Taxonomy inference for tabular data is a critical task of schema inference, aiming at discovering entity types (i.e., concepts) of the tables and building their hierarchy. It can play an important role in data management, data exploration, ontology learning, and many data-centric applications. Existing schema inference systems focus more on XML, JSON or RDF data, and often rely on lexical formats and structures of the data for calculating similarities, with limited exploitation of the semantics of the text across a table. Motivated by recent works on taxonomy completion and construction using Large Language Models (LLMs), this paper presents two LLM-based methods for taxonomy inference for tables: (i) EmTT which em beds columns by fine-tuning with contrastive learning encoder-alone LLMs like BERT and utilises clustering for hierarchy construction, and (ii) GeTT which ge nerates table entity types and their hierarchy by iterative prompting using a decoder-alone LLM like GPT-4. Extensive evaluation on three real-world datasets with six metrics covering different aspects of the output taxonomies has demonstrated that EmTT and GeTT can both produce taxonomies with strong consistency relative to the Ground Truth.

Sometimes it's not just the data you have that makes a difference for your mobile app or game business. It's also about how you look at it, according to digital marketing agency YellowHead. YellowHead has specialized in app store optimization (ASO), or obtaining mobile users by optimizing an app for the way it can be discovered in an app store. As the cost of user acquisition soars, mobile game and app developers need alternatives. With app store optimization, developers make sure that their keywords, descriptions, icons, and metadata make their app easily discoverable amid a sea of a few million apps.

By any measure, Uber is off to a terrible start in 2017. A plaintive account of Uber's misogynistic culture by an ex-employee went viral, unleashing a flood or corroborating stories. Travis Kalanick, the embattled CEO, was further shamed by the release of a video displaying boorish behavior in his encounter with an Uber driver. This was followed by disclosures of Uber's use of defeat software to evade regulatory agency monitoring, by damaging pre-trial motions in an IP theft lawsuit that puts Uber's self-driving vehicle program at risk, by revelations of inadequacies in Uber's driver screening procedures, and by the disclosure that Uber was secretly spying on its own and Lyft drivers for competitive advantage. Adding to these tumultuous challenges, a number of Uber senior executives, including President Jeff Jones and corporate communications head Rachel Whetstone, have opted or been asked to resign in the past month.

From stopping cyberattacks to operating autonomous vehicles to visually searching through a wine database, 140 startups using AI as a core part of their products raised $1.05B in funding in Q3'16. Since 2012, deals and dollars to AI startups have been on a rise, and this year is extending that trend. Our AI category includes companies applying AI solutions to verticals like healthcare, security, advertising, and finance as well as those developing general-purpose AI tech. Our list excludes robotics (hardware-focused) and AR/VR startups, which we've analyzed separately here and here. Our analysis includes all equity funding rounds and convertible notes.

At the start of December, Stephen Hawking issued a stark warning: Automation and AI are going to destroy middle-class jobs, risking massive political upheaval. "The automation of factories has already decimated jobs in traditional manufacturing," the famed physicist wrote, "and the rise of artificial intelligence is likely to extend this job destruction deep into the middle classes." It's an issue that Shahar Waiser knows about first-hand: In the coming years and decades, almost his entire workforce will become obsolete. The Russian-born entrepreneur is the CEO of Gett -- a taxi app used by thousands of cabbies in more than 100 cities around the world. And all of their jobs are at risk of being replaced by self-driving cars.

From stopping cyberattacks to operating autonomous vehicles to visually searching through a wine database, 140 startups using AI as a core part of their products raised $958M in funding in Q3'16, making it the second-highest quarter for funding after Q2'16. Since 2012, deals and dollars to AI startups have been on a steady rise, and this year is extending that trend. Our AI category includes companies applying AI solutions to verticals like healthcare, security, advertising, and finance as well as those developing general-purpose AI tech. Our list excludes robotics (hardware-focused) and AR/VR startups, which we've analyzed separately here and here. Our analysis includes all equity funding rounds and convertible notes.

Toyota and Volkswagen are the latest automakers to forge alliances with ride-hailing companies, deals that could see the car makers not only sell cars to drivers of the app companies but also develop jointly on-demand mobility technologies. On Wednesday, Toyota said it was making a strategic investment in Uber Technologies as part of a bigger partnership that would include leasing of its cars to Uber drivers. Car purchasers can lease their vehicles from Toyota Financial Services and cover their payments through earnings generated as Uber drivers, the Japanese car giant said in a statement. Toyota said it will also explore collaboration in a variety of other areas, such as developing in-car apps that support Uber drivers, sharing knowledge and accelerating research efforts. Uber already has an autonomous car project, though it isn't clear whether the collaboration between Toyota and Uber will include the development of these types of vehicles.

Carmakers Toyota and Volkswagen have struck separate partnerships with rideshare companies Uber and Gett. The Japanese company will invest an unspecified amount in Uber and offer new leasing options for its drivers. Toyota said the two companies would share also knowledge and speed up their research efforts in areas such as driverless cars. Volkswagen announced an investment in Gett, an Israel-based rideshare operator. Toyota said that as patterns of car usage continued to change, it wanted the collaboration to be about more than simply providing vehicles but to also collaborate on technology such as in-car apps.

People don't want cars, they want rides. And they're scrambling to do something about it. Just months after GM poured money into Lyft (the one with the pink mustasche), Toyota and Volkswagen both said today they were joining up with other ride-hailing rivals. Toyota, meanwhile, is partnering with Uber to, among other things, let people automatically deduct their car payments from the fares they make as Uber drivers. Clearly automakers have Silicon Valley envy.