IBM 5 in 5

IBM’s past “5 in 5” predictions – where are they now?

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IBM announced its annual “5 in 5” technology predictions. This year’s batch of predictions is focused on accelerating the discovery of new materials to enable a more sustainable future. We must speed up the discovery process to more quickly identify materials that will help society address the pressing challenges contained in the UN Sustainable Development Goals, from fostering good health and clean energy to bolstering sustainability, climate action, responsible production — and so much more.

Thanks to the work of our researchers and collaborators, we expect to make significant progress towards this goal in the next five years. And judging by IBM Research’s successful track record with past 5 in 5 predictions, we have good reason to be optimistic.

Below are some recent examples that highlight progress achieved toward realizing previous 5 in 5 forecasts and provide some insights into our long-term commitment to develop innovative solutions that can be implemented as IBM products and services, or shared with partners for commercialization or further development.

PAIRS “macroscope” helps with COVID-19 monitoring

IBM scientists, Xiaoyan Shao (left) and Conrad Albrect, are interacting with the IBM PAIRS Geoscope service.

In 2017, IBM Research predicted that, by 2022 we will use machine-learning algorithms and software to help us organize information about the physical world, helping bring the vast and complex data gathered by billions of devices within the range of our vision and understanding.

The following year, IBM Research introduced an experimental “macroscope” offering named IBM PAIRS Geoscope. In this context, a macroscope is a system of software and algorithms to bring all of Earth’s complex data together to analyze it by space and time for meaning. PAIRS is a unique cloud-centric geospatial information and analytics service that can accelerate the discovery of new insights. The industry has successfully adapted “macroscope” for a few use cases, including commodity trading and vegetation management for electric utilities.

This year, IBM researchers used PAIRS to achieve a macroscopic view of the impact of and response to COVID-19. A PAIRS query of New York City’s light intensity as observed at night beginning in mid-March of 2020, for example, revealed a substantial dimming of night light due to reduced business activity and traffic that may offer an early market intelligence signal. Other COVID-19-related queries since the beginning of the pandemic indicate drastic drops in CO2 emissions in major population centers worldwide.

Detailing how an AI-powered robot microscope could clean our dirty oceans

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IBM researcher and Master Inventor Tom Zimmerman with his invention, an autonomous AI microscope designed to continually monitor in real time the health of our water.

One of IBM’s 2018 predictions was that, in five years, small autonomous AI microscopes, networked in the cloud and deployed around the world, will continually monitor the condition of the natural resource most critical to our survival: water.

Since that prediction, IBM researchers have continued developing an end-to-end system that includes a semi-automated, AI-powered microscope that could monitor plankton and help researchers correlate plankton behavior with environmental health. As part of an NSF-funded exploratory science project, the researchers have published several papers – including in Scientific Reports and bioRxiv  – that describe their system in greater detail.

AI can identify plankton and classify the organisms based on form, shape and behavior with no external supervision. The technology also has the ability to recognize automatically any anomalous plankton trait and re-train itself with the new information, providing scientists with the most up-to-date insight from the data.

Together, the instrument, anomaly detector and automation could provide a comprehensive system that analyzes water samples and reports back on the microorganisms living in that sample. The researchers continue to work on the creation of an inexpensive, low-power unit that could be incorporated into autonomous underwater gliders to collect samples and share that data on the cloud to create a scalable solution.

In a separate project involving AI and ocean conservation, IBM is also working with marine research organization Promare to launch the Mayflower Autonomous Ship this September. Powered by AI and the energy from the sun, the Mayflower Autonomous Ship will set sail across the Atlantic Ocean travelling from Plymouth, England, to Plymouth, Mass., on the 400th anniversary of the original Mayflower departure in 1620. The vessel will spend vast amounts of time at sea, helping scientists gather critical data about ocean threats including microplastic pollution using an AI sensor similar to an “electronic tongue.”

New partners collaborate on anti-counterfeiting crypto-anchors

A crypto-anchor prototype developed by IBM researchers.

In 2018, we predicted that within five years, cryptographic anchors and blockchain technology will ensure a product’s authenticity – from its point of origin to the hands of the customer.

IBM Research is currently working in partnership with crypto-anchor vendors to take our three-layered system a step closer to commercialization. One such vendor – Austrian company Authentic Vision – has developed technology consisting of a unique holographic fingerprint that can be produced only once. The company’s mobile app works on any smartphone equipped with computer vision technology to read the holographic fingerprint and instantly authenticate a product. Authentic Vision uses next-generation void foil materials to make its security tag tamper evident, and a smartphone can be used to automatically verify the authenticity of the physical product.

IBM Research is also partnering with crypto-anchor vendor tesa scribos, whose tesa ValiGate product marking technology is copy-protected and authenticated automatically without human error. That enables physical products to communicate safely and automatically with their blockchain twins, turning this technology into real benefit for consumers and brand owners.

Lattice cryptography makes the cut

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IBM researcher Cecelia Boschini working on the type of complex math problems used in lattice cryptography to hide data from hackers.

Two years ago, IBM predicted that, by 2023, new methods of cyberattack would make today’s security measures woefully inadequate. Eventually, a fault-tolerant, universal quantum computer with millions of qubits could quickly sift through the probabilities and decrypt even the strongest common encryption, rendering this foundational security methodology obsolete.

In August 2019, IBM announced it would begin providing quantum-safe cryptography services on the IBM public cloud in 2020 and now offers a Quantum Risk Assessment from IBM Security to help customers assess their risk in the quantum world. Additionally, IBM cryptographers prototyped the world’s first quantum computing safe enterprise class tape, an important step before commercialization.

Lattice-based cryptography is an important part of IBM’s quantum-safe security strategy. Lattice cryptography hides data inside complex algebraic structures called lattices. The difficulty in solving these math problems is useful for cryptographers, because they can apply this intractability to protect information, even when quantum computers are strong enough to crack certain types of today’s encryption techniques. The National Institute of Standards and Technology’s (NIST) latest list of candidates for quantum safe cryptography standards includes several based on lattice-based cryptography, including CRYSTALS

Lattice-based cryptography is also the basis of another encryption technology called Fully Homomorphic Encryption (FHE), which could make it possible to perform calculations on data without ever seeing sensitive data or exposing it to hackers. In July 2020, IBM Research announced a new FHE toolkit for Mac, iOS and Linux, bringing FHE to multiple Linux distributions for IBM Z and x86 architectures. IBM also conducted a pilot earlier this year with Brazil’s Banco Bradesco SA, where the company homomorphically encrypted data and showed it was possible to run predictions with the same accuracy as without encryption and with adequate performance. As a result, enterprises from banks to insurers can safely outsource the task of running predictions to an untrusted environment without the risk of leaking sensitive data.

Quantum computing graduates from the playground

Another of our 2018 predictions anticipated that the effects of quantum computing would reach beyond the research lab within five years, to be used extensively by new categories of professionals and developers looking to solve problems once considered unsolvable.

That same year, IBM researchers proved a quantum advantage over classical computers for certain mathematical problems using shallow quantum circuits. We expanded the IBM Q Network’s global academic and commercial reach, announcing an academic partnership with Portugal’s Minho University, and IBM Q Hubs at North Carolina State University, Bundewsehr University-Munich, and the University of Montpellier, as well as the first industry members of the IBM Q Hub at Japan’s Keio University: JSR, Mitsubishi UFJ Financial Group (MUFG), Mizuho Financial Group, and Mitsubishi Chemical.

IBM Quantum likewise made significant advances across the hardware and software stack, with the fourth-generation 20-qubit device that doubled the average accuracy of the previous version and the release of new Qiskit elements: Aqua for chemistry and Aer for simulations. The following year, IBM introduced IBM Q System One, the world’s first integrated quantum computing system. The client-deployed, premium IBM Q System One has, for the first time, enabled superconducting quantum computers to operate beyond the confines of the research lab.

In July of 2020, IBM Quantum introduced a move toward a frictionless quantum development experience with the Qiskit Optimization module. The module enables easy, efficient modeling of optimization problems using DOcplex – IBM Decision Optimization CPLEX modeling. The new module offers programmers glimpse of the vast number of applications where quantum optimization may have an enormous impact in the future, once quantum systems are available at the required scale.

And that future may not be far off. Announced at the 2020 IBM Quantum Summit, IBM unveiled its quantum technology roadmap to take us to the large full-stack quantum computing systems of the future with quantum advantage. IBM scientists are currently developing a suite of increasingly high-performance quantum computing systems, with a 1,000-plus-qubit quantum processor, called IBM Quantum Condor, targeted for the end of 2023. This clear vision of quantum advantage now feels like an achievable goal within the coming decade.

A look at IBM’s roadmap to advance quantum computers from today’s noisy, small-scale devices to larger, more advance quantum systems of the future. Credit: StoryTK for IBM

A look at IBM’s roadmap to advance quantum computers from today’s noisy, small-scale devices to larger, more advance quantum systems of the future. Credit: StoryTK for IBM

 

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This green, post-consumer waste could be turned into pure PET monomer, the most commonly used plastic polymer in the world, using IBM Research’s VolCat chemical recycling process.

A radical new plastic recycling process moves closer to commercialization

In 2019 IBM predicted that, in the next five years, plastic recycling advancements like VolCat, a selective digestion process developed in IBM Research using a Volatile Catalyst, could be adopted around the globe to combat global plastic waste. We anticipated that, for example, people at a grocery store buying a bottle of soda or container of strawberries would take comfort in knowing the plastic they had purchased won’t end up in the ocean, but instead will be repurposed and put back on the shelf.

This year, IBM Research plans to kick off the next phase of its plan to commercialize the innovative VolCat plastic recycling process. VolCat uses a benign organic catalyst to selectively digest the most common household plastic – polyethylene terephthalate (PET) – back to its monomer constituents. After purification, the monomer can easily be re-polymerized to form new PET.

IBM Research is planning to partner with an industry partner to design, build and operate a pilot plant to prove the scalability and economics of the VolCat process. If successful, that work would progress to manufacturing plants all over the world. The biggest challenge is applying IBM’s kilogram-scale research and development processes to a much larger operation. That means ensuring VolCat can continuously and cost-effectively process a large volume of plastic waste containing a wide variety of impurities. Success will enable manufacturers to make plastics, fibers or films out of the resulting monomers, without the need to create new plastics from petrochemicals.

VP Exploratory Science, IBM Research

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