From "cameo" to "io," OpenAI keeps trying to call its new and upcoming releases by names that resemble existing trademarks. In September, OpenAI launched a way for users to generate a digital likeness of themselves they could use to create personalized deepfake videos . This is one of the core features in Sora, OpenAI's app for sharing AI videos inside a TikTok-style feed. The self-deepfaking feature was called "cameo," and with that standout feature, Sora quickly rose to the top of Apple's iOS download charts. This feature name led to a trademark lawsuit with Cameo, the app where fans can pay celebrities to record personalized videos.

Twelve laboratories around the world have joined forces to map neuronal activity in a mouse's brain as it makes decisions. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. Neuroscientists from around the world have worked in parallel to map, for the first time, the entire brain activity of mice while they were making decisions. This achievement involved using electrodes inserted inside the brain to simultaneously record the activity of more than half a million neurons distributed across 95 percent of the rodents' brain volume.

The United States Patent and Trademark Office has rejected Neuralink's attempt to trademark the product names Telepathy and Telekinesis, citing pending applications by another person for the same trademarks. Neuralink, the brain implant company co-founded by Elon Musk, filed to trademark the names in March. But in letters sent to Neuralink in August, the trademark office is refusing to allow the applications to move forward. It says Wesley Berry, a computer scientist and co-founder of tech startup Prophetic, previously filed trademark applications for Telepathy in May 2023 and Telekinesis in August 2024. Prophetic is building a wearable headset to induce lucid dreaming, but only Berry is the author of the trademark applications, not Prophetic.

The US Patent and Trademark Office has refused one of Tesla's initial attempts to trademark the term "Robotaxi" because it believes the name is generic and already in use by other companies, according to a filing spotted by TechCrunch. Tesla was hoping to trademark the term in connection to its planned self-driving car service, but now it'll have to reply with more evidence to change the office's mind. The main issue outlined in the USPTO decision is that "Robotaxi" is "merely descriptive," as in its an already commonly used term. A robotaxi typically refers to the self-driving cars used in services like Waymo. As long as Silicon Valley has believed money could be made selling autonomous vehicles (and the rides you can take in them), the term has been in use.

Elon Musk's xAI is facing a potential trademark dispute over the name of its chatbot, Grok. The company's trademark application with the US Patent and Trademark Office has been suspended after the agency argued the name could be confused with that of two other companies, AI chipmaker Groq and software provider Grokstream. Now, a third tech startup called Bizly is claiming it owns the rights to "Grok." This isn't the first time Musk has chosen a name for one of his products that other companies say they trademarked first. Last month, Musk's social media platform settled a lawsuit brought by a marketing firm that claimed it owns exclusive rights to the name X. Bizly and xAI appear to have arrived at the name Grok independently.

Text summarization is the process of condensing a piece of text to fewer sentences, while still preserving its content. Chat transcript, in this context, is a textual copy of a digital or online conversation between a customer (caller) and agent(s). This paper presents an indigenously (locally) developed hybrid method that first combines extractive and abstractive summarization techniques in compressing ill-punctuated or un-punctuated chat transcripts to produce more readable punctuated summaries and then optimizes the overall quality of summarization through reinforcement learning. Extensive testing, evaluations, comparisons, and validation have demonstrated the efficacy of this approach for large-scale deployment of chat transcript summarization, in the absence of manually generated reference (annotated) summaries.

Message oriented and robotics middleware play an important role in facilitating robot control, abstracting complex functionality, and unifying communication patterns between sensors and devices. However, using multiple middleware frameworks presents a challenge in integrating different robots within a single system. To address this challenge, we present Wrapyfi, a Python wrapper supporting multiple message oriented and robotics middleware, including ZeroMQ, YARP, ROS, and ROS 2. Wrapyfi also provides plugins for exchanging deep learning framework data, without additional encoding or preprocessing steps. Using Wrapyfi eases the development of scripts that run on multiple machines, thereby enabling cross-platform communication and workload distribution. We finally present the three communication schemes that form the cornerstone of Wrapyfi's communication model, along with examples that demonstrate their applicability.

Annually, e-commerce platforms incur substantial financial losses due to trademark infringements, making it crucial to identify and mitigate potential legal risks tied to merchant information registered to the platforms. However, the absence of high-quality datasets hampers research in this area. To address this gap, our study introduces TMID, a novel dataset to detect trademark infringement in merchant registrations. This is a real-world dataset sourced directly from Alipay, one of the world's largest e-commerce and digital payment platforms. As infringement detection is a legal reasoning task requiring an understanding of the contexts and legal rules, we offer a thorough collection of legal rules and merchant and trademark-related contextual information with annotations from legal experts. We ensure the data quality by performing an extensive statistical analysis. Furthermore, we conduct an empirical study on this dataset to highlight its value and the key challenges. Through this study, we aim to contribute valuable resources to advance research into legal compliance related to trademark infringement within the e-commerce sphere. The dataset is available at https://github.com/emnlpTMID/emnlpTMID.github.io .

More than a decade ago, when Shahzad Younas started a website specifically for Muslims to meet and marry, he thought his problems would be the typical kind – attracting users, expanding the business, earning a profit. Instead, his biggest hurdle has been figuring out how to fend off a competitor that is suing him in multiple countries on multiple fronts with the aim, he said, of "stifling competition". Younas, 38, a British investment banker turned entrepreneur, has been butting heads since 2016 with the online dating giant Match Group, which owns Match.com, At issue are elements of his website's branding – elements that Match has argued create confusion between its platforms and Younas's. The latest blow came in late April when Younas lost a trademark appeal in the United Kingdom.

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