AI NewsJudge orders OpenAI to turn over hiring records in Apple trade secrets case

Judge orders OpenAI to turn over hiring records in Apple trade secrets case

3:15 AM IST · October 14, 2026

A judge has ruled that Apple will gain expedited access to OpenAI’s hiring materials in the trade secrets-focusedlawsuit the iPhone maker filedagainst OpenAI in July. Specifically, the court will allow Apple to view documents associated with OpenAI’s interviews with former Apple employees who applied for roles within its consumer hardware and robotics groups ahead of the rumored launch of OpenAI’s first hardware device. These documents could include interview checklists, guides, instructions, manuals, and scripts, as well as technical presentations and records showing that interview discussions had included references to Apple technology or components. The court gave OpenAI five days to turn over materials it has already collected and 14 days for any other materials related to this request, agreeing with Apple that these documents should be expedited. The case comes as OpenAI develops a consumer hardware device that could one day potentially rival the iPhone — or smartphones more generally — if the AI device becomes a central part of consumers’ lives and how they engage with software and services. In its lawsuit, AppleaccusedOpenAI of a pattern of theft, which includes direct complaints about former employees using Apple laptops to download confidential material and files that contained information about unannounced technologies, features, and products, including technical specifications, engineering presentations, and proprietary project data. Apple also said that former Apple employees at OpenAI coached others considering leaving Apple for OpenAI on what information to bring to their interviews, among other allegations. U.S. District Judge Edward Davila didn’t greenlight all of Apple’s requests for expedited access to OpenAI documents and messages relevant to the case. Buthe did rulethat Apple could access the interview materials, alongside private LINE messages (from a messaging app) between individuals named in the case, including OpenAI employees Chang Liu and Alyssa Peng. The judge also approved depositions for Liu and Peng, along with a third individual, OpenAI’s chief hardware officer, Tang Yew Tan. All three are former Apple employees. However, the judge denied Apple’s request to expedite its access to OpenAI’s research and development in specific areas, like metal finishes and power management. He also denied several of Apple’s broader discovery requests, like access to OpenAI’s hardware research or information about what its former employees created while working at OpenAI. That denial isn’t final, though; the judge left the door open for Apple to narrow its requests and try again.

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Facebook is giving users more control over their algorithm

Facebook is the latest social media platform to give usersgreater control over the algorithmthat determines what appears in their feeds. Metaannouncedthe launch of its new AI-powered feature, “Your Algorithm,” on Tuesday, a feature it first launched on Instagram. The new tool allows Facebook users to influence the content they see in Feed and Reels by describing their preferences in their own words using natural language. Rather than relying entirely on automated recommendations, users can now communicate directly with the platform about the topics and content they want to see more or less frequently. According to Meta, the feature is designed to make content recommendations more relevant. Users can adjust their preferences and interact with the algorithms responsible for ranking and recommending posts, with changes reflected in their recommendations in real time. The company has also updated Facebook’s three-dot menu, making it easier for users to manage their content preferences directly from individual posts. By opening the menu, users can access “Your Algorithm” or select the “Interested” and “Not interested” options to indicate whether particular content aligns with their preferences. Meta says the platform may ask follow-up questions to better understand what users liked or disliked, allowing them to provide more detailed feedback. Users can explain what they want to see more or less of, helping Facebook refine its recommendations based on their responses. The introduction of “Your Algorithm” reflects Meta’s broader effort to give people more influence over their social media experiences as AI increasingly shapes content discovery. The move signals a shift away from the traditional recommendation systems that have shaped social media experiences for years, bringing the platform closer to streaming services that allow users to personalize recommendations based on their interests and preferences. The launch also builds on Meta’s existing personalization efforts across its other platforms.Instagramintroduced Your Algorithm in June, extending customization options across Feed and Explore after first launching the feature for Reels in December 2025. Threadsalso introduced its own related feature, called “Dear Algo,” which allows users to influence the content recommended to them.

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Flox Intelligence is building AI to keep wildlife away from trains, airports, and roads

When I was eight, I remember our train to Mumbai ground to a halt with a great noise. When we started moving again, a good eight hours later, someone pointed out a mangled tail, of all things, hanging from a branch close to the tracks. The train, you see, had apparently hit a wild bison at full speed, and the impact damaged the engine so badly that it had to be towed away for repairs. For a long time, I thought such things only happened in places like rural India, but I learned a few years ago that wildlife and infrastructure do not mix anywhere on the planet. The FAAestimatesthat wildlife strikes have cost U.S. civil aviation about $272 million a year on average between 1990 and 2025. In France, the rail operator SNCFsayswandering animals affect more than 8,000 trains across the country each year and are among its five leading causes of delays. In Brittany, 120 trains hit animals in 2023 alone, disrupting 660 services and causing more than 15,000 minutes of delays. Reading about all that damage, to both infrastructure and animals, inspired Sara Nozkova (pictured above on the left) to develop a wildlife-deterrent system that works differently from the sirens, lights, fences, falcons, and culling traditionally used to keep animals away from roads, train tracks, airports, and other infrastructure. “I was convinced the answer was not a louder deterrent,” she told TechCrunch. After spending 13 years working in transportation and autonomous vehicles, Nozkova had learned how quickly the systems we build to navigate roads and other controlled environments fail once nature enters the equation. “We have taught machines to be brilliant, but only inside the environments we engineered for them,” she said. “Cities, factory lines, warehouses. Fixed geometry, known objects. Stepping outside into nature, I saw firsthand how the same machines quickly go blind. Because nature is complex and always alive.” So instead she joined the AI lab at KTH Royal Institute of Technology in Stockholm and started working on a system that could change its deterrent responses based on what an animal nearby is doing, and even what kind of animal it is. That work turned intoFlox Intelligence, which spun out of KTH in 2020 and is one of the finalists at this year’s Startup Battlefield 200 pitch competition atTechCrunch Disrupt, taking place this year at Moscone West in San Francisco October 13-15. Flox makes edge devices that process data on-site rather than in the cloud. Like autonomous vehicles, they use perception systems to sense their surroundings, but theirs are trained on wildlife behavior. A motion sensor wakes the device when it detects movement, triggering a camera that uses on-device models to identify nearby animals. The device then emits a species-appropriate sound to scare them away. Nozkova says the system learns from experience, too, and varies its responses so animals don’t get habituated to repeated signals. The company currently sells battery-operated devices that can be mounted on poles, trees, and other structures. It also offers a software platform that shows clients where the devices are deployed and what’s happening on the ground. The platform can also generate reports for regulatory compliance and for uses like biodiversity monitoring. The longer-term goal is to make the software portable enough to run on machines that work outside, including trains, cars, and drones. Nozkova says about 150 Flox devices are live in North America, Europe, and Australia at airfields and airport perimeters, road and rail corridors (especially fence ends and crossings along wildlife corridors), national parks, agricultural land, urban areas, mining sites, and critical infrastructure such as electrical substations. The company sells edge units up front, then charges an annual software and AI subscription after the first year. Flox also has OEM partnerships with companies that pay an annual fee to deploy its software on vehicles, like trains. Train manufacturer Alstom is one such partner. The company expects to end 2026 with revenue of about $1.5 million, Nozkova said. As unique as Flox’s product and approach are, the startup is not without competition. Robin Radar’sScarecrowalso uses species-specific distress calls to disperse birds and it records the activity, whileiCHASEsells a system that detects birds with computer vision and targets them with a moving laser, adjusting its response as needed. Nozkova says her moat is the breadth of the system and the data Flox has collected in the field, which she calls “ground truth on what actually makes a moose or a grizzly bear move safely.” “Physical AI is walking out of the factory and into the messy, alive outdoors,” Nozkova says. “Every machine that operates outside — trains, trucks, drones, tractors, robots — will need to understand nature, and nature intelligence is the next layer of the perception stack. Almost nobody is building it.” The company has raised about $5 million across pre-seed and seed rounds so far, with the seed round led by Unconventional Ventures and Tilia Impact Ventures. Co-investors across the rounds include GENIUS NY, Norrsken, Satgana, and angel investors, Nozkova said. The company is now opening a $10 million Series A, which would mostly go toward growing from about 150 devices to several thousand deployed units and extending the underlying system beyond its current wildlife use cases.

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