Machine learning can enable software to adapt and improve the execution of tasks and processes autonomously.
For businesses, machine learning can enable software to adapt and improve the execution of tasks and processes autonomously. This saves time and money while empowering employees to focus on value-adding, strategic, and creative tasks. Businesses that have already benefitted from the power of machine learning are called Fast Learners, and they experience benefits from improved customer satisfaction and increased profitability. Some have improved customer support with machine learning chatbots, and nearly half of all Fast Learners expect revenue growth of more than six percent from 2018 to 2019.
But what sets Fast Learners apart from their competition? What makes them so willing to take the perceived – yet much lower than expected – risk of embracing this new technology? As I work with them in implementing machine learning across their businesses, five key traits become more obvious every day:
- C-level, strategic priority: Fast Learners’ senior-most management sees the strategic value of machine learning and fosters a workplace environment that is not afraid of change.
- Increased competitive differentiation: Fast Learners see machine learning as a pragmatic yet innovative way to stand out in a crowded market, not as a gimmick or fad.
- New revenue and profitability: Machine learning is a valuable source of revenue and profitability for Fast Learners. They look to bring about fundamental, rather than incremental, change and believe machine learning’s potential in business model innovation is enormous.
- Key processes close to home: Spending money on locally sourced business functions is important to Fast Learners – they spend more on local functions than they do on ones from low-cost regions.
- Enterprise-wide strategy: Fast Learners look at what machine learning can do for their business in a holistic way rather than forcing it into a purpose that may not be the best fit.
Of these traits, I believe that C-level strategic priority and enterprise-wide strategy are the most important. These two traits often go hand in hand – where senior management is aware of the opportunities and limitations of machine learning, they are more likely to look at what the technology can do for their business in a holistic way with enterprise-wide strategy. The other traits simply follow naturally.
Equally apparent are the reasons businesses do not implement machine learning. Most commonly, they lack those aforementioned traits. But often, there are also misconceptions about the effort and cost required to implement machine learning solutions. Many simply don’t know where to start or are afraid to fall victim to yet another technological fad.
But the machine learning hype is well-warranted. Fast Learners who began their machine learning journey before most people had ever even heard of the technology have since created a lasting impact across the breadth of their organizations that goes far beyond hype. For example, one Chinese shoe company used machine learning to enable customers to design their own shoes and wear them within one week. Your business can launch such lasting innovations, too.
The enormous possibilities of 5G for mobility
Huawei Consumer Business Group (CBG) launched its HUAWEI 5G customer-premises equipment (CPE), the world’s first commercial terminal device supporting the globally recognized 3GPP telecommunication standard for 5G. This device marks a milestone as Huawei sets the stage for the next generation of wireless connectivity. To ensure peak performance from its 5G CPE, Huawei uses its self-developed Balong 5G01 chipset – the world’s first commercial chipset supporting the 3GPP standard for 5G, with theoretical downlink speeds of up to 2.3Gbps. It supports 5G across all frequency bands including sub-6GHz and millimeter wave (mmWave) to offer a complete 5G solution suitable for multiple use cases. The Balong 5G01 makes Huawei the first company offering an end-to-end 5G solution through its network, devices and chipset-level capabilities.
“5G technology will underpin the next leap forward for our intelligent world, where people, vehicles, homes and devices are fully connected, delivering new experiences, insights and capabilities,” said Richard Yu, CEO of Huawei Consumer Business Group. “Since 2009, Huawei has invested US$600 million in research and development into 5G technologies, where we have led the way with innovations around network architecture, spectrum usage, field verification and more. From connected vehicles and smart homes to AR/VR and hologram videos, we are committed to developing a mature 5G ecosystem so that consumers can benefit from a truly connected world that transforms the way we communicate and share.”
The HUAWEI 5G CPE has two models, low frequency (sub6GHz) 5G CPE and high frequency (mmWave) 5G CPE respectively. The HUAWEI low frequency 5G CPE is small and lightweight, compatible with 4G and 5G networks, and has proven measured download speeds of up to 2Gbps – 20 times that of 100Mbps fiber. This provides an ultra-fast experience, allowing users to enjoy VR video and gaming experiences, or download a TV show within a second. The HUAWEI high frequency 5G CPE is available in indoor and outdoor units.
5G networks set new standards for high speed, wide bandwidth, low latency wireless connections, with a peak downlink rate of 20Gbps, support for one million devices per square kilometer and latency as low as 0.5ms. 5G promises an enhanced connection between people and the Internet of Things, raising the potential for the number of devices that can be connected and the amount and type of data that can be shared between them.
Huawei CBG has developed a 5G device strategy which utilizes the high-speed, low-latency, big-connectivity qualities of 5G to create richer, more varied connected experiences for users. This strategy includes smartphones, mobile Wi-Fi, industrial modules and other devices to connect people and objects in their homes, vehicles and beyond.
Huawei has partnered with over 30 global telecommunication carriers, including Vodafone, Softbank, T-Mobile, BT, Telefonica, China Mobile and China Telecom. In 2017, Huawei began testing 5G commercial networks with partners. Huawei completed interoperability testing and started offering the first round of 5G commercial networks in 2018.
A huge Siberian road (over 21,000 km) to join the Russian border with the state of Alaska (USA
Russian Railways President Vladimir Yakunin, presented a plan that aims to build a huge Siberian road (over 21,000 km) to join the Russian border with the state of Alaska (USA), crossing a narrow section Bering Sea that separates Asia and North America.
This project, called Trans-Eurasian Belt Development (TEPR) provides for the creation of this road parallel to the existing Trans-Siberian railway, which will pass through cities like London (Great Britain), Moscow (Russia), Nome and Fairbanks (Alaska) and New York (USA). During his presentation, held at the Russian Academy of Science, was not elaborated on the economic aspects, beyond the statement that the cost will be “billions of dollars”, no date was put to the hypothetical development project.
Windows Hello introduces biometric authentication – using your face, fingerprint or iris to unlock your device
Alibaba shows drone delivery ambitions with test in China
Alibaba’s drones lifted off last week in the company’s first trial delivery flights in China, according to Bloomberg. The move comes as its U.S. competitor Amazonbattles to get its own drone program off the ground and Google tests its own autonomous delivery drones. The Chinese e-commerce company partnered with Shanghai YTO Express Logistics to deliver ginger tea packets to 450 Chinese customers who volunteered for the drone tests. The drones had a 2.2-pound payload capacity and a 6.2-mile range. Amazon, which has also been testing drone delivery overseas, is attempting to push its own drone delivery program forward in the U.S., only to be challenged by safety and privacy regulations. The Seattle-based e-commerce company aims to deliver products by drone to consumers in 30 minutes or less. Like Chinese regulators, the FAA is considering license requirements for drone operators. Internet commerce companies aren’t the only ones hovering around drones. Search companies like Google and social media platforms like Facebook are converging in on the technology, in addition to concepts like artificial intelligence, robotics and augmented reality. Even though drones aren’t directly applicable to most of these tech companies’ primary business models, they don’t want to be left behind to become the next Microsoft Corp., struggling to catch up to tech companies which invested in the future. Alibaba is seeking approval from the Chinese government to move forward with commercial drone delivery.
Logistics Viewpoints: My Supply Chain Resolutions (Steve Banker)
(Reading Report) To remember that supply chains should be built backward from the customer. One way to do this is to use a Perfect Order metric as a key way of measuring the supply chain organization. But the question remains if my organization improves from 88 percent to 92 percent, is that good enough? Ultimately, value is determined by customers, and they do this by comparing one organizations delivery capabilities with other organizations capabilities. New Customer-Centric Supply Chain Metrics have emerged that can help to answer this question. And finally, it is worth remembering that large customers serve different types of customers, in different channels. To delight customers, while remaining profitable, it is very likely a company will need to segment their supply chain. For customers buying high profit margin products, higher service levels are justified. For cost sensitive customers, lower service levels can be justified.
Building a supply chain backwards from the customer also involves becoming demand driven. The more demand signals can be generated from the actual end customer, even if that final customer is a few tiers down the supply chain, rather than from historical shipment data, the better a supply chain organization will be able to serve the customer. At many large companies, Lean continuous improvement programs are well entrenched in manufacturing. But I’ve toured few shipper warehouses where it was obvious that Lean programs were part of the culture. And while it is necessary that Lean be supported by top down management support, the best lean programs are truly bottom up.
To remember that unlocking value will more often involve breaking down siloes than attaining operational excellence within a silo. This has long been a central tenant of supply chain management. For example, having a manufacturing organization achieve high throughput based on long production runs makes no sense if a company ends up with excess inventory. However, manufacturing and logistics folks both see themselves as part of an end to end supply chain. Functions like invoicing, human resources, and IT may not. It is not just breaking down boundaries between manufacturing, distribution, and transportation that is important. If you truly build a supply chain backwards from a customer, you may find that new forms of integration and process improvement require working with parts of the organization not seen as contained within the supply chain organization, or even within the company. This process has been going on for a while. Sales and Operations Planning (S&OP) have brought sales and marketing into collaboration with the supply chain. Now as S&OP is morphing into Integrated Business Planning, the touch points with finance are becoming much tighter. But even this is not enough. At a large global company, if you were to staple yourself to an order as it moved through an organization – for example, manufacturing in Europe, inventory in a DC in Brazil, and delivery to a client in Peru – you would likely be shocked by the excess inventory required and the service cycle time. And the constraints would take you to parts of the organization you would never have thought to look at.
IDC, which published its general predictions, but it has also given very specific information about certain trends such as the Internet of Things or IoT. Some trends spanning 2015 and a few months beyond. For example, IDC believes that within two years, 9 out of 10 technological networks have suffered a security breach related to IoT. This will force the CISOs to put the batteries, looking for new protections. “While” specifies IDC, “many [of these gaps] shall be considered ‘inconvenient’ ‘rather than a problem.
In three years, half of these networks should have lost the “excess capacity” they enjoy today. Moreover, almost all data centers, or 90% to be exact, will accommodate infrastructure management that is considered non-traditional.
Other numbers provided by IDC are those who point out that in 2018, 40% of the data associated with IoT will be managed by the network, 60% of proprietary solutions will have become open source and 16% of the population promote global phenomenon of interconnected because it belong to Generation Y devices, much better prepared to face new challenges.
It is expected that the Internet of Things narrow ties with smart cities, wearable devices and cloud computing technology, favoring such trends. And if events unfold as expected IDC, within five years, “all industries have launched initiatives IoT”.
According to the latest study on Internet of Things (IoT) prepared by the lab VINT Sogeti, this sector will generate a turnover of 596,000 million euros worldwide in 2022. The five sectors that generate more business according to the report will be : intelligent building construction, with 213,000 million; Automotive (175,000 million euros), utilities, with 44,000 million smart cities (21,000 million) and industry, with 17.000 million euros.
The same report, which covers studies on IoT as Pike Research analyst or companies like Bosch, notes that the concept of smart cities aglutinará investments diverse environments such as smart buildings, cars and energy suppliers. Thus, from 2010 to 2020, the development of such cities and projects based on IoT within them will generate an investment volume of 87,000 million euros.
This fourth report on IoT the VINT Institute focuses precisely on the cities of the future. The report analyzes how this concept has gained momentum and rapid developments taking, based on five basic technological concepts and grouped following abbreviations low SMACT (Social, Mobile, Analytics, Cloud and Things).
The report said 11 key areas within the cities for the deployment of Internet of Things: health, food, traffic, logistics, administration, networking, retail, supply chain, smart meters, tourism and e-administration.
Currently, existing projects that reflect three models approach to the concept of smart city: City in a Box (cities to the letter in which planes all the necessary infrastructure is contemplated), Sensitive City (based on the use of sensors that collect behaviors and routines inhabitants) and City as a Platform (set of applications and technology to collect data and apply to infrastructure).