Machine learning is beginning to make a large impact in catalysis research, according to Bryan Goldsmith, Jacques Esterhuizen, and Jin-Xun Liu of the Univ. of Michigan, Christopher Bartel of the Univ. of Colorado Boulder, and Christopher Sutton of the Fritz Haber Institute of the Max Planck Society in their July AIChE Journal Perspective article, "Machine Learning for Heterogeneous Catalyst Design and Discovery." Novel catalysts are crucial for several applications, such as energy generation and storage, sustainable chemical production, and pollution mitigation. The current trial-and-error approaches to new catalyst discovery and synthesis are expensive and time-consuming. As an alternative, machine learning can be used to identify the top catalyst candidates before experimental testing, thereby accelerating catalyst discovery and design. Goldsmith and colleagues highlight several examples where machine learning is making an impact on heterogeneous catalysis research, such as: accelerating the determination of catalyst active sites and catalyst screening; finding descriptors and patterns in catalysis data; determining interatomic potentials for catalyst simulation; and discovering and analyzing catalytic mechanisms.
Artificial intelligence (AI) today is the new frontier in the digital transformation journey enterprises have already embarked on. But adoption to solve real problems and drive business outcomes has been slow. Driving up adoption is critical to unlock the real promise of AI and is going to depend on how we approach AI. And that opportunity is in front of us thanks to industry-optimized augmented intelligence. Most realistic and successful AI initiatives have been focused on augmenting human abilities with powerful machine intelligence.
Digital transformation is no longer an "if" but a "when" for enterprises across both public and private sector. The promise of greater efficiency, customer-centric products and services, rapid response to changing regulatory or economic requirements – and the chance to compete with disruptive start-ups percolating every sector of the economy can no longer be overlooked. The challenge is how to get started and get the runs on the board that build innovation momentum. Google Cloud's Nigel Watson believes machine learning and artificial intelligence (AI) offer the most straightforward way to demonstrate what digital transformation can deliver. Watson is Head of Cloud Technology Partners, Japan and Asia Pacific for Google Cloud.
This is just a small slice of how technology automation has changed over the past 20 years, and I assume we can all acknowledge that AI is gaining momentum, albeit regulatory authorities, legislators and lawyers not being fully sure how to adapt or embrace the change that's currently happening. Artificial Intelligence is here, it's the hot topic or the popular kid everyone wants to play in the park with. AI and automation are bringing us daily benefits; Internet and Big Data are becoming an essential part of both our work and private lives and we now have the capacity to collect huge sums of information too cumbersome for a person to process. But what will this future bring in terms of issues, policies and regulations? Will programmers and researchers be obliged to study ethics and morals as compulsory modules throughout their learning paths?
Simply mentioning the European Commission's General Data Protection Regulation (GDPR) is enough to send shivers down the backs of businesses which have had to make rapid changes to be ready in time for the deadline. The cutoff point for organizations to conform to the new GDPR legislation has passed, but emails are still flooding in from companies hoping that you will re-subscribe and give them consent to contact you, some online services have -- at least temporarily -- become unavailable for EU visitors, and we are likely to see disruption for some time to come as companies catch up. The new framework, which impacts all EU member states, requires businesses to be more transparent in connection to what data they collect and store from users, to report the discovery of data breaches within 72 hours, and to manage information securely. The core of the legislation was designed to bring some order to the lackluster rules surrounding data collection, the masses of information stored for no business purpose, and the constant threat of data breaches. However, many organizations have been left floundering -- unsure of where their information is, how it is recorded, what has been collected in the first place and for how long, whether or not user consent for storage has been granted, and if this data has been secured.
From high-tech unicorns to specialty chemicals, the country's economy is moving swiftly beyond its lower-margin roots. The Chinese are now the world's most avid online purchasers of goods and services, which they are likely to pay for with a mobile device. The deepening digital ethos reflects a broader consumerization of the Chinese economy. These trends are creating fertile grounds for digital start-ups while also transforming traditional industries such as specialty chemicals as they supply materials for advanced industries and higher-margin consumer goods. Global companies in China should ensure that they're not competing for yesterday's markets.
Health Catalyst introduced Touchstone at HIMSS18 and, in so doing, described it as a performance discovery, prioritization, benchmarking and recommendation tool. "Touchstone is built from the ground up on the latest AI and software from Silicon Valley," said Dale Sanders, President of Technology, Health Catalyst. "Touchstone's recommendation engine, which borrows from Amazon and Netflix, gives you not just comparative benchmarks but recommendations to improve your performance against benchmarks." The technology includes risk models based on artificial intelligence and anomaly detection algorithms that hospitals can use to pinpoint underperforming areas. Touchstone performs risk-adjusted benchmarking by culling data in claims, cost-accounting systems, EHRs, external benchmarks and operations to risk-adjust benchmarking, to "guide users to the data and analyses of greatest relevance to their work and to the organization's goals," the company said.
"IoT helps cities to predict accidents and crime as well as gives doctors real-time insight into information from pacemakers or biochips," said Ahmed Banafa of San Jose State University at a recent webinar. "IoT optimizes productivity across industries through on equipment and machinery, creates truly smart homes with connected appliances, and provides critical communication between self-driving cars."