The Posha and the Thermomix TM7 are the closest things to a home robot chef that mere mortals can afford. The catch is that you're the prep cook. The holiday is still almost a week away, and I'm sick of Thanksgiving. I've already made four rounds of mashed potatoes, three of mac and cheese, and three turkeys (with more still waiting in my fridge) as part of testing smart probes to help smoke turkeys outside and preparing seven-course holiday meal kits for friends and family. I was eager to finally outsource some of the cooking by testing two very different robo-chef devices, the Thermomix TM7 and the Posha kitchen robot . Both promise to plan my meals and also do most of the cooking, which sounds pretty good to me. The Thermomix descends from a German device launched in 1968--a time when the best-known robot chef was cartoon Rosie on --that was essentially a blender with a heater. It's since caught on big in countries from Italy to Portugal to Australia, and over the years it's added multi-tier steaming, baking, proofing, a touchscreen, an encyclopedic recipe app, and a whole lot of smart features.

Ukraine's president has urged the European Union to back a plan to release billions of euros in frozen Russian cash to help fund the country's defence. As EU leaders met in Brussels, Volodymyr Zelensky said he hoped they would make a positive decision about using €140bn (£122bn) in Russian assets currently held in a Belgian clearing house. The controversial move would would be on top of sanctions the block has imposed on Russia - the latest on Thursday targeting the Kremlin's oil revenues. They followed US measures against Russia's oil industry earlier - the first time President Donald Trump has sanctioned Moscow as he grows frustrated over President Vladimir Putin's refusal to end the war. On Wednesday evening, the US president confirmed that a planned meeting with Putin in Budapest had been shelved indefinitely.

One of Chantal Akerman's Best Films Is in Legal Limbo The Belgian-born director's 1994 coming-of-age masterwork, about a precocious teen-ager's romantic audacity, can't be reissued because of its needle drops. Much of direction is production: the material conditions under which a movie is made plays a major role in the creative process. Movie lovers tend to think of producers as dictators of formulas, oppressors of originality, the enemies of art, but that just reflects the unfortunate history of studio filmmaking in Hollywood and elsewhere. In fact, producing a movie can be a kind of art in itself, a practical imagining of possibilities for filmmakers that they wouldn't themselves have come up with. The complete retrospective of Chantal Akerman's work that runs at from September 11th to October 16th includes a superb instance of this phenomenon--of visionary production fostering directorial artistry--in her "Portrait of a Young Girl at the End of the 60s in Brussels," an hour-long movie from 1994.

We address in this article the the quality of the WikiNER corpus, a multilingual Named Entity Recognition corpus, and provide a consolidated version of it. The annotation of WikiNER was produced in a semi-supervised manner i.e. no manual verification has been carried out a posteriori. Such corpus is called silver-standard. In this paper we propose WikiNER-fr-gold which is a revised version of the French proportion of WikiNER. Our corpus consists of randomly sampled 20% of the original French sub-corpus (26,818 sentences with 700k tokens). We start by summarizing the entity types included in each category in order to define an annotation guideline, and then we proceed to revise the corpus. Finally we present an analysis of errors and inconsistency observed in the WikiNER-fr corpus, and we discuss potential future work directions.

Light goods vehicles (LGV) used extensively in the last mile of delivery are one of the leading polluters in cities. Cargo-bike logistics and Light Electric Vehicles (LEVs) have been put forward as a high impact candidate for replacing LGVs. Studies have estimated over half of urban van deliveries being replaceable by cargo-bikes, due to their faster speeds, shorter parking times and more efficient routes across cities. However, the logistics sector suffers from a lack of publicly available data, particularly pertaining to cargo-bike deliveries, thus limiting the understanding of their potential benefits. Specifically, service time (which includes cruising for parking, and walking to destination) is a major, but often overlooked component of delivery time modelling. The aim of this study is to establish a framework for measuring the performance of delivery vehicles, with an initial focus on modelling service times of vans and cargo-bikes across diverse urban environments. We introduce two datasets that allow for in-depth analysis and modelling of service times of cargo bikes and use existing datasets to reason about differences in delivery performance across vehicle types. We introduce a modelling framework to predict the service times of deliveries based on urban context. We employ Uber's H3 index to divide cities into hexagonal cells and aggregate OpenStreetMap tags for each cell, providing a detailed assessment of urban context. Leveraging this spatial grid, we use GeoVex to represent micro-regions as points in a continuous vector space, which then serve as input for predicting vehicle service times. We show that geospatial embeddings can effectively capture urban contexts and facilitate generalizations to new contexts and cities. Our methodology addresses the challenge of limited comparative data available for different vehicle types within the same urban settings.

The European Commission is pressing the accelerator on investment in weapons and defense technologies. From a total 590 million invested between 2017 and 2020, Brussels has moved to a 7.3 billion ( 7.9 billion) package for the 2021 to 2027 period. This year alone, the European Defense Fund (EDF) has put 1.1 billion on the plate, divided into 34 calls for as many military-related research topics. From developing new drone models to sensors to increase radar capabilities. From systems to counter hypersonic missile attacks to enhancements in the analysis of images collected by satellites. From "smart weapons" to advanced communication technologies.

Mark Zuckerberg's Meta will not release an advanced version of its artificial intelligence model in the EU, blaming the decision on the "unpredictable" behaviour of regulators. The owner of Facebook, Instagram and WhatsApp is preparing to issue its Llama model in multimodal form, meaning it is able to work across text, video, images and audio instead of just one format. Llama is an open source model, allowing it to be freely downloaded and adapted by users. However, a Meta spokesperson confirmed the model would not be available in the EU. "We will release a multimodal Llama model over the coming months – but not in the EU due to the unpredictable nature of the European regulatory environment," the spokesperson said.

Apple has become the first big tech company to be charged with breaking the European Union's new digital markets rules, three days after the tech giant said it would not release artificial intelligence in the bloc due to regulation. On Monday, the European Commission said that Apple's App Store was preventing developers from communicating with their users and promoting offers to them directly, a practice known as anti-steering. "Our preliminary position is that Apple does not fully allow steering. Steering is key to ensure that app developers are less dependent on gatekeepers' app stores and for consumers to be aware of better offers," Margrethe Vestager, the EU's competition chief said in a statement. On X, the European commissioner for the internal market, Thierry Breton, gave a more damning assessment.

This story originally appeared in WIRED Italia and has been translated from Italian. The latest in a series of duels announced by the European Commission is with Bing, Microsoft's search engine. Brussels suspects that the giant based in Redmond, Washington, has failed to properly moderate content produced by the generative AI systems on Bing, Copilot, and Image Creator, and that as a result, it may have violated the Digital Services Act (DSA), one of Europe's latest digital regulations. On May 17, the EU summit requested company documents to understand how Microsoft handled the spread of hallucinations (inaccurate or nonsensical answers produced by AI), deepfakes, and attempts to improperly influence the upcoming European Parliament elections. At the beginning of June, voters in the 27 states of the European Union will choose their representatives to the European Parliament, in a campaign over which looms the ominous shadow of technology with its potential to manipulate the outcome. The commission has given Microsoft until May 27 to respond, only days before voters go to the polls.

AI-generated deepfake pictures, video or audio of existing people, places or events must be labeled as artificially manipulated. There's extra scrutiny for the biggest and most powerful AI models that pose "systemic risks," which include OpenAI's GPT4 -- its most advanced system -- and Google's Gemini. The EU says it's worried that these powerful AI systems could "cause serious accidents or be misused for far-reaching cyberattacks." They also fear generative AI could spread "harmful biases" across many applications, affecting many people. Companies that provide these systems will have to assess and mitigate the risks; report any serious incidents, such as malfunctions that cause someone's death or serious harm to health or property; put cybersecurity measures in place; and disclose how much energy their models use. Brussels first suggested AI regulations in 2019, taking a familiar global role in ratcheting up scrutiny of emerging industries, while other governments scramble to keep up. In the U.S., President Joe Biden signed a sweeping executive order on AI in October that's expected to be backed up by legislation and global agreements. In the meantime, lawmakers in at least seven U.S. states are working on their own AI legislation.