Artificial intelligence dominates the technology conversation. Meanwhile, quantum computing has been advancing rather more quietly. New hardware, better error correction and an accelerating move toward post-quantum security suggest that it is time to pay attention.
While AI gets a lot of press, quantum computing has been advancing rather more quietly.
That may be about to change.
In March 2026, Google announced that it was setting a 2029 timeline for its migration to post-quantum cryptography. The reason was not that a quantum computer capable of breaking today's encryption had suddenly appeared. It has not.
Google's concern is that progress in quantum hardware, quantum error correction and estimates of the resources required to attack current cryptography have reached the point where simply waiting to see what happens is no longer a sensible security strategy.1
Google is not alone in putting the end of this decade firmly on the quantum calendar.
Microsoft now says it is aiming for a scalable quantum computer by 2029 following the introduction of Majorana 2 in June 2026.2 IBM is targeting 2029 for its planned fault-tolerant Starling system.3 QuEra says its first fault-tolerant neutral-atom system, Libra, is planned for availability through Amazon Braket in 2028.4
Company roadmaps are not promises from the laws of physics. Quantum computing has a long history of ambitious targets, difficult engineering and changed timelines.
But when several companies using fundamentally different technologies are converging on the end of the decade, it is worth understanding what they are actually trying to build.
You probably depended on quantum technology before you even started reading this article.
If you used GPS on your way to work, its position calculations depended on extraordinarily precise atomic clocks whose operation relies on quantum physics. Your phone and computer depend on semiconductor transistors. Much of the internet relies on lasers carrying information through optical fibre.
None of this is new.
These technologies are examples of what is often called Quantum 1.0, the first quantum technology revolution. Scientists learned enough about the behaviour of matter and light at atomic and subatomic scales to build devices that rely on quantum mechanics.
NIST describes technologies including GPS, lasers and atomic clocks as part of the quantum technology already embedded in everyday life.5
We are now moving into what researchers call Quantum 2.0.
The distinction is important.
Instead of simply building devices whose operation depends on quantum mechanics, scientists and engineers are increasingly able to create, control and manipulate individual quantum states and intentionally exploit phenomena such as superposition and entanglement.
Quantum computing is one of the clearest examples.
| Quantum 1.0 | Quantum 2.0 | |
|---|---|---|
| Core idea | Build technologies based on our understanding of quantum mechanics. | Deliberately create, control and manipulate individual quantum states. |
| Examples | Transistors, lasers, atomic clocks, semiconductors and MRI. | Quantum computers, quantum networks, quantum communications and advanced quantum sensors. |
| What changed? | We learned how quantum behaviour could make useful technology possible. | We are learning how to engineer quantum behaviour itself. |
| Role of entanglement | Usually not intentionally controlled as a technological resource. | Entanglement can be deliberately generated, manipulated and used. |
A conventional computer uses binary digits, or bits, as its fundamental unit of information. A bit is represented as either 0 or 1.
A quantum computer uses quantum bits, or qubits.
A qubit can exist in a quantum superposition of the states we label 0 and 1. When multiple qubits are carefully controlled, effects such as interference and entanglement can allow a quantum computer to process some problems in fundamentally different ways from conventional computers.
If that does not feel particularly intuitive, you are in good company.
The useful thing is that we have become remarkably good at using it anyway.
A normal computer stores and processes information using bits.
At the simplest level, a bit has one of two states, represented as 0 or 1.
A quantum computer uses quantum bits, or qubits.
A qubit can occupy a quantum state described as a combination of the states we label 0 and 1 until it is measured. This is known as superposition.
You will sometimes hear this described as a quantum computer "trying every answer at once".
That is catchy, but it is not a particularly good explanation.
The useful part comes from carefully manipulating quantum states so that interference increases the probability of useful outcomes and suppresses others.
Qubits can also become entangled. Their states then become correlated in ways that cannot be completely described by considering each qubit independently.
Superposition, interference and entanglement allow some quantum algorithms to approach certain mathematical and physical problems very differently from classical computers.
The important word is "some".
A quantum computer is not simply a normal computer that runs everything much faster. It is a different computational tool that may offer large advantages for particular kinds of problems.
No.
Your laptop does not need a quantum processor to write an email, render a website, run accounting software or play a video.
Graphics processing units did not replace CPUs. AI accelerators have not replaced conventional computing. Quantum processors are more likely to become another specialised computational resource.
Future high-performance systems may combine classical processors, GPUs, AI accelerators and quantum processors, often connected through cloud and high-performance computing infrastructure.
IBM describes its direction as quantum-centric supercomputing. Other companies are similarly designing quantum processors to work alongside classical systems rather than replace them.
So the useful question is not:
It is:
One of the most interesting things about quantum computing in 2026 is that nobody has yet won the hardware argument.
There is not yet a quantum equivalent of deciding that silicon transistors are how modern computers will be built.
Different companies are attempting to create reliable qubits using fundamentally different physical systems.
| Approach | How the qubit is produced | Examples | Potential strength | Major challenge |
|---|---|---|---|---|
| Superconducting qubits | Artificial quantum circuits made from superconducting materials and operated at extremely low temperatures. | Google IBM Rigetti | Very fast operations and substantial engineering experience. | Noise, cryogenic complexity and the large resource requirements of error correction. |
| Trapped ions | Individual electrically charged atoms held and manipulated using electromagnetic fields and lasers. | Quantinuum IonQ | Very high fidelity and strong connectivity between qubits. | Operations can be slower and scaling large systems remains difficult. |
| Neutral atoms | Individual uncharged atoms trapped, arranged and controlled using lasers. | QuEra Atom Computing Google research | Potentially very large and reconfigurable arrays of highly uniform atoms. | Maintaining control and fidelity as systems scale. |
| Photonic | Quantum information is carried using particles of light. | PsiQuantum Xanadu | Photons are naturally suited to networking and potentially compatible with semiconductor manufacturing. | Reliably generating, routing, controlling and detecting enormous numbers of photons. |
| Topological | Quantum information is intended to be encoded using specially engineered topological states. | Microsoft | If successful, some error resistance could come from the underlying physics of the qubit. | The approach is scientifically difficult and Microsoft's interpretation of its topological evidence remains debated. |
| Silicon spin | The spin state of electrons confined in semiconductor structures is used as a qubit. | HRL Diraq Quantum Motion | Extremely small qubits with potential compatibility with semiconductor fabrication. | Precise control, uniformity and interconnection at large scale. |
| Bosonic or cat qubits | Quantum information is encoded in carefully engineered oscillator states. | AWS | Hardware can be designed to suppress particular errors before full error correction. | Still an early architecture requiring substantial scaling. |
| Quantum annealing | A specialised quantum system evolves toward low-energy configurations representing possible solutions. | D-Wave | Already usable for particular optimisation and sampling experiments. | It is a specialised architecture and not equivalent to a universal gate-based quantum computer. |
D-Wave's Advantage2 annealing system, for example, became generally available in 2025 with more than 4,400 qubits.6
That number cannot sensibly be compared directly with Google's 105-qubit Willow processor because the systems have different architectures, capabilities and purposes.
This is why raw qubit counts make poor league tables.
A machine with 1,000 unreliable physical qubits is not necessarily more useful than a smaller system with much better fidelity.
Connectivity, error rates, coherence, gate quality, logical qubits, error correction and the number of reliable operations all matter.
| Organisation | Technology | Important recent milestone | Date | Where it is heading |
|---|---|---|---|---|
| Google Quantum AI | Primarily superconducting, now also researching neutral atoms | Willow demonstrated below-threshold error correction. Quantum Echoes later demonstrated what Google describes as verifiable quantum advantage. | 2024 to 2026 | Long-lived logical qubits and eventually a large error-corrected computer. |
| IBM | Superconducting | IBM and University of Chicago researchers reported a quantum-advantage experiment using 70 encoded logical qubits. IBM then connected and cooled its first modular cryogenic systems. | 30 Jul and 19 Aug 2026 | IBM Quantum Starling in 2029, planned around 200 logical qubits and 100 million quantum operations. |
| Microsoft | Topological | Majorana 2. Microsoft reports qubits around 1,000 times more reliable than its previous QPU and mean parity lifetimes around 20 seconds. | 2 Jun 2026 | A scalable quantum computer targeted for 2029. |
| Quantinuum | Trapped ions | Helios executed an approximate Quantum Fourier Transform across 98 physical qubits and a logical implementation using up to 12 logical qubits. | 29 Jul 2026 | Higher-fidelity logical computation integrated with classical HPC and AI systems. |
| IonQ | Trapped ions | Continuing development of its next-generation systems after announcing the first sale of a planned 256-qubit system in 2026. | 2026 | Larger modular trapped-ion systems, networking and quantum interconnects. |
| QuEra | Neutral atoms | Announced Libra, its planned first fault-tolerant quantum computer, for Amazon Braket. | 15 Jun 2026 | Cloud-accessible fault-tolerant neutral-atom computing targeted for 2028. |
| PsiQuantum | Photonics | Broke ground on its Moreton Bay Central facility in Queensland, intended to host a utility-scale fault-tolerant photonic quantum computer. | 18 Jun 2026 | Large fault-tolerant photonic systems using semiconductor manufacturing and optical networking. |
| D-Wave | Quantum annealing | Advantage2 is commercially available through D-Wave's Leap service with more than 4,400 qubits. | 2025 onward | Specialised quantum optimisation, sampling and hybrid computing. |
Google's position demonstrates how unsettled the field remains.
Its Willow processor uses 105 superconducting qubits. In 2024, Google demonstrated that increasing the size of an error-correcting surface code could reduce rather than amplify logical errors, an important result on the path toward fault tolerance.7
In October 2025, Google reported its Quantum Echoes experiment. Google described this as the first verifiable quantum advantage demonstrated by an algorithm running on quantum hardware.
For the specific problem tested, Google reported that Willow executed the algorithm approximately 13,000 times faster than the classical comparison.8
Then, in March 2026, Google announced that its Quantum AI programme was also expanding into neutral-atom quantum computing while continuing its superconducting programme.9
That does not necessarily mean Google has lost faith in superconducting qubits.
It means the hardware question remains open enough for one of the world's best-funded quantum programmes to investigate more than one answer.
IBM's quantum roadmap has produced several important developments this year.
On 30 July 2026, IBM and researchers from the University of Chicago reported an experiment using 70 encoded logical qubits, 2,415 logical two-qubit operations and 468 logical T gates.
IBM describes the work as satisfying fundamental criteria for quantum advantage while also providing evidence that the computation returned an accurate result.10
Then, on 19 August 2026, only days before this article was published, IBM announced that it had successfully joined and cooled two modular cryogenic systems into a single environment.
The architecture is designed eventually to connect hundreds of quantum chips. IBM says the two modules can reach temperatures below 15 millikelvin.3
IBM is aiming to deliver Starling in 2029, a fault-tolerant system the company expects to support 200 logical qubits and 100 million quantum operations.
IBM also broadened its hardware expertise in July 2026 when it announced an agreement to acquire HRL Laboratories, whose work includes silicon-spin qubits and quantum sensing.11
Microsoft is pursuing perhaps the most scientifically distinctive route.
Instead of accepting highly fragile physical qubits and relying entirely on increasingly sophisticated layers of error correction, Microsoft has spent years trying to create topological qubits.
The attraction is straightforward.
If quantum information can be stored in a state that is inherently less vulnerable to local disturbances, some of the protection against error could come from the physics of the qubit itself.
On 2 June 2026, Microsoft introduced Majorana 2.
The new processor replaces the aluminium used in Majorana 1 with lead and uses a revised semiconductor structure.
Microsoft reports qubits around 1,000 times more reliable than those in its previous QPU, operations on microsecond timescales and mean parity lifetimes of approximately 20 seconds, sometimes exceeding a minute.2
Microsoft says this progress has allowed it to move its target for a scalable quantum computer forward to 2029.
There is, however, an important scientific qualification.
Some independent physicists remain sceptical that Microsoft has conclusively demonstrated the topological behaviour on which its claims depend. Nature reported continued scientific debate following the Majorana 2 announcement.12
That does not make Majorana 2 unimportant. It makes the distinction between a company claim and scientific consensus important.
Microsoft has reported substantial experimental progress. Other physicists are examining whether the evidence supports Microsoft's interpretation. The position is not yet settled.
The emerging story is therefore not really AI versus quantum computing.
The technologies are already beginning to interact.
Microsoft says AI-assisted research helped its team investigate and optimise the material stack used in Majorana 2.
Google DeepMind and Google Quantum AI have also developed machine-learning approaches to quantum error correction.
That relationship may eventually run in both directions. Quantum computers might support particular AI workloads or generate information that is difficult for classical systems to calculate.
Claims that quantum computing is about to make all AI exponentially more powerful, however, deserve the same caution as claims that AI is about to solve every other technical problem.
Quantum computing is most promising when the mathematical or physical structure of a problem can exploit quantum mechanics.
This does not mean a quantum computer automatically solves every difficult problem in those categories.
A theoretically faster quantum algorithm, a laboratory demonstration and a commercially useful solution are three different things.
Much of the history of quantum computing has existed in the distance between them.
Healthcare routinely appears in lists of industries that quantum computing will supposedly "revolutionise".
That word should make us slightly suspicious.
There are plausible applications.
One of the strongest potential healthcare connections comes through chemistry and molecular science. Accurate simulation of molecules and quantum interactions could eventually contribute to drug discovery, protein and molecular research, and the development of new materials used in medicine.
Google's Quantum Echoes research provides an interesting example. Its proof-of-principle experiments used quantum computation alongside nuclear magnetic resonance data to investigate molecular geometry. Google identifies areas including drug discovery and materials research as possible future applications.8
Other research areas include precision medicine, optimisation, genomic analysis and quantum machine learning.
But research interest is not the same thing as demonstrated clinical advantage.
A 2025 systematic review published in npj Digital Medicine examined whether quantum machine-learning algorithms outperform classical methods in digital health.
The researchers initially identified 4,915 studies. Only 16 met the final criteria for examining realistic operating environments using quantum hardware or noisy simulations.
Their conclusion was important: performance differences between quantum and classical approaches showed no consistent trend supporting empirical quantum utility in digital health.13
That is exactly the sort of finding technology companies and educators should pay attention to.
Quantum computing has genuine potential in healthcare.
It does not need exaggerated claims to make it interesting.
There is a slightly amusing point for anyone working in medical imaging.
Medical imaging professionals have already been working with quantum physics for decades.
MRI depends on quantum properties of atomic nuclei and nuclear magnetic resonance. PET depends on physical processes involving positron annihilation and photon detection.
Neither of those technologies is a quantum computer.
Nor would a quantum computer simply be connected to an X-ray system and suddenly produce better radiographs.
Potential medical-imaging applications are more likely to involve computational tasks such as optimisation, reconstruction, modelling or analysis.
These are legitimate areas of research, but they remain research areas.
At Virtual Medical Coaching, we spend a great deal of time thinking about how technology moves from an interesting technical capability to something that genuinely improves learning or professional practice.
Quantum computing deserves exactly the same test.
Ironically, one of the first major consequences of quantum computing may arrive before the cryptographically relevant quantum computer itself.
Much of today's public-key cryptography depends on mathematical problems that are extremely difficult for classical computers.
A sufficiently capable fault-tolerant quantum computer running algorithms such as Shor's algorithm could make some of those problems dramatically easier.
That threatens widely deployed public-key systems based on integer factorisation and discrete logarithms, including RSA and elliptic-curve cryptography.
This does not mean every form of encryption becomes useless.
Symmetric cryptography is affected differently and can use larger key sizes to retain appropriate security margins.
Because information can be stolen now and stored.
An attacker does not necessarily need to decrypt it today.
They can keep it until a machine capable of breaking the encryption exists.
This threat is usually described as harvest now, decrypt later or store now, decrypt later.
So for information that must remain confidential for ten, twenty or thirty years, the relevant question is not:
It is:
Healthcare organisations hold exactly the sort of personal information that can remain sensitive for decades.
Another common misconception is that protecting against quantum computers requires quantum technology.
It does not.
Post-quantum cryptography, or PQC, runs on conventional computers.
It uses mathematical approaches selected to resist attacks from both classical computers and future quantum computers.
In August 2024, the US National Institute of Standards and Technology finalised its first three principal post-quantum cryptography standards.14
| Standard | Algorithm | Purpose |
|---|---|---|
| FIPS 203 | ML-KEM | Key encapsulation for establishing shared encryption keys. |
| FIPS 204 | ML-DSA | Post-quantum digital signatures. |
| FIPS 205 | SLH-DSA | Hash-based post-quantum digital signatures. |
NIST has encouraged organisations to begin transitioning rather than waiting for a cryptographically relevant quantum computer to appear.
On 25 March 2026, Google made the issue considerably more concrete.
It announced a 2029 timeline for post-quantum cryptography migration, citing progress in quantum hardware, error correction and estimates of the quantum resources required to factor cryptographic keys.1
Google also said Android 17 was integrating post-quantum digital-signature protection using ML-DSA.15
The important point is not that Google knows a cryptographically relevant quantum computer will arrive in 2029.
It does not.
The important point is that one of the world's largest technology and security organisations believes the migration problem is sufficiently significant that the work should be underway before then.
Google is not unusual in deciding that preparation needs to begin before a cryptographically relevant quantum computer exists.
Governments and cybersecurity agencies around the world are already moving from recognising the threat to setting migration dates, funding national quantum programmes, building quantum-safe infrastructure and publishing practical implementation guidance.
The scale of those responses varies considerably.
| Country or region | Policy position | What it is actually doing |
|---|---|---|
| United States | Standards plus an accelerated federal migration programme. | NIST finalised the first three principal PQC standards in 2024 and now says organisations should begin migration. A June 2026 Executive Order requires high-value US federal systems to use PQC for key establishment by the end of 2030 and for digital signatures by the end of 2031, while retaining the broader 2035 transition goal.18 |
| European Union | Coordinated PQC migration across member states. | The EU has adopted a coordinated implementation roadmap for PQC. Member states are expected to establish national transition planning, move high-risk and complex systems toward quantum-safe protection by 2030, and progress the wider migration toward 2035. The EU is also developing quantum-safe communications infrastructure.19 |
| United Kingdom | Explicit national migration milestones. | The NCSC expects organisations to complete discovery and initial migration planning by 2028, migrate their highest-priority systems by 2031 and complete migration across systems, services and products by 2035.16 |
| Singapore | Practical organisational migration plus quantum-safe network infrastructure. | Singapore has moved beyond general strategy. Its Cyber Security Agency, GovTech and IMDA released a Quantum-Safe Migration Handbook and Quantum Readiness Index in July 2026 to help organisations assess and execute migration. Singapore has also been developing national quantum-safe network infrastructure.20 |
| Canada | A funded national quantum strategy covering computing, communications, sensing and PQC. | Canada's National Quantum Strategy is backed by C$360 million in dedicated funding. One of its three missions is to protect privacy and cybersecurity through post-quantum cryptography and secure quantum communications, supported by a specific PQC and quantum-communications roadmap.21 |
| Australia | National quantum industry strategy plus operational PQC guidance. | Australia has had a National Quantum Strategy since 2023, covering research, infrastructure, skills, standards and commercialisation. The Australian Signals Directorate also maintains specific guidance for planning a migration to post-quantum cryptography and has incorporated approved PQC algorithms into its cryptographic guidance.22 |
| New Zealand | The risk is acknowledged in national cybersecurity strategy. | New Zealand's Cyber Security Strategy 2026-2030 explicitly warns that quantum computing could render current encryption methods obsolete. That is sensible recognition of the risk, but the publicly stated response is less developed than the detailed migration timetables, implementation tools, dedicated quantum funding and quantum-safe infrastructure programmes already visible in several comparable countries.17 |
The United States has standardised the cryptography and accelerated federal migration. The UK has set staged migration deadlines. The EU has a coordinated regional roadmap. Singapore is giving organisations migration tools while developing quantum-safe network infrastructure. Canada has committed dedicated national funding. Australia combines a national quantum strategy with operational PQC guidance.
New Zealand, by comparison, has at least recognised the issue in its national cybersecurity strategy.
Recognising that quantum computing may eventually threaten encryption is no longer particularly forward-looking.
The more useful question is what a country, organisation or technology provider is actually doing to prepare for it.
Nobody knows.
There are now demonstrations described by their developers as quantum advantage on selected problems.
There are increasingly sophisticated logical-qubit experiments.
There are detailed engineering roadmaps toward fault-tolerant machines.
There are also formidable unresolved problems involving error correction, manufacturing, control systems, cryogenics, interconnection, algorithms and scale.
Different organisations also mean different things when they use phrases such as quantum advantage, utility scale, fault tolerant, useful and scalable.
That is why dates such as 2028 and 2029 should be treated as engineering roadmaps rather than appointments with destiny.
Some predictions are considerably safer.
Increasingly, the important questions involve error rates, fidelity, connectivity, logical qubits, error correction and how many reliable operations a system can actually perform.
Education often encounters new technology at one of two unhelpful points.
We either teach it as science fiction long before anyone can use it, or wait until it is embedded in professional practice and then scramble to explain it.
Quantum computing now sits somewhere between those positions.
Students entering healthcare, medical imaging, engineering, cybersecurity and computing in 2026 may spend much of their careers in a world where quantum processors are simply another specialised computing resource available through cloud infrastructure.
More immediately, some will work with systems whose cryptographic foundations are being redesigned now because of quantum computers that have not yet been built.
That alone makes a degree of quantum literacy useful.
Not because every healthcare professional needs to learn quantum mechanics.
But because professionals should understand enough about emerging technologies to distinguish:
Artificial intelligence went through repeated cycles of excitement, disappointment and renewed investment.
Then several things matured together: computing power, algorithms, data, infrastructure and commercially useful applications.
The result was not that every prediction about AI became true.
It was that AI crossed a threshold where ignoring it stopped being sensible.
Quantum computing may or may not follow the same path.
Different hardware architectures are still competing. Some important scientific claims remain contested. Many potential commercial and healthcare applications have not yet demonstrated an advantage over classical approaches.
But Google is changing its cryptographic infrastructure because of the quantum threat.
NIST has already standardised new cryptographic algorithms because of it.
Microsoft, IBM, Google, Quantinuum, IonQ, Amazon, QuEra, PsiQuantum, D-Wave and others are taking very different and very expensive approaches to building it.
New Zealand's national cybersecurity strategy is planning for it.
And companies are now putting dates such as 2028 and 2029 on machines that would have sounded decidedly more distant only a few years ago.
So while AI continues to get most of the press, it is probably time we started paying a little more attention to quantum computing too.
Not because the quantum revolution has arrived.
Because some of the preparations for it already have.
Quantum 1.0 describes technologies developed using our understanding of quantum mechanics, including transistors, lasers, semiconductors and atomic clocks. These technologies already underpin modern computing, communications, GPS and many medical technologies.
What is Quantum 2.0?Quantum 2.0 describes a newer generation of technologies in which scientists deliberately create, manipulate and exploit quantum states. Quantum computers, quantum networks and advanced quantum sensors are examples.
What is quantum computing in simple terms?Quantum computing is a form of computation that manipulates quantum states rather than ordinary binary bits. It can exploit effects including superposition, entanglement and interference to perform particular types of calculation differently from classical computers.
Is a quantum computer faster than a normal computer?Not generally. Quantum computers may outperform classical computers on specific classes of problems. For ordinary computing tasks, conventional computers remain more appropriate.
Can quantum computers break encryption?A sufficiently large fault-tolerant quantum computer could threaten widely used public-key cryptographic systems such as RSA and elliptic-curve cryptography. A machine capable of doing this at the required scale does not currently exist.
What is post-quantum cryptography?Post-quantum cryptography uses algorithms designed to run on ordinary computers while resisting attacks from both conventional and future quantum computers.
Why are organisations changing encryption before quantum computers are ready?Encrypted information can be captured today and stored for later decryption. Data that must remain confidential for many years can therefore face a quantum-related security risk before a cryptographically relevant quantum computer exists.
Will quantum computing be used in healthcare?Potential applications include molecular modelling, drug discovery, precision medicine, optimisation and some forms of data analysis. Current evidence does not demonstrate a consistent quantum advantage for digital-health machine learning.
Can quantum computing improve medical imaging?Possibly in future computational tasks such as optimisation, modelling, reconstruction or analysis. There is currently no established general clinical quantum advantage in medical imaging.
Is Microsoft's Majorana 2 a real quantum computer?Majorana 2 is an experimental quantum processor based on Microsoft's topological approach. Microsoft reports major improvements in reliability and is targeting a scalable system by 2029. Some independent physicists remain unconvinced that the claimed topological behaviour has been conclusively demonstrated, so the scientific interpretation remains debated.
Which company has the best quantum computer?There is no simple answer. Major quantum-computing companies use different architectures and performance measures. Physical qubit count alone is not a useful way to determine which system is most capable.
When will useful quantum computers arrive?There is no agreed date. Several companies currently have major fault-tolerant or scalable-computing targets around 2028 to 2029, but these remain engineering roadmaps rather than guaranteed delivery dates.
Virtual Medical Coaching develops healthcare simulation software for medical and allied health education. Our work focuses on turning complex technical and clinical concepts into experiences where learners can practise, make decisions, observe consequences and develop understanding before working with patients.
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