Plug-in hybrids are supposed to be the best of both worlds--the convenience of a gas-powered car with the climate benefits of a battery electric vehicle. But new data suggests that some official figures severely underestimate the emissions they produce. According to new real-world driving data from Europe, plug-in hybrids produce roughly 3.5 times the emissions official estimates suggest. The difference is largely linked to driver habits: people tend to charge plug-in hybrids and drive them in electric mode less than expected. It's important to close the gap between expectations and reality not only for individuals' sake, but also to ensure that policies aimed at cutting emissions have the intended effects.

Now the think tank behind the report has published an updated analysis, showing how the makeup of global AI talent has changed since--during a critical period when the industry has shifted significantly and become the hottest technology sector. The team at MacroPolo, a think tank that focuses on US-China relations, studied the national origin, educational background, and current work affiliation of top researchers who gave presentations and had papers accepted at NeurIPS, a top academic conference on AI. Their analysis of the 2019 conference resulted in the first iteration of the Global AI Talent Tracker. They've analyzed the December 2022 NeurIPS conference for an update three years later. I recommend you read the original report, which has a very well-designed infographic that shows the talent flow across countries.

Bengaluru features in the top five cities on Harvard Business review where diversity is high in the AI sector. Diversity and inclusive pool of talent developing AI matters to the reviewers as AI developers are influenced by their own world views, which, in turn, guide them in their selection of applications, datasets, and training of algorithms. The data from the Fletcher school, Tufts university is derived and pitted against indicators such as talent pool, investments, diversity of talent, evolution of the country's digital foundations or TIDE. The reviewers believe that the factors collectively give companies a way to prioritise their AI talent sourcing choices by scoring the different locations on the concentration, quality and diversity of the AI talent pool. Top four cities are San Francisco, New York, Boston and Seattle respectively.

Artificial intelligence (AI) has crossed a threshold. "In the past five years, AI has made the leap from something that mostly happens in research labs or other highly controlled settings to something that's out in society affecting people's lives," says Michael Littman, chair of the One Hundred Year Study on Artificial Intelligence, hosted at Stanford. It's easy to see what he's talking about: The technology's impact can be seen introducing automation, driving efficiency gains and enhancing productivity, creating new jobs, and reducing risks associated with cyber-threats and fraud. During the pandemic, AI enabled more effective testing for Covid-19 and faster vaccine development, and helped manage grocery supply chains and tailor lessons for individual students affected by remote schooling. As AI expands into more and more facets of our lives, there is also more scrutiny on who's developing it.

The number of artificial intelligence (AI) researchers in Canada's private sector is proportionally higher than that of other countries, according to Montreal-based Element AI's 2020 Global AI Talent Report. The report found that Canada has 367 AI researchers, making it second only to the US. The Global AI Talent Report measured the size of the available talent pool in the AI industry through self-reported data on social media and demand via the monthly total job postings for the same role up to August 2020. The goal of the report is to assess the most current global patterns for the worldwide AI talent pool. The report tracked 477,956 people worldwide working in the AI industry, of which 61 percent worked in productization, 38 percent in engineering, and a mere one percent in research.

As roles and tasks shift in tandem with the expansion of new technologies, and the division of work between human and machine is redrawn, it is of critical importance to monitor how those changes will impact the evolution of economic gender gaps. Artificial Intelligence (AI) is a prominent driver of change within the transformations brought about by the Fourth Industrial Revolution (4IR), and can serve as key marker of the trajectory of innovation across industries.19 In partnership with the LinkedIn Economic Graph Team, the World Economic Forum aims to provide fresh evidence of the emerging contours of gender parity in the new world of work through near-term labour market information. The increasing expansion of AI is creating the demand for a range of new skills, among them neural networks, deep learning, machine learning, and "tools" such as Weka and Scikit-Learn. AI skills are among the fastest-growing specializations among professionals represented on the LinkedIn platform.

If you've ever used the Internet to transfer money between accounts or apply for a bank loan or trade, you're probably aware of how deeply rooted fintech has become in our day-to-day lives. In 2018, about 61% of Americans used digital banking services and this number is set to exceed 65% in 2022. One of the newly-emerged traits of the 4th Industrial Era, fintech is an application of fast-evolving digital technologies to improve and facilitate financial services. Companies are rapidly adopting fintech to keep abreast of the competition. The investments into this industry are also impressive: in 2018, it attracted over $16 billion investment in the UK alone, according to KMPG.

In the emergent war to have the best artificial intelligence capability, academia might have the most casualties. According to the National Science Foundation, 57 percent of new computer-science doctoral graduates in the United States take industry jobs, meaning they leave academia for the private sector. This is compared to 38 percent a decade ago, according to The Wall Street Journal. Given that academia is the primary breeding ground for skills in emerging fields like AI, what would a constant academic exodus of talent in the field mean for the future development of its talent pool? One of the biggest concerns is that there will be fewer graduates with a thorough education in AI. "The number of graduating master's and Ph.D.-level computer scientists may decrease, which is the opposite to what the current market is demanding," said Peter Morgan, chief AI officer at Ivy Data Science, an AI-as-a-service platform and training company based in New York City.

In the emergent war to have the best artificial intelligence capability, academia might have the most casualties. According to the National Science Foundation, 57 percent of new computer-science doctoral graduates in the United States take industry jobs, meaning they leave academia for the private sector. This is compared to 38 percent a decade ago, according to The Wall Street Journal. Given that academia is the primary breeding ground for skills in emerging fields like AI, what would a constant academic exodus of talent in the field mean for the future development of its talent pool? One of the biggest concerns is that there will be fewer graduates with a thorough education in AI. "The number of graduating master's and Ph.D.-level computer scientists may decrease, which is the opposite to what the current market is demanding," said Peter Morgan, chief AI officer at Ivy Data Science, an AI-as-a-service platform and training company based in New York City.