The disruptions – which happen near-instantly – need to be detected as early as possible. So far, simulations have been unable to deliver fast enough predictions – so the researchers turned to machine learning, which has shown promising results for disruption prediction. The goal: to meet the 95 percent correct disruption prediction threshold required by the under-construction ITER Tokamak, which will be the larger fusion reactor in the world. Julian Kates-Harbeck (lead author on the paper published in Nature) answered this challenge by developing the Fusion Recurrent Neural Network (FRNN), an AI disruption prediction tool. FRNN learns from thousands of experimental runs – tracking plasma current, temperature, density and other variables – and attempts to learn which factors signal imminent disruptions. To meet the level of reliability that ITER will demand, the researchers ran FRNN on powerful machines. After initial runs on Tiger (a cluster at Princeton University), they turned to the (now-decommissioned) Titan supercomputer, where they ran FRNN on 6,000 Nvidia Tesla K20X GPUs.
Quontic Bank opened a checking account for a bitcoin ATM company a few weeks ago and is in the process of completing a contract to deliver banking services to another crypto startup. The bank wouldn’t name either client. “We’re just taking steps so that when the regulatory environment becomes more crypto-friendly, we don’t have a lot of catching up to do,” said Quontic chief executive Steven Schnall, who acquired the bank in 2009. “We’re looking to diversify our product offering and our customer mix by entering into that field.” While Schnall wouldn’t say how big he wants Quontic’s crypto business to be, he claimed the pending contract “could impact millions of Americans.” Crypto-friendly banks are extremely rare, in part because of the extra work they have to do complying with know-your-customer (KYC) and anti-money laundering (AML) regulations. “Banks and other financial institutions have to look out for any suspicious activity,” said Joshua Klayman, head of the blockchain and digital assets practice at law firm Linklaters.
AI systems have already been designed to help or hurt humans. A group at UCSF recently built an algorithm to save lives through improved suicide prevention, while China has deployed facial recognition AIsystems to subjugate ethnic minorities and political dissenters. Therefore, it’s impossible to assign valence to AI broadly. It depends entirely on how it’s designed. To date, that’s been careless. AI blossomed with companies like Google and Facebook, which, in order to give away free stuff, had to find other ways for their AI to make money. They did this by selling ads. Advertising has long been in the business of manipulating human emotions. Big data and AI merely allowed this to be done much more effectively and insidiously than before. AI disasters, such as Facebook’s algorithms being co-opted by foreign political actors to influence elections, could and should have been predicted from this careless use of AI. They have highlighted the need for more careful design, including by AI pioneers like Stuart Russell, who now advocates that “standard model AI” should be replaced with beneficial AI.
Online skimming is a variation of a criminal tactic used to gain access to payment card information. Until recently, it was more commonly associated with physical fraud, in which criminals use a device (‘skimmer’) that interacts with a victim’s payment card. One of the most common skimming methods is to place a duplicate card reader on top of an ATM’s payment card slot. Criminals can then siphon off card details as the card enters the machine. This reader will typically be paired with a pinhole camera or duplicate keypad placed over the machine so that the fraudsters can log the customer’s PIN. Online skimming works in much the same way, except the ATM is replaced by an online payment form and the physical skimming device is replaced by malicious code. Magecart is the umbrella term used involving criminal groups exploiting vulnerabilities that mostly target Magento-based online stores or content management systems. A number of recent data breaches such as Ticketmaster/British Airways was believed to be part of such credit card skimming operations.
Edge computing has been touted as one of the lucrative, new markets made feasible by 5G Wireless technology. For the global transition from 4G to 5G to be economically feasible for many telecommunications companies, the new generation must open up new, exploitable revenue channels. 5G requires a vast, new network of (ironically) wired, fiber optic connections to supply transmitters and base stations with instantaneous access to digital data (the backhaul). As a result, an opportunity arises for a new class of computing service providers to deploy multiple µDCs adjacent to radio access network (RAN) towers, perhaps next to, or sharing the same building with, telco base stations. These data centers could collectively offer cloud computing services to select customers at rates competitive with and features comparable to, hyperscale cloud providers such as Amazon, Microsoft Azure, and Google Cloud Platform. Ideally, perhaps after a decade or so of evolution, edge computing would bring fast services to customers as close as their nearest wireless base stations.
DevOps shops can use feature flags in conjunction with other application deployment methods, including what Condo referred to as a progressive release methodology. Rather than the typical pattern of releasing approved code and then deploying that release to production, a progressive release instead deploys latent code to production, where it is then tested or held until a designated time and switched on. A feature flag, in this instance, makes that final changeover as simple as pressing a button. But feature flags also create significant technical debt if left unchecked -- technical debt that IT admins must clean up or otherwise manage during troubleshooting, new releases and other ops tasks. Organizations that rely on feature flags have two options, Condo said: "They could leave the feature flag there, because they have some greater strategy about how they manage things ... or [flag code removal] becomes part of the normal routine, and [admins] remove that code so that it never gets turned off accidentally and [there are] fewer flags to manage."
Technology shifts such as the iPhone, the Android with its emphasis on opensource, WordPress slashing the cost of building a website, the cloud reducing the need for startups to invest in expensive hardware — helped create a space for startups. As for London — immigration may have been another factor: As Espinal pointed out, he originally hails from Honduras, worked in the US, came to the UK from the US, as the UK visa system allowed this. “At the time, immigration regulation favoured highly skilled migrants.“ Espinal says you can unpick the tech story in terms of afters and befores — pre-SEIS post-SEIS, pre/entrepreneur relief, post-entrepreneur relief — EIS, the emergence of accepted ways of providing shareholder agreements, convertibles, cross border investing. Vidra reckons that the 2012 Olympics was a factor — the second wave, anyway. What with that and the Royal Wedding, the London brand name was strong. The Olympics illustrated another point; it was said that every nation competing in the games had 10,000 supporters from the local population.
In early June, a powerful DDoS attack hit Telegram. The attack was carried out primarily from Chinese IP addresses, which gave founder Pavel Durov reason to link it to the demonstrations in Hong Kong; in his words, the political opposition there uses Telegram to organize protests, which Beijing takes a very dim view of. The only headline attack this quarter seemingly driven by commercial considerations targeted video game developer Ubisoft on June 18 — just before the release of its new Operation Phantom Sight expansion for the game Rainbow Six Siege. It caused connection problems for many players, and even provoked calls on Reddit for better DDoS protection. The largest would-be DDoS attack in Q2 turned out to be a false alarm. In late June, some segments of the Internet experienced operational issues worthy of a major DDoS offensive, but the actual cause lay elsewhere. As it turned out, a small ISP in Pennsylvania had made a configuration error, turning itself into a priority route for some Cloudflare traffic. The provider could not handle the load, and thousands of websites serviced by Cloudflare went down as a result.
Unfortunately, many companies learn the hard way that when it comes to supply chain technology, it is not “one size fits all” or “technology for technology’s sake.” Stalled projects, unrealized benefits, disrupted operations, and customer and employee frustration point to the importance of selecting the right kind of emerging technology based on your operating profile and future outlook of your business. By far, the biggest driver of disruption for companies is e-commerce and the extraordinarily high service expectations it is creating. In fact, a recent report from DHL Supply Chain, “The E-Commerce Supply Chain: Overcoming Growing Pains,” found that pressure to fulfillcustomer expectations continues to challenge businesses building out e-commerce offerings and the new supply chains they need. Customers expect a great, painless e-commerce purchase experience with an ever-shortening delivery time. We are noticing profile changes in other market verticals as well, as order sizes decrease and service expectations increase.
British consumer goods and healthcare giant Reckitt Benckiser Group Plc recently made some waves when it named PepsiCo’s Laxman Narasimhan as its next chief executive officer, looking outside its own ranks for a new leader after a difficult few years. Interestingly, he replaces Rakesh Kapoor, another Indian who had been at the helm for eight years. Narasimhan’s appointment is the latest in a series of appointments of Indian-origin CEOs at top global firms in the last decade or so. Think – Vasant Narasimhan (Novartis), Sundar Pichai (Google), Satya Nadella (Microsoft), Shantanu Narayen (Adobe), Ajay Banga (Master Card), Ivan Menezes (Diageo), Sonia Syngal (Old Navy), Rajeev Suri (Nokia) and more recently Vivek Sankaran, President & CEO of Albertsons Companies and Nitin Paranjpe, global COO at Unilever.There’s no ignoring the trend of Indians making it to global leadership roles at multinational firms. And while this trend has largely been noticed in the tech firmament and Silicon Valley where the geek background helped in no small measure, the other industries surprisingly are not far behind.
Quote for the day:
"Limitations are what someone else tries to impose on you. Don't accept it. Question it!" -- Elizabeth McCormick