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This Indigenous Language Survived Russian Occupation. Can It Survive YouTube?

WIRED

This Indigenous Language Survived Russian Occupation. YouTube's search and recommendation algorithms are driving children to Russian-language content even when they seek out videos in Kyrgyz, creating a cultural shift that concerns some parents. When anthropology researcher Ashley McDermott was doing fieldwork in Kyrgyzstan a few years ago, she says many people voiced the same concern: Children were losing touch with their indigenous language. The Central Asian country of 7 million people was under Russian control for a century until 1991, but Kyrgyz (pronounced kur-giz) survived and remains widely spoken among adults. McDermott, a doctoral student at the University of Michigan, says she also heard that some kids in rural villages where Kyrgyz dominated had spontaneously learned to speak Russian.


YouTube was down for thousands of users in the US

Engadget

Samsung Galaxy Unpacked 2026 is Feb. 25 Valve's Steam Machine: Everything we know It was also down in some other countries. YouTube is experiencing an outage across the United States, with users in other countries like Canada, India, the Philippines, Australia and Russia also having problems with accessing the website. The issue seems to have started at around 8 PM Eastern time and reached 338,000 reports on Downdetector before starting to taper down. More users reported having issues accessing the app, but I personally lost access to the web homepage first. As of 9:22 PM, users are still reporting being unable to access YouTube on Reddit .


aa7ef4c0f4aaabf376088a1a74e09d4c-Supplemental-Datasets_and_Benchmarks.pdf

Neural Information Processing Systems

Pleaseprovideadescription.531 We want to provide an open-source large-scale music dataset for the research com-532 munity. Such large datasets do not yet exist in this domain, and we believetheyare533 neededtodemocratize innovationinmusicresearch andML-assisted musiccreation.534




BBC director general to depart in April after resignation

BBC News

The BBC's director general is to leave the broadcaster in April, five months after he announced his resignation amid a storm about the way Panorama edited a Donald Trump speech. Tim Davie stayed in his post after announcing his resignation in November, but will depart on 2 April. He will be replaced by an interim DG, Rhodri Talfan Davies, who has been director of nations since 2021 and is currently leading the BBC's work on generative AI. The search is under way for a permanent director general, one of the most demanding jobs in the British media. Davie has been responsible for dealing with a series of scandals and crises since becoming the BBC's 17th director general in 2020.


Google AI Overviews cite YouTube more than any medical site for health queries, study suggests

The Guardian

No hospital network, government health portal, medical association or academic institution came close to YouTube's number of citations, the researchers said. No hospital network, government health portal, medical association or academic institution came close to YouTube's number of citations, the researchers said. How the'confident authority' of AI Overviews is putting public health at risk Google's search feature AI Overviews cites YouTube more than any medical website when answering queries about health conditions, according to research that raises fresh questions about a tool seen by 2 billion people each month. The company has said its AI summaries, which appear at the top of search results and use generative AI to answer questions from users, are "reliable" and cite reputable medical sources such as the Centers for Disease Control and Prevention and the Mayo Clinic. However, a study that analysed responses to more than 50,000 health queries, captured using Google searches from Berlin, found the top cited source was YouTube .


I'm watching myself on YouTube saying things I would never say. This is the deepfake menace we must confront Yanis Varoufakis

The Guardian

I'm watching myself on YouTube saying things I would never say. These inventions trigger rage, but also optimism. I t was my blue shirt, a present from my sister-in-law, that gave it all away. It made me think of Yakov Petrovich Golyadkin, the lowly bureaucrat in Fyodor Dostoevsky's novella The Double, a disconcerting study of the fragmented self within a vast, impersonal feudal system. It all started with a message from an esteemed colleague congratulating me on a video talk on some geopolitical theme.


From shrimp Jesus to erotic tractors: how viral AI slop took over the internet

The Guardian

Clockwise from top left: Shrimp Jesus, Nayib Bukele, Justin Bieber and Super Cat League. Clockwise from top left: Shrimp Jesus, Nayib Bukele, Justin Bieber and Super Cat League. In the algorithm-driven economy of 2025, one man's shrimp Jesus is another man's side hustle. AI slop - the low-quality, surreal content flooding social media platforms, designed to farm views - is a phenomenon, some would say the phenomenon of the 2024 and 2025 internet. Merriam-Webster's word of the year this year is "slop", referring exclusively to the internet variety.


Quilt-1M: One Million Image-Text Pairs for Histopathology

Neural Information Processing Systems

Recent accelerations in multi-modal applications have been made possible with the plethora of image and text data available online. However, the scarcity of analogous data in the medical field, specifically in histopathology, has slowed comparable progress. To enable similar representation learning for histopathology, we turn to YouTube, an untapped resource of videos, offering $1,087$ hours of valuable educational histopathology videos from expert clinicians.From YouTube, we curate QUILT: a large-scale vision-language dataset consisting of $802, 144$ image and text pairs.QUILT was automatically curated using a mixture of models, including large language models, handcrafted algorithms, human knowledge databases, and automatic speech recognition.In comparison, the most comprehensive datasets curated for histopathology amass only around $200$K samples.We combine QUILT with datasets from other sources, including Twitter, research papers, and the internet in general, to create an even larger dataset: QUILT-1M, with $1$M paired image-text samples, marking it as the largest vision-language histopathology dataset to date. We demonstrate the value of QUILT-1M by fine-tuning a pre-trained CLIP model. Our model outperforms state-of-the-art models on both zero-shot and linear probing tasks for classifying new histopathology images across $13$ diverse patch-level datasets of $8$ different sub-pathologies and cross-modal retrieval tasks.