• Apple labels PQ3 as “Level 3” security, highlighting its robust properties for iMessage.
• PQ3 adds a post-quantum key to Apple device registration for iMessage.
• PQ3 adds a rekeying mechanism for iMessage, enhancing security.

The imperative for impregnable security measures has reached a crescendo in the ever-accelerating march toward quantum computing dominance. Today, as the quantum supremacy specter looms, the clamor for steadfast cryptographic shields has amplified. So, in a groundbreaking move, Apple has unveiled PQ3, a cutting-edge post-quantum cryptographic protocol tailored for iMessage. Touted by the tech giant as possessing “unparalleled” security features, PQ3 represents a paradigm shift in communication security.

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At the heart of Apple’s embrace of post-quantum cryptography (PQC) lies a deep understanding of the evolving threat landscape. Simply put, as quantum computing advances, traditional cryptographic methods face unprecedented challenges, making the integration of PQC imperative for safeguarding sensitive data and preserving user privacy. 

For context, with their exponential computational power, quantum computers can potentially render existing encryption algorithms obsolete, posing significant risks to data security. Recognizing this, Apple has proactively invested in research and development to pioneer cryptographic solutions capable of withstanding quantum attacks.

That’s where the latest addition to Apple’s cryptographic arsenal, the PQ3 protocol, represents a paradigm shift in communication security. By introducing a new post-quantum encryption key within the iMessage registration process, Apple ensures that data exchanged through its platform remains protected against future quantum threats. PQ3 also incorporates advanced security features, such as a rekeying mechanism within iMessage conversations, designed to mitigate the impact of critical compromises and bolster overall resilience. 

“To our knowledge, PQ3 has the strongest security properties of any at-scale messaging protocol in the world,” Apple’s Security Engineering and Architecture (SEAR) team stated in a blog post a week ago.

PQ3 for iMessage integrates post-quantum key establishment and ongoing self-healing ratchets. Source: Apple

A quantum leap in messaging security

Traditionally, messaging platforms rely on classical public key cryptography like RSA, elliptic curve signatures, and Diffie-Hellman key exchange for secure end-to-end encryption. These algorithms are based on complex mathematical problems deemed computationally intensive for conventional computers, even with Moore’s law in play. But the advent of quantum computing poses a new challenge.

A powerful enough quantum computer could solve these mathematical problems in novel ways, potentially jeopardizing the security of end-to-end encrypted communications. While quantum computers capable of decryption aren’t yet available (as far as we know, supervillains notwithstanding), well-funded attackers can prepare by exploiting cheaper data storage. They accumulate encrypted data now, planning to decrypt it later with future quantum technology—a tactic called “harvest now, decrypt later.”

When iMessage launched in 2011, it became the first widely available messaging app with default end-to-end encryption. Over the years, Apple has continually enhanced its security features. In 2019, the iPhone maker bolstered the cryptographic protocol by transitioning from RSA to elliptic curve cryptography (ECC) and safeguarding encryption keys within the secure enclave, increasing protection against sophisticated attacks. 

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“Additionally, we implemented a periodic rekey mechanism for cryptographic self-healing in case of key compromise. These advancements underwent rigorous formal verification, ensuring the robustness of our security measures,” the blog post reads. So, the cryptographic community has been developing post-quantum cryptography (PQC) to address the threat of future quantum computers. These new public key algorithms can run on today’s classical computers without requiring quantum technology. 

Designing PQ3

Designing PQ3 involved rebuilding the iMessage cryptographic protocol to enhance end-to-end encryption, meeting specific goals:

1. Post-quantum cryptography: PQ3 protects all communication from current and future adversaries by introducing post-quantum cryptography from the start of a conversation.
2. Mitigating key compromises: It limits the impact of critical compromises by restricting the decryption of past and future messages with a single compromised key.
3. Hybrid design: PQ3 combines new post-quantum algorithms with current elliptic curve algorithms, ensuring increased security without compromising protocol safety.
4. Amortized message size: To minimize additional overhead, PQ3 spreads message size evenly, avoiding excessive burdens from added security.
5. Formal verification: PQ3 undergoes standard verification methods to ensure robust security assurances.

According to Apple, PQ3 introduces a new post-quantum encryption key during iMessage registration, using Kyber post-quantum public keys. These keys facilitate the initial critical establishment, enabling sender devices to generate post-quantum encryption keys for the first message, even if the receiver is offline.

PQ3 also implements a periodic post-quantum rekeying mechanism within conversations to self-heal from crucial compromise and protect future messages. This mechanism creates fresh message encryption keys, preventing adversaries from computing them from past keys.

The protocol utilizes a hybrid design, combining elliptic curve cryptography with post-quantum encryption during initial critical establishment and rekeying. Rekeying involves transmitting fresh public key material in line with encrypted messages, with the frequency of rekeying balanced to preserve user experience and server infrastructure capacity.

PQ3 continues to rely on classical cryptographic algorithms for sender authentication and essential verification to thwart potential quantum computer attacks. These attacks require contemporaneous access to a quantum computer and cannot be performed retroactively. However, Apple noted that future assessments will evaluate the need for post-quantum authentication as quantum computing threats evolve.

Apple iPhone 15 series devices are displayed for sale at The Grove Apple retail store on release day in Los Angeles, California, on September 22, 2023. (Photo by Patrick T. Fallon / AFP)

Why PQ3 on iMessage matters for iPhone Users

Integrating PQ3 into iMessage signifies a monumental leap forward in privacy and security for iPhone users. With the exponential growth of data and the looming specter of quantum computing, traditional encryption methods face unprecedented challenges. PQ3 mitigates these risks by providing quantum-resistant protection, ensuring that your conversations remain shielded from future threats. 

In essence, PQ3’s implementation in iMessage demonstrates Apple’s interest in safeguarding user privacy and staying ahead of emerging security threats. Beyond its robust encryption capabilities, PQ3 introduces a host of additional security features designed to enhance the overall integrity of iMessage. These include secure fundamental establishment mechanisms, cryptographic self-healing protocols, and real-time threat detection capabilities. 

By incorporating these advanced security measures, Apple ensures that iMessage remains a bastion of privacy in an increasingly interconnected world.

When can iPhone users expect the update?

Support for PQ3 will begin with the public releases of iOS 17.4, iPadOS 17.4, macOS 14.4, and watchOS 10.4. Already available in developer previews and beta releases, PQ3 will automatically elevate the security of iMessage conversations between devices that support the protocol. As Apple gains operational experience with PQ3 globally, it will gradually replace the existing protocol within all sustained conversations throughout the year.

The post Apple updates iMessage to protect iPhone users from quantum attacks appeared first on TechHQ.

• What technology trends can we expect to hit big in 2024?
• Generative AI dominated 2023 – will its bubble burst in 2024?
• Security remains a strong trend – what will this year bring?

We’ve all lived through technological advancements that were once considered sci-fi. Some of us were there when the web was unveiled 31 years ago, marking the first glimpses of a future where “browsing” took on a whole new meaning. While there have been many technological advancements over the succeeding years, 2023 may have been one of the most disruptive, with AI, in particular large language models, transforming the industry, and the world.

AI has already altered the software industry, but believe it or not, we are still at the very beginning of AI’s narrative. What’s to come in the future is hard to predict, but according to the highly renowned O’Reilly learning platform, we can start to have a clearer indication of what to expect through shifting patterns.

Relaying to O’Reilly’s internal “Units Viewed” metric, this snapshot of trends is measured by data within the O’Reilly report covering January 2022 to November 2023. According to this O’Reilly report, technology adoption in companies tends to be gradual, with established technology stacks evolving slowly over time. This is why it is important to recognize the unique technology landscapes of individual companies.

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O’Reilly software trends for 2024

O’Reilly found that programmers continued to write software throughout 2023, despite a decline in interest or usage. This in no way implies a decrease in the overall significance of software development, and the impact of software on our daily lives continues to grow.

A trend that will not change is that of software developers designing larger, increasingly complex projects. The uncertainty, however, is whether generative AI will help manage this growing complexity or add a new layer of complexity itself. Many are using AI systems, like GitHub Copilot, to write code, using AI has a quick fix. In fact, O’Reilly found that 92% of software developers are now using AI to create low-level code.

This leaves a few questions:

• Is AI capable of doing high-level design?
• How will AI change things software developers want to design?

Perhaps the key question is how can humans collaborate with generative AI to design systems effectively? There’s little doubt that humans will still be required to understand and specify designs. And, while there has been an overall decline in most software architecture and design topics according to O’Reilly, there are notable exceptions. For instance, enterprise architecture, event-driven architecture, domain-driven design, and functional programming are examples of topics that have either shown growth or experienced relatively small declines.

These changes indicate a shifting landscape in software development; one that leans more towards the design of distributed systems that handle substantial real-time data flows. The apparent growth in content in these evolving fields seems to reflect a focus on addressing challenges posed by managing large volumes of data in distributed systems.

There has also been a microservices decline. According to O’Reilly, this popular architectural approach experienced a 20% drop in interest during 2023, with many developers advocating for a return to monolithic applications. It seems organizations are using microservices as a trend, rather than as a necessity, which could lead to challenges if they are implemented poorly.

Design patterns also saw a decline (16%) in interest among developers, which may be driven by AI’s involvement in writing code, and a growing focus on maintaining existing applications. This points to a trend where design patterns are growing in importance and software becomes more flexible, even in legacy applications. However, when there has been a burst of interest in pattern designs, there has also been a surge in pattern abuse, such as developers implementing FactoryFactoryFactory factories.

O’Reilly’s report suggests a shift in interest regarding software development, primarily influenced by practical considerations, and occasional misapplications of methodologies.

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Generative AI is getting more expensive

O’Reilly AI trends for 2024

Right now, the GPT family of models is the main talking point when it comes to AI. In 2023 alone, user numbers went up a staggering 3,600%. This was kickstarted by the introduction of ChatGPT in November 2022, of course. As far back as 2020, however, GPT-3 was making a splash on the AI scene, with GPT 1 and 2 launched in 2018 and 2019 respectively.

O’Reilly’s analysis has shown that interest in the broader field of natural language processing (NLP) has experienced a substantial increase, specifically a 195% rise among its users. This is a growing trend that is expected to continue throughout 2024, with software developers inclined to focus on building applications and solutions using the APIs provided for GPT and other language models. Therefore, they may become less interested in ChatGPT.

Other substantial gains included Transformers (a type of deep learning model architecture), up 325%, and generative models, up 900%. Prompt engineering, only introduced in 2022, has become a significant topic, with a similar usage to Transformers. NLP is used almost twice as much as GPT, although, according to O’Reilly’s data, the next year will be driven hugely by GPT models and generative AI.

Here are some other key insights taken from O’Reilly’s analysis, giving us a clearer indication of AI trends for 2024:

• Deep learning remains fundamental to modern AI, with a reported 19% growth in content usage, while other AI techniques, such as reinforcement learning, have also seen positive gains.
• Programming libraries, such as PyTorch, a Python library, continue to grow and dominate programming in machine learning and AI, with a 25% increase.
• TensorFlow has reversed a decline with a modest 1.4% gain, and it seems there is a noticeable decline in interest for scikit-learn and Keras.
• Interest in operations for machine learning (MLOps) has increased by 14%. This reflects the recognition of the importance of deploying, monitoring, and managing AI models.
• LangChain, a framework for generative AI applications, is showing signs of emergence, particularly in the retrieval-augmented generation (RAG) pattern.
• Vector databases are expected to gain importance, albeit with specialized usage.

Throughout 2024, and beyond, generative AI’s influence is set to span various industries, including logistics, finance, manufacturing, pharmaceuticals, healthcare, and government.

That indicates a dynamic and evolving landscape in the year to come.

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O’Reilly security trends for 2024

Another topic that saw serious interest gains among developers in 2023 is security. According to O’Reilly, the majority of related search topics showed growth from 2022 through 2023, with network being the most used topic, seeing a 5% growth year-over-year, closely followed by a 22% growth in governance.

DevSecOps saw one of the largest growths in usage amongst security topics of 30%, while interest in application security topics increased by 42%. This indicates a move towards using security throughout the entire process of software development.

Additional things to watch in 2024

Rise of the machines in 2024? O’Reilly has ideas…

O’Reilly’s analysis signals a variety of technology trends for 2024. Here are some other trends we expect to experience as the year goes on:

• With a 175% growth, cloud native has become the most used cloud-related topic. This suggests a widespread shift of companies towards developing primarily for the cloud as their main deployment platform.
• Experiencing a 36% rise, Microsoft Power BI seems set to continue as one of the most widely used data topics.
• There has been an increased focus on professional development, project management, and project communications, signifying developers’ enhancement of “soft skills” through upskilling.
• CompTIA A+ encountered the most significant growth in content usage at 58%, suggesting a large increase in people looking to start IT careers.

Mike Loukides, vice president of emerging technology content at O’Reilly, said, “This year marks a rare and genuinely disruptive time for the industry, as the emergence of generative AI promises important changes for businesses and individuals alike.”

But, Loukides continued, saying, “Efficiency gains from AI do not, however, replace expertise. Our data signals a shift for programming as we know it, with consequences for skills, job prospects, and IT management.” With new innovations rolling out as the year progresses, it’s a time for preparation, with upskilling more critical than ever before.

The post O’Reilly report predicts technology trends for 2024 appeared first on TechHQ.

• Quantum technology investment in the UK.
• Public-private partnerships benefit from funds.
• Brain scanning and transport, among other projects.

The UK government has earmarked £45m to accelerate the use of quantum computing for the UK economy, focusing on energy, healthcare, and transport.

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Projects targeted for funding include a navigation system for trains that will improve safety by installing quantum sensors in tunnels and a brain scanner that is potentially capable of diagnosing epilepsy and dementia.

The National Quantum Strategy [pdf], published in March 2023, committed £2.5bn in funding over ten years from this year, 2024, with more than £1bn expected to be added by private sector investment as projects progress. The Strategy, described by the government as “bold and ambitious,” will develop the UK’s capabilities in hardware, supply chains, imaging, and communications.

The recent £45m investment comprises £30m from the UK Research and Innovation (UKRI) Technology Missions Fund and the UK’s National Quantum Computing Centre (NQCC), and will be joined by £15m from the Quantum Catalyst Fund, a fiscal body aimed at leveraging quantum technologies by government agencies.

Quantum technology investment comments

The UK Science Minister Andrew Griffiths visited Cerca Magnetics on February 5th, 2024, to highlight the announcement. The company is a tertiary body formed as a spin-off from publicly funded research at the University of Nottingham. The Minister said:

“This further £45 million in funding underscores our commitment to support bright UK innovators who are pushing boundaries and seizing the potential of this technology to transform our public services. Cutting-edge work on a quantum-enabled brain scanner, which will be a beacon of hope for those battling neurological conditions, is just one example. The UK is already a global leader in quantum and to maintain that position, this government will continue to invest in this transformational technology propelling the UK into a new era of technological prowess and economic growth.”

“IBM quantum computer” by IBM Research is licensed under CC BY-ND 2.0.

The UKRI and NQCC partnership focuses not on the theoretical possibilities of quantum technologies but on bringing practical examples of use cases to the point of validation. It chose projects for its funding from a competition of proposals from UK organizations.

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What are qubits in quantum computing – and why you should care?

There are currently seven projects going forward on that basis that are considering superconductivity, photonics, neutral atoms, and trapped ion processors that hold qubits in electromagnetic fields.

Director of the NQCC, Dr Michael Cuthbert, said: “Over the coming 15 months, these prototype quantum computing platforms will be deployed into the newly established NQCC facility, giving us a valuable insight into the maturity, characteristics and capabilities available across a range of hardware architectures. This next phase of the NQCC will be one of huge promise, establishing a unique state-of-the-art facility with on-premises access to a range of qubit modalities at scale.”

Professor Will Drury, executive director, digital and technologies at Innovate UK, said, “This could be transformative for life in the UK and will create new, well-paid jobs that will boost our future economy.”

Quantum technologies rely on quantum states of very small amounts of matter, which exist, in computing terms, as both 0 and 1 until observed (superposition). Pairs of entangled quanta reflect one another’s state, making data transfer instantaneous. A major challenge for developers of quantum computing is preventing external influences (such as heat) from affecting a quantum ‘bit’ (qubit), so it resolves into a static state until such a change is required.

However, when stable, groups of qubits in superposition are capable of massively parallel processing as the bits can represent a huge number of possible outcomes. Results from quantum computers are probabilistic, so they require a deterministic co-processor, usually a “traditional” computer, to interpret results.

Quantum investments in context

Research and project development, therefore, is highly complex due to the number of required components for any practical deployment. That fact is reflected in the collaborative nature of many ongoing quantum projects and the broad-brush approach to the UK government’s quantum technology investments in this type of advancement.

The £2.5bn commitment spread over ten years represents an annual outlay of 0.02% of the UK government’s managed expenditure annually. By comparison, the net cost of catering at the UK’s Houses of Parliament for the financial year 2021-2022 was £7.5m, so the government’s desire for quantum projects ranks ~33 times higher than feeding and watering its Members of Parliament [pdf].

What’s next? Quantum technology, that’s what.

The post UK confirms entanglement with quantum technologies appeared first on TechHQ.

• Technology in 2023 has been revolutionary.
• Among the technology that has changed the world in 2023, AI (LLMs) have been a significant standout.
• The drive towards aplying generative AI in every industry has meant a great focus on data center questions.

As the 2023 calendar draws to its end, it’s time for our annual write-up of the technology events and trends on which we’ve focused this year.

Each of the writers in the Hybrid News stable has their particular specialisms and interests, so our round-up of the big trends in tech in 2023 is best served by giving each a voice here on the pages of Tech HQ.

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X goes back to the future on content moderation

Content moderation in 2023

Tony Fyler writes:

You never know what you’ve got, or what you’ve had, until either it’s gone or it’s under threat.

That’s content moderation in 2023.

The rules of decent society, carried over onto social media networks, have always presumed there would be agreed rules of engagement, and enough humans to adequately police that engagement.

But with the coming of Elon Musk to then-Twitter, just as with the coming of Donald Trump to the White House, those rules began to fray. Musk fired a vast majority of his content moderation team on arriving at Twitter, both in an attempt to cut costs at the legendarily unprofitable platform and as part of a campaign to extend “free” speech into areas that seek to de-legitimize the ideas of diversity, equity, and inclusion.

Meta followed suit in terms of cutting staff from its content management and fact-checking teams across 2023, raising serious fears for the impartiality of social media reporting of key events like the 2024 Presidential election.

As the fundamental role of social media shifts from pure entertainment to including more journalistic functions, the role of content moderation will become ever more important – without it, active disinformation, or the equivalence of facts and lies, replaces an informed democracy.

X continues to challenge content moderation assumptions.

Quantum computing technology goes mainstream in 2023

Aaron Raj writes:

Quantum computing is still a relatively expensive piece of technology for most organizations. While the industry is still being developed, investments have been pouring in for quantum computing research, with more organizations now experimenting with potential use cases.

IBM, in particular, has been at the forefront of quantum computing research and development in 2023. The IBM Quantum Network has seen tremendous progress among its members. The Cleveland Clinic and IBM unveiled the first deployment of an onsite private sector quantum computer in the US, which will be dedicated to healthcare research.

IBM also unveiled the Quantum Heron, the first in a new series of utility-scale quantum processors. The 133 qubit processor offers five times improvement over the previous best records set by IBM Eagle.

Apart from IBM, several other quantum computing companies have also recorded milestones in 2023. Among them is IonQ, a quantum computing company offering a fully managed quantum computing service with AWS. There is also Horizon Quantum Computing, a Singaporean-based company building software development tools to unlock the potential of quantum computing hardware. The company raised a significant investment earlier this year and has established an engineering center in Europe.

Perhaps the biggest take away from quantum computing in 2023 will be the implementation of post-quantum cryptography to unify and drive efforts to address the threats posed by quantum computing. The National Institute of Standards and Technology (NIST) will publish in 2024 the guidelines required to ensure a fluid migration to the new post-quantum cryptographic standard.

Large language models loom large in 2023

James Tyrrell writes:

Many people would pick AI as the technlogy of 2023, but those in the know would dig a bit deeper and recognize large language models (LLMs) as the real heroes of the story. Throughout the, the impact of LLMs has been remarkable.

Enterprise software providers have integrated natural language search into their products so that users can query business data as if they were talking to a knowledgeable colleague. And we have LLMs to thank for that breakthrough. Whether LLMs can push the cost of intelligence (close) to zero, as OpenAI’s Sam Altman has forecast, remains to be seen. But billion parameter models capable of next-word prediction are certainly clever (and know how to stack a book, nine eggs, a laptop, a bottle, and a nail on top of each other, should you ever be faced with a complex and life-questioning stacking dilemma).

One of the most beautiful things about LLMs is that they can be trained on unlabelled data. You just have to mask a word in a sentence and have the algorithm find the most likely candidate – tuning the model weights as you go.

Such unsupervised learning has allowed LLMs to vacuum up virtually all of the text on the internet in every published language. We now have multilingual business avatars which are only too happy to meet and greet customers 24/7 and virtual agents that can handle common contact center voice calls with ease. What’s more, compression techniques such as dynamic sparsity allow models to run at the edge and put LLMs in your pocket.

Smartphone chips and augmented reality processors are being designed with neural engines to help us query the world as we go about our daily lives. That’s great news for remote maintenance, and LLMs have an abundance of productivity plus points – many more of which are sure to play out in 2024. The statistical magic that LLMs bring to the table shines bright – at least in most directions. Having LLMs fill in the gaps in human thought could turn out to be a double-edged sword, though. And the jury is out on whether AI is good or bad news for jobs – technology writers included!

Will write wurdz for cash… the future of content creation?

2023: the year in data centers

Fiona Jackson writes:

Love it or hate it, AI (or LLMs – thanks, James) was the hot topic of the last year – as confirmed by the Collins Dictionary. The visibility that ChatGPT brought the technology resulted in consumers demanding that products and services should match its level of intelligence. Naturally, this demand has been passed on to product and service providers – and then to the data centers that support them. It’s no longer just research departments and specialized industries that need to have AI workloads hosted, and data center operators have been scrambling to keep up.

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Verne Global transitions its Finnish underground data center to liquid cooling

Across the world, racks are being densified, new direct-to-chip cooling solutions are being built, and energy-efficient strategies are being implemented to handle the increased computational requirements. TechHQ visited Iceland in October to check out whether their claims of sustainable data solutions were true, and even with the naturally cold temperatures making direct air cooling a viable option, it turns out many are investigating more efficient liquid cooling alternatives to future-proof themselves against further demand. In five years’ time, 2023 will be looked back on as a turning point in data solution visibility.

From the public’s perspective, they will go from faraway, almost mythological facilities that enable ‘the cloud’ to familiar infrastructure, built into skyscrapers, supermarkets, or architecturally impressive buildings that draw the eye. But their new presence in society will not just be physical: as discussions about AI, data handling, and technological infrastructure will permeate everyday conversations, concerns regarding sustainability, ethics, and the societal impact of these advancements will become public discourse, fostering a deeper understanding of the pivotal role these data solutions play.

The year of ubiquitous AI

Muhammad Zulhusni writes:

In 2023, AI firmly established itself as a staple in our daily lives, initiating an era where it’s no longer a futuristic concept but a tangible, integral reality. This year marked a shift from AI being a source of curiosity and entertainment to becoming a critical tool across various domains.

The emergence of “prompt whisperers” exemplified the evolving interaction with AI, guiding users in creating effective prompts and blending AI services for enhanced outputs. AI’s influence was profoundly felt in the workplace, making headlines for winning photography competitions and excelling in academic exams. ChatGPT’s user base reached 100 million by February, a testament to its widespread acceptance.

Other significant developments included the launch of Google’s chatbot Bard, Microsoft incorporating AI into Bing, and Snapchat’s introduction of MyAI. GPT-4’s release in March further advanced AI capabilities, particularly in document analysis.

Major corporations like Coca-Cola and Levi’s leveraged AI for advertising and creating virtual models. The year also saw culturally impactful moments, such as the viral image of the Pope in a Balenciaga jacket and calls for a pause in AI development. Amazon integrated AI into its offerings, while Japan made notable rulings on AI training and copyright. In the US, screenwriters went on strike over AI-generated scripts and actors, highlighting the growing influence and controversy surrounding AI.

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How generative AI in Google is powering change in every sector

AI’s rapid advancement in 2023 has significant implications for the future, particularly in reshaping job markets, education, and policy-making. It’s driving crucial conversations around ethics, privacy, and data security, prompting new regulations and standards. The democratization of AI tools is sparking innovation across industries, fostering an environment of rapid technological progress.

Five years from now, 2023 will be seen as the beginning of the AI revolution, setting the stage for AI to be an integral, ethically integrated part of our lives, revolutionizing our interactions with technology and society.

2023, a year of fading Red Hat

In 2023, technology giant Red Hat lost its mind. Or its soul.

Joe Green writes:

2023 saw Red Hat’s crown slip out from under the brim of the company’s fedora. For years the poster child of how an open source company could make real money, Red Hat suddenly decided to annoy and negatively impact the community of developers, admins, and IT professionals who – let’s be honest – make sure a sizeable chunk of the world’s computers keep doing their thing.

Early in the year, the byte-for-byte copy of Red Hat Enterprise Linux, CentOS, was canned with little notice, and more recently, the company decided the (previously open source) source code for RHEL was to be placed behind what amounted to a paywall.

Many commentators placed the blame on the perceived ‘bad guy,’ namely IBM, who’s owned the Linux outfit since 2019. But regardless of where the decisions came from, the imperative behind the moves was commercial – a short-term maximizing of profits at the expense of long-term continuity, goodwill, and the collectivist ethos on which Red Hat and the internet were built.

There are significant parallels in the myopic mindset between Red Hat’s courses of action and those of all human activity with regard to the accelerating climate disaster we are living in. Despite the cost of failure being higher in 30 years by a huge factor, both we and Red Hat/IBM choose short-termism, indolence, and profiteering over positive and collective action to assure a future.

“2023 Happy New Year Taiwan Kaohsiung 高流幸福式元旦煙火” by 黃昱峰 is licensed under CC BY-NC-SA 2.0

Did 2023 kick off the era of quantum utility?

The post The standout technology of 2023 – our writers speak appeared first on TechHQ.

• Quantum computing uses electrons rather than transistors, for a much more rapid solution to complex problems.
• There’s every likelihood that the technology will be able to rapidly reduce current encryptions to dust.
• The quantum race is largely between China and a handful of western companies.

We may be on the verge of revolutionary AI problem-solving with news of IBM’s quantum computing advancements. (We say “may” in tribute to Werner Heisenberg and his famous principle, and because nothing since has ever been entirely certain in the quantum world).

We are living in a golden age of artificial intelligence, with innovations seemingly bombarding us every day. The trend has continued with IBM announcing advancements in a new kind of computing that is capable of solving extraordinarily complex problems in just a few minutes.

Why is this newsworthy? Surely that’s what all computers do?

Yes, but today’s supercomputers would need millions of years to solve problems as complex as the ones IBM is making progress with.

Welcome to the wonderful world of quantum.

Quantum computing is a technology being developed by companies like IBM and Google.  Operating in a fundamentally different way to classical computing, it relies on quantum bits (qubits) and principles including superposition and entanglement. As the name suggests, quantum physics is an intrinsic part of quantum computing. We may even need a quantum computer to explain how this type of computing works, but this technology is without question changing the world.

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Tips on where and when to use a quantum computer

A new age of computing

Everything we know is pushed to the limits with quantum computing. From science to finances and from AI to computational power, this “supercomputer” offers the potential for solutions to problems that are currently intractable for classical computers.

The revolutionary nature of quantum computing lies in its potential to transform problem-solving approaches. It has the potential to tackle previously unsolvable problems, and impact many fields worldwide. It presents a paradigm shift akin to the introduction of classical computing, though in comparison, quantum computing’s possibilities are on a vastly different and exponentially more powerful scale.

IBM director of research Dario Gill believes quantum computing will have a significant impact on the world, but that society is not yet prepared for such changes.

“It feels to us like the pioneers of the 1940s and 50s that were building the first digital computers,” he said. It’s plain to see how much impact digital computers have had on the world since the 1950s, but quantum computing is another kettle of deeply unusual fish.

“We are now at a stage where we can do certain calculations with these systems that would take the biggest supercomputers in the world to do,” Gill explained. But the potential of this technology is only just being realized. The goal is to continue the expansion of quantum computing capabilities, so that “not even a million or a billion of those supercomputers connected together could do the calculations of these future machines.”

A quantum computer from IBM – the future appears to be agreeably steampunk.

We have already witnessed significant progress in this field of technology, but the difference now is that Dario Gill, and others working in the quantum field, have a clear plan or strategy in place for further advancements. That means the rate of progress is only expected to accelerate – possibly at a pace that will surprise the world.

Today, computers process information on transistors, something they have done since the advent of the transistor switch in 1947. Over time, however, the speed and capabilities of computers have increased substantially. This is due to the continuous advancement of technology. This enhancement stems from the strategy of densely integrating an increasing number of transistors onto a single chip, reaching a scale of billions of transistors in today’s computer chips.

Computers require billions of transistors because they are in either an “on” or “off” state. Known as complementary metal-oxide-semiconductor (CMOS) technology, quantum computing is now presenting alternatives to this hallmark of classic computing.

Rather than using transistors, quantum computing encodes information and data on electrons. These particles, thanks to the rules of quantum mechanics, can exist in multiple states simultaneously, much like a coin spinning in the air. Simultaneously, it shows aspects of both heads and tails. Unlike traditional computing methods, that deal with one bit of data at a time on a transistor, quantum computing uses qubits. These can store and process exponentially more information because of their ability to exist in multiple states at once.

Classical computers require a step-by-step process when finding information or solving problems. Quantum computers, on the other hand, are capable of finding solutions much faster by handling numerous possibilities concurrently.

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How can quantum computing help my business?

The quantum computing race

Like any up-and-coming technology, countries around the world are vying for quantum supremacy. Currently, private free enterprises and state-directed communism are the main competitors. In other words, the race is “between China on one side, and IBM, Google, Microsoft, [and] Honeywell,” according to physicist Michio Kaku. These are the “big boys” of quantum computing.

America has approximately 180 private firms researching quantum computing, most of which fund themselves. The US also has a number of government initiatives investing heavily in quantum research. Along with IBM, Google, and Microsoft, institutions including NASA, DARPA, and NIST are at the forefront of quantum computing and technology development.

Quantum computing – bringing the sci-fi home.

China has been making substantial investments in quantum development and research for a number of years. For instance, it has several state-backed initiatives and research institutions, including the Chinese Academy of Sciences, all working on quantum technology. Large corporations, including Alibaba and Huawei, are also involved in quantum computing research.

The US government currently spends close to $1 billion a year on quantum research, whereas China has named quantum as a top national priority. New standards for encryption are to be published by the US in 2024, something that will cause waves (or potentially particles) in the quantum field.

If you’re looking for revolutions in computing as big as quantum, you’re probably looking back to the machine that cracked the Enigma code…

The winner of this quantum race will have striking implications, as Kaku believes the nation or company that succeeds “will rule the world economy.”

Think OpenAI and ChatGPT, but with the potential to crack any code, open any safe, and of course, demand any price.

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Quantum computing challenges

As we immerse ourselves in quantum computing’s promising possibilities and how it is a savior to all of humanity’s problems, we must not forget the challenges it also faces. For instance, coherence times need to be enhanced and machines require scaling up to operate effectively with quantum computing.

Hartmut Neven, founder and manager of Google’s Quantum Artificial Intelligence Lab, believes that small improvements and effective integration of existing pieces are key to building larger quantum systems. “We need little improvements here and there. If we have all the pieces together, we just need to integrate them well to build larger and larger systems”.

Neven and his team aim to achieve significant progress in quantum computing over the next five or six years. He believes that quantum computing holds the key to solving problems in fields like chemistry, physics, medicine, and engineering that classical computers are currently, and will always, be incapable of. “You actually require a different way to represent information and process information. That’s what quantum gives you,” he explained.

Further challenges persist due to the delicate nature of qubits, which are prone to errors and interference from the surrounding environment. As James Tyrrell discusses here, efforts to mitigate this noise and enhance the reliability of quantum computers are underway. The expansion of the (Quantum-Computing-as-a-Service) QCaaS ecosystem is expected to shift the focus from technical intricacies to practical applications. This will potentially allow users to harness the power of quantum computing for real-world problem-solving.

The development of quantum computing is accelerating at an exponential rate. Over the next decade or so, Dario Gil sees no reason why quantum computing can expand to thousands of qubits. He believes that systems will be built “that will have tens of thousands and even a 100 thousand qubits working with each other.” Where quantum technology goes from here is (thank you, Werner!) distinctly uncertain, but if the excitement is anything to go by, it may potentially have the answers to all the world’s problems.

The Quantum System Two. Scary cool computing power.

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Where and when to use a quantum computer? It’s one of the most common questions that experts, such as Kirk Bresniker – Chief Architect at Hewlett Packard Labs, get asked by business leaders. Enterprises want to know where in the IT portfolio quantum computers will bring the most significant rewards and when is the right time for firms to invest in solutions.

For decades, quantum computing developers have been promising big things from quantum computers, which is understandable. Quantum computers are costly to develop, and being modest about the technology isn’t going to win over investors. However, it’s important to note that quantum computers aren’t universal computing devices.

“Quantum computing promises transformational gains for solving some problems, but little or none for others,” write MIT Sloan School of Management researchers in a paper dubbed “The Quantum Tortoise and the Classical Hare” submitted to arXiv.

Curious about the impact of quantum computing, but don't have a PhD in Physics? Our new article "The Quantum Tortoise and the Classical Hare" may be the framework you need: https://t.co/aOAmObjjtu

— Neil Thompson (@ProfNeilT) November 17, 2023

The team, led by Neil Thompson – whose career includes appointments at Lawrence Livermore National Laboratories, Bain and Company, The United Nations, the World Bank, and the Canadian Parliament – has come up with a simple framework for understanding which problems quantum computing will accelerate (and which it will not).

Quantum computers open the door to probabilistic computing, with quantum gates adding a twist to each of the qubits in the calculation. As the system evolves, the qubits interact and point to the most likely solution to the problem that they’ve been arranged to describe.

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How can quantum computing help my business?

Prodding a bit further, if we consider classical machines as mapping business questions onto maths – a perspective shared by Scott Buchholz, Global Quantum Lead at Deloitte Consulting, at this year’s D-Wave Qubits conference – then quantum computers give us the chance to use physics instead.

It turns out that some questions are easier to map onto physics than others, and this gets to one of the key considerations in the MIT framework on where and when to use a quantum computer.

Much of the talk on progress in quantum computing surrounds the number of qubits. Systems are notoriously noisy, which adds to the number of physical qubits that are required – to facilitate error correction on logical qubits. On top of this, there are multiple ways of engineering the superposition of ones and zeros through the use of superconducting, trapped ion, photonic, or silicon spin qubits.

Each quantum computing developer has its own preferred approach, and as you walk down the path of trying to understand how quantum computing works, the discussion becomes one about the technology. And this is fine. Large companies can engage their R&D teams and have conversations with hardware developers.

When to use a quantum computer – a rule of thumb

However, just as you don’t need to understand what’s happening inside a CPU to benefit from a laptop, companies can focus their attention on the kinds of problems that quantum computers can help with, rather than getting bogged down with the numbers and types of qubits.

In their decision-making framework, Thompson and his colleagues identify two determinants in understanding when to use a quantum computer – the efficiency of the algorithm and the scale of the problem that needs to be solved.

“The problem size matters because the benefit of an algorithmic advantage is larger for larger problems,” explains the team. “This means that if a problem is too small, the classical computer will have already completed the problem by the time the quantum computer’s algorithmic benefit kicks in.”

Quantum computers are often mentioned in terms of being able to tackle problems that are effectively impossible with classical machines. But the researchers want to guide enterprises on other opportunities too, where a quantum economic advantage exists.

Their analysis also considers technology roadmaps so that companies can assess when the window for using a quantum computer could open up for them.

Problems that become exponentially harder to solve as the size of the problem increases are interesting candidates when thinking about alternatives to using classical computing machines. And Thompson and his co-authors – Sukwoong Choi and William Moses – provide a useful rule of thumb.

“If a classical algorithm takes exponential time and there exists a polynomial quantum algorithm, you’re likely to get a speedup,” they comment when discussing their framework on when to use a quantum computer.

Examples of quantum computing as a service (QCaaS) providers

It’s worth pointing out that companies don’t have to invest in bare metal hardware. For most customers, their first experience of what qubits are capable of will be via the cloud using one of a number of QCaaS providers.

Amazon Braket makes it straightforward for firms to work with different types of quantum computers and circuit simulators. Amazon advertises that Braket comes with one free hour of simulation time per month, lowering the cost barrier to getting started.

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QCaaS hardware associated with Bracket includes gate-based superconducting processors from Rigetti and OQC, neutral atom-based quantum processors from QuEra, and IONQ’s gate-based ion-trap processors.

Microsoft’s Azure Quantum cloud service is another option for firms. Here, users get access to systems from Quantinuum, QCI, and PASQAL, as well as the quantum computing hardware mentioned above.

And companies can also access quantum computing solutions in the cloud using QCaaS platforms operated by developers such as IBM, Google, and D-Wave.

There’s no shortage of options, and with frameworks to guide enterprises on where and when to use a quantum computer, now is a good time to think about the types of algorithms supporting your operations and whether qubits can provide an economic advantage to the bottom line.

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Fintech firms rely on clever software and mobile apps to jump ahead of conventional financial players such as older banks and payment providers. Such high-tech thinking in finance extends to the use of quantum computing as a way of maximizing business profits, helping fintech firms and other progressive companies extend their advantage.

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A recent example of how quantum computing can help business can be seen in the use of commercially relevant solvers by Satispay, a European fintech based in Italy. Wanting to accelerate the adoption and usage of its novel payments network, Satispay built a proof-of-concept using D-Wave’s quantum annealing technology, which is ideal for tackling optimization problems.

“Together with D-Wave, we’ve built a quantum-hybrid application that has demonstrated immediate business value at scale, helping us more effectively manage our rewards program to save money, improve rewards appreciation, and drive increased membership,” Dario Brignone, founder and CTO of Satispay told investors.

To understand why Brignone looked to quantum computing for answers, rather than use classical machines, it’s helpful to consider how the Milan-headquartered fintech – which operates in Italy, France, Germany, and Luxemburg – grows its market footprint.

What is Satispay?

Italy, the home of Satispay, is fuelled by espresso. But until Brignone and his fintech colleagues put their heads together, it was unheard of to pay for the nation’s favorite serving of coffee by card. The hold-up was payment processing fees, which meant that coffee shops would rarely accept anything, but cash, for food and drink bills of less than 10 Euros.

Recognizing a fintech opportunity, Satispay created its own network that eliminated all of the intermediaries that are traditionally involved in e-payments, which – as a result – was more efficient and cheaper. Bricks-and-mortar stores can accept transactions up to 10 Euros without any charges, while transactions above that value attract a fixed fee of just 20 cents.

Quantum computing helps Satispay’s business by puzzling out the best combination of rewards, which are designed to attract new customers and keep existing users engaged with the app. When fintech users open Satispay, they see a list of merchants near them with their current location at the top of the list –for example, if they are already inside a physical store or coffee shop.

Considering the example of a user buying a coffee, they simply ‘push’ the amount digitally to the store owner, who can view the transaction on their own app, or even using a regular point-of-sale terminal. Incentives for customers include cashbacks, such as receiving 20% cashback on all purchases in a given store. But there are also variations, including having the reward for a first purchase only, and incremental cashbacks that become more attractive as customers return and shop again.

Biglietto per il trasporto ancora più smart grazie alla collaborazione tra GTT e Satispay. L'app che ti consente di acquistare online in modo sicuro sull'app TO Move, selezionandolo come metodo di pagamento. Inserisci il codice promo “GTT” hai un bonus di benvenuto di 5€. pic.twitter.com/wUUf1yN78m

— GTT Torino (@GTT_Torino) October 24, 2023

“The challenge for Satispay was how to best match those offers with those who wanted to take up on them,” Murry Thom – VP of Quantum Business Innovation at D-Wave told TechHQ. “And the key step when running the optimization is to focus on what you are trying to optimize.”

In the case of Satispay, the fintech payments firm wanted the largest growth in its customer network for a fixed budget. However, given that multiple factors are all tied to the same budget, it’s a problem that can get complicated even at a modest scale when modeled using a classical computer.

The good news for Satispay, highlighting how quantum computing can help business operators, is that the solver built by the team showed an improvement of 50% in customer rewards programs for the same budget. And this gets straight to the ‘immediate business value’ that Brignone mentioned in his statement.

Quantum computing can help firms achieve a range of business objectives. Staying in the world of finance, another popular application for using physics to solve complex problems that would be too time-consuming for classical computers, is managing financial risk.

Quantum algorithms have been applied in the area of portfolio management – for example, to help asset holders determine how much capital to hold for worst-case scenarios.

How to program a quantum computer?

When we use our laptops and smartphones, it’s unlikely that many of us are racking our brains trying to picture electrons flowing through transistors. However, quantum bits (qubits) have proven to be a captivating topic – for example, thanks to concepts such as superposition and entanglement that begin to describe how computation takes place.

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That being said, users wanting to discover how quantum computing can help their business don’t need to puzzle over why qubits can be both zero and one and get to grips with a Hamiltonian or Eigenspectrum. Quantum computing vendors such as D-Wave and others have numerous tutorials available that answer common questions on how to program a quantum computer.

Also, for popular tasks such as solving optimization problems, there’s a good chance that there’s already a model that users can build upon rather than having to start from scratch. Satispay plans to put its application into production and expects its internal teams to be using the quantum computing tool on a weekly basis.

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• Unpredictable quantum keys are a mind-boggling way to ensure data safety.
• That which cannot be predicted, can be neither cracked nor hacked.
• Preparing for a quantum future right now makes sound business sense for your data.

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How can quantum computing help my business?

As part of our look into the businesses using the UK’s Cyber Runway from Plexal in 2023, we talked to a handful of this year’s cohort. George Dunlop, co-founder and director of partnerships at Quantum Dice, a provider of unpredictable quantum keys, was next to sit down with us.

We felt the need to make an early confession.

THQ:

Hi George.

Quantum.

Every time we read about quantum technology, it boggles our brain for a good half hour before it even starts to make sense. But quantum technology is often described as the next big revolutionary model in the tech world – and yet it’s here. Now.

What’s the market like for unpredictable quantum keys right now? And how has it been moving in the last year or two?

GD:

We’ve seen a great maturation in the space, but it’s not an uncommon experience that you just described with quantum. The focus in the market right now is really driving value in applications.

THQ:

So making esoteric physics into business value?

GD:

Exactly.

In quantum technology, we’ve seen physics move from an academic research area to an ecosystem of technology applications. Emerging solutions are coming to demonstrate specific, clear commercial value. One of the most mature areas in quantum technology right now is in its application to cybersecurity, which is driving value around the unpredictable quantum keys we use to lock and unlock our data.

The value add of quantum keys.

In the past few years, we’ve also seen significant acceleration in the cybersecurity industry, which has uncovered a couple of vulnerabilities in existing solutions, where quantum can offer a value add.

Most notably, we’ve seen the discovery of a vulnerability in firewalls, where it was found that the keys companies were using had insufficient entropy or randomness.

THQ:

The second law of thermodynamics. Entropy increases…

GD:

And if you want to produce better quantum keys, you need a good and trusted locksmith for your cybersecurity applications – which is where quantum technology can come in.

THQ:

We’ve spoken to other players in the quantum market, and it seems to be a reverse-driven process, right? The weaknesses in our current cybersecurity posture were often discovered by people looking at the things they’d have to do to ensure their cybersafety once the big quantum technology explosion happens, when we get quantum computers that point and laugh at what we currently call data security.

To what extent do people understand the need for things like quantum keys at this stage?

Let him who hath understanding reckon the number of the keys…

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GD:

That depends who you ask. If you ask the general public, probably not at all. But in cybersecurity and industry, it’s been known and understood since the late 90s.

As you say, the big quantum point is coming – the point where quantum computing becomes stable enough to become a mundane reality. We can debate when it’s coming, but it’s known that it’s on the horizon. So yes, it’s fairly well understood, and there has been that sort of reverse-engineering at work. Sometimes you don’t know a vulnerability is there until you go looking to solve something you’re assuming will be there in the future.

THQ:

Be fair – that sounds very quantum…

GD:

So if we talk about quantum, there’s this application, but then there’s also what the technologies themselves can enable.

The thing in the past few years that has really driven understanding has been adding quantum to standards. The most recent development was NIST in the US issuing the draft standards for the tools that will be used to protect against quantum computers.

Now, if you have a vulnerability, or you have a risk, the key step is being able to measure that risk, so you can quantify both your exposure and your areas of vulnerability. So, one of the most mature areas is quantum key generation, which means there are actually benefits the technology can add now, by being able to measure the quality of your keys in real time.

That’s a measurement that quantum systems offer, where you’re able to measure where your randomness comes from, and actually delve down into the origin of your trust.

Quantum keys: the dummies’ guide.

THQ:

Boggling jussst slightly, but let’s stick with it. We understand how quantum random number generators would work in terms of locking things up. We’re a little sketchy on how they then can be unlocked by the rightful owner of the data.

GD:

Right. If you think of your enterprise as a building, you build your walls, your doors, your locks and your keys, to protect your data or yourself.

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There are many tools and bits of software you can use. For example, you can use software encryption as a lock to protect our data. Now, when you ask the question “How do you want to unlock the data?,” we’re talking about using quantum, an area of physics, to create high quality keys.

Quantum technology is also being used to create better locks for your data, for which the key can be produced to unlock it in the same way that a quantum computer for example would do (another area of quantum physics being used to break the whole house down – but it’s still a tool).

So when I talk about Quantum Dice producing high quality keys, we’re using the measurability we can use to provide proof and trust in the keys that you’re making, in the same way that you’d use another area of physics to build trust in a different tool you’re building.

When you really care about data security – go quantum.

THQ:

Wait, wait, we think we’re getting it. So just like you use gravity to test the effectiveness of a spirit level, you use the principles of quantum physics – entropy, randomness and the gang – to test the effectiveness of a key, so companies can be reasonably sure that the key locks and unlocks their data – but that nothing else can get in or out?

GD:

Something like that.

There are ways and means of using quantum to lock and unlock data. And the key consideration for anyone in security is having trust and verification in the process by which you do that.

That’s the power of unpredictable quantum keys.

Still confused? Watch this.

THQ went for a short lie down in a darkened room at this point. When we came back, Jonathan Wood of security and compliance firm C2 Cyber was waiting for us, with unusual answers to questions of intelligence.

The post Unpredictable quantum keys – using physics as cybersecurity appeared first on TechHQ.

Quantum computers are often pitched as being able to perform calculations – or at least certain kinds of calculations – more efficiently than classical machines. However, for companies, the advantage of using quantum technology could relate to more than just a speed-up of their operations. Monte Carlo integration engines give users the opportunity to run risk management algorithms on qubits, which could give businesses a clearer view of the road ahead.

What is Monte Carlo Simulation?

Understanding the likelihood of an event taking place is helpful across a range of industries. Stockbrokers, in particular, have a keen interest in how different assets could fare as market conditions develop. And trades are based not just on price expectations, but on whether those thresholds will be reached at a certain point in time – for example, when considering financial derivatives such as futures and options contracts.

Naturally, stock prices can move along various paths and are dependent on numerous parameters, to a greater or lesser extent. What’s more, considering portfolio management, the price of one stock may be dependent on another, which can send analysts in circles if they approach the modeling process as a conventional maths problem.

An alternative way of picturing how path-dependent behavior could play out is to use Monte Carlo methods, which rely on the fact that a random sample can – under the right conditions – shine a useful light on future events. “We care about quantities right down the tail,” Steven Herbert – Head of Algorithms at Quantinuum, a full-stack quantum computing company combining Cambridge Quantum and Honeywell Quantum Solutions, told TechHQ.

Herbert and his colleagues have built what they dub a Modular Engine for Quantum Monte Carlo Integration that gives users in financial markets and other sectors a computational tool for evaluating the interplay between parameters in complex systems.

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Simulations can be run to consider large numbers of possible paths based on random conditions to reflect the likelihood of events, such as the probability of catastrophic failure. Repeating the process over and over again emphasizes strong signals in the results. And data could help companies to determine how much capital to hold to prevent default. “Risk management is going to be the killer app,” said Herbert.

Quantum computing is based on the idea that it’s possible to prepare a quantum state that encodes every answer for every input. Given sufficient coherence time, measurements indicate the most likely outcome. However, qubits are highly susceptible to noise and can lose their state, which is a challenge for developers of quantum computing technology.

Quantinuum gets around this problem in its quantum Monte Carlo engine by chunking the computation into shorter segments. Rather than consider the Monte Carlo integral as a whole, it’s possible to decompose the expression as a Fourier series, with each harmonic estimated using a shallow quantum circuit.

The strategy allows the team to run its computation as blocks that fit into the coherence time. “Fourier series computation works really nicely,” notes Herbert.

The Quantum Revolution is here! Discover how Quantum Computing is supercharging AI in finance.

Georges-Olivier Reymond, CEO of @pasqalio, and Christophe Michel from @CreditAgricole dive into Quantum Accelerated AI.

Watch now: https://t.co/SZE9zF8Kvt#B2BRocks #Quantum #AI

— OVHcloud (@OVHcloud) September 21, 2023

Another approach to squeezing as much performance as possible from current hardware, known as Noisy Intermediate-Scale Quantum (NISQ) devices, is the use of TKET – an SDK that optimizes quantum gate design.

Quantum algorithms can be assembled using well-known building blocks, but a less intuitive gate arrangement could be better suited to the task, and TKET solves that design problem. “It’s highly optimized and means that you’re getting as much computation as you can in the box,” Herbert explains.

Clients want the higher precision that techniques such as quantum Monte Carlo integration provide to be straightforward to adopt for use in financial risk management and to benefit other use cases. And hiding the complexity of building quantum circuits in software is a step in that direction.

In fact, analysts may one day sit down and not even know that they are using a quantum computer as the user experience evolves. But, as Herbert points out, quantum computing is a whole new industry that’s being built from scratch.

Future of risk management and other applications

Given how novel the technology is, it’s not surprising that a learning curve still exists in understanding how enterprises can benefit fully from advances in the field. On TechHQ, we’ve written about how quantum computers can help to solve supply chain issues and improve logistics, but the applications don’t stop there.

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Quantum computing is extremely broad in scope. Tools can help with not just risk management in the financial sector, but also modeling chemical reactions, developing better medicines, and much more besides. And while that may spread developers thin, in terms of focusing on each of the individual use cases, it is great news for investment.

Earlier this year, Deloite’s Insights team updated its analysis of the quantum computing sector based on levels of capital investment and other signals, such as patent filings for hardware technology. “Globally, the financial services industry’s spending on quantum computing capabilities is expected to grow 233x from just US$80 million in 2022 to US$19 billion in 2032, growing at a 10-year CAGR of 72%,” write the researchers, highlighting how financial services firms are amongst those loading up on the opportunities to get ahead.

It could be the case that customers using quantum tools for derivative pricing, portfolio risk calculations, regulatory reporting, and other risk management activities play a role in softening the sharp edges – making quantum computing solutions easier to adopt elsewhere.

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Nature has no shortage of lessons for device makers looking to make better products with a host of properties that come easily in the natural world. Many thousands of years of evolution have yielded computing systems such as the human brain, which can operate on the power of a dim lightbulb. And Circuits of Life – a UK-based project featuring experts in computational biology and other disciplines – is taking inspiration from the protein-based electronics necessary for life on Earth and aims to build key components to order.

On TechHQ we’ve written about how slime mold has an incredible ability to solve mazes and perform optimizations that would challenge conventional computers. And nature turns out to be rich in computational capabilities.

In his book ‘Quantum Supremacy’, Michio Kaku points out that plants have quantum computing-like properties. For example, leaves are incredibly efficient in photosynthesizing light into chemical energy – much more so than classical physics would suggest.

And Kaku describes to readers how photons of light incident on the leaf surface are channeled counterintuitively like golf balls being hit in all directions yet still finding their way to the hole. Considering leaves as quantum solvers may feel peculiar, but biology is no stranger to properties that have device appeal.

Circuits of life as a molecular toolkit

“The flow of electrons within protein-based circuitry is essential to life, underpinning cellular energy generation and photosynthesis,” writes the Circuits of Life team, introducing its latest findings in the Proceedings of the National Academy of Sciences (PNAS).

In the paper, Ross Anderson and his co-authors describe how to make conductive, biodegradable wires from designed proteins, which could – the researchers believe – open up a new era of environmentally friendly programmable bioelectronics.

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The molecular wires, which are comparable in size to features found on silicon chips, are said to be compatible with conventional electronic components made from copper or iron. And, thanks to their protein origins, these nanostructures may also provide a bridge to the biological machinery responsible for generating energy in all living organisms.

Circuits of Life got the go-ahead in 2022 when the proposal to create and comprehend the way that nature builds its electronics was awarded GBP 4.9 million in funding, as part of the BBSRC’s flagship Strategic Longer and Larger (sLoLa) grant scheme. And the support provides five years of funding to build completely new protein-based circuitry, catalysts, and light-harvesting assemblies.

For example, it’s thought that the dynamic nature of proteins could help lower the energy barrier to substrate entry and product exit – offering catalytic support to bioreactions. Artificial bio-inspired electron-conducting circuitry could also lead to novel sensors for diagnosing disease and detecting environmental pollutants.

@uwaterloo Scientists create 'artificial leaf' that turns carbon dioxide into fuel.The "artificial leaf" technology mimics photosynthesis by taking carbon dioxide and converting it into methanol and oxygenhttps://t.co/OjQ34YiLND pic.twitter.com/7QmgkXGdX5

— R+T PARK (@RTPARKUW) November 4, 2019

Nature’s ability to transport electrons is fundamental to cellular respiration – the method by which living organisms obtain energy from food – and photosynthesis. And understanding in more detail how proteins and other related structures enable these bioengineering marvels has benefits for cleantech and building better medical devices.

Artificial leaves capable of turning carbon dioxide into fuel could solve the dual problem of providing green energy and consuming products that would otherwise contribute to global warming.

Bioelectronic medicine – exploring novel neural interfaces

In medicine, there’s great interest in being able to selectively modulate the autonomic nervous system. Neural engineering studies have indicated how it’s possible to act on the internal state of the body and compensate for damaged or dysfunctional elements.

“For decades, several devices known as neural prostheses have used electrical pulses to communicate with the nervous system to improve health and save lives,” writes Marina Cracchiolo and colleagues from the BioRobotics Institute of Sant’Anna School of Advanced Studies, based in Italy. “These devices act by substituting or modifying the activity of a dysfunctional or injured nerve or a neural circuit, which in turn directly controls muscles or sensory organs.”

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However, circuits of life – such as the computer-simulated building blocks proposed by Anderson and co-workers in the UK – could zoom in and take bioelectronic medicine to a whole new level. Biocompatible, miniaturized devices raise the prospect of targeting individual nerves to modulate and decipher neural signaling patterns, paving the way for advances in bioelectronic medicine.

Galvani Bioelectronics – a joint venture between pharmaceuticals firm GSK and Google X spinout Verily – is an example of one med-tech developer aiming to transform patient lives through precision neuromodulation. And it’s clear that being able to lean on not just conventional electronics, but also to learn from how nature manages electron flow will pay dividends.

Returning to the idea of circuits of life – bioelectronics inspired by nature – computers play a major role in proposing how to build nanoscale protein wires for long-range electron transfer. The first step is to devise a modular protein platform for creating well-folded variants that can then be extended as part of a computational design strategy.

Techniques such as NMR spectroscopy and cryogenic electron microscopy allow workers to visualize their creations and gather structural insight that can’t be simulated in the digital world. And physical experiments provide confidence in the fidelity of the design process.

“To fully unlock the diverse functional repertoire of the natural oxidoreductases, it will be necessary to integrate molecular dynamics simulations and continuum electrostatics calculations, and other prediction tools, into the design process to define and modulate biophysical properties,” concludes the Circuits of Life team in their write-up.

The group’s comments point to the direction of travel in the project, which still has plenty more to offer the field on top of its early breakthrough in creating a microscopic toolkit of ‘green’ tuneable electrical components.

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