Globally renowned brands would not, ordinarily, want to be associated with Germany's far-right opposition. But Tesla, one of the world's biggest corporate names, does not have a conventional chief executive. After Elon Musk backed Alternative für Deutschland (AfD) – calling the party Germany's "only hope" – voters are considering an alternative to Tesla. Data released on Thursday showed that registrations of the company's electric cars in Germany fell 76% to 1,429 last month. Overall, electric vehicle registrations rose by 31%.

The stock market is a crucial component of the financial system, but predicting the movement of stock prices is challenging due to the dynamic and intricate relations arising from various aspects such as economic indicators, financial reports, global news, and investor sentiment. Traditional sequential methods and graph-based models have been applied in stock movement prediction, but they have limitations in capturing the multifaceted and temporal influences in stock price movements. To address these challenges, the Multi-relational Dynamic Graph Neural Network (MDGNN) framework is proposed, which utilizes a discrete dynamic graph to comprehensively capture multifaceted relations among stocks and their evolution over time. The representation generated from the graph offers a complete perspective on the interrelationships among stocks and associated entities. Additionally, the power of the Transformer structure is leveraged to encode the temporal evolution of multiplex relations, providing a dynamic and effective approach to predicting stock investment. Further, our proposed MDGNN framework achieves the best performance in public datasets compared with state-of-the-art (SOTA) stock investment methods.

Global venture capital firms are pouring money into the semiconductor startups developing the next generation of chips. Semiconductors, which have become a valued asset, are used in virtually almost every industry, including 5G networks, automation, the Internet of Things, financials, smart homes, smart cities, virtual reality (VR), augmented reality and self-driving cars. Sunghyun Park, a former quant developer at Morgan Stanley in New York, launched artificial intelligence semiconductor startup Rebellions with four co-founders to enter this red-hot industry in 2020. Today, the South Korea-based company that builds chips designed for artificial intelligence applications, announced it has raised a $50 million (62 billion KRW) Series A from investors, including Temasek's Pavilion Capital, Korean Development Bank, SV Investment, Mirae Asset Capital, Mirae Asset Ventures, IMM Investment, KB Investment and KT Investment. Its existing backers Kakao Ventures, GU Equity Partners and Seoul Techno Holdings also participated in the round, Park told TechCrunch.

Electric vehicles are no longer the main way to compare carmakers, with self-driving cars now the main race over the coming years, according to JPMorgan. The investment bank reckons Daimler (ETR:DAI), Stellantis NV (NYSE:STLA, EPA:STLA), Renault and Volkswagen Group (XETRA:VOW) "will benefit the most from this trend" and they are its key picks among the traditional automotive original equipment manufacturers (OEMs), a group that also includes BMW, Ford Motor Company (NYSE:F), General Motors Company (NYSE:GM), Toyota, Mazda, Honda, Hyundai and Kia. "Electrification is no longer a differentiating factor amongst OEMs, in our view," the US investment bank said. "Rather, cash generation and the race into autonomous driving will be over the coming years," JPM said in a note to clients on Monday. Looking at the auto market in the past year, the analysts said it was becoming "increasingly evident" that the traditional OEMs are using their strong free cash flow to "speed their way into electrification and autonomous driving to compete against new start-ups".

Modern financial markets are extremely complex with hedge funders, investment banks and retail investors trading millions of stocks globally every second. By applying quantum technology to algorithmic trading, it would be possible to trigger share dealings based on market variables in a way that currently isn't possible with today's much slower computers. Smart cities, where everything from rubbish disposal to traffic flow can be controlled using IoT sensors alongside AI and machine learning technologies, are becoming more widespread. Working with Lisbon's transit system during the 2019 Web Summit, it used quantum computing to route buses efficiently through the city. Capable of analyzing large amounts of data simultaneously and at speed, quantum computers promise much greater levels of accuracy, particularly when it comes to providing predictions for smaller, more specific regions.

The middle and working classes have seen a steady decline in their fortunes. Sending jobs to foreign countries, the hollowing out of the manufacturing sector, pivoting toward a service economy and the weakening of unions have been blamed for the challenges faced by a majority of Americans. According to a new academic research study, automation technology has been the primary driver in U.S. income inequality over the past 40 years. The report, published by the National Bureau of Economic Research, claims that 50% to 70% of changes in U.S. wages, since 1980, can be attributed to wage declines among blue-collar workers who were replaced or degraded by automation. Artificial intelligence, robotics and new sophisticated technologies have caused a wide chasm in wealth and income inequality.

Frequently described as the world's most important number because it underpins trillions of dollars of transactions, the London interbank offered rate (Libor) has persisted until now despite a scandal that caused lasting reputational damage to the entire financial system. Libor is the key interest rate benchmark for mortgages, loans and contracts but it has been tainted since 2012 when it emerged that banks had misstated their Libor rate submissions, often in collusion, to make better returns. The controversy led to at least five traders going to jail in the UK, and US and UK regulators extracting penalties totalling about $10bn. Regulators want Libor phased out by December 31 2021, and banks are pivoting to alternative risk-free rates such as Sonia (sterling overnight interbank average rate). Its demise is already a headache for law firms and banking clients, which must examine hundreds of thousands of legal contracts containing references to the Libor rate and then rewrite and "repaper" them to ensure they include the new reference rates.

US investment bank JP Morgan has hired a machine learning expert to deploy the technology across its investable indices business, The TRADE has learnt. Fredrik Giertz has been appointed vice president in equity derivatives structuring at JP Morgan, having joined the bank last month in the newly-created role. A spokesperson at JP Morgan confirmed the appointment. Based within the investable index division at JP Morgan in London, Giertz will focus on growing and developing quantitative strategies that use machine learning techniques for the investment bank. He has several years' experience in managing quantitative strategies, from alternative risk to more advanced strategies using machine learning technology.

Individuals, businesses, and governments are unprepared for the coming wave of deepfake attacks by malicious cyber criminals. For the unaware, "deepfake" refers to artificial intelligence generated false media that pretends to be the authentic version of what it emulates. In English…it is fake pictures, videos, and audio of real people or the creation of fake people in the same mediums. Commanding several of the seven traditional patterns of artificial intelligence, deepfakes use algorithms that mimic voice, mannerisms, facial expressions, body language, and lip movements to look deceptively real; creating audio and video clips of events that never occurred. These images are spread on social media and in the news, as most viewers are totally unaware of the lack of authenticity.

As lawmakers in Brasilia debated a controversial pension overhaul for months, a robot more than 5,000 miles away in London kept a close eye on all 513 of them. The algorithm, designed by technology startup Arkera Inc., tracked their comments in Brazilian newspapers and government web pages each day to predict the likelihood the bill would pass. Weeks before the legislation cleared its biggest obstacle in July, the machine's data crunching allowed Arkera analysts to predict the result almost to the letter, giving hedge fund clients in New York and London the insight to buy the Brazilian real near eight-month lows in May. It's since rallied more than 8%. This is the kind of edge that a new generation of researchers are betting will upend the research marketplace.