From Silicon To New Forms Of Computing
The computing industry was born when mechanical devices started to perform calculus that was, until then, reserved for the human brain. But it was with vacuum tubes and, later on, transistors that true computers started to be created.
The next revolution was the silicon computer chips, with ever-growing transistor density for ever-growing computation power.
Source: Mobile First
Currently, the semiconductor industry is experimenting with increasingly powerful systems to create chips in the 5nm and even 2nm range. This is bringing us ever closer to a problem, as, at one point, using smaller and smaller silicon transistors will not be possible anymore.
One single atom of silicon is a theoretical limit, but practical engineering problems will probably make it happen before that threshold.
So, will computing power stop progressing from here? Probably not.
However, the solution will be to perform computation using entirely new principles. There are actually many potential ways to perform computing without relying on silicon transistors. We can look at the most promising ideas without going into the technical details.
Non-Silicon Semiconductors
A semiconductor is a material with the ability to switch between being conductive (transmits electric current, creates a “1” data in binary) or an isolant (blocks electric current, creates a “0” data in binary).
Silicon has been the material of choice for creating semiconductor chips, but plenty of alternatives are now being explored. Any material displaying the property called band gap can be a good candidate.
Source: Energy Education
Vanadium Dioxide
For a long time, vanadium dioxide has been seen as a good option to replace silicon. This is because it undergoes a phenomenon known as “undergoing metal-insulator transitions,” which takes only a trillionth of a second.
The speed of the metal-insulator transition should allow for faster and smaller electronics compared to classical silicon-based electronics.
Recent research has managed to study vanadium dioxide deposited on a substrate of titanium dioxide.
They also discovered that titanium dioxide can be a semiconductor as well. This discovery could allow for creating neuromorphic chips that could learn at the hardware level, taking inspiration from the brains of living systems with neurons.
Thanks to its very quick Insulator-To-Metal transition, vanadium dioxide with an active substrate of titanium dioxide could be used to create Mott neuron-like spiking oscillators able to replicate at the hardware level biological neurons.
Graphene
Another good candidate is graphene, a 2D material with extremely high electric conductivity. It is even a potential superconductor and a “wonder material” whose properties are still being discovered in real-time.
You can read more about the first-ever successful efforts to make graphene into a semiconductor material in our article “Graphene Semiconductors – Are They Finally Here?”
Organic Materials
According to a recent discovery, organic material could be forced to form a 2D structure similar to graphene. This could make them as ultra-conductive as graphene, while naturally displaying semiconductor properties, contrary to graphene which has to be “forced to do so”.
You can learn more about this option in “Can Organic Semiconductors Combine the Benefits of Graphene & Silicon?”
Optimizing Semiconductors Power Usage
An issue with using ever quicker and smaller transistors is the growing power consumption.
An alternative could be to use a technique called “redox gating.” This relies more on a chemical reaction (redox) and could drastically reduce power demand.
If the price of computing starts to rise from power costs more than the chips themselves, this is a solution we might see implemented as well. We explored the latest news on this topic in “Redox Gating Could Lead to New Levels of Efficiency in Tiny Electronics”.
Photonics
Alternative semiconductor materials try to replace silicon. But what if computing was done entirely without using electrons, transistors, and semiconductors?
This is the idea of photonics, looking to perform computing directly with light.
Light is the fastest thing in the universe, so it could be orders of magnitude quicker than silicon and semiconductor-based computing.
In practice, photonics might still involve silicon but could also rely on crystals.
Due to light”s wave-like nature, photonics design relies on curves and unique (and somewhat not technologically mature yet) design principles that differ from those used for semiconductors.
Source: Synopsis
Quantum Computing
Computing could also be performed by measuring not electric current but the quantum state of particles.
Instead of generating 0 and 1 (no current or current), it uses “quantum bits,” called qubits, where particle data is either 0 AND 1 at once, or 1, or 0.
Because of the fundamental difference in the calculation, quantum computing is not an alternative to “normal” computing but rather a complement.
Standard computing works linearly and struggles with very complex calculations, like climate modeling, cryptography, or the 3D configuration of complex molecules like proteins. And this is precisely the type of calculation that quantum computing is expected to excel at.
So, while maybe not replacing silicon, quantum computers could perform better tasks that were previously almost impossible for silicon chips.
You can read more about the latest news in quantum computing in our article “The Current State of Quantum Computing”.
Biological Organoids
Our brains are essentially supercomputers, at least when it comes to processes like pattern recognition, language, etc. And very efficient at that, consuming barely a few dozen watts.
A Swiss startup, FinalSpark has now developed a 0.5mm large sphere (organoids) made of 10,000 human neurons. And uses it to perform computation. The service will even be accessible through the cloud.
This is a very new field, and it is unclear yet how far it will go. But who knows, maybe one day our self-driving devices will run on neurons instead of chips.
Top 10 Non-Silicon Stock
1. International Business Machines Corporation
International Business Machines Corporation (IBM) was the leading force behind the commercialization of the first mainframe computer. However, it has fallen behind in the production volume of other tech giants like Apple, TSMC, and NVIDIA.
It is, however, at the forefront of the development of quantum computers. For example, it developed its 127-qubit “Eagle” quantum computer, which was followed by a 433-qubit system known as “Osprey.”
And this is now followed by “Condor”, a 1,121 superconducting qubit quantum processor based on cross-resonance gate technology, together with “Heron”, a quantum processor at the very edge of the field.
IBM is invovled in most of the other cutting-edge innovations in computing and the semiconductors industry. These include conducting organic materials, neuromorphic computing, photonics, etc.
To some extent, IBM has become a “patent company” with expertise in developing new computing methods and licensing them to the industry.
So far, it seems very determined to hold as many key patents in all the non-silicon computing methods it can get, replicating its past success when contributing massively to developing the semiconductor industry into the giant it is today.
2. Microsoft Corporation
Already a leader in “normal” cloud services, Microsoft is a pioneer in offering quantum computing cloud services with Azure Quantum.
It is entirely possible that most quantum computing in the future will be done “remotely”, relying on cloud services like Microsoft’s, instead of direct access to a quantum computer.
This is especially likely as most of the quantum computing applications will be researched by biochemists, material science experts, climate scientists, and other specialists with no specific background in quantum computing.
So relying upon dedicated professionals working at firms like IBM, Microsoft, or Google to handle the computing part makes more sense than hiring or training people untrained to the field.
Microsoft service offers “hybrid computing”, mixing quantum computing with traditional cloud-based supercomputer service.
Source: Microsoft
Instead of vertical integration, Microsoft’s approach to quantum computing has been to establish partnerships with leaders in the field covering virtually all the technologies possible to achieve quantum computing, like IonQ (IONQ), Pasqal, Quantinuum, QCI (QUBT), and Rigetti (RGTI).
Source: Microsoft
Microsoft also established at the end of 2023 a collaboration with Photonic, a company working on merging quantum computing and photonics.
Microsoft has also been working on analog photonic chips for the finance industry.
Quantum computing is not central to Microsoft’s business, at least for now. It is nevertheless a central actor of the sector and might make for a “safer” stock pick over directly acquiring shares of its quantum computing partners that are publicly traded, like QCI or Rigetti.
3. Alphabet Inc.
Google is very active in quantum computing, mostly through its Google Quantum AI lab and Quantum AI campus in Santa Barbara.
Google’s quantum computer made history in 2019 when Google claimed to have achieved “quantum supremacy” with its Sycamore machine, performing a calculation in 200 seconds that would have taken a conventional supercomputer 10,000 years.
But maybe the greatest contribution of Google will be in software, an activity where it has a much better track record than hardware (search, GSuit, Android, etc.). Google’s Quantum AI already makes available a suite of software designed to assist scientists in developing quantum algorithms.
Google is also an active backer of photonics companies like Lightmatter.
Google is likely to be one of the companies setting the standards of quantum computing software & programming, giving a privileged place to direct where the field will evolve in the future. Its powerful network and VC activity will also likely give a place in any other non-silicon-based form of computing.
4. Intel
Intel is a major chip producer and seems to target to leverage this strength into the quantum computing arena.
It recently released “Tunnel Falls”, the “ most advanced silicon spin qubit chip”. What is remarkable about it is that it is not a prototype but a chip built at scale, with a 95% yield rate across the wafer and voltage uniformity. This opens the way to mass production of quantum computing chips, something for now elusive in a nascent and quickly changing industry.
Source: Intel
Faithful to its roots, Intel is also developing the software to utilize its chips, with the release of the Intel Quantum SDK. This provides the guideline for programmers to develop software for quantum computing compatible with Intel quantum chip design, which has historically been a very strong & profitable business moat for Intel’s conventional chip business.
Source: Intel
The arrival of scalable quantum chip manufacturing could be as revolutionary for the industry as any other more technical scientific breakthrough, bringing down costs, and setting common programming standards and chip architectures.
At the end of 2023, Intel decided to divest its photonics business to Jabil (JBL).
Overall, Intel is making progress in quantum computing and seems to have a clear strategy to focus on this topic above photonics and other alternatives.
5. Nvidia
The leading manufacturer of graphic cards and, more recently, cryptocurrency mining rigs and AI chips has now truly evolved from a PC parts manufacturer to one of the global tech giants.
Nvidia is also active in the quantum computing space, with its NVIDIA DGX Quantum combining normal chips and quantum computing using the newly open-sourced CUDA quantum software platform.
Source: Nvidia
Looking to reinforce its lead in AI, Nvidia has also released its QuantumX-800 for AI-optimized networking in data centers.
When it comes to photonics, Nvidia has forged a partnership with TSMC and Broadcom. It will look to create a single module through co-packaged optics (CPO) integrating classical silicon chips and photonics.
Overall, Nvidia’s success is tightly linked to the current AI boom, and quantum computing and photonics come second. However, it will benefit from the growth of these sectors as well and seems to be holding on to stay in the race.
6. Quantinuum / Honeywell
Quantinuum is the result of the merger of Honeywell Quantum Solutions and Cambridge Quantum (and, as mentioned, a partner of Microsoft quantum cloud computing).
Quantinuum seems, for now, to focus on segments less explored by other quantum computing systems, notably financial and supply chain-related analyses, through its Quantum Monte Carlo Integration (QMCI) engine, launched in September 2023.
QMCI applies to problems that have no analytic solution, such as pricing financial derivatives or simulating the results of high-energy particle physics experiments, and promises computational advances across business, energy, supply chain logistics, and other sectors.
Like Microsoft, quantum computing is not the central part of Honeywell’s business, which is more centered around products in aerospace, automation, and specialty chemicals and materials.
However, considering every single one of these business segments could benefit from quantum computing, it is not hard to see the business case for Honeywell to get involved.
So this makes Honeywell both a provider of quantum computing services and one of the companies that could benefit from the application of quantum computers to real-life business cases, something the integration of Quantinuum into the group should help foster at a quicker pace than its industrial competitors.
7. Synopsys
Any photonic system will have to be integrated as seamlessly as possible with silicon systems, at least initially. Synopsys can help with this.
The company is a specialist in silicon design and verification, meaning its software is used to design new chips, including ultra-advanced 5nm chips and below.
The company also offers software for photonics described as “The industry’s only seamless design flow for photonic devices, systems, and integrated circuits”. This allows for handling the design and simulation of new photonics devices.
Source: Synopsis
The company has also developed a joint venture with Juniper Network to create OpenLight, a photonics company using indium phosphide.
8. Juniper Network
Juniper claims to offer the #1 cloud-native wireless solution and the only AI-driven WiFi network. This puts it directly in competition with older and more established giants like Cisco. Juniper’s technology, Juniper Mist, is claimed to be more scalable, flexible, and better at anomaly detection than Cisco’s equivalent offers.
The company’s solutions rely heavily on AI, with its AI engine “Marvis” used at all network levels, from user to data center.
Source: Juniper
Regarding security, Juniper also shows outstanding results on firewalls, threat defense, and defense against exploits, outperforming most vendors like Fortinet, Palo Alto, Zscaler, etc.
Juniper also offers Photonic Integrated Circuits (PICs), which are currently mostly used for data transmission and sensors. They are expected to be an integral part of future photonics-based computers.
Source: Synopsis
9. Rigetti Computing, Inc.
Riggeti is a quantum computing company, “owning critical IP for our breakthrough multi-chip processor and the hybrid quantum-classical approach that has become the predominant quantum computing architecture.”.
The company is integrating all the steps needed for quantum computing, from chip design and manufacturing up to cloud delivery of the computing power.
Source: Rigetti
The company is focused not so much on adding as many qubits as possible (as giants like Intel are doing) but on perfecting their existing product and achieving a very high level of fidelity and speed, making it a more reliable commercial product.
Its latest iteration, the 84-qubit Ankaa-3, is expected to be revealed in the second half of 2024. Based on the Ankaa concept, the company aims for a 336+ qubit system in the long run.
Source: Rigetti
In December 2023, Rigetti started sales of the 9-qubit system Novera, a “mini quantum computer” selling for “only” $900,000 and a 4-6 weeks delivery.
The first clients included Fermilab’s SQMS Center, the Air Force Research Lab, and Horizon Quantum Computing.
The company announced in spring 2024 that it would join the Russel 3000 Index.
10. IPG Photonics
IPG is a laser manufacturer that produces virtually all types of lasers, including fiber, diode, UV, and deep UV lasers. With 6,200 employees, it ships 42,000+ laser devices per year.
Its specialty is in fiber lasers, with high levels of precision and the ability to do laser pulses as short as a femtosecond (one quadrillionth of a second).
IPG lasers are currently used for:
While advances in photonics chips will be required to create entirely photonics-based computers, we already know that it will integrate a lot of a specific and already common component: lasers.
The light for photonic computing needs to be based on very stable light emitted by the laser. So leaders in the laser industry, like IPG, would benefit from a boom in laser demand from the semiconductor industry switching progressively to photonics.
And in that nascent segment, ultra-short laser impulses can be turned into ultra-fast computing power.
