generative AI for clients in the Kingdom of Saudi Arabia. IDC expects annual worldwide spending on AI-centric systems to surpass $300 billion by 2026, with many leading organizations in Saudi Arabia exploring and. Investing in generative AI use cases as they prepare for the emergence of an "AI everywhere" world. Building upon their 20-year partnership, IBM and Lenovo will collaborate to deliver AI solutions comprised of technology from the IBM watsonx portfolio of AI products, including the Saudi Data and Artificial Intelligence Authority (SDAIA) open-source Arabic Large Language Model (ALLaM). And Lenovo infrastructure. These solutions are expected to help government and business clients in the Kingdom to accelerate their use of AI to improve public services and make data-driven decisions in areas such as fraud detection, public safety, customer service, code modernization. And IT operations."Today's announcement represents an critical step in the longstanding relationship between IBM and Lenovo," revealed Giovanni Di Filippo, President of EMEA, Infrastructure Solutions Group at Lenovo. "We're pleased to deepen our partnership to bring IBM's fit-for-purpose generative AI offerings together with Lenovo's infrastructure solutions for both on-premises and cloud use to provide clients in Saudi Arabia with solutions designed to meet their unique needs in this fast-paced growing market."Organizations in Saudi Arabia are currently able to access ALLaM through watsonx; use advanced AI capabilities to train, tune, and. Deploy ALLaM; and run their AI workloads on Lenovo infrastructure for both on-premises and cloud use cases. The new solutions are expected to provide additional ways for clients to harness the power of Generative AI with an approach based on transparency, trust, and choice."IBM and. Lenovo have a rich history of joint innovation and partnership that spans two decades," revealed Ayman AlRashed, Regional Vice President, IBM Saudi Arabia. "We look forward to this new collaboration to bring together Lenovo's infrastructure offerings and IBM's AI portfolio, which utilizes small. Efficient, open-source models targeted for specific use cases and geographic requirements. Together we will drive even greater value for our mutual clients in the Kingdom."Statements regarding IBM's and Lenovo's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.
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Scientist worked out how to transfer data between two machines using quantum teleportation
Last week, researchers at Oxford University . They claim the distance is irrelevant as the experiment should have worked regardless of each computer's location. The breakthrough is remarkable as it partially solves a stumbling block in quantum computing.
Instead of transistors, like traditional computers, quantum computers use qubits. Qubits potentially allow for more options than the on/off of transistors, facilitating far more complex calculations. However, engineers have yet to figure out how to miniaturize the hardware, and it takes tens of thousands of qubits to perform complex calculations.
In the meantime. Researchers are trying to find ways to link multiple quantum computers to act as one unit. The idea is not dissimilar to distributed computing with traditional computers – connecting many computers on a network to work on one problem. Protein folding is an example. In fact, the research paper is titled "Distributed quantum computing across an optical network link."
However, quantum computers cannot communicate the same way PCs do. To network two (or more, theoretically) quantum computers, quantum objects must be positioned at the sending and receiving ends. Those objects must then become entangled. Entanglement sets both qubits to an unknown but connected state – think Schrödinger's Cat. Once the qubit's state is measured on the sending end, the entangled receiving qubit takes on the same state instantly.
Without getting deep into the complex operations of quantum computing. The act of entangling qubits on two or more machines in different locations indicates that it is possible to build a quantum network. Such interconnections can provide the necessary extra qubits to execute more complex programs and operations.
Furthermore, entangled data provides more accurate calculations. Transferring information from a quantum computer to a traditional machine that we can read and. Interpret presents a higher error rate – another hurdle scientists have struggled to mitigate. Transferring qubit states from one quantum computer to another is lossless, meaning researchers do not have to worry about errors until the linked computers return a result.
To achieve this breakthrough. The scientists created two ion traps (masthead) connected via a two-meter optical cable. Each trap held one strontium and one calcium ion. The calcium ion acted as a local memory unit, while the strontium acted as the interface of the quantum network. The optical cable allowed lasers to fire photons to kickstart entanglement.
Although entanglement was not 100 percent successful with every photon fired, a failure did not disrupt the states of the ions. So the researchers could keep trying without having to reset the entire experiment. Furthermore, entanglement produced a measurable photon, which signaled to the team that it achieved entanglement, a fortunate and. Significant byproduct.
Once entangled, the scientist could "teleport" specific gate operations to the receiving ions. After many rounds of testing Grover's algorithm, the team found the simple network returned accurate calculations about 70 percent of the time. However, they noted that the errors were unrelated to the teleportation process. As expected, local operations at either end of the hardware produced the mistakes. The team believes that using commercial quantum hardware will yeild more accurate results.
It is a groundbreaking development in quantum computing but. Is still in the early stages. While the teleportation is not limited by distance, it is limited to the length of optical cable available. It's unclear if it could use existing optical infrastructure, but it's doubtful, considering network noise could present an issue. Nevertheless, the fact that we have developed a way for quantum computers to exchange data instantly is astounding.
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Market Impact Analysis
Market Growth Trend
| 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|
| 4.9% | 5.9% | 6.2% | 6.9% | 7.3% | 7.5% | 7.6% |
Quarterly Growth Rate
| Q1 2024 | Q2 2024 | Q3 2024 | Q4 2024 |
|---|---|---|---|
| 6.9% | 7.2% | 7.4% | 7.6% |
Market Segments and Growth Drivers
| Segment | Market Share | Growth Rate |
|---|---|---|
| Semiconductors | 35% | 9.3% |
| Consumer Electronics | 29% | 6.2% |
| Enterprise Hardware | 22% | 5.8% |
| Networking Equipment | 9% | 7.9% |
| Other Hardware | 5% | 5.3% |
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity:
Competitive Landscape Analysis
| Company | Market Share |
|---|---|
| Apple | 18.7% |
| Samsung | 16.4% |
| Intel | 12.9% |
| NVIDIA | 9.8% |
| AMD | 7.3% |
Future Outlook and Predictions
The Lenovo Expand Strategic landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:
Year-by-Year Technology Evolution
Based on current trajectory and expert analyses, we can project the following development timeline:
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:
Innovation Trigger
- Generative AI for specialized domains
- Blockchain for supply chain verification
Peak of Inflated Expectations
- Digital twins for business processes
- Quantum-resistant cryptography
Trough of Disillusionment
- Consumer AR/VR applications
- General-purpose blockchain
Slope of Enlightenment
- AI-driven analytics
- Edge computing
Plateau of Productivity
- Cloud infrastructure
- Mobile applications
Technology Evolution Timeline
- Technology adoption accelerating across industries
- digital transformation initiatives becoming mainstream
- Significant transformation of business processes through advanced technologies
- new digital business models emerging
- Fundamental shifts in how technology integrates with business and society
- emergence of new technology paradigms
Expert Perspectives
Leading experts in the hardware tech sector provide diverse perspectives on how the landscape will evolve over the coming years:
"Technology transformation will continue to accelerate, creating both challenges and opportunities."
— Industry Expert
"Organizations must balance innovation with practical implementation to achieve meaningful results."
— Technology Analyst
"The most successful adopters will focus on business outcomes rather than technology for its own sake."
— Research Director
Areas of Expert Consensus
- Acceleration of Innovation: The pace of technological evolution will continue to increase
- Practical Integration: Focus will shift from proof-of-concept to operational deployment
- Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
- Regulatory Influence: Regulatory frameworks will increasingly shape technology development
Short-Term Outlook (1-2 Years)
In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing hardware tech challenges:
- Technology adoption accelerating across industries
- digital transformation initiatives becoming mainstream
These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.
Mid-Term Outlook (3-5 Years)
As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:
- Significant transformation of business processes through advanced technologies
- new digital business models emerging
This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.
Long-Term Outlook (5+ Years)
Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:
- Fundamental shifts in how technology integrates with business and society
- emergence of new technology paradigms
These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.
Key Risk Factors and Uncertainties
Several critical factors could significantly impact the trajectory of hardware tech evolution:
Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.
Alternative Future Scenarios
The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:
Optimistic Scenario
Rapid adoption of advanced technologies with significant business impact
Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.
Probability: 25-30%
Base Case Scenario
Measured implementation with incremental improvements
Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.
Probability: 50-60%
Conservative Scenario
Technical and organizational barriers limiting effective adoption
Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.
Probability: 15-20%
Scenario Comparison Matrix
| Factor | Optimistic | Base Case | Conservative |
|---|---|---|---|
| Implementation Timeline | Accelerated | Steady | Delayed |
| Market Adoption | Widespread | Selective | Limited |
| Technology Evolution | Rapid | Progressive | Incremental |
| Regulatory Environment | Supportive | Balanced | Restrictive |
| Business Impact | Transformative | Significant | Modest |
Transformational Impact
Technology becoming increasingly embedded in all aspects of business operations. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.
The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.
Implementation Challenges
Technical complexity and organizational readiness remain key challenges. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.
Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.
Key Innovations to Watch
Artificial intelligence, distributed systems, and automation technologies leading innovation. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.
Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.
Technical Glossary
Key technical terms and definitions to help understand the technologies discussed in this article.
Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.
quantum computing intermediate
RAM intermediate
algorithm intermediate
interface intermediate
platform intermediate
SSD intermediate
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