With OpenAI’s memory upgrade, ChatGPT can recall everything you’ve ever shared with it, indefinitely. Similarly, Google has opened the context window with “Infini-attention,” letting large language models (LLMs) reference infinite inputs with zero memory loss. And in consumer-facing tools like ChatGPT or Gemini, this means persistent, personalized memory across conversations, unless you manually intervene.

The sales pitch is seductively simple: less friction, more relevance. Conversations that feel like continuity: “Systems that get to know you over your life,” as Sam Altman writes on X. Technology, finally, that meets you where you are.

In the age of hyper-personalization — of the TikTok For You page, Spotify Wrapped, and Netflix Your Next Watch — a conversational AI product that remembers everything about you feels perfectly, perhaps dangerously, natural.

Forgetting, then, begins to look like a flaw. A failure to retain. A bug in the code. Especially in our own lives, we treat memory loss as a tragedy, clinging to photo albums and cloud backups to preserve what time tries to erase.

But what if human forgetting is not a bug, but a feature? And what happens when we build machines that don’t forget, but are now helping shape the human minds that do?

🇷🇺 🦮 📶 The future is here!

In #Russia, stray #dogs are getting a side hustle as moving Wi-Fi routers, to increase their chances of getting adopted - not a joke!

lai-fi.com
meduza.io/en/feature/2025/12/0…

#news #article #wifi #routers #blackout #internet #adoption #adopt #animal #animals #animalrights #animalwelfare #gear #backpack #dog #dognews #russian #russians #rus #it #tech #technology #stray #mobile #новости #вайфай #роутеры #блэкаут #интернет #усыновление #усыновить #meduza

Bonus video of Swiss-German in the wild included. If you think German sounds harsh, you'll love the Zuerich dialect. At least it's all done in sing-song fashion, as is called for.

A real-world trial by scientists in Switzerland has demonstrated that wireless EV charging can achieve up to 90 percent efficiency compared with conventional cable-based systems, while offering far greater convenience.

Supported by the Swiss Federal Office of Energy and the cantons of Zurich and Aargau, the project, called INLADE, was carried out by researchers from Empa in collaboration with the electric utility Eniwa AG.

Through this first-of-its-kind initiative, the team tested wireless inductive charging under real-life conditions in Switzerland. They are certain that what has long been routine for phones and electric toothbrushes could soon become a reality for EVs.

“The aim was to test the existing technology in everyday use, clarify technical and regulatory issues and demonstrate its potential for the energy transition,” Mathias Huber, from Empa’s Chemical Energy Carriers and Vehicle Systems lab, said.

archive.is link

If you’re near Rochester, New York, the price for a carton of Target’s Good & Gather eggs is listed as $1.99 on its website. If you’re in Manhattan’s upscale Tribeca neighborhood, that price changes to $2.29. It’s unclear why the prices differ, but a new notice on Target’s website offers a potential hint: “This price was set by an algorithm using your personal data.”

A recently enacted New York State law requires businesses that algorithmically set prices using customers’ personal data to disclose that. According to the law, personal data includes any data that can be “linked or reasonably linked, directly or indirectly, with a specific consumer or device.” The law doesn’t require businesses to explicitly state what information about a person or device is being used or how each piece of information affects the final price a customer sees. The law includes a carve-out for the use of location data strictly to calculate cab or rideshare fares based on mileage and trip duration but not for other purposes.

The law also requires that the disclosure is “clear and conspicuous.” Target’s disclosure is not the easiest to find–a customer would have to know to click the “i” icon next to the price of an item, then scroll to the bottom of the pop-up. In the past, the courts have held that it’s not always reasonable to assume that a customer will click on “more information” links when it’s not required.

Members of OASIS Open, the global open source and standards organization, have approved the Open Document Format (ODF) for Office Applications V1.4 as an OASIS Standard, the organization’s highest level of ratification. ODF V1.4 improves developer documentation, adds new features, and maintains full backward compatibility.

The release of ODF V1.4 coincides with the 20th anniversary of ODF as an OASIS Standard. Over two decades, ODF has served as a vendor-neutral, royalty-free format for office documents, ensuring that files remain readable, editable, and interoperable across platforms. Governments and international organizations, including NATO, the European Commission, and countries across multiple continents, have adopted ODF for document exchange.

“ODF V1.4 is the effort to evolve the ODF format to its newer challenges, adding relevant clarification and additions to the existing ODF V1.3,” said Patrick Durusau, OpenDocument TC co-chair. “We are pushing hard to meet expectations of the Office software industry.”

OpenDocument V1.4 contains enhancements in accessibility, professional document formatting, and advanced functionality across text documents, spreadsheets, and presentations. Improvements include better support for assistive technologies, enhanced visual design capabilities, and expanded features for data analysis and technical documentation. These updates strengthen OpenDocument’s role as a comprehensive solution for modern workplace productivity and inclusive document creation.

“ODF provides a vendor-neutral foundation for office productivity and collaboration worldwide. With V1.4, the standard continues to evolve, supporting cloud collaboration, richer multimedia, and standardized security,” said Svante Schubert, OpenDocument TC co-chair. “The format will remain reliable across platforms for years to come. Looking ahead, ODF is moving beyond document exchange toward standardized, semantic change-based collaboration — enabling precise, meaningful sharing of interoperable changes across platforms.”

OpenAI may soon be forced to explain why it deleted a pair of controversial datasets composed of pirated books, and the stakes could not be higher.

At the heart of a class-action lawsuit from authors alleging that ChatGPT was illegally trained on their works, OpenAI’s decision to delete the datasets could end up being a deciding factor that gives the authors the win.

It’s undisputed that OpenAI deleted the datasets, known as “Books 1” and “Books 2,” prior to ChatGPT’s release in 2022. Created by former OpenAI employees in 2021, the datasets were built by scraping the open web and seizing the bulk of its data from a shadow library called Library Genesis (LibGen).

As OpenAI tells it, the datasets fell out of use within that same year, prompting an internal decision to delete them.

But the authors suspect there’s more to the story than that. They noted that OpenAI appeared to flip-flop by retracting its claim that the datasets’ “non-use” was a reason for deletion, then later claiming that all reasons for deletion, including “non-use,” should be shielded under attorney-client privilege.

To the authors, it seemed like OpenAI was quickly backtracking after the court granted the authors’ discovery requests to review OpenAI’s internal messages on the firm’s “non-use.”

In fact, OpenAI’s reversal only made authors more eager to see how OpenAI discussed “non-use,” and now they may get to find out all the reasons why OpenAI deleted the datasets.