Expanded carrier screening: Is it worth it? Carrier screening tests would-be parents for hidden genetic mutations that might affect their children. It initially involved testing for specific genes in at-risk populations. Expanded carrier screening takes things further, giving would-be parents an option to test for a wide array of diseases in prospective parents and egg and sperm donors. The companies offering these screens "started out with 100 genes, and now some of them go up to 2,000," Sara Levene, genetics counsellor at Guided Genetics, said at a meeting I attended this week. "It's becoming a bit of an arms race amongst labs, to be honest."

Is A.I. Actually a Bubble? The narrative of boom and bust is familiar--but also out of step with the possibilities of a new technology. Over the past few months, I've introduced artificial intelligence into the hobby life of my seven-year-old son, Peter. On Saturdays, he takes a coding class, in which he recently made a version of rock-paper-scissors, and he really wants to make more sophisticated games at home. I gave ChatGPT and Claude a sense of his skill level, and they instantaneously suggested next steps. Claude proposed trying to recreate Pong in Scratch, a coding environment for kids.

'Children's cafeterias' in Japan hit record 12,601 sites, survey reveals The number of children's cafeterias that provide free or low-cost meals mainly to children in need in Japan rose by more than 1,700 from the previous fiscal year, according to a survey by a nonprofit organization. The number of children's cafeterias, which provide free or low-cost meals mainly to children in need in Japan, has reached a record 12,601 this fiscal year, according to a survey by a nonprofit organization. The total rose by more than 1,700 from the previous fiscal year, said the survey released Thursday by Musubie, a Tokyo-based nonprofit supporting kodomo shokudō programs nationwide. The nonprofit organization said the expansion reflected efforts by central and local governments to create comfortable spaces for children. We aim to create an environment that makes it easier to start and sustain kodomo shokudō programs, Musubie head Rie Mishima said at a news conference.

Abrego Garcia released as U.S. bid to detain him ruled'constitutionally infirm' Salvadoran migrant and U.S. resident Kilmar Abrego Garcia arrives at a U.S. Immigration and Customs Enforcement field office in Baltimore, Maryland, on Aug. 25. A federal judge in Maryland has ordered the immediate release of Kilmar Armando Abrego Garcia, a Salvadoran migrant at the center of political and legal battles as a symbol of U.S. President Donald Trump's hard-line immigration policies. U.S. District Judge Paula Xinis held on Thursday that U.S. officials lacked legal grounds to keep Abrego Garcia in custody and that his ongoing detention appeared to be "constitutionally infirm." Abrego Garcia has been fighting Trump administration efforts to deport him while also defending against human smuggling charges in Tennessee. U.S. officials' latest plan had been to send him to Liberia, but a judge has blocked that for now.

All 50 economists expect the Bank of Japan to raise its benchmark rate to 0.75% at a policy meeting set to conclude next Friday, a Bloomberg survey of BOJ watchers found. The Bank of Japan will raise its policy interest rate next week, resuming a hiking cycle for the first time since January, according to a Bloomberg survey of BOJ watchers. All 50 economists expect the central bank to raise its benchmark rate to 0.75% at a policy meeting set to conclude next Friday, according to the poll. This is the first time every respondent has predicted a rate shift under Gov. Kazuo Ueda's watch. The BOJ is expected to restart the cycle of hikes after pausing for months to assess the impact from U.S. President Donald Trump's tariff campaign.

Magnitude 6.7 quake off Aomori triggers tsunami advisory Areas under a tsunami advisory are shown in yellow following a magnitude 6.7 earthquake on Friday | JAPAN METEOROLOGICAL AGENCY A magnitude 6.7 earthquake triggered a tsunami advisory for parts of Hokkaido as well as the coasts of Aomori, Iwate and Miyagi prefectures on Friday. The quake struck at 11:44 a.m., registering 4 on Japan's seismic intensity scale in some areas. Waves of up to 1 meter are possible in areas under the advisory, according to the Japan Meteorological Agency (JMA). A tsunami advisory, a level lower than a tsunami warning, urges those in the area to stay away from the ocean. Evacuation is not required under an advisory.

OpenAI and its investor Microsoft have been sued over a Connecticut murder-suicide in the latest case to blame ChatGPT for dangerous psychological manipulation of users. OpenAI and its investor, Microsoft, have been sued over a Connecticut murder-suicide in the latest case to blame the popular ChatGPT chatbot for dangerous psychological manipulation of users. The lawsuit turns on the actions of a 56-year-old man who lived with his 83-year-old mother in Greenwich, Connecticut, and had been conversing for months with the chatbot over his fear that he was under surveillance and people were trying to kill him. In August, according to police and the state medical examiner, Stein-Erik Soelberg killed his mother, Suzanne Adams, then took his own life. Soelberg's dialogue with ChatGPT convinced him that he had made the chatbot conscious, and that he had been implanted with a "divine instrument system" in his neck and brain, which related to a "divine mission," according to a complaint filed Thursday in California Superior Court in San Francisco, where OpenAI is based.

With the widespread application of multimodal large language models in scientific intelligence, there is an urgent need for more challenging evaluation benchmarks to assess their ability to understand complex scientific data. Scientific tables, as core carriers of knowledge representation, combine text, symbols, and graphics, forming a typical multimodal reasoning scenario. However, existing benchmarks are mostly focused on general domains, failing to reflect the unique structural complexity and domain-specific semantics inherent in scientific research. Chemical tables are particularly representative: they intertwine structured variables such as reagents, conditions, and yields with visual symbols like molecular structures and chemical formulas, posing significant challenges to models in cross-modal alignment and semantic parsing. To address this, we propose ChemTable-a large scale benchmark of chemical tables constructed from real-world literature, containing expert-annotated cell layouts, logical structures, and domain-specific labels. It supports two core tasks: (1) table recognition (structure and content extraction); and (2) table understanding (descriptive and reasoning-based question answering). Evaluation on ChemTable shows that while mainstream multimodal models perform reasonably well in layout parsing, they still face significant limitations when handling critical elements such as molecular structures and symbolic conventions. Closed-source models lead overall but still fall short of human-level performance. This work provides a realistic testing platform for evaluating scientific multimodal understanding, revealing the current bottlenecks in domain-specific reasoning and advancing the development of intelligent systems for scientific research.

While significant progress has been made in research and development on open-source and cost-efficient large-language models (LLMs), serving scalability remains a critical challenge, particularly for small organizations and individuals seeking to deploy and test their LLM innovations. Inspired by peer-to-peer networks that leverage decentralized overlay nodes to increase throughput and availability, we propose GenTorrent, an LLM serving overlay that harnesses computing resources from decentralized contributors. We identify four key research problems inherent to enabling such a decentralized infrastructure: 1) overlay network organization; 2) LLM communication privacy; 3) overlay forwarding for resource efficiency; and 4) verification of serving quality. This work presents the first systematic study of these fundamental problems in the context of decentralized LLM serving. Evaluation results from a prototype implemented on a set of decentralized nodes demonstrate that GenTorrent achieves a latency reduction of over 50% compared to the baseline design without overlay forwarding. Furthermore, the security features introduce minimal overhead to serving latency and throughput. We believe this work pioneers a new direction for democratizing and scaling future AI serving capabilities.

Representation alignment (REPA) guides generative training by distilling representations from a strong, pretrained vision encoder to intermediate diffusion features. We investigate a fundamental question: what aspect of the target representation matters for generation, its \textit{global} \revision{semantic} information (e.g., measured by ImageNet-1K accuracy) or its spatial structure (i.e. pairwise cosine similarity between patch tokens)? Prevalent wisdom holds that stronger global semantic performance leads to better generation as a target representation. To study this, we first perform a large-scale empirical analysis across 27 different vision encoders and different model scales. The results are surprising; spatial structure, rather than global performance, drives the generation performance of a target representation. To further study this, we introduce two straightforward modifications, which specifically accentuate the transfer of \emph{spatial} information. We replace the standard MLP projection layer in REPA with a simple convolution layer and introduce a spatial normalization layer for the external representation. Surprisingly, our simple method (implemented in $<$4 lines of code), termed iREPA, consistently improves convergence speed of REPA, across a diverse set of vision encoders, model sizes, and training variants (such as REPA, REPA-E, Meanflow, JiT etc). %, etc. Our work motivates revisiting the fundamental working mechanism of representational alignment and how it can be leveraged for improved training of generative models. The code and project page are available at https://end2end-diffusion.github.io/irepa