Ukrainian drone strikes have knocked out two of five data centers belonging to the Russian tech giant Yandex. The damage has left Yandex, known as “Russia’s Google” because it operates the country’s most popular search engine, struggling to maintain its AI chatbot and other online services.
The Ukrainian drones struck Yandex data centers in the Sasovo and Kaluga regions of Russia on October 8 and October 9, according to Reuters. Those actions came as a direct response to a Russian drone strike campaign targeting Ukraine’s data centers, which has disrupted mobile phone and Internet services for thousands of Ukrainians since late September.
“We continue to respond to Russia’s attacks on Ukraine, and we’re doing so with high precision,” said Ukrainian President Volodymyr Zelenskyy in a post on X. “Another data center was hit as well—our symmetrical response.”
A recent study of actual coding practices across hundreds of firms finds that human code review forms a significant "bottleneck" for the overall efficiency of AI coding tools, resulting in "little evidence that firms increase software output or reduce employment" by using them. Any efficiency increased during the actual coding phase, the study authors find, is "absorbed by downstream constraints in the production process"; as "the code review process significantly increases in length, pull requests are more likely to require revisions, and reviewers leave more comments."
Cut once, measure twice
To come to these conclusions, Harvard University researchers Fiona Chen and James Stratton made use of aggregated analytics data from Jellyfish, which measures the granular output of engineering teams. That data encompasses 300 million individual "work events" (e.g., commits and pull requests) and issue management software data across more than 700,000 employees at over 700 relevant software development firms from 2021 through March of 2026.
Last month we covered the winner of Nikon's Small World in Motion video: Ning Xu of Tsinghua University in China, whose video captured tiny cilia beating in the airways of a child with a rare respiratory disorder. But allegations surfaced about Xu's use of AI while making the video. Nikon launched an investigation and concluded that Xu's entry did not comply with competition rules. The new winner is Nguyen Nam Nhat of Vietnam with a video of a tiny roundworm and a single-celled organism (above).
According to a BBC report, some researchers expressed concern that Xu's video had structural abnormalities and that cell features appeared and disappeared in a way one would not see in actual cellular biology. Others spotted what looked like AI watermarks embedded within the source files. Xu said he used AI “to distinguish and visualize features in the reconstructed grayscale images”; however, he denied that AI was used "to generate the experimental movie, the cilia, or their motion.”
Founded in 2011, the Nikon Small World in Motion competition is a spinoff of the company’s Small World Photomicrography Competition, which has been around since 1974. Both are meant “to showcase the beauty and complexity of things seen through the light microscope”—one through still photographs, the other through photovideography, taking advantage of all the technological advances that now allow users to make movies or time-lapse images through the microscope.
The other winners also moved up a notch with Xu's disqualification. Benedikt Pleyer of Bavaria, Germany, placed second with a video of jellyfish larvae suspended in water droplets; Andrew Moore of Howard Hughes Medical Institute in the US placed third with a video of synchronized cell division in neighboring cells; Patrick Hickey of Hypha Research Ltd. in Edinburgh, Scotland, placed fourth with a video of the dynamics of mitochondria and chloroplasts in Turtle Vine leaf cells; and Igor Adameyko placed fifth with a video of a tiny, colorful sea slug (Cyerce kikutarobabai) on the move.
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