This event will give an overview of AI concepts and applications. It is the first in a series of events targeting business people who wants to learn more about AI and how it can be used in business. Subsequent events will focus on industry-specific use cases, illustrating how these concepts come to play in a business setting, one industry at a time. Stockholm AI works to fortify Stockholm's position as an AI hub by facilitating knowledge-sharing around AI. Our community of data maniacs is the largest technical AI community in Northern Europe, with almost 3000 members. The combined knowledge of our members is huge.
Swedish startup firm Sango has unveiled its first project: an autonomous all-electric minibus that it hopes represents the next evolution step in the public transportation industry. The team says it will soon proceed to test it out on Stockholm streets. The shuttle bus comes powered by an array of lithium-ion batteries and a single electric motor. It can cover around 200 kilometers (124 miles) on a single charge and currently stays capped at 15 km/h (9.3 mph) for safety reasons. When the tech gets polished enough, the limit will be raised to 50 km/h (31 mph). The cab offers six seats with optional partitions and Internet access for those willing to enjoy some privacy.
Artificial Intelligence (AI) is a way to train the computers to do things that humans can do-an intelligence adding human capabilities to machines. Machine Learning (ML) refers to the machines learning on their own without needing explicit programming. ML is an application of AI that facilitates automatic learning for a system and allows it to improve from experience. Thus a program can be generated by integrating its input and output. AI is the process of acquisition of knowledge intelligence and its application. ML refers to the acquisition of knowledge or skill. If you are thirsting for more knowledge on AI/ML you have the right avenue-AIDed Learning. The Asian Institute of Design (AID) in its continued endeavor of disseminating "Knowledge for All" is organising second of its webinar series, "WHY ARTIFICIAL INTELLIGENCE IS MUCH MORE THAN ONLY MACHINE LEARNING?" Dr. Carl Gustaf Jansson, Professor Emeritus in Artificial Intelligence, KTH Royal Institute of Technology, Stockholm, Sweden. He is currently the Director for the Master School of EIT ICT Labs and also KTH ICT Research Platform, Vice Dean of the KTH ICT School and Chairman for the KTH Recruitment Committee for Computer Science and Information Technology. Dr. Jansson has been instrumental in the development of two of KTH´s 5-year M.Sc programs: Computer Science (1985) and Information Technology (1999). He has supervised more than 30 PhD students in Artificial Intelligence/Applied Logic and HCI and served as chairman of Graduate Studies in ICT for more than 10 years. He has also served in the management boards of two National Swedish Graduate Schools. Dr B. Ravindran heads the Robert Bosch Centre for Data Science & Artificial Intelligence (RBC-DSAI) at IIT Madras, the leading interdisciplinary AI research center in India. He is the Mindtree Faculty Fellow & Professor in the Department of Computer Science and Engineering at IIT Madras. Have a fun, interactive and fruitful learning.
Autonomous and semi-autonomous trucks promise to help an industry facing a shortage of drivers and increasing e-commerce demand, but they need to demonstrate efficiency for logistics adoption. Einride AB, which has been developing electric and autonomous trucks, today launched its Intelligent Freight Mobility Platform. The system is intended to help logistics fleet managers and drivers plan routes and loads, track shipments, and monitor energy efficiency. In February, Einride began recruiting the first remote operators for its trucks. The Stockholm-based startup also announced the beta of the Intelligent Freight Mobility Platform.
Anyone who runs a business knows that one of the hardest things to do is accuse a customer of malfeasance. That's why, before members of Scandinavian Airlines' (SAS) fraud detection unit accuse a customer of attempting to scam the carrier's loyalty points program, the detectives need confidence that their case is solid. "It would hurt us even more if we accidentally managed to say that something is fraud, but it isn't," said Daniel Engberg, head of data analytics and artificial intelligence for SAS, which is headquartered in Stockholm, Sweden. The airline is currently flying a reduced schedule with limited in-flight services to help slow the spread of COVID-19, the disease caused by the novel coronavirus. Before the restrictions, SAS handled more than 800 departures per day and 30 million passengers per year.
Google Cloud has kindly offered to provide attendees with lunch delivered via Uber Eats. We will share the details with those that register a few days before the workshop. Please note we are only able to provide lunch for people located in Stockholm, Sweden. We want to emulate as much as possible real-world connections in a remote setting: we will go through a fun ice breaker activity together to break down the stranger barrier. We will share the details at the workshop, but hint, it involves spirit animals .
In the U.S. and other countries, aging populations and growing logistics demand have resulted in shortages of truck drivers. Autonomous trucks could help relieve those shortages. Einride AB today announced that it plans to hire what it called "the first autonomous and remote truck operator in the freight mobility space." The Stockholm-based company said it will hire drivers in Sweden next month, followed by the U.S. in the third quarter. The remote operators would begin commercial services in Sweden in Q3 2020 and in the U.S. in Q4 2020.
--Enabling cellular connectivity for drones introduces a wide set of challenges and opportunities. Communication of cellular-connected drones is influenced by 3-dimensional mobility and line-of-sight channel characteristics which results in higher number of handovers with increasing altitude. Our cell planning simulations in coexistence of aerial and terrestrial users indicate that the severe interference from drones to base stations is a major challenge for uplink communications of terrestrial users. Here, we first present the major challenges in coexistence of terrestrial and drone communications by considering real geographical network data for Stockholm. Then, we derive analytical models for the key performance indicators (KPIs), including communications delay and interference over cellular networks, and formulate the handover and radio resource management (H-RRM) optimization problem. Afterwards, we transform this problem into a machine learning problem, and propose a deep reinforcement learning solution to solve H-RRM problem. Especially, the heat-maps of handover decisions in different drone's altitudes/speeds have been presented, which promote a revision of the legacy handover schemes and redefining the boundaries of cells in the sky. I NTRODUCTION Commercial drone applications have attracted profound interest in recent years in a wide set of use-cases, including area monitoring, surveillance, and delivery .
This article is a summary of a talk I gave at the yearly Webstep's "Kompetensbio" event. Every year Webstep invites all developers to this free event that happens in some nice local cinema, where they can enjoy interesting tech-talks and watch some exciting movie. This year, for the first time, the event took place in three cities: Uppsala, Malmö and Stockholm. Ever since I was a child and to this day, I was a big Science-fiction fan. Growing up in a small town in former Eastern bloc country, was not really a lot of fun. Especially if you were smart and curious.
My eyes were opened to many new opportunities to integrate economics, design thinking, big data and data science (AI / ML / DL) to further my case for a Nobel Prize in Economics (which I'd prefer not to be awarded posthumously). So, while we wait for that call from Stockholm, let's take a look at my 10 favorite 2019 blogs: There are many valuable lessons that data scientists can learn from the movie "Mr. And maybe the biggest challenge for the development of smart, autonomous products is knowing when "good enough" is actually "good enough". When trying to optimize the operations of these smart, autonomous products, one must be prepared to realize that the current path to performance optimization may not actually be the optimal path, and the data science team must be prepared to jettison their existing work and try a different approach that might lead to a better performing analytic model. This is an important lesson for the creation of our AI-induced "smart" products – that there must be constant testing, learning, and maybe even some unlearning and re-starting afresh in order to find the optimal models.