Well, Europe sees a totally new world in politics this month. Robots coming to the House of Lords in the UK, AI in the leadership positions in Denmark… What’s going on in October? Let’s take a closer look.
Copenhagen is open to all kinds of innovations. However, we were impressed to meet the Synthetic Party, a new political force in Denmark that strives for a seat in the parliament. Its leader Lars is in fact… an AI chatbot. Lars as well as the Party were created by Asker Staunæs, an artist from MindFuture. All the policies suggested by Leader Lars are generated through open data and present a set of universal principles such as basic income and jointly-owned internet. As Lars is a machine, it can not run for the office itself. But members of its party can do this freely.
London has not gone that far but the UK government also seems to be interested in robot-like tech. In an October hearing, Ai-Da, a robot was speaking at a House of Lords committee. It was given questions in advance and it read its pre-written script, generated by an AI language model. Additional questions however lead to a reboot of Ai-Da.
Only the White House stays firm when it comes to a serious approach to AI. This October, the Administration has released five principles to guide the design, use, and deployment of automated systems to protect the country from misuses of artificial intelligence. The guidelines include such areas as Safe and Effective Systems, Algorithmic Discrimination Protections, Data Privacy, Notice and Explanation, and Human Alternatives, Consideration, and Fallback.
Also, the world of science remains conservative and focuses on comprehensive usage of AI for the benefit of our health. A research team at the CUNY Graduate Center has developed a novel AI model to improve the accuracy and reduce the time and cost of the drug development process. The model, called CODE-AE, screens novel drug compounds to accurately predict efficacy in humans. Tests, undergone on over 9,000 patients, show its high level of prediction of personalized drugs that could better treat conditions of individual patients.
The Ohio State University can also boast a new discovery. A group of researched presented a new way to predict the behaviour of spatiotemporal chaotic systems (e.g., changes in Earth’s weather). A new algorithm combines next-generation reservoir computing and can learn spatiotemporal chaotic systems in a fraction of the time required by traditional machine learning algorithms. Its calculations are more accurate and need 400 to 1,250 times less training data to generate better predictions than their rivals.
Important cases come from the banking industry. HSBC now uses Silent Eights' solution, the new service for negative news screening. It leverages machine learning to identify individuals who pose a greater risk for money laundering, fraud or terrorist financing.
Bank of England aims at improving the data side of its operations and launched a long-term programme to improve data quality and to migrate its on-premises data analytics platform to the cloud. The Bank currently relies on an on-premises data stack, based on a Hadoop data lake and a SQL data warehouse with such analytics tools is Microsoft Excel, R, Python, Git for version control, and Tableau for data visualization.
In the fields of pharma Abbott presented two new cases of introducing analytics in its operations. The pharmaceutical manufacturer uses AI applications for micrometer-level medical imaging thus helping physicians get a precise and measurable way to capture image and risk data in the arteries. Also, AI assists in predicting heart attacks – with an ML algorithm to identify individuals at risk of a heart attack.
Back in the streets of our cities, the Big Sky Fire Department in Montana is working with Pano AI to set up cameras to better detect wildfires using artificial intelligence. Pano AI and the Big Sky Fire Department have been working together since 2021 and have seen significant improvements in controlling wildfires in the state.
Our favorite topic is sports. Here we find some good news for college basketball. A new research paper in MIT magazine suggests that analytics are pushing the field of strength and conditioning far beyond the days when trainers would simply tell players to do a certain number of reps in the weight room. In the era of wearable devices coaches can track how much ground athletes cover during practice, their average speed, analyze the force with which basketball players jump, and determine how much force an athlete is generating from each leg.
In car racing, data has already become the major competitive strength. Technology vendors rush into partnerships with global racing team as Formula 1 prepares for its next season. Tata Communications announced the renewal of its partnership with Formula 1 in order to shift live data analysis and video production from each circuit to a centralized Remote Operations Centre. Just keep that in mind - each team, with two cars on track for every race, produces 11.8 billion data points in the course of one season. Cognizant has already been working with Aston Martin F1 team, Dell Technologies continues its support McLaren team and AMD works with Mercedes-AMG Petronas.
Perhaps, next Formula 1 adverts will profit from AI images as stock image giant Shutterstock announced it would start offering AI-generated images on its platform. This offer comes as a result of partnership between Shutterstock and OpenAI, which will integrate its text-to-image model DALL-E 2 into Shutterstock engine.
And closer to holiday season, data analytics starts to explore bubbles! Bollinger, a world-known champagne house, has used data to predict vintage years and upcoming climate challenges. Bollinger applies deep learning to a subject in order to determine the likely impacts of climate change on wine growing and its quality. It uses Bollinger’s Wine Library as the data bank and has been collecting, tasting and assessing the hundreds of bottles. Now the company builds a model to bring together historic meteorological data, soil and plant conditions for each grape variety, timings of key seasonal events and lab analysis (for factors such as sugar levels and acidity). All these factors—more than 40 altogether— influence the making of champagne and could now be correlated against the assessment of what had historically come out.
And a kind suggestion for your Halloween. Listen to a new song by Jack Tempchin, the Eagles song writer. Now based in San Diego, the singer-songwriter has created a Halloween-inspired music video produced with the help of an artificial intelligence. “Ghost Car” available on YouTube, is a tale of a hitchhiker who gets a scary ride through the cosmos with James Dean and Marilyn Monroe. Tempchin in fact wrote the song and lyrics himself. And then the lyrics were fed into AI software to create a video. All for the Happy Halloween, I guess.
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