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Artificial Intelligence & Quantum Computing the Next Big Thing? – Medium

How can Quantum Physics empower AI?Photo by Anton Maksimov 5642.su on Unsplash

Quantum computers based on quantum physics can be much faster than normal computers, at least in solving some mathematical problems. How can the area of artificial intelligence, data science & Co. profit?

First lets look into what a quantum computer is and why they are faster:

A quantum computer uses qubits, which can exist in superposition and be entangled, to perform computations. By leveraging these quantum properties and applying quantum gates, quantum algorithms can solve certain problems more efficiently than classical computers. However, building practical and scalable quantum computers is still an active area of research, and many technical challenges need to be overcome before they can be widely deployed[1][2}.

So now to the question of how quantum computing could possibly enable faster processing times for AI models. In the future, quantum computers could solve certain problems much more efficiently than ordinary computers by exploiting the unique properties of the subatomic world.

Experts have been wondering whether these problems could also include machine learning. This is a form of artificial intelligence in which computers look for patterns in data and learn rules that they use to draw conclusions even in unknown situations[3]. So yes quantum computing can be much faster but is the answer exact enough?, since we have learned that this output is probabilistic so the output can be different although the input is the same. So the unanswered question is whether there are scenarios in which quantum machine learning offers an advantage over the classical variant?

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3 Quantum Computing Stocks to Make You the Millionaire Next Door: 2024 Edition – InvestorPlace

Millionaire-maker quantum computing stocks are inherently risky but offer massive payoff

Source: Boykov / Shutterstock.com

Quantum computing is the next evolution of computing. Its benefit is that, at its core, it is capable of solving problems that classical computers cannot. Classical computers often rely on brute force to find solutions to complex problems. However, like all things, there is a barrier. These millionaire-maker quantum computing stocks will push computing past its current limits.

Faster computing times have vast applications. Just about everything today relies on computers and, as the field develops, investment is sure to rise. That makes the quantum computing stocks below incredibly interesting. Compound annual growth rates in the sector are expected to reach above 38% between 2023 and 2028. Thus, an investment today could yield substantial returns for millionaire-maker quantum computing stocks.

Source: Amin Van / Shutterstock.com

IonQ (NYSE:IONQ) has developed the IonQ Forte quantum computer, while emerging as one of the sectors top stocks.

Its shares have really blossomed in 2023, providing investors with strong returns but not returns without volatility. The companys shares were below $4 at the beginning of the year, but shot up to almost $20 in August. It currently resides at around $12. So, it was both rewarded and punished in 2023.

The companys Forte quantum computers are currently available through the three leading Cloud providers; Amazons (NASDAQ:AMZN) AWS, Microsofts (NASDAQ:MSFT) Azure and Alphabets (NASDAQ:GOOG, NASDAQ:GOOGL) Google Cloud.

Company revenues grew by 122% in the third quarter, reaching $6.1 million. While that was above the high end of guidance, Its 22 cent EPS was 7 cents lower than expected. Yet, the company increased its guidance for the full year to a high of $22 million from a previous high of $19.3 million.

Source: Shutterstock

FormFactor (NASDAQ:FORM) is an interesting, diversified way to play the emergence of quantum computing stocks. The company is not primarily engaged in the business of quantum computing. Instead, FormFactor is a semiconductor company.

The company sells probe cards which are used for chip testing. Semiconductor testing and measurement is a growing, high-margin business worthy of investment.

However, FormFactor also recently released a quantum computing chip which has thrust it into the conversation relating to quantum computing. Clearly, FormFactor is a more diverse and potentially lower-risk option in millionaire-maker quantum computing stocks.

Financially, the stock is somewhat of a mixed bag: Earnings were roughly 17% better than expected but revenues were roughly 4% lower than anticipated. The company shares are also relatively well established and trade for just over $37. Thus, they dont have the same runaway growth potential as IonQs, for example. Nevertheless, they do have the potential to provide substantial returns in the future.

Source: Shutterstock

Quantum Computing (NASDAQ:QUBT) is, in my opinion, the stock with the most potential to create millionaires. The company is very small and produced a mere $50,000 in revenues in the third quarter.

That revenue is largely attributable to the provision of professional services to both public and commercial firms. Although the companys revenues continue to be small, there is a positive to take from its most recent earnings report: Revenues increased by 111% during the first nine months of 2023, reaching $283,000.

Quantum Computing has released five products over the previous 17 months, completed its first hardware sale and begun to build out of its quantum chip facility. Although its revenues remain modest, the company is resolute that at some point its continued ability to progress will lead to large contracts.

The company has developed a particularly strong relationship with NASA, securing its third subcontract award from the agency in July. Its clear that the government will continue to fund the development of the field. If Quantum Computing can provide results, the skys the limit.

On the date of publication, Alex Sirois did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed in this article are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

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3 Quantum Computing Stocks to Make You the Millionaire Next Door: 2024 Edition - InvestorPlace

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The Future of Quantum Computing in Environmental and Health Sciences – The Quantum Insider

Insider Brief

PRESS RELEASEUniversity of Waterloo/December 15, 2023Practical and scalable quantum computers are still in the early stages of development, and many technical challenges need to be overcome before they can be widely used for various applications. Researchers and companies globally, as well as right here at the University of Waterloo, are diligently pushing the boundaries of quantum computing technology, driving forward innovations in this emerging field.

The Transformative Quantum Technologies (TQT) program hosted its annual Quantum Opportunities and Showcase on December 14, at the Research Advancement Centre 2 (RAC2).

TQT is a collaborative research initiative supported by the Institute for Quantum Computing (IQC) at Waterloo. It aims to accelerate the development and use of impactful quantum devices. The University is not only dedicated to ground-breaking research but has spun out more than 15 quantum startups. This combination of world leading facilities, researchers and innovations is why Waterloo is referred to as Canadas quantum valley.

The showcase delivered a deep dive into the world of quantum technologies and their potential applications in the fields of environmental and health sciences. The event allowed for researchers, students and industry to come together and discuss ways to advance the field and provide examples of the capabilities of quantum computing. The day included insightful panels, presentations and a tour of the state-of-the-art research labs at the IQC and TQT.

Left to right: Tracey Forrest, program director, TQT, Shirley Tang, associate dean, research, Faculty of Science, Alexandre Cooper-Roy, research associate and senior technical lead, Quantum Simulation and Transformative Quantum Technologies, Weinan Zhao, postdoctoral fellow, Neil Rowlands, engineering fellow, Honeywell Aerospace

Kicking things off in a panel discussion on quantum in the environment, experts discussed where quantum could help in the future when it comes to measuring, monitoring and mitigating the environmental impacts of human activity on the atmosphere, our oceans and in our terrestrial ecosystems.

All this environmental monitoring, data collection and processing takes immense computing power. Quantum computers have the potential to solve certain problems much faster than traditional computers. They are particularly well-suited for tasks such as factoring large numbers, searching large databases and simulating systems, which are challenging for traditional computers to handle efficiently.

In addressing the vast challenges of monitoring water, air and soil impacted, the current system of sequential sampling is economically impractical due to the extensiveness and remoteness of areas involved, said Dr. Shirley Tang, associate dean of research in the Faculty of Science. To overcome this, quantum technology may offer a promising solution by enabling simultaneous monitoring of multiple sites using remote sensor technology, revolutionizing our approach to understanding environmental changes.

The panel also discussed how using quantum computing for environmental assessment raises challenges as quantum sensors may work well in a lab environment, but do not fare well in rugged terrain.

I encourage reaching out to potential beneficiaries of quantum technology, understanding their specific needs and adoption criteria, Alexandre Cooper-Roy said, a research associate and senior technical lead for Quantum Simulation and Transformative Quantum Technologies. Mining companies, operating in noisy and dirty environments, they have a very different operation criteria than what happens in the lab. So, its very important to engage at the earlier stage.

Left to right: Dmitry Pushin, professor, Department of Physics and Astronomy, Michael Reimer, professor, Department of Electrical and Computer Engineering, Troy Borneman, senior scientist, High Q Technologies, Michal Bajcsy, professor, Department of Electrical and Computer Engineering, Subha Kalyaanamoorthy, professor, Department of Chemistry

The health panel explored ways that quantum technologies could be used in a range of applications from medical imaging to drug discovery and the development of personalized medicine.

A recurring theme was how quantum scientists need to regularly consult with end users of quantum devices from technicians to clinicians.

Our quantum device, designed for high sensitivity, became more impactful when we identified real-world problems through conversations with those who could guide us in integrating it into their workflows, Troy Borneman said, a senior scientist at a quantum startup called High Q Technologies. This approach proved effective in making a meaningful impact, especially in addressing economic and time efficiency concerns in large biological or health problems.

In our case at High Q Technologies, we recognized a significant challenge in biology related to understanding protein folding and structural biology. This led us to design a system with high sensitivity for electron paramagnetic resonance, a crucial aspect for pharmaceutical companies and their drug development techniques, Borneman said.

After the panel discussions, the potential of quantum applications came to life through insightful posters and guided tours of the quantum labs at the Research and Advancement Centre (RAC2). Waterloos students and researchers presented how they use the cutting-edge equipment to develop their innovative projects and discussed possible commercialization avenues, establishing foundations for tangible impact.

Right: Graduate student Connor Kapahi demonstrates quantum opportunities in optometry

This showcase highlights Waterloos leadership in advancing quantum computing, a developing scientific field, to generate new technologies for positive human progress in the realms of environmental and health sciences.

The TQT program has demonstrated agility in addressing needs and providing ongoing support for ambitious research-to-application activities, as discussed today, said Tracey Forrest, program director, Transformative Quantum Technologies. Since its launch in 2016, TQT has assisted more than 600 researchers, including students, postdocs and nearly 50 faculty members at the University of Waterloo.

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How Quantum Computing Trends Will Impact Pharma in 2024: Q&A With Erik Huestis, Partner at Foley Hoag – Pharmaceutical Executive

Huestis discusses the ways that quantum simulation and quantum systems can be used in areas such as drug discovery and the creation and protection of intellectual property in the life sciences industry.

Erik Huestis, a partner at the law firm Foley Hoag, serves as co-chair of the firms technology industry group. He recently discussed how quantum computing may be used in the coming year by the life sciences and biotech industries.

Pharmaceutical Executive: What are the benefits of using quantum computing over classical computing for the pharma industry?

Erik Huestis: The exciting thing about quantum computing, as compared to classical computing, is that it is inherently easier to simulate quantum systems using quantum systems. Particularly in the near term, quantum simulation is whats most exciting to me. The application in biotech is that its extremely computationally prohibitive to compute attributes of molecules, of complex compounds in a classical regime, but quantum simulation and universal quantum computing allows us to compute those properties of pharmaceutically interesting molecules on a reasonable time scale with reasonable precision. That feeds directly into the discovery pipeline.

PE: How can innovators in biotech create and protect quantum intellectual property?

Huestis: In biotech in particular, the focus is going to be on the algorithm side, as opposed to the hardware side. The average biotech isnt developing new lasers or chips, but they are in a unique situation to create new algorithms, both purely-quantum and quantum-classical hybrid.

On the purely quantum side, optimized algorithms for predicting the kinds of properties that a pharmaceutical company cares about is an interesting avenue. More broadly, there are some really interesting avenues combining quantum computing into hybrid solutions. For example, bringing to bear these quantum algorithms that have an advantage of classical algorithms as part of an end-to-end artificial intelligence driven development pipeline.

It's very tempting to conflate quantum computing and AI, but theyre very different. There is a whole suite of problems, however, that quantum computing is really good at solving that work nicely into broader AI systems. When I think of a biotech and protection opportunities, my mind goes to what kind of system architectures combining quantum computing and drug discovery and screening processes are being solved.

PE: Will 2024 be the year that quantum computers break-through, similar to how AI performed in 2023?

Huestis: Its important to be a little more fine grained about that analysis. In AI, 2023 was the year people became aware of generative. That technology isnt new, however, and has been simmering for quite some time. AI has been deployed in a variety of other fields for quite a while.

Quantum simulation could be really important in the next year. Are we going to achieve a error-resistant, gate-based quantum computer next year? No. Thats further down the road. There are very interesting near-term applications in quantum simulation or analog quantum computation that I do think will have a significant impact in 2024, even while were waiting for continued advancements in error-correction, gate-based digital quantum computers.

PE: Can you discuss digital twins in quantum computing?

Huestis: Digital twin is a catch all phrase regarding the simulation of a patient or a process. It meshes really nicely with the idea of quantum simulation. Its the idea that in the absence of being able to perform direct measurements of a slew of compounds, we can do some quantum simulation that illuminates the molecular properties of compounds of interest very rapidly.

In that respect, I suppose that quantum simulation is kind of a form of digital twin. More generally, I dont think quantum computing is that suited to the kinds of broader applications that come to mind, such as looking at patient data, hospital systems, or those sorts of things in a broad way. It turns out that classical computing and conventional AI models work really well for that kind of thing.

But for anything that has a quantum element, digital twinning speaks to the strength of quantum computation as a platform.

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Quantum computing progress hindered by noise – ReadWrite

Over the past two decades, numerous businesses such as Google, Microsoft, and IBM have joined the race to develop quantum computing. Investors have contributed well over $5 billion towards the ultimate goal of creating the next major innovation. Quantum computers utilize the unusual rules of atomic and subatomic matter to process data in ways unattainable by traditional or classical computers. This technology could revolutionize industries like drug development, cryptography, finance, and supply chain management.

However, the primary challenge hampering the progress of quantum computing is the issue of noise and decoherence, which lead to errors in computations. Qubits, the fundamental unit of quantum computing, are highly sensitive to their environment, and any disturbance or fluctuations in temperature can cause them to lose their quantum state, affecting the accuracy and reliability of calculations.

Despite the potential of quantum computing, it remains fragile and susceptible to even the slightest disturbance, such as a stray photon produced by heat, an accidental signal from nearby electronics, or a physical vibration. This noise causes chaos, leading to errors or even bringing quantum computation to a halt. Scientists and researchers are diligently working on ways to mitigate this issue, utilizing strategies like error correction algorithms, better materials, and improved isolation techniques. The race towards a truly functional and efficient quantum computer hinges on finding the perfect balance between inherent fragility and maintaining performance capabilities.

Researchers believed they might have to work with noisy components. Many sought applications that would still be practical with limited capacity. Although this search has not been particularly successful, recent theoretical and experimental advancements have given researchers hope that noise issues might finally be tackled. These advancements include developing innovative error-correcting techniques and refining hardware designs to minimize interference, driving renewed optimism within the scientific community.

Sabrina Maniscalco, a professor at the University of Helsinki studying the impact of noise on computations, admitted that a decade ago, she dismissed quantum computing due to fundamental issues. However, technological advancements and innovative research around quantum computing began addressing these challenges, changing her perspective and revealing its immense potential to transform industries and solve complex problems.

A mix of hardware and software techniques shows potential in reducing, managing, and correcting quantum errors, aiming to enhance stability and improve overall performance. Researchers are making significant strides toward achieving fault-tolerant quantum computing by combining advanced algorithms with robust hardware designs.

Featured Image Credit: Photo by Markus Winkler; Pexels

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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POLARISqb And Scientist.com Partner to Offer Online Access to Quantum-Aided Drug Design – The Quantum Insider

Insider Brief

PRESS RELEASE POLARISqb, the first company to build quantum-enabled molecular optimization tools for drug discovery, and Scientist.com, the life science industrys leading online marketplace for outsourced research, have partnered to offer researchers onlineaccess to POLARISqbs Quantum-Aided Drug Design (QuADD) platform. Scientist.com marketplace users can now utilize quantum computing to create optimized molecular libraries for drug design in days rather than months.

POLARISqb was the first company to develop a drug discovery platform that utilizes the well-documented optimization power of todays quantum computers, stated Bill Shipman, CTO and Co-Founder of POLARISqb. We look forward to working with the teamat Scientist.comto make this platform available to their vast network of scientists and researchers, who can use our tools to accelerate the search for novel drug candidates. POLARISqb uses quantum annealing computers that complete calculations more than 500x faster than conventional computers.

QuADD is a software platform that translates the molecular library building problem into an optimization problem which can be solved with a quantum annealing computer. QuADD targets a specific binding pocket to find novel, bioavailable, and synthesizable lead-like hits from a potential chemical space of up to 10^30 molecules in 1-3 days. The input for the QuADD pipeline is a customer-defined structure of the protein binding pocket and ligand. The output is a library of candidates that target the specific binding pocket of interest and have molecular properties that meet the goals of the drug discovery project. The company has recently released several white papers describing how QuADD achieves these results.

At Scientist.com, we are committed to supporting companies like POLARISqb that are at the cutting edge of drug research innovation, said Kevin Lustig, PhD, CEO and Founder of Scientist.com. POLARISqbs QuADD software has the potential to significantly accelerate the discovery of new drug candidates for hundreds of human diseases.

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DARPA Research Leads to Groundbreaking Discovery in Quantum Computing, Developing the World’s First Logical … – The Debrief

A team of Harvard scientists working on a project funded by the Defense Advanced Research Projects Agency (DARPA) has announced a significant breakthrough in the field of quantum computing.

Researchers working with the Optimization with Noisy Intermediate-Scale Quantum (ONISQ) program say they have created the worlds first quantum circuit using logical quantum bits (qubits). The innovation marks a significant stride towards fault-tolerant quantum computing, promising to revolutionize the design of quantum computer processors.

Established in 2020, DARPA says the ONISQ program aims to develop ways to surpass the capabilities of classical supercomputers in solving combinatorial optimization problems, a challenging class of problems relevant to defense and commercial sectors.

The Optimization with Noisy Intermediate-Scale Quantum devices (ONISQ) program aims to exploit quantum information processing before fully fault-tolerant quantum computers are realized, DARPA wrote indocumentsprovided during a 2019 Proposers Day event. This effort will pursue a hybrid concept that combines intermediate-sized quantum devices with classical systems to solve a particularly challenging set of problems known as combinatorial optimization.

In early 2020, DARPA awarded a $6.3 million contract to ColdQuanta, a quantum computing company based in Colorado, to lead the ONISQ project. In November 2023, ColdQuanta underwent a rebranding to Infleqtion, shifting its focus to commercial quantum computing products.

DARPA credited this recent quantum computing breakthrough to the collaborative efforts of researchers from Harvard, MIT, QuEra Computing, Caltech, and Princeton. The research team was led by the co-director of the Harvard Quantum Initiative and professor of physics, Dr. Mikhail Lukin.

In their research, the ONISQ team focused on Rydberg qubits a type of physical, non-logical qubits. Through this effort, they successfully developed techniques to create error-correcting logical qubits from these noisy Rydberg qubits.

Logical qubits are essential for realizing fault-tolerant quantum computing, as they maintain their quantum state despite errors, making them reliable for solving complex problems.

The Harvard laboratory successfully built quantum circuits comprising around 48 Rydberg logical qubits the largest assembly of logical qubits to date.

The homogeneous nature of Rydberg qubits, where each qubit behaves identically, offers a significant advantage over other qubit types like superconducting qubits, which are unique and non-interchangeable. This homogeneity enables rapid scaling and easy manipulation using lasers on a quantum circuit.

Dr. Mukund Vengalattore, ONISQ program manager at DARPAs Defense Sciences Office, highlighted the transformative potential of the discovery.

Rydberg qubits have the beneficial characteristic of being homogenous in their properties meaning each qubit is indistinguishable from the next in how they behave, Dr. Vengalattore said in astatementissued by DARPA. Thats not the case for other platforms such as superconducting qubits where each qubit is unique and therefore not interchangeable.

According to Dr. Vengalattore, Rydberg qubits can be dynamically reconfigured and transported across the quantum circuit using laser tweezers, allowing for operations not limited to sequential processes. This capability opens up new paradigms in designing scalable quantum computing processors.

Dr. Guido Zuccarello, a technical adviser for the ONISQ program, praised DARPAs exploratory approach as playing a crucial role in unlocking the potential of Rydberg qubits in quantum computing.

If anyone had predicted three years ago when the ONISQ program began that Rydberg neutral atoms could function as logical qubits, no one would have believed it, Dr. Zuccarello said. Its the DARPA way to bet on the potential of these less-studied qubits along with the more well-studied ions and superconducting circuits. As an exploratory program, ONISQ gave researchers the leeway to explore unique and new applications beyond just the optimization focus.

As a result, the Harvard-led team was able to leverage much more of the potential of these Rydberg qubits and turn them into logical qubits, which is a very significant discovery.

While significantly more than 48 logical qubits are required to tackle the problems envisioned for quantum computers, researchers say the revolutionary advent of early error-corrected quantum charts a path toward large-scale logical processors.

The breakthrough also challenges the traditional belief that millions of physical qubits are necessary for fault-tolerant quantum computing. Thanks to dynamically reconfigurable quantum circuits, the number of logical qubits needed to solve specific problems could be far fewer than previously thought.

DARPA attributed the accelerated application of Rydberg quantum sensing techniques to the agencys nearly twenty-year commitment to quantum research and bridging the gaps between quantum sensing and quantum information science.

According to Dr. Vengalattore, the ONISQ researchers could draw upon a rich toolbox of quantum knowledge developed through multiple DARPA programs.

This toolbox included deep fundamental and technical insights from many DARPA programs, including OLE [Optical Lattice Emulator], QuASAR [Quantum-Assisted Sensing and Readout], ATN [All Together Now], and DRINQS [Driven and Nonequilibrium Quantum Systems], Dr. Vengalattore elaborated.

The technical details of the Harvard teams breakthrough are detailed in a paper published inNature, offering a glimpse into the future of quantum computing.

Ultimately, the advent of quantum computing stands to revolutionize the world in profound ways akin to the transformative impact of the internet.

The technological leap promises a paradigm shift in processing power and efficiency by taking advantage of quantum mechanical phenomena, redefining our approach to problem-solving across various fields, from cryptography to materials science and beyond.

Experts believe the ripple effects from quantum computing will likely permeate every aspect of society, potentially reshaping industries, economies, and day-to-day life, marking a new era in human technological progress.

As Dr. Vengalattore notes, this recent discovery is not just an end but another step toward making quantum computing a reality.

As exciting and transformative as these results are, we see this as a stepping stone towards a longer-term vision of actualizing disruptive pathways to error-corrected quantum computing and other areas of quantum technology.

Tim McMillan is a retired law enforcement executive, investigative reporter and co-founder of The Debrief. His writing typically focuses on defense, national security, the Intelligence Community and topics related to psychology. You can follow Tim on Twitter:@LtTimMcMillan. Tim can be reached by email:tim@thedebrief.orgor through encrypted email:LtTimMcMillan@protonmail.com

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Spiking Nano-oscillators Provide New Insight into Quantum Materials and Advanced Computing – The Quantum Insider

Insider Brief

UNIVERSITY RESEARCH NEWSSan Diego/December 18, 2023/UC San DiegoMany functions of the human body operate in sync, such as the coordination of our arms and legs when walking or how the different lobes of our brain work together to process information. Synchronicity also exists in engineered systems such as the harmonic oscillators used in clocks and radio circuits. However, synchronicity has not been studied extensively in spiking oscillators, despite their potential for use in advanced materials and neuromorphic, or brain-like, computing.

Now scientists from the University of California San Diego have discovered that when nano-oscillators made from vanadium dioxide spike, they exhibit a unique kind of synchronicity. Their results appear in The Proceedings of the National Academy of Sciences.

This work was led by fifth-year graduate student Erbin Ben Qiu. Although Qiu is in the Department of Electrical and Computer Engineering in UC San Diegos Jacobs School of Engineering, he conducted this work in the lab of Distinguished Professor of Physics Ivan K. Schuller. Qiu said he appreciated the opportunity to explore a new area of interdisciplinary research that capitalized on expertise from engineering and physics.

This research initiative used several UC San Diego facilities, including a sputtering system and the X-ray machine in Schullers lab to create the thin films and analyze their crystal structures. A maskless laser lithography machine and etching machine in Nano3 was used to fabricate the spiking nano-oscillators. Finally, advanced transport measurement equipment was used to study the unique behaviors of these nano-oscillators, which are thermally coupled yet electrically decoupled.

In harmonic oscillators, if you increase the coupling strength, the synchronicity between two oscillators will become stronger, or more robust. A similar result was expected with spiking nano-oscillators; however, the experiment showed that stronger coupling strength via increased voltage caused disruptions in synchronization patterns, leading to a stochastic state or regime.

Stochastic states are, by definition, based on random probability and impossible to precisely predict. However, with these spiking nano-oscillators, although the stochastic synchronization pattern alternated unpredictably, there was always a synchronization pattern to it.

Our system is always in sync, stated Qiu. It goes from an initial fixed synchronization pattern to a stochastic regime, but even then, it is still synchronized. Then it goes back to another fixed synchronization pattern.

This unexpected outcome may prove useful in cybersecurity applications, specifically in implementing a true random number generator. In fact, these spiking nano-oscillators have already passed multiple tests in the Statistical Test Suite from the National Institute of Standards and Technology (NIST) to prove their viability in this area.

In addition to cybersecurity, this research has important implications for artificial intelligence and neuromorphic computing, because it shows that quantum material-based spiking oscillators can behave in ways that mimic neurons.

This work was funded by the Air Force Office of Scientific Research (FA95502210135) and the U.S. Department of Energy, Office of Science, Basic Energy Sciences (DE-SC0019273) through the Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C).

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Featured image: Thermally coupled spiking nano-oscillators synchronize, emulating the synchronization occurs in our brains. Credit: Mario Rojas/ UC San Diego)

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A computer vision and machine learning system that monitors and controls workup processes – Phys.org

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A team of chemists and engineers at the University of British Columba working with colleagues at pharmaceutical company Pfizer has developed a chemical processing system combining computer vision with a real-time machine-learning monitoring system for use in conducting chemical workup processes. Their paper is published in the journal Chemical Science.

In chemistry, workup processes are activities conducted to isolate a pure product through selective separation from other components. It is often tedious, which, besides being unpleasant, leads to mistakes or omissions. In this new effort, the research team has attempted to automate the process by combining computer vision with real-time monitoring techniques, a machine-learning system and computer processing, along with appropriate hardware, to carry out a workup process without assistance from human chemists.

The system developed by the team, called Heinsight2.0, as its name suggests, builds on knowledge learned from its predecessor, Heinsight1.0. Its components include a webcam (either overhead or side-mounted), reaction vessel, dosing unit, temperature probe and overhead stirrer. It also has a secondary device that allows for displaying iControl, real-time reaction trends, EasyMax and CV model output.

The system works by monitoring a workup process and controlling it by sending signals at appropriate times to direct the action as it happens. The system controls the action by responding as a chemist would as events unfold. If a material changes from one desired color to another, for example, the system can recognize that and use it as a cue to instigate a follow-up action.

The researchers note that, like a human chemist, the system is capable of monitoring multiple sensory cues and responding to them in desired ways. It can also operate under many types of scenarios, such as those involving the use of solid-liquid mixing, crystallizations, exchange distillations and liquid-to-liquid extraction.

They also note that they have made the program script publicly available, which means other chemists could build their own units and then use the code to run their systems in the same way. They also plan to continue work on their system to give it more capabilities.

More information: Rama El-khawaldeh et al, Keeping an "eye" on the experiment: computer vision for real-time monitoring and control, Chemical Science (2023). DOI: 10.1039/D3SC05491H

Journal information: Chemical Science

2024 Science X Network

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DOD’s cutting-edge research in AI and ML to improve patient care – DefenseScoop

The Defense Departments responsibility to its active and veteran service members extends to their health and well-being. One organization driving innovation for patient care is the DODs Uniformed Services University. And within the university is a center known as the Surgical Critical Care Initiative, SC2i a consortium of federal and non-federal research institutions.

In a recent panel discussion with DefenseScoop, Dr. Seth Schobel, scientific director for SC2i, shared how cutting-edge research in artificial intelligence and machine learning improves patient care. Schobel elaborated on one specific tool called the WounDx Clinical Decision Support Tool which predicts the best time for surgeons to close extremity wounds.

[These wounds] are actually one of the most common combat casualty injuries experienced by our warfighters. We believe the use of these tools will allow military physicians to close most wounds faster, and it has the potential to save costs and avoid wound infections and other complications. We believe by using this tool well increase the success rate of military surgeons on closing these wounds at first attempt [improving rates] from 72% to 88% of the time, he explained.

Uniformed Services Universitys Chief Technology and Senior Information Security Officer, Sean Baker, joined Schobel on the panel to elaborate on how when IT and medical research teams work together, they can drive better health outcomes in patient care.

Overall, our job is to provide cutting-edge tools into the hands of clinical experts, recognizing that risk management does not mean risk avoidance. Clinical care is not going to advance without taking some measure of digital risks, he explained.

Baker added, We need to continue to empower our users across the healthcare space, across government, to use these emerging capabilities in a risk-informed way to take this into the next level of education, of research, of care delivery.

Schobel and Baker both underlined AI and MLs disruptive potential to positively improve patient care in the near future.

We need to be ready for this [disruptor] by understanding how these tools are built and how they apply in different clinical settings. This will dramatically improve a data-driven and evidence-based healthcare system, Schobel explained. By embracing these considerations, the public health sector, as well as the military, can harness the power of AI and ML to enhance patient care and improve health outcomes, and really be at the forefront of that transformation for the future of healthcare.

Googles Francisco Rubio-Bertrand, who manages federal healthcare client business, reacted to the panel interview, saying: We believe that Google, by leveraging its vast resources and expertise, can be a driving force in advancing research and healthcare. Through access to our powerful cloud computing platforms and extensive datasets, we can significantly accelerate the development of AI/ML models specifically designed to address pressing needs in the healthcare sector.

Watch the full discussion to learn more about driving better patient care and health outcomes with artificial intelligence and machine learning.

This video panel discussion was produced by Scoop News Group for DefenseScoop, and underwritten by Google for Government.

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