IBM recently announced its initiative to build commercially available universal quantum computing systems. The “IBM Q” quantum systems and services will then be delivered to users via the IBM Cloud platform.
IBM has announced an initiative to build commercially available universal quantum computing systems. “IBM Q” quantum systems and services will be delivered via the IBM Cloud platform. While technologies that currently run on classical computers, such as Watson, can help find patterns and insights buried in vast amounts of existing data, quantum computers will deliver solutions to important problems where patterns cannot be seen because the data doesn’t exist and the possibilities that you need to explore to get to the answer are too enormous to ever be processed by classical computers.
IBM also announced:
- The release of a new API (Application Program Interface) for the IBM Quantum Experience that enables developers and programmers to begin building interfaces between its existing five quantum bit (qubit) cloud-based quantum computer and classical computers, without needing a deep background in quantum physics.
- The release of an upgraded simulator on the IBM Quantum Experience that can model circuits with up to 20 qubits. In the first half of 2017, IBM plans to release a full SDK (Software Development Kit) on the IBM Quantum Experience for users to build simple quantum applications and software programs.
The IBM Quantum Experience enables anyone to connect to IBM’s quantum processor via the IBM Cloud, to run algorithms and experiments, work with the individual quantum bits, and explore tutorials and simulations around what might be possible with quantum computing.
“IBM has invested over decades to growing the field of quantum computing and we are committed to expanding access to quantum systems and their powerful capabilities for the science and business communities,” said Arvind Krishna, senior vice president of Hybrid Cloud and director for IBM Research. “Following Watson and blockchain, we believe that quantum computing will provide the next powerful set of services delivered via the IBM Cloud platform, and promises to be the next major technology that has the potential to drive a new era of innovation across industries.”
IBM intends to build IBM Q systems to expand the application domain of quantum computing. A key metric will be the power of a quantum computer expressed by the “Quantum Volume”, which includes the number of qubits, quality of quantum operations, qubit connectivity and parallelism. As a first step to increase Quantum Volume, IBM aims at constructing commercial IBM Q systems with ~50 qubits in the next few years to demonstrate capabilities beyond today’s classical systems, and plans to collaborate with key industry partners to develop applications that exploit the quantum speedup of the systems.
IBM Q systems will be designed to tackle problems that are currently seen as too complex and exponential in nature for classical computing systems to handle. One of the first and most promising applications for quantum computing will be in the area of chemistry. Even for simple molecules like caffeine, the number of quantum states in the molecule can be astoundingly large – so large that all the conventional computing memory and processing power scientists could ever build could not handle the problem.
IBM’s scientists have developed techniques to efficiently explore the simulation of chemistry problems on quantum processors (https://arxiv.org/abs/1701.08213 and https://arxiv.org/abs/1612.02058) and experimental demonstrations of various molecules are in progress. In the future, the goal will be to scale to even more complex molecules and try to predict chemical properties with higher precision than possible with classical computers.
Future applications of quantum computing may include:
- Drug and Materials Discovery: Untangling the complexity of molecular and chemical interactions leading to the discovery of new medicines and materials;
- Supply Chain & Logistics: Finding the optimal path across global systems of systems for ultra-efficient logistics and supply chains, such as optimising fleet operations for deliveries during the holiday season;
- Financial Services: Finding new ways to model financial data and isolating key global risk factors to make better investments;
- Artificial Intelligence: Making facets of artificial intelligence such as machine learning much more powerful when data sets can be too big such as searching images or video; or
- Cloud Security: Making cloud computing more secure by using the laws of quantum physics to enhance private data safety.
“Classical computers are extraordinarily powerful and will continue to advance and underpin everything we do in business and society. But there are many problems that will never be penetrated by a classical computer. To create knowledge from much greater depths of complexity, we need a quantum computer,” said Tom Rosamilia, senior vice president of IBM Systems. “We envision IBM Q systems working in concert with our portfolio of classical high-performance systems to address problems that are currently unsolvable, but hold tremendous untapped value.”
IBM’s roadmap to scale to practical quantum computers is based on a holistic approach to advancing all parts of the system. IBM will leverage its deep expertise in superconducting qubits, complex high performance system integration, and scalable nanofabrication processes from the semiconductor industry to help advance the quantum mechanical capabilities. Also, the developed software tools and environment will leverage IBM’s world-class mathematicians, computer scientists, and software and system engineers.
“As Richard Feynman said in 1981, ‘…if you want to make a simulation of nature, you’d better make it quantum mechanical, and by golly it’s a wonderful problem, because it doesn’t look so easy.’ This breakthrough technology has the potential to achieve transformational advancements in basic science, materials development, environmental and energy research, which are central to the missions of the Department of Energy (DOE),” said Steve Binkley, deputy director of science, US Department of Energy. “The DOE National Labs have always been at the forefront of new innovation, and we look forward to working with IBM to explore applications of their new quantum systems.”
Growing the IBM Q Ecosystem
IBM believes that collaborating and engaging with developers, programmers and university partners will be essential to the development and evolution of IBM’s quantum computing systems. Since its launch less than a year ago, about 40,000 users have run over 275,000 experiments on the IBM Quantum Experience. It has become an enablement tool for scientists in over 100 countries and, to date, 15 third-party research papers have been posted to arXiv with five published in leading journals based on experiments run on the Quantum Experience.
IBM has worked with academic institutions, such as MIT, the Institute for Quantum Computing at the University of Waterloo, and École polytechnique fédérale de Lausanne (EPFL)
to leverage the IBM Quantum Experience as an educational tool for students. In collaboration with the European Physical Society, IBM Research – Zurich recently hosted students for a full-day workshop to learn how to experiment with qubits using the IBM Quantum Experience.
“Unlocking the usefulness of quantum computing will require hands-on experience with real quantum computers,” said Isaac Chuang, professor of physics and professor of electrical engineering and computer science at MIT. “For the Fall 2016 semester of the MITx Quantum Information Science II course, we featured IBM’s Quantum Experience as part of the online curriculum for over 1,800 participants from around the world. They were able to run experiments on IBM’s quantum processor and test out for themselves quantum computing principles and theories they were learning.”
In addition to working with developers and universities, IBM has been engaging with industrial partners to explore the potential applications of quantum computers. Any organisation interested in collaborating to explore quantum applications can apply for membership to the IBM Research Frontiers Institute, a consortium that develops and shares a portfolio of ground-breaking computing technologies and evaluates their business implications. Founding members of the Frontiers Institute include Samsung, JSR, Honda, Hitachi Metals, Canon, and Nagase.
“We heavily invest in R&D and have a strong interest in how emerging technologies such as quantum computing will impact the future of manufacturing,” said Nobu Koshiba, President of JSR, a leading chemical and materials company in Japan. “Our pipelines of innovations range from synthetic rubbers for tires to semiconductor and display materials, along with products in the life sciences, energy and environmental sectors. By having exposure to how quantum computing can provide new computational capability to accelerate materials discovery, we believe this technology could have a lasting impact on our industry and specifically our ability to provide faster solutions to our customers.”
IBM is making the specs for its new Quantum API available on GitHub (https://github.com/IBM/qiskit-api-py) and providing simple scripts (https://github.com/IBM/qiskit-sdk-py) to demonstrate how the API functions.
Now IBM’s Watson joins IoT revolution in agriculture
Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production
IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.
By 2050, the world will need to feed two billion more people without an increase in arable land . IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.
Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”
New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.
Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.”
The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 . Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.
The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.
Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.
IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.
The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.
 The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”
 Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10
What if Amazon used AI to take on factories?
By ANTONY BOURNE, IFS Global Industry Director for Manufacturing
Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.
At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.
If Amazon did factories
If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.
Manufacturing with knowledge
Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.
In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.
As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.
Knowledge for manufacturing
For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.