Automatic processes, machine learning, and robotization force a constant updating of the knowledge for those professionals responsible for logistics in MNCs and SMEs. On one hand, ERP systems have become the nerve center of companies and within these the logistics sector is the true heart and engine of all activity. Specialized logistics services companies proliferate and create models that are responsible for the dynamization of international trade, both B2B and B2C. These systems transcend the mere management we have known so far, processing thousands of data generated from all departments of the company or collected by automata. This data is systematically analyzed and managed by algorithms that generate automatic decisions, learning from successes and errors. But if there is something that is causing the entire logistics process to change in a radical way, it is robotization. Until date, a large number of personnel dedicated to logistics processes such as product and merchandise handling, order issuance, warehouse and inventory control or replenishment management were needed. However, robots are replacing these functions and ending, to a large extent, with the need for labour. These are capable of carrying a load of up to 500 Kg from one end to another of the warehouse. And even move it from one warehouse to another. In the same way, they can rotate 360 degrees on its axis, rise to load merchandise or deposit it gently at any point. We need to consider that they do much faster than humans without getting sick or requiring rest. Within five minutes, the robots recharge and have a range of 4 or 5 hours. So they can cover a full 8-hour shift with a total of ten minutes of recharging. Consequently, they can perfectly cover three daily shifts. It has no conflict between them or collective claims and they are immediately replaceable in case of breakdown or need for maintenance. The logistics robotization process is generating profound changes in the business model that affect all areas, especially the human resource management. According to reports from the World Economic Forum, by 2025 the replacement of human personnel with robots in all basic professional areas will have reached 52%. This means the loss of countless unskilled jobs. That will be compensated with the creation of 58 million qualified jobs, necessary for the robotic revolution, in the next 10 years. It is not difficult to think that technical qualifications will be one of the challenges to overcome in this whole process. Featured examples of robotization in large multinationals Two of the most prominent precursors within this logistics reorganization have been two giants of online commerce; Alibaba and Amazon. Amazon’s experience Amazon has more than one hundred thousand robots dedicated to managing the orders of its customers and all its stores are currently automated. Quite the opposite of destroying employment, the company has doubled the workforce since 2016, currently having more than 500,000 workers. Kiva robots, used by the firm, can easily replace physical work and repetitive activities that are easily programmable. But the same does not happen with another set of required skills that are demanded in new positions to add value. Alibaba’s model With its logistics model, it has facilitated the penetration of thousands of companies in different international markets. Process automation and artificial intelligence are the engines of productivity in our day and this, in turn, is the key factor in competitiveness. Only through these logistic processes is possible to manage the huge volume of orders for days like Black Friday or the Alibaba shopping festival. JD’s case Another Chinese marketing giant, JD has recently surpassed Alibaba with a warehouse capable of processing more than 200,000 orders daily with only the supervision of 4 people. The objective of this company is to provide service to all of China on the same day as long as the order is generated before 11 am. The company has not only invested millions in robots for warehouses but also done so in the incorporation of automatic systems in trucks, means of transport and distribution drones. Prof. https://mlafrica.com/wp-content/uploads/2020/04/Stock-Trading-with-Artificial-Intelligence.jpeg V. Rodriguez
Will Artificial Intelligence reach the level of the human intellect by 2040?
Technological singularity is a hypothesis that predicts that there will come a time when artificial intelligence will be able to improve itself recursively. In theory, machines that are capable of creating other machines even more intelligent, resulting in intelligence far superior to human beings and, which could be even more shocking, beyond our control. AI, Machine Learning, Neural Networks… these are terms that transmit feelings which are equally of hope and fear of the unknown. In the next 20 years, there will be more technological changes than in the last 2 millennia. The technology is much faster than the brain – a calculator multiplies 5-digit numbers in tenths of a second – but it works differently, for example, it does not have the level of connections equivalent to that of neurons in a human brain. However, if the exponential speed of Moore’s law does not stop and the investigations of neural networks of giant corporations such as Google continue to advance by 2040 the degree of technological integration in our lives will far exceed the capacity of the human brain. The word singularity was taken from astrophysics: a point in space-time – for example, inside a black hole – in which the rules of ordinary physics are not lost. It was associated with the explosion of artificial intelligence during the 1980s by science-fiction novelist Vernor Vinge. At a NASA symposium in 1993, Vinge predicted that in 30 years there would be technological means to create superhuman intelligence called Singleton which refers to a “world order in which there is a single decision-making entity at the highest level, capable of exerting effective control over its domain and preventing internal or external threats to its supremacy”. In addition to this, he assured that, shortly after, we would reach the end of the human era. Throughout history, some technological advances have caused fear. The fear of the new and the unknown is understandable, however, all technologies can be modified for good or for evil, as you can use fire to heat and cook food, or to burn people In the case of the singularity, it seems clear that one must be cautious, regulating its development but without limiting it and, above all, trying to ensure that this future artificial intelligence learns from ethical and moral values, as well as from mistakes and successes of the species. We must be clear in our conception of the term. Human beings and machines are meant to co-exist in symbiosis and not rivalry. Mortality as an “option” by 2045? On the other hand, we could analyze if mortality will be “optional” by 2045. Google has already started extravagant research initiatives as they realized that curing aging is possible and that is why they are creating companies such as ‘Calico’ or ‘Human Longevity’, which are investigating it, but also non-profit organizations such as the Methuselah Foundation. It is evident that the possibilities are real since immortality already exists in nature. Some cells are immortal and the stem cells affected the quality of reproducing indefinitely, just like cancer cells. One of the steps to achieve this is to fully comprehend the structure of incurable diseases today, and then eradicate them. Thus, as it happens with HIV, a controllable chronic disease, or diabetes. We must propose the same with aging: turn it into a controllable chronic disease, and later on, cure it for good. It is essential to begin human trials with rejuvenation technologies that have been shown useful in other animals leading to advancements in human clinical trials as well. Prof. https://mlafrica.com/wp-content/uploads/2020/04/Stock-Trading-with-Artificial-Intelligence.jpeg V. Rodriguez is an Asst. Professor at Universal Business School.
Predicting people’s driving personalities
Self-driving cars are coming. But for all their fancy sensors and intricate data-crunching abilities, even the most cutting-edge cars lack something that (almost) every 16-year-old with a learner’s permit has: social awareness. While autonomous technologies have improved substantially, they still ultimately view the drivers around them as obstacles made up of ones and zeros, rather than human beings with specific intentions, motivations, and personalities. But recently a team led by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has been exploring whether self-driving cars can be programmed to classify the social personalities of other drivers, so that they can better predict what different cars will do — and, therefore, be able to drive more safely among them. In a new paper, the scientists integrated tools from social psychology to classify driving behavior with respect to how selfish or selfless a particular driver is. Specifically, they used something called social value orientation (SVO), which represents the degree to which someone is selfish (“egoistic”) versus altruistic or cooperative (“prosocial”). The system then estimates drivers’ SVOs to create real-time driving trajectories for self-driving cars. Testing their algorithm on the tasks of merging lanes and making unprotected left turns, the team showed that they could better predict the behavior of other cars by a factor of 25 percent. For example, in the left-turn simulations their car knew to wait when the approaching car had a more egoistic driver, and to then make the turn when the other car was more prosocial. While not yet robust enough to be implemented on real roads, the system could have some intriguing use cases, and not just for the cars that drive themselves. Say you’re a human driving along and a car suddenly enters your blind spot — the system could give you a warning in the rear-view mirror that the car has an aggressive driver, allowing you to adjust accordingly. It could also allow self-driving cars to actually learn to exhibit more human-like behavior that will be easier for human drivers to understand. “Working with and around humans means figuring out their intentions to better understand their behavior,” says graduate student Wilko Schwarting, who was lead author on the new paper that will be published this week in the latest issue of the Proceedings of the National Academy of Sciences. “People’s tendencies to be collaborative or competitive often spills over into how they behave as drivers. In this paper, we sought to understand if this was something we could actually quantify.” Schwarting’s co-authors include MIT professors Sertac Karaman and Daniela Rus, as well as research scientist Alyssa Pierson and former CSAIL postdoc Javier Alonso-Mora. A central issue with today’s self-driving cars is that they’re programmed to assume that all humans act the same way. This means that, among other things, they’re quite conservative in their decision-making at four-way stops and other intersections. While this caution reduces the chance of fatal accidents, it also creates bottlenecks that can be frustrating for other drivers, not to mention hard for them to understand. (This may be why the majority of traffic incidents have involved getting rear-ended by impatient drivers.) “Creating more human-like behavior in autonomous vehicles (AVs) is fundamental for the safety of passengers and surrounding vehicles, since behaving in a predictable manner enables humans to understand and appropriately respond to the AV’s actions,” says Schwarting. To try to expand the car’s social awareness, the CSAIL team combined methods from social psychology with game theory, a theoretical framework for conceiving social situations among competing players. The team modeled road scenarios where each driver tried to maximize their own utility and analyzed their “best responses” given the decisions of all other agents. Based on that small snippet of motion from other cars, the team’s algorithm could then predict the surrounding cars’ behavior as cooperative, altruistic, or egoistic — grouping the first two as “prosocial.” People’s scores for these qualities rest on a continuum with respect to how much a person demonstrates care for themselves versus care for others. In the merging and left-turn scenarios, the two outcome options were to either let somebody merge into your lane (“prosocial”) or not (“egoistic”). The team’s results showed that, not surprisingly, merging cars are deemed more competitive than non-merging cars. The system was trained to try to better understand when it’s appropriate to exhibit different behaviors. For example, even the most deferential of human drivers knows that certain types of actions — like making a lane change in heavy traffic — require a moment of being more assertive and decisive. For the next phase of the research, the team plans to work to apply their model to pedestrians, bicycles, and other agents in driving environments. In addition, they will be investigating other robotic systems acting among humans, such as household robots, and integrating SVO into their prediction and decision-making algorithms. Pierson says that the ability to estimate SVO distributions directly from observed motion, instead of in laboratory conditions, will be important for fields far beyond autonomous driving. “By modeling driving personalities and incorporating the models mathematically using the SVO in the decision-making module of a robot car, this work opens the door to safer and more seamless road-sharing between human-driven and robot-driven cars,” says Rus. The research was supported by the Toyota Research Institute for the MIT team. The Netherlands Organization for Scientific Research provided support for the specific participation of Mora.
ML Africa successfully hosted the inaugural AI & The Future of Healthcare Summit
Artificial intelligence and machine learning are the most trending and dominating technologies of our times. These are shaping the future and impacting on our daily lives. For businesses and government, adoption and agile adoption of these technologies is imperative. Machine learning Africa celebrates its successful hosting of the inaugural AI & The Future of Healthcare Summit at Hilton Sandton on the 30th of October 2019. It was a wonderful event where technology enthusiasts were sharing insights into the development of AI driven healthcare solutions that improve patient outcomes. The discussions focused on the future of healthcare, patient engagement, the public and private sector collaboration, digital health strategy, AI in Radiology, precision medicine, the future of robots in healthcare, diagnostic technologies and upskilling healthcare workforce. Key note speakers included: Prof. Nelishia Pillay, Head of the Department of Computer Science at the University of Pretoria, Johan Steyn, AI Enthusiast, Portfolio Lead: DevOps & Software at IQBusiness South Africa, Joel Ugborogho, Founder of CenHealth, Dr. Jonathan Louw, MB.ChB, MBA, CEO of the South African National Blood Service (SANBS), Basia Nasiorowska, CEO at NEOVRAR, Josh Lasker, Co-Founder, Abby Health Stations, Dr. Jaishree Naidoo, Paediatric Radiologist and CEO of Envisionit Deep AI, Prof. Antonie van Rensburg, PrEng, Chief Digital Officer IoTDot4, Dr. Darlington Mapiye (PhD) Technical Lead for the data driven healthcare team at IBM Research Africa, Dr. Boitumelo Semete, Executive Cluster Manager, CSIR, and Yusuf Mahomedy, Chief Executive of the Association Executive Network of Southern Africa (AENSA) The event was made possible through partnership with Envisionit Deep AI, a medical technology company that utilizes artificial intelligence to streamline and improve medical imaging diagnosis for radiologists. Their AI model RADIFY will augment and improve the radiology reading and thereby relieve the bottlenecks we face in medical imaging. Other event partners present were Evolutio, SANBS, IQBusiness, IoTDot4 and ICITP. If you would like to increase your proficiency further in emerging technologies and deploy the most effective strategies within your organization, the Digital Health workshop would be another exciting and relevant event to consider. Entitled ‘Accelerating Digital Health Services’, the workshop is brought in partnership with Cenhealth, on the 5th of December 2019. In preparation for the upcoming changes in the healthcare industry, it is imperative for all healthcare institutions not be left behind in their digital transformation journey.
The Future of the Maritime Logistics Industry: Unmanned ships from 2020
+27 10 634 0880 There are no drones only across the sky but also on land and sea and Rolls Royce has focused on the latter for its commercial strategy as far as vessels are concerned. The company, which no longer manufactures cars -transferred the automobile division to BMW- is a conglomerate that operates in the aeronautical, aerospace, maritime and energy sectors. They have a clear-cut commitment to the seas: launch unmanned ships by mid-2020. In the meantime, the Rolls-Royce Blue Ocean research team has already launched a virtual reality prototype in its office in Alesund, Norway, which simulates the views from a ship’s command bridge in 360 degrees. The manufacturer hopes that ship captains can maneuver hundreds of unmanned ships from the ground, without any need to approach the sea. The idea is that during this year the first fleet of unmanned ships will be built. The first would be tugboats or ferries, boats that make simple, short-sized journeys in controlled environments. At first, all risks must be minimized, in order to avoid any possibility of unforeseen events. The next stage would be the launch of cargo ships, with increasing complexity, especially because they sail in international waters. As of today, there is no legislation that covers unmanned commercial shipping. And the approval of international regulation is always slower than that processed by individual countries. Unmanned ships, according to Rolls Royce, will reduce operating costs by 20%. Companies, therefore, buy ships to increase their profit margins. The other side of technology is the possible loss of jobs. It will not be necessary to have a crew either a large contingent of security personnel. However, piracy will surely remain a threat that requires the presence of minimal security personnel while keeping in mind that there will not be as many lives at stake in the absence of crew members as the risk for cargo theft. Although, Rolls-Royce pointed out that new jobs will be created. The operations will have to be performed from the ground. It is an unmanned craft, not autonomous. Cybersecurity will be a key element assuring secured communications links between the ship and land, hence new profiles will be necessary. By replacing the control bridge along with the other systems where the crew is usually accommodated – including electricity, air conditioning, water, and waste treatment system- the ships will withstand more cargo, reducing costs and increasing revenue. In addition to this, according to the initial calculations, these ships will be 5% lighter and consume between 12 to 15% less fuel ensuring a greener performance. Similarly, electric fuel-free ships are being researched in order to consider their implementation. Waterfall Office Park Gardens Elevation, Midrand. 1686 | +27 10 634 0880 | info@mlafrica.com Machine Learning Africa provides insight into emerging machine learning technologies and their inevitable impact in transforming Africa. Provides a platform where innovators, technology vendors, end users and enthusiasts discuss latest innovations and technologies that transform businesses and the broader society. Menu Contact Us Waterfall Office Park Gardens Elevation, Midrand. 1686 Tel: +27 10 634 0880 Email: info@mlafrica.com Gallery © 2019 Machine Learning Africa. All rights reserved. Twitter Facebook Dribbble Youtube Pinterest Medium
Email Threat Report
Despite organizations adopting ‘secure’ email gateways and extensive employee training, 94% of cyber-attacks still start in the inbox. It’s clear a more advanced approach to email security is needed. Able to spot the subtlest signals of attack, Darktrace Antigena Email recognizes malicious activity even in ‘clean emails’ – preventing threats from reaching the inbox. Read the 2020 Email Security Threat Report now to discover what today’s threat landscape looks like and how Darktrace AI autonomously neutralizes all email-borne threats, from malware in fake invoices to C-level impersonation attacks. Download now