Services such as Google TV and Amazon's Fire TV have recommendation systems, as well as search functions, that may prioritise some content over others. Services such as Google TV and Amazon's Fire TV have recommendation systems, as well as search functions, that may prioritise some content over others. World's broadcasters urge EU to tighten rules for big tech in smart TV battle The world's largest broadcasters have pushed for the EU to enforce its toughest regulations against virtual TVs and smart assistants built by Google, Amazon, Apple and Samsung . The call came in a letter from the Association of Commercial Television and Video on Demand Services in Europe (ACT), whose members include Canal+, RTL, Mediaset, ITV, Paramount+, NBCUniversal, Walt Disney, Warner Bros Discovery, Sky and TF1 Groupe. The letter argues that big tech companies have growing control over the operating systems of smart TVs and voice assistants, allowing them to act as "gatekeepers" funnelling users towards some content and away from others.

Interpreting object-referential language and grounding objects in 3D with spatial relations and attributes is essential for robots operating alongside humans. However, this task is often challenging due to the diversity of scenes, large number of fine-grained objects, and complex free-form nature of language references. Furthermore, in the 3D domain, obtaining large amounts of natural language training data is difficult. Thus, it is important for methods to learn from little data and zero-shot generalize to new environments. To address these challenges, we propose SORT3D, an approach that utilizes rich object attributes from 2D data and merges a heuristics-based spatial reasoning toolbox with the ability of large language models (LLMs) to perform sequential reasoning. Importantly, our method does not require text-to-3D data for training and can be applied zero-shot to unseen environments. We show that SORT3D achieves state-of-the-art zero-shot performance on complex view-dependent grounding tasks on two benchmarks. We also implement the pipeline to run real-time on two autonomous vehicles and demonstrate that our approach can be used for object-goal navigation on previously unseen real-world environments. All source code for the system pipeline is publicly released at https://github.com/nzantout/SORT3D.

Netflix has started testing a new search feature powered by OpenAI that can help customers find movies and shows to watch, according to Bloomberg. The streaming service has reportedly given select users in Australia and New Zealand the option to use the tool. It will allow users to search for terms other than a specific show's title, an actor's name or the genre they want to watch. Bloomberg says it will give them a way to search for content using more specific terms, like their mood. Presumably, that means the service can surface dramatic shows for a search query that says "sad," and seeing as it's powered by generative AI, users will most likely be able to use natural language in their search terms.

These tools apply basic strategies that work well for random problems but miss critical patterns in structured instances. SAT encodings of real problems contain inherited patterns from graph layouts, data connections, and domain-specific rules. The transformation to Conjunctive Normal Form (CNF) obscures these patterns. Current local search methods skip these structures in favor of general approaches. This paper addresses these limitations by introducing a framework that leverages LLMs to generate local search strategies tailored to encoding structures, enabling solvers to take advantage of these patterns for improved performance. Our research addresses three questions: 1. How can LLMs analyze PySAT [Ignatiev et al., 2024] code to interpret how problem structure translates to SAT clauses? 2. How can we create local search strategies that recognize and exploit these encoding patterns?

For nearly two years, the world's biggest tech companies have said that AI will transform the web, your life, and the world. But first, they are remaking the humble search engine. Chatbots and search, in theory, are a perfect match. A standard Google search interprets a query and pulls up relevant results; tech companies have spent tens or hundreds of millions of dollars engineering chatbots that interpret human inputs, synthesize information, and provide fluent, useful responses. No more keyword refining or scouring Wikipedia--ChatGPT will do it all.

Google Photos has a decent search experience right now. I was recently trying to find some photos of my sister's engagement from a few years ago, and a simple "yellow dress" with her name added in front brought all the images to my fingertips within moments. But Google thinks it can do even better and is now supercharging the search function with improvements to natural language processing and, you guessed it, artificial intelligence. Improving the search experience is crucial because our online photo libraries are getting bigger and bigger every year. That means it's harder to find those photos from Dad's 60th birthday without sifting through so much other stuff.

Kara Frederick, tech director at the Heritage Foundation, discusses the need for regulations on artificial intelligence as lawmakers and tech titans discuss the potential risks. The way people search for information online could soon be changing as artificial intelligence continues to advance, and with it a new company could dethrone what has long been the king of online searching. "It's certainly conceivable that AI could ultimately replace search, especially if AI can learn what its user wants and deliver more relevant responses," Jon Schweppe, the Policy Director of the American Principles Project, told Fox News Digital while cautioning that there are still a lot of unknowns with the technology. "We are in the nascent stages of the AI revolution and it's still not clear that these companies know how to monetize it." The comments come as new search product called Perplexity has quickly become one of the most talked about platforms in technology, with an AI-driven search function that rivals or even bests traditional search platforms such as Google and Bing, according to a report from the New York Times.

When Walmart announced it would be holding a CES keynote for the first time, we were admittedly a little skeptical. Now it all makes sense, though: America's largest retailer came to CES 2024 in Las Vegas to talk about AI. In a joint announcement on Tuesday, the company said that it's teaming up with Microsoft to build what it bills as AI-powered shopping experiences. In his keynote, Walmart CEO Doug McMillon described how the integration of AI across its website and apps will be used to study shopper behavior and suggest future purchases. As you might expect, given Microsoft's involvement, the artificial intelligence underpinning these experiences will be powered by large language models made available through this partnership with Microsoft.

How often do you turn to Google? If you're focused on privacy, there are better options. Tap or click for alternatives to Google that work well without gathering so much of your data. Tap or click for reasons you should ditch Dr. Google. When it comes to finding what you want, some tricks make the job easy.

The CyberGuy Kurt Knutsson presents tech toys that could be great gifts for children this holiday season. How often do you turn to Google? If you're focused on privacy, there are better options. Tap or click for alternatives to Google that work well without gathering so much of your data. Tap or click for reasons you should ditch Dr. Google.