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A deep learning technique to solve Rubik's cube and other problems step-by-step

#artificialintelligence

Colin G. Johnson, an associate professor at the University of Nottingham, recently developed a deep-learning technique that can learn a so-called "fitness function" from a set of sample solutions to a problem. This technique, presented in a paper published in Wiley's Expert Systems journal, was initially trained to solve the Rubik's cube, the popular 3-D combination puzzle invented by Hungarian sculptor Ernő Rubik. "The aim of our paper was to use machine learning to learn to solve the Rubik's cube," Colin G. Johnson, one of the researchers who carried out the study, told TechXplore. "Rubik's cube is a very complex puzzle, but any of the vast number of combinations is at most 20 steps from a solution. So the approach we take here is to try and solve the problem by learning to do each of those steps individually."


What Buddhism can do for AI ethics

#artificialintelligence

The explosive growth of artificial intelligence has fostered hope that it will help us solve many of the world's most intractable problems. However, there's also much concern about the power of AI, and growing agreement that its use should be guided to avoid infringing upon our rights. Many groups have discussed and proposed ethical guidelines for how AI should be developed or deployed: IEEE, a global professional organization for engineers, has issued a 280-page document on the subject (to which I contributed), and the European Union has published its own framework. The AI Ethics Guidelines Global Inventory has compiled more than 160 such guidelines from around the world. Unfortunately, most of these guidelines are developed by groups or organizations concentrated in North America and Europe: a survey published by social scientist Anna Jobin and her colleagues found 21 in the US, 19 in the EU, 13 in the UK, four in Japan, and one each from the United Arab Emirates, India, Singapore, and South Korea.


The strange bedfellows of AI and ethics

#artificialintelligence

Over the last decade, we have heard a lot of doom-saying about how artificial intelligence (AI) would result in the loss of huge numbers of jobs. However, the picture (across both public and private sectors) is now starting to look not only more nuanced but also more positive. A 2017 report from consultancy PWC suggested that embedding AI across all sectors is likely to create thousands of jobs. In the UK, one estimate suggests that it could contribute as much as 5% of GDP within 10 years. That's not to say that we won't lose jobs, because we undoubtedly will.


Machine Learning 'on the rocks' 🥃

#artificialintelligence

Apparently, the project's domain relies on the most popular liquor in the world -- Whiskey. A dark spirit coming from a great variety of grains, distilled throughout the world and arriving at quite a number of styles (Irish, Scotch, Bourbon etc) [1]. Scotland, Ireland, Canada & Japan are among the famous exporters and on an international scale, the global production almost reaches the level of $95m revenue [2]. The main scope, hereof, is to introduce in a… 'companionable' way, how helpful can the Clustering Algorithms prove to be, anytime we need to find patterns in a (large) dataset. Actually, it might be considered as a powerful expansion of the standard Exploratory Data Analysis (EDA), which is often very beneficial to try, before using Supervised Machine Learning (ML) models.


2021 will be the year of MLOps

#artificialintelligence

January is the customary time to make predictions on what the year holds in store. Working in partnership with companies across multiple industries that are looking to develop data science and AI skills in their workforce, I have a good vantage point on the trends that are developing across the realm of technology. In addition, I have published recent research with colleagues at Cambridge University about the challenges that face organizations with deploying machine learning. From this perspective, there is a clear picture forming that 2021 will be a turning point within leading businesses for making a priority of operationalizing AI. In fact, the second half of 2020 has seen a new crop of tools, platforms and startups receiving investment to provide solutions to this difficult problem.


Tinder sees massive rise in mentions of 'courting' and 'flirting' in bios

Mashable

Tinder has released data showing a dramatic rise in mentions of the words "courting" and "flirting" in dating app bios, spelling a return to good old fashioned wooing. According to Tinder, "courting" has been included in 81 percent more Tinder bios this year, compared to February 2020. Interestingly, that data pertains to users aged between 18 and 25, meaning Gen Z daters seem to be showing an interest in more traditional forms of romancing. The dating app thinks that the popularity of period dramas like Netflix's Bridgerton are the reason for this. The term "flirting" has also seen a massive increase in 2021, with 132 percent more mentions in bios than the previous year.


Cameras and sensors could help stop e-scooter riders crashing into pedestrians

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London (CNN Business)Electric scooter companies are turning to technology to try to reduce accidents and injuries among riders and pedestrians. The problem has become so severe that countries including Singapore, France and Spain have banned e-scooters on pedestrian walkways. A study of more than 100 riders surveyed at an emergency room in Washington, DC, found that nearly three in five were injured while riding on a sidewalk, even in places where it was prohibited. Swedish operator Voi -- which has more than 6 million registered scooter riders across 50 European cities -- has partnered with Dublin startup Luna to develop a system of cameras and sensors that can detect what surface a scooter is riding on, as well as the presence of nearby pedestrians. The technology works in real time.


Literature Should Be Taught Like Science - Issue 97: Wonder

Nautilus

In the past quarter century, enrollment in college English departments has sunk like the Pequod in Moby Dick. Meanwhile enrollment in science programs has skyrocketed. Elon Musk, not Herman Melville, is the role model of the digital economy. But it doesn't have to be that way, says Angus Fletcher, 44, an English professor at Ohio State University. Fletcher is part of "group of renegades," he says, who are on a mission to plug literature back into the electric heart of contemporary life and culture. Fletcher has a plan--"apply science and engineering to literature"--and a syllabus, Wonderworks: The 25 Most Powerful Inventions in the History of Literature, his new book. Before the England-born Fletcher got his Ph.D. in literature at Yale, he earned an undergraduate degree in neuroscience, followed by a four-year stint in a neurophysiology lab at the University of Michigan. He switched careers when he realized the biology of the brain wouldn't take him far enough toward understanding our need for stories. "What's special about the human brain is its power of storytelling," Fletcher says.


Facebook CTO says tech pessimism is 'founded on real concerns of the negative impacts of technology'

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Facebook's Chief Technology Officer Mike Schroepfer believes the pessimism surrounding technology in the world today is "founded on real concerns of the negative impacts of technology." In an interview on Tuesday with the president of the Oxford Union, the Oxford University debating society, Schroepfer said that in some cases "we haven't really always done the homework upfront" and thought about what a "bad actor" might do with a particular product before releasing it. A Facebook spokesperson told CNBC on Wednesday that he was talking about the tech industry as a whole as opposed to Facebook specifically. The social media giant has been widely criticized for a range issues including the spread of hate speech and misinformation, influencing elections, being addictive, and failing to keep children safe on its platform. "The thing that's often true of new technologies and advancements is they often have very clear, acute examples where things change or are disruptive," said Schroepfer. "It may be a loss of jobs or a new form of scammer abuse. It's something that's really easy to understand as'bad.' And then they have very generalized improvements in the quality of life. So if I say I've increased the GDP overall by 3%, I've made everyone slightly more prosperous, but it's harder to weigh against these very acute, specific harms."


Insurtech and Artificial Intelligence

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The rapid development of converging technologies is bringing about fundamental changes to the insurance industry. In the long term, organisations that are slow to embrace these new technologies will struggle to compete and to retain their place in the market. In the insurance sector, the use of technology to innovate or disrupt is known as'insurtech'. This is an elastic term that takes in the use of new technologies by both start-ups and incumbent insurance companies to transform access to and analysis of data, build new products, drive customer engagement and squeeze inefficiencies from the current insurance model. Technologies such as telematics, the internet of things including smart home technologies, aerial imagery and drone technologies are giving insurers new ways to access data while developments in artificial intelligence (AI), machine learning and natural language processing are enabling insurers to process, analyse and gain insights from these large data sources.