There is still a long way to go before we see 5G's real power. But its technological force is such that it's invoked trade wars between the US and China, both vying to be the leading edge in 5G deployment. The potential of 5G hasn't been met, but it's tipped to provide lightning-fast connectivity required for smart city infrastructure and autonomous vehicles, among a raft of next-gen use cases. But as we ponder 5G's future applications, some are choosing to look even further ahead. In Finland, the University of Oulu in announced project "6Geneis"-- the first research programs that focused on developing the future of communication.
Drone delivery service Wing is launching its own air-traffic control app to keep its craft safe in the skies. The company, owned by Google-parent Alphabet, recently started making deliveries in parts of Australia and Finland. Wing's new iOS and Android app aims to'help users comply with rules and plan flights more safely and effectively,' providing a rundown of airspace restrictions and hazards as well as events nearby that could interfere. The new app, Open Sky, is being released to drone flyers in Australia this month according to Wing. 'The design of our software has required a detailed understanding of flight rules -- along with buildings, roads, trees, and other terrain -- that allow aircraft to navigate safely at low altitudes, and we've used it to complete tens of thousands of flights on three continents,' Wing said in a blog post.
Organised around the three main pillars that constitute the Council of Europe core values, human rights, democracy, and the rule of law, panel discussions addressed the challenges and opportunities of AI development for individuals, for societies, and for the viability of our legal and institutional frameworks, and explored options for ensuring that effective mechanisms of democratic oversight are in place.
Helsingin Sanomat responded to the bafflement by stating that the election engine's algorithm was built to recommend parties, not single candidates, that best correspond to a citizen's political views. This arrangement left perfectly suited candidates to the sidelines of the engine's suggestions. As a result of public discussion about the engine's function the newspaper published its algorithm for everyone to see. It also modified the algorithm based on the suggested improvements it received. Meeri Haataja was thrilled about the conversation.
There is great potential for the use of Artificial intelligence (AI) by cities. With the help of AI, we can provide more responsive services to citizens. However, AI poses ethical issues that need special attention, as Chief Digital Officers of London and Helsinki here we explain why and suggest an approach for city government. The use of automation and machine learning systems is not a new phenomenon in public administration, but it is being transformed in how it is being used -- from automating simple transactions to more complex problem-solving. Today we see adoption across a range of municipal services -- chatbots in customer services, prioritisation of housing repairs, traffic signalling, demand-responsive transport, even library book management systems.
The research surrounding methods of information retrieval is an entire field of science whose specialists aim to provide us with even better search results – a necessity as the amount of data constantly keeps growing. To succeed in their quest, researchers are focusing on the interaction between humans and computers, connecting methods of machine learning to this interaction. One of these researchers is Dorota Głowacka, who assumed an assistant professorship in machine learning and data science at the Helsinki Centre for Data Science HiDATA at the beginning of 2019. Głowacka is studying what people search for and how they interact with search engines, with a particular focus on exploratory search. This is a search method that helps find matters relevant to the person looking for information, even if they are not entirely certain about what they are looking for to begin with.
Mika Lintilä the Minister of Economic Affairs in Finland appointed a steering group in May 2017 to figure out how they could become one of the world's top countries within the field of Applied AI. In October 2017, Finland was the first European Union country to put a national action plan on AI into writing. This seems quite a lot earlier than most other countries in Scandinavia. At around that time they were scheduled to release their final report April 2019. However they also released a report at the time called Finland's Age of Artificial Intelligence that touched upon their strengths and weaknesses in AI with eight specific recommendations to turn the country into a global leader.
The Nordic nation has pledged to go carbon neutral by 2035 – not bad for one of the coldest countries in the world. The Hollywood star says he wants to solve climate change with robots. Details are scant, but come on, he's Iron Man! Millions of people are rejoicing as iTunes shuffles of this mortal coil. Apple says the long-hated app will still survive on Windows, however. Forget "my kid could draw that" – now robots are producing bad art.
As scientists continue to toil away at creating machine learning algorithms that will one day enslave humanity save us all, artificial intelligence researchers have discovered that computers are outpacing human doctors in a number of important areas. We've already seen the ability of AI to spot things like cancer, and a new study reveals that a digital brain may also be better at predicting overall mortality and specific conditions such as heart attack with greater accuracy than a trained individual. The research, which was presented at the International Conference on Nuclear Cardiology and Cardiac CT, suggests that we may be fast approaching a day when artificial intelligence works hand-in-hand with medical professionals to anticipate life-threatening problems before they occur. The researchers, led by Dr. Luis Eduardo Juarez-Orozco of the Turku PET Centre in Finland, trained a machine learning algorithm on a data set of nearly 1,000 patients. The data, which spanned six years for each patient, included dozens of variables that the computer had to digest in order to draw correlations between instances of death and heart attack with data on various heart and blood flow readings.