After Apple's "worldwide developers conference in June, we went looking for possible "suppliers" for the new "Apple Intelligence" and "Apple vision pro"!

 

During its June 2024 Worldwide Developer Conference (WWDC), Apple introduced a new feature called "Apple Intelligence." This initiative represents Apple's latest efforts in integrating advanced AI and machine learning capabilities across its ecosystem.

"Apple Intelligence" is designed to enhance the user experience by providing more personalized and context-aware services. Here are some key aspects highlighted during the announcement:

1. Contextual Assistance: Apple Intelligence offers deeper contextual understanding, enabling Siri and other Apple services to better understand user intent, respond more accurately to complex queries, and provide more relevant suggestions based on the user's habits, preferences, and environment.

2. On-device Processing: Emphasizing privacy, Apple Intelligence processes data primarily on-device, ensuring that sensitive information remains secure and under the user's control. This approach also allows for faster and more efficient AI-driven features, as data doesn't need to be sent to the cloud for processing.

3. Integration Across Devices: Apple Intelligence seamlessly integrates across Apple's ecosystem, including iPhones, iPads, Macs, and the new Vision Pro. This cross-device intelligence allows for a more unified experience, where Apple's services can anticipate user needs and provide a consistent experience, no matter which device is being used.

4. Enhanced Siri: The capabilities of Siri have been significantly improved with Apple Intelligence, making it more responsive and capable of handling more complex tasks, such as multi-step commands and predictive suggestions based on user behavior.

5. Personalized Experiences: By leveraging machine learning, Apple Intelligence can create more personalized experiences, whether through content recommendations, tailored notifications, or adaptive interfaces that respond to the user's specific preferences.

This introduction of Apple Intelligence is seen as part of Apple's broader strategy to leverage AI and machine learning to differentiate its products and services, while maintaining a strong emphasis on user privacy and security.

"Apple Intelligence," which encompasses advanced AI and machine learning capabilities across Apple's ecosystem, relies heavily on a combination of in-house technologies and components from various suppliers. While Apple designs much of the software and custom hardware for its AI capabilities, several key companies supply the underlying technologies that enable Apple Intelligence to function effectively. These companies provide components ranging from processors and sensors to machine learning software tools.

Here are some of the primary companies that likely supply technology products used in Apple Intelligence:

1. TSMC (Taiwan Semiconductor Manufacturing Company): TSMC manufactures Apple's custom-designed chips, including the A-series and M-series processors. These chips are critical for on-device AI processing, enabling the machine learning features that drive Apple Intelligence.

2. Broadcom: Broadcom supplies wireless communication components and chips that support Wi-Fi and Bluetooth connectivity, crucial for the seamless operation of Apple devices in the Apple Intelligence ecosystem.

3. Qualcomm: While Apple designs its own chips, Qualcomm has supplied modems for cellular connectivity, which are vital for real-time data processing and AI-driven tasks that require internet access.

4. Sony: Sony is a key supplier of camera sensors used in Apple's devices. These sensors, combined with Apple's image processing algorithms, enable advanced computer vision capabilities that are part of Apple Intelligence, such as object recognition and augmented reality.

5. Lumentum Holdings Inc.: Lumentum provides VCSEL (Vertical-Cavity Surface-Emitting Laser) components used in 3D sensing and facial recognition technologies, like Face ID, which are integrated into the Apple Intelligence framework.

6. Cirrus Logic: Cirrus Logic supplies audio chips and codecs that support voice recognition, a key component of Apple Intelligence features like Siri.

7. Synaptics: Synaptics provides touch and display driver technology, which is integral to the user interface aspects of Apple Intelligence, ensuring smooth and responsive interactions.

8. Cadence Design Systems and Synopsys: These companies provide electronic design automation (EDA) tools that Apple uses to design its custom silicon chips, including those that power AI and machine learning functions.

9. Arm Ltd.: While Apple designs its own chips, the architecture for these chips is based on technology licensed from Arm. This architecture is crucial for the energy-efficient performance of Apple's AI and machine learning workloads.

10. NVIDIA: Although Apple largely uses its own GPUs for AI processing, NVIDIA has been a key player in the broader AI ecosystem and might influence or provide tools and technologies that integrate with Apple's development environments, especially for AI research and development.

Apple typically keeps details about its specific suppliers and the exact components used in proprietary technologies like Apple Intelligence confidential. However, these companies are known to play critical roles in the supply chain for Apple's broader AI and machine learning infrastructure.

IONQ has been developing Trapped Ion quantum computing for over 9 years and they have support from Government, Industry and Institutional investors

 

The latest news on IonQ highlights several significant developments in the company's progress in quantum computing. 

Recently, IonQ announced that it has secured a $5.7 million contract with the Department of Defense (DOD) through the Applied Research Laboratory for Intelligence and Security (ARLIS). This contract has the potential to grow to over $40 Million

This contract involves designing a networked quantum computing system aimed at enhancing cybersecurity for multiparty quantum computation. The project includes research into "blind quantum computing," where the quantum computer is unaware of the information it processes, a critical feature for secure communications.

In addition to this contract, IonQ has also demonstrated technical advancements by achieving a two-qubit native gate fidelity of 99.9% using barium ions, which is expected to improve the accuracy of quantum computations. The company also reported strong financial performance, with a revenue of $11.4 million for Q2 2024, surpassing expectations and raising its full-year revenue guidance to $38-$42 million.

The latest news on IonQ highlights several significant developments in the company's progress in quantum computing. Recently, IonQ announced that it has secured a $5.7 million contract with the Department of Defense (DOD) through the Applied Research Laboratory for Intelligence and Security (ARLIS). This contract involves designing a networked quantum computing system aimed at enhancing cybersecurity for multiparty quantum computation. The project includes research into "blind quantum computing," where the quantum computer is unaware of the information it processes, a critical feature for secure communications.

In addition to this contract, IonQ has also demonstrated technical advancements by achieving a two-qubit native gate fidelity of 99.9% using barium ions, which is expected to improve the accuracy of quantum computations. The company also reported strong financial performance, with a revenue of $11.4 million for Q2 2024, surpassing expectations and raising its full-year revenue guidance to $38-$42 million.

These developments reinforce IonQ's position as a leader in quantum computing and reflect its continued commitment to advancing the technology for both commercial and governmental applications.

For more details, you can explore the recent articles on IonQ's achievements and contracts​ (The Quantum Insider)​ (Photonics).

IonQ is a leading company in the field of quantum computing, founded on deep academic and technical expertise. Here's a brief overview of its technical history:

Founding and Key People

• Who: IonQ was co-founded by Chris Monroe and Jungsang Kim in 2015. Chris Monroe is a physicist with significant contributions to quantum information science, particularly in trapped-ion quantum computing. Jungsang Kim is an expert in quantum optics and photonics, particularly in scalable quantum computing architectures.
• Where: The company was founded in College Park, Maryland, leveraging proximity to the University of Maryland, where Monroe was a faculty member and a leader in quantum research.

Technical Foundation

• What: IonQ’s technology is based on trapped-ion quantum computing, which uses individual ions (charged atoms) as qubits. These qubits are manipulated using lasers to perform quantum operations. Trapped-ion systems are known for their high fidelity, meaning they can perform quantum operations with very low error rates.
• How: The use of ytterbium and barium ions as qubits forms the core of IonQ’s approach. These ions are trapped using electromagnetic fields in a vacuum, and lasers are used to cool the ions and perform quantum gate operations. The company has made significant strides in error correction and fidelity, achieving 99.9% gate fidelity with barium ions, which is critical for the scalability of quantum systems.

Timeline of Major Milestones

• 2015: IonQ was founded with the goal of commercializing trapped-ion quantum computing.
• 2017: IonQ publicly announced its first prototype quantum computer, demonstrating a small-scale system that showcased the potential of trapped-ion technology.
• 2019: The company released its quantum systems to the cloud via partnerships with Amazon Braket and Microsoft Azure, making quantum computing more accessible to developers and researchers worldwide.
• 2021: IonQ became the first pure-play quantum computing company to go public through a merger with a special purpose acquisition company (SPAC), trading on the NYSE under the ticker "IONQ".
• 2022-2024: IonQ made several advancements in quantum error correction, gate fidelity, and scalability. The company also secured multiple government contracts and expanded its commercial partnerships, including notable collaborations with companies like Hyundai and Airbus.

Technical Achievements

• Where: IonQ’s research and development are primarily conducted at its facilities in Maryland, but the company also collaborates with academic institutions and other tech companies globally.
• How (cont’d): IonQ's approach is characterized by continuous improvements in qubit fidelity, error rates, and system scalability. The company is working on advancing from smaller quantum systems to more complex, larger-scale systems capable of solving real-world problems.

Impact and Future Directions

IonQ continues to push the boundaries of what is possible with quantum computing. Their focus remains on improving the fidelity and scalability of their quantum systems, making quantum computing practical and commercially viable. With strong backing from both the public and private sectors, IonQ is well-positioned to remain at the forefront of the quantum computing revolution.

For further details, you might want to check out IonQ’s official website and publications related to quantum computing from academic sources such as the University of Maryland and Duke University.

As of August 2024, institutional investors hold approximately 41.42% of IonQ's stock. Some of the key institutional stakeholders include:

1. The Vanguard Group, Inc. - Holding the largest institutional stake with approximately 8.9% of the shares.
2. BlackRock, Inc. - The second-largest institutional investor with about 5.9% of the shares.
3. SG Americas Securities LLC - Holds around 1.26% of the shares, showing significant interest from financial institutions.
4. Bank of New York Mellon Corp - Recently increased its holdings to about 0.43% of the shares.

In addition to these major players, other institutional investors, including DNB Asset Management AS and Rhumbline Advisers, have also increased their stakes in IonQ recently. 

Collectively, the top 25 shareholders control less than half of the company's shares, indicating that the stock is widely held, with no single entity having a dominant influence.

This broad institutional interest signals confidence in IonQ’s potential in the quantum computing industry, despite the inherent risks and volatility associated with this emerging technology.

For more detailed information, you can explore sources such as MarketBeat and Simply Wall St.

IonQ has established partnerships with several key players in both government and the business sector, reflecting its strong position in the quantum computing field.

Government Partnerships:

1. Department of Defense (DOD): IonQ has been contracted to develop a networked quantum computing system for the DOD through the Applied Research Laboratory for Intelligence and Security (ARLIS). This partnership includes a focus on cybersecurity and "blind quantum computing" protocols, enhancing secure communication capabilities​ (Photonics).

2. U.S. Air Force Research Lab (AFRL): IonQ has a significant contract with the AFRL, involving the deployment of barium-based trapped ion quantum computing systems for quantum networking research and application development​ (Photonics).

3. Department of Energy (DOE): IonQ is involved in research with the DOE, specifically with Oak Ridge National Laboratory, to explore how quantum technology can be used to modernize the power grid​ (Photonics).

Business Partnerships:

1. Amazon Web Services (AWS): IonQ provides quantum computing services through AWS's Amazon Braket platform. This partnership has been extended to improve accessibility and global operations, enabling developers to leverage IonQ’s quantum technology​ (The Quantum Insider).

2. Microsoft Azure: Similar to its partnership with AWS, IonQ offers its quantum computing services through Microsoft Azure Quantum, integrating with one of the leading cloud computing platforms​ (Simply Wall St).

3. Google Cloud Marketplace: IonQ's quantum computing systems are also available through Google Cloud, further expanding its reach in the cloud computing ecosystem​ (MarketBeat).

4. Airbus: IonQ collaborates with Airbus to explore quantum computing applications in aerospace, particularly in optimizing flight routes and improving the efficiency of aircraft design​ (Photonics).

5. Hyundai Motor Company: This partnership focuses on using quantum computing to enhance battery technology and optimize manufacturing processes in the automotive industry​ (Photonics).

These partnerships underscore IonQ's strategy of leveraging both government and commercial collaborations to advance quantum computing technology and integrate it into real-world applications.

Trapped ion quantum computing is considered to be in a leadership position in the race for quantum supremacy due to several key advantages:

1. High Fidelity and Low Error Rates

Trapped ion systems have demonstrated exceptionally high fidelity in quantum operations, with error rates that are among the lowest in the industry. For example, IonQ has achieved a two-qubit gate fidelity of 99.9% using barium ions​ (The Quantum Insider). This high accuracy is crucial for performing reliable quantum computations and scaling up the number of qubits in a quantum computer.

2. Scalability and Connectivity

Trapped ions can be scaled more easily compared to other quantum computing approaches. Each ion in a trapped ion system can be individually manipulated and entangled with others, allowing for a high degree of connectivity between qubits. This is in contrast to other systems, such as superconducting qubits, where connectivity is often limited to neighboring qubits.

3. Error Correction Capabilities

The inherent design of trapped ion systems makes them particularly suited for implementing quantum error correction, a critical component for building large-scale, fault-tolerant quantum computers. The use of error correction techniques, such as those developed by IonQ, helps reduce the overall error rate in quantum computations and enables the execution of more complex algorithms​ (The Quantum Insider).

4. Mature Technology Base

The technology underlying trapped ion quantum computing is well-established, with decades of research in atomic physics and laser technology. This maturity has allowed companies like IonQ to rapidly advance their systems and make them commercially viable. Additionally, trapped ion technology has been validated in various academic and research settings, lending credibility to its potential for achieving quantum supremacy.

5. Versatility and Flexibility

Trapped ion systems are highly versatile, capable of executing a wide range of quantum algorithms. The ability to reconfigure and program these systems with high precision makes them suitable for a variety of applications, from cryptography to material science.

6. Stable and Long-Lasting Qubits

Trapped ions are physically stable and can remain in a quantum state for relatively long periods, which is essential for performing lengthy computations. The ions are held in a vacuum, which protects them from environmental noise and helps maintain their coherence over time.

7. Government and Industry Support

The leadership position of trapped ion computing is further reinforced by significant support from both government agencies and private industry. Partnerships with institutions like the Department of Defense, and collaborations with tech giants like Amazon and Microsoft, provide trapped ion systems with the resources and platforms needed to scale and deploy their technology effectively​ (Photonics)​ (Simply Wall St).

These factors collectively contribute to trapped ion quantum computing's strong position in the ongoing race to achieve quantum supremacy, where the goal is to perform computations that are practically impossible for classical computers.

What exactly is, "Blind" Quantum Computing, what are it's benefits, who will use the technology and who is leading the charge?

Reasons why IONQ is leading the quantum computing race, the burgeoning QCAAS market and the Quantum Ai race!

Quantum computing leaders - a comparison of IBM and IONQ and their different approaches to quantum computing!

Quantum computing technology will advance Ai tech exponentially in the coming years, and in fact, "exponentially" may be too small a word!

 

Quantum computing has the potential to significantly advance AI technology in the coming years, potentially leading to exponential improvements in certain areas. However, the extent and speed of these advancements depend on several factors, including technological breakthroughs, integration with classical computing, and the development of specialized quantum algorithms for AI. Here’s how quantum computing could impact AI technology:

Potential Impacts of Quantum Computing on AI

1. Accelerated Machine Learning:

   • Quantum Machine Learning (QML): Quantum computers can process vast amounts of data and perform complex calculations much faster than classical computers. Quantum machine learning algorithms, such as quantum support vector machines and quantum neural networks, could dramatically speed up training times and improve the efficiency of AI models.
   • Feature Selection and Optimization: Quantum algorithms can perform complex optimization tasks more efficiently, potentially improving feature selection and hyperparameter tuning in machine learning models.

2. Enhanced Data Processing:

   • Big Data Analysis: Quantum computing’s ability to handle and process large datasets could lead to breakthroughs in analyzing big data, a common challenge in AI applications.
   • Parallelism: Quantum computers can evaluate many possibilities simultaneously due to quantum parallelism, which could lead to faster data processing and more robust AI models.

3. Improved AI Model Accuracy:

   • Better Simulations: Quantum computing can simulate complex systems more accurately than classical computers, potentially improving AI models that rely on simulations, such as those used in climate modeling, drug discovery, and material science.
   • Precision and Complexity: The precision and ability to model complex interactions at a quantum level could lead to AI models that better capture intricate patterns and correlations in data.

4. Optimization and Decision-Making:

   • Combinatorial Optimization: Quantum algorithms, such as the Quantum Approximate Optimization Algorithm (QAOA), are designed to tackle combinatorial optimization problems more efficiently, which can be beneficial in areas like logistics, scheduling, and resource allocation.
   • Faster Decision-Making: AI systems that require rapid decision-making, such as autonomous vehicles and real-time trading systems, could benefit from the speed and efficiency of quantum computations.

5. Natural Language Processing:

   • Improved NLP Models: Quantum computing might enable the development of more advanced natural language processing (NLP) models that can better understand and generate human language, leading to improvements in applications like chatbots, translation, and sentiment analysis.

Challenges and Considerations

1. Quantum-Classical Integration:

   • Hybrid Systems: For the foreseeable future, quantum computing will likely complement rather than replace classical computing. Effective integration between quantum and classical systems is essential to harness quantum advantages for AI.
   • Algorithm Development: Developing quantum algorithms specifically tailored for AI applications is a significant challenge and requires advancements in both quantum computing and AI research.

2. Hardware Limitations:

   • Current Capabilities: Quantum computers are still in the early stages of development, with limited qubit counts and coherence times. Significant hardware advancements are necessary before they can tackle large-scale AI problems.
   • Error Correction: Implementing effective quantum error correction is crucial for reliable quantum computations. Overcoming decoherence and noise is a major hurdle in making quantum computers practical for AI tasks.

3. Scalability:

   • Qubit Scaling: Scaling up the number of qubits while maintaining coherence and control is a significant technical challenge. Quantum computing’s impact on AI will depend on overcoming these scalability issues.

4. Algorithm Suitability:

   • Problem Fit: Not all AI problems are suited for quantum computing. Identifying problems where quantum computers can provide a clear advantage is crucial for realizing their potential.

Timeline and Expectations

• Short-Term Impact: In the short term, quantum computing is likely to provide incremental improvements in specific areas of AI, particularly in optimization and simulations. Hybrid quantum-classical systems may start to show advantages in niche applications.
• Medium to Long-Term Impact: As quantum hardware and algorithms mature, we may see more widespread adoption and significant breakthroughs in AI capabilities. This could lead to exponential advancements in areas like machine learning, data processing, and decision-making.

Conclusion

Quantum computing has the potential to significantly advance AI technology by providing faster processing, improved optimization, and enhanced model accuracy. While it is unlikely to replace classical computing entirely, it could complement existing AI technologies and lead to breakthroughs in certain areas.

The timeline for these advancements depends on overcoming current challenges in quantum hardware, algorithm development, and integration with classical systems. As these challenges are addressed, we can expect quantum computing to play an increasingly important role in driving AI innovation and solving complex problems that are currently beyond the reach of classical computers.

As Tech giant, Apple, prepares to announce it's jump into the Ai realm, new partnerships will most likely become investment targets!

Advantages of IonQ's Trapped Ion Technology

1. High-Fidelity Operations:

   • Precision and Control: IonQ's trapped ion qubits achieve high gate fidelities, often exceeding 99%, which is critical for accurate quantum computations. This precision allows them to execute complex algorithms with minimal errors compared to other quantum computing platforms.
   • Reduced Error Rates: High fidelity reduces the need for error correction, making computations more efficient and reliable.

2. Long Coherence Times:

   • Stability: Trapped ions have long coherence times, meaning they can maintain their quantum states longer than many other qubit technologies. This stability is essential for executing lengthy or complex algorithms without decoherence.

3. Scalability:

   • Modular Approach: IonQ is developing scalable architectures that allow for the addition of more qubits while maintaining control and coherence. Their approach aims to build larger quantum systems that can handle more complex problems.
   • Integration with Optical Technologies: IonQ uses lasers to manipulate qubits, which can be scaled and integrated into modular systems, providing a pathway to larger quantum computers.

4. Versatile Quantum Algorithms:

   • Broad Algorithmic Capability: IonQ's platform supports a wide range of quantum algorithms, from quantum machine learning to optimization and cryptographic applications. Their systems can efficiently execute both variational quantum algorithms and traditional quantum algorithms like Shor’s and Grover’s.

5. Error Mitigation Techniques:

   • Advanced Error Mitigation: While full quantum error correction is still in development, IonQ uses sophisticated error mitigation techniques to improve the fidelity of computations and ensure reliable results.

IonQ’s Position in the Quantum Computing Industry

1. Research and Development:

   • Continuous Innovation: IonQ is at the forefront of quantum research, collaborating with academic institutions and research labs to push the boundaries of quantum computing.
   • Patented Technologies: IonQ holds numerous patents related to their trapped ion technology, reinforcing their position as a technological leader.

2. Commercial Partnerships:

   • Collaborations: IonQ has established partnerships with major tech companies like Microsoft and Amazon to integrate their quantum solutions into cloud platforms, making quantum computing more accessible.
   • Industry Applications: IonQ is actively working on developing quantum solutions for industries such as pharmaceuticals, finance, and logistics, demonstrating practical use cases for their technology.

3. Competitive Edge:

   • Unique Advantages: IonQ’s use of trapped ions gives them a unique edge over other quantum computing approaches like superconducting qubits or topological qubits, which may face challenges related to coherence times and error rates.
   • Leadership in Algorithms: Their capability to execute complex quantum algorithms efficiently places them among the leaders in the quantum computing race.

Comparison with Other Quantum Technologies

1. Superconducting Qubits (e.g., Google, IBM):

   • Strengths: Superconducting qubits are currently popular due to their rapid development and ease of integration with existing semiconductor technologies. They have shown significant progress in increasing qubit counts.
   • Weaknesses: These qubits often have shorter coherence times and may require more extensive error correction.

2. Photonic Qubits (e.g., Xanadu, PsiQuantum):

   • Strengths: Photonic qubits offer advantages in terms of speed and potential scalability due to their use of light.
   • Weaknesses: Challenges include managing interactions and entanglement between photons.

3. Topological Qubits (e.g., Microsoft):

   • Strengths: Topological qubits promise inherently robust error correction due to their unique properties.
   • Weaknesses: The technology is still in early stages and requires significant breakthroughs for practical implementation.

Update: Aug 6th 2024 

IONQ will design a first of it's kind, multi-node, blind, quantum computing system for ARLIS!

This contract extends IONQ's work with the U.S. Federal Government on quantum initiatives and technical advancements! The contract is worth $40 Mil

Conclusion

IonQ's trapped ion technology places them at or near the top of the most advanced quantum computing systems. Their high-fidelity operations, long coherence times, scalability, and ability to execute a wide range of quantum algorithms make them a leader in the field. While other quantum technologies offer their own strengths and are advancing rapidly, IonQ's unique advantages and ongoing innovations ensure that they remain a key player in the quantum computing landscape. Their leadership is further reinforced by strategic partnerships and the development of practical quantum applications across various industries.

There are reasons why IONQ is considered a leader in developing and deploying Quantum computing technology!

MAG Aerospace has partnered with the Harvard Alum at Zapata Ai to advance it's global airborne intelligence and electronic warfare platform

IBC Copper Alloys Receives $1.3 Million Order From Asian Precision Manufacturing Multinational

Tiny Canadian firm, IBC Alloys having breakout year in U.S. Aerospace

Our top pick of 2015 in the Microcap Space, IBC Advanced Alloys Corp, is on a roll.
In the past six months it has signed no less than four (4) new contracts with Aerospace
companies and has many more "irons in the fire". Technicals are extremely bullish.

This small Canadian listed firm, has four operating plants in the USA and the U.S. Aerospace industry is becoming it's oyster.

Here are the headlines:

• April 20, 2015
  IBC Copper Alloys Receives $1.3 Million Order from Asian Precision Manufacturing Multinational
  

---

• April 8, 2015
  IBC Engineered Materials Receives Purchase Order from UTC Aerospace Systems
  

---

• March 25, 2015
  IBC Engineered Materials Receives Purchase Order from Kaman Corporation
  

---

• November 3, 2014
  IBC Advanced Alloys Partners with Baoshida Swissmetal and Avins to Develop and Distribute a New High Performance Alloy
  

---

• 
  

---

• October 1, 2014
  IBC to Present at IAEA Technical Meeting on Accident Tolerant Nuclear Fuels
  

---

• September 15, 2014
  IBC Advanced Alloys Delivers First UAS Components to Defense Dept
  

---

• September 8, 2014
  Lockheed Martin Awards Contract to IBC Engineered Materials for BeralCast® Castings for F-35 Lightning II
  

---

---

Up 30% in the past month, IBC Advanced Alloys is making great progress utilizing it's proprietary materials casting technology.  The aerospace industry is only now coming to know this technology and it's benefits.  We think the sky s the limit for this up and comer.

Remember, penny stocks are "highly speculative", and should never constitute more than 5-10% of any portfolio. They are not for the faint of heart. Money you need for retirement should not be invested in "any" speculative stocks.

Having said that, we have been following this tiny gem for over a year now and accumulating it's stock on dips.  From here on in, I doubt if there will be many dips to take advantage of, but that doesn't matter now that contracts are getting signed one after another.

With their foot in the door of U.S. Aerospace and defense contractors, and several new partners in Europe, expansion of this microcap should be astronomical in the coming year or so.  We're holding on the for what we expect will be an incredible ride.

Ed

NOTE: IBC Advanced Alloys is currently a penny stock and trades on the Toronto Venture Exchange under the symbol IB.

It also trades on the OTC in the U.S. under the symbol  IAALF.