Premium automotive manufacturers face increasingly complex forecasting challenges due to high product variety, sparse variant-level data, and volatile market dynamics. This study addresses monthly automobile demand forecasting across a multi-product, multi-market, and multi-level hierarchy using data from a German premium manufacturer. The methodology combines point and probabilistic forecasts across strategic and operational planning levels, leveraging ensembles of LightGBM models with pooled training sets, quantile regression, and a mixed-integer linear programming reconciliation approach. Results highlight that spatiotemporal dependencies, as well as rounding bias, significantly affect forecast accuracy, underscoring the importance of integer forecasts for operational feasibility. Shapley analysis shows that short-term demand is reactive, shaped by life cycle maturity, autoregressive momentum, and operational signals, whereas medium-term demand reflects anticipatory drivers such as online engagement, planning targets, and competitive indicators, with online behavioral data considerably improving accuracy at disaggregated levels.

Analyzing stocks and making higher accurate predictions on where the price is heading continues to become more and more challenging therefore, we designed a new financial algorithm that leverages social media sentiment analysis to enhance the prediction of key stock earnings and associated volatility. Our model integrates sentiment analysis and data retrieval techniques to extract critical information from social media, analyze company financials, and compare sentiments between Wall Street and the general public. This approach aims to provide investors with timely data to execute trades based on key events, rather than relying on long-term stock holding strategies. The stock market is characterized by rapid data flow and fluctuating community sentiments, which can significantly impact trading outcomes. Stock forecasting is complex given its stochastic dynamic. Standard traditional prediction methods often overlook key events and media engagement, focusing its practice into long-term investment options. Our research seeks to change the stochastic dynamic to a more predictable environment by examining the impact of media on stock volatility, understanding and identifying sentiment differences between Wall Street and retail investors, and evaluating the impact of various media networks in predicting earning reports.

As companies such as Alphabet (GOOG, GOOGL) and Microsoft (MSFT) tussle to make the best artificial intelligence technology, one expert questioned whether they are going about it in the right way. "Alan Turing famously proposed that the test for intelligence, what we later called the Turing Test, was'how similar can an AI be to a human?' Trying to mimic humans has been kind of a goal of a lot of computer scientists ever since," Stanford Digital Economy Lab Director Erik Brynjolfsson said on Yahoo Finance Live (video above). "Can we fool humans so you can't tell the difference?" he continued. "I think it's a very evocative goal, but it's also a trap. The reason it's a trap is that if we make AI that mimics humans, it actually destroys the value of human labor and it leads to more concentration of wealth and power."

Microsoft (MSFT) on Tuesday unveiled what could be the biggest threat to Google's (GOOG, GOOGL) search empire in years with the release of its new Bing search engine powered by OpenAI's ChatGPT technology. It's a new paradigm for search," Microsoft CEO Satya Nadella said during an unveiling event held at Microsoft's Redmond, Washington campus. "Rapid innovation is going to come. A race starts today in terms of what you can expect. We are going to move fast." But Google controls 93% of the marketplace compared to Bing's 3%. So why bother starting a war? Simple: Microsoft wants a larger slice of the $570 billion digital advertising market. In 2022, the company saw $18 billion in ad revenue through search and LinkedIn. Google, meanwhile, pulled in $59 billion in Q4 alone. To that end, Microsoft has outfitted Bing with generative AI powered by a more advanced version of OpenAI's popular ChatGPT chat bot. One example of how this comes into practical use is by searching for whether a new LG ...

Though others have interviewed ChatGPT, I had some anxiety-riddled questions of my own: Will you take my job? Is the singularity upon us? These questions are half facetious, half serious. If you've been hidden away and somehow missed the ruckus, here's what all the commotion's about: In November, conversational AI tool ChatGPT took the world by storm, crossing one million users a mere five days after its release, according to its developer, San Francisco's OpenAI. If you are still one of those who think this is all hype, take it up with Microsoft (MSFT).

Generative AI, like OpenAI's ChatGPT, could completely revamp how digital content is developed, said Nina Schick, adviser, speaker, and A.I. thought leader told Yahoo Finance Live (video above). "I think we might reach 90% of online content generated by AI by 2025, so this technology is exponential," she said. "I believe that the majority of digital content is going to start to be produced by AI. You see ChatGPT... but there are a whole plethora of other platforms and applications that are coming up." The surge of interest in OpenAI's DALL-E and ChatGPT has facilitated a wide-ranging public discussion about AI and its expanding role in our world, particularly generative AI. "ChatGPT has really captured the public imagination in an extremely compelling way, but I think in a few months' time, ChatGPT is just going to be seen as another tool powered by this new form of AI, known as generative AI," she said.

For me, autonomous vehicles inspire profound fascination and deep fear. I'm fascinated by their prospects for the future--their inevitability. I also constantly wonder: how can we make this mode of travel safe? How's it possible a self-driving car could ever be safe? At CES 2023, I started to get some answers.

The viral success of OpenAI's ChatGPT has triggered discussions everywhere these days from the classroom to the boardroom. This amounts to a crucial moment for AI, Alice Xiang, Head of Sony Group's (SONY) AI Ethics Office and AI Lead Research Scientist, told Yahoo Finance Live (video above). "We're really seeing an inflection point with AI ethics, where it's going from being just something that companies are doing on their own… [and now] we're seeing policymakers really dive into this space." Xiang added: "This raises a lot of really interesting questions around how we ensure that we have governance processes in place to make sure AI that's built is compliant with relevant laws." As consumers encounter AI more frequently, and with excitement and fear, regulators are taking notice.

The artificial intelligence sector is thriving across the globe.

Vivek Astvansh explains how ChatGPT works and believes ChatGPT has the potential to replace human beings whose job is to refer to volumes of information contained on the internet, in textbooks, or in memory, and produce information based on that available content. Astvansh is an Assistant Professor in the Department of Marketing at the Kelley School of Business at Indiana University and an Adjunct Professor of Data Science at the Luddy School of Informatics, Computing, and Engineering at Indiana University. Don't Miss: Valley of Hype: The culture that built Elizabeth Holmes WATCH HERE: About Yahoo Finance: At Yahoo Finance, you get free stock quotes, up-to-date news, portfolio management resources, international market data, social interaction and mortgage rates that help you manage your financial life. Yahoo Finance Plus: With a subscription to Yahoo Finance Plus get the tools you need to invest with confidence. Discover new opportunities with expert research and investment ideas backed by technical and fundamental analysis.