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Summaries are not the original full articles. ## PyRUA-DataFarm: LLM Agent as a Cost-Efficient Teleoperator for Real-Ready Robot Data DevFeed: [PyRUA-DataFarm: LLM Agent as a Cost-Efficient Teleoperator for Real-Ready Robot Data]() Original publisher: [Read original article]() Author: Kewei Zhang, Juncheng Ma, Guodong Lv, Duomin Wang, Feixiang Ruan, Ruiyang Si, Chuanrui Zhang, Yuxuan Chen, Hao Chen, Yichen Liu, Yintianrun Zhang, Yufan Deng, Enze Xie, Daquan Zhou Published: 2026-11-04T05:00:00Z Content type: article Language: en Sources: [arXiv: Artificial Intelligence]() Topics: [Large Language Model](), [AI-Ready Data]() Tags: [actions](), [adapting](), [agent](), [api](), [automatic](), [camera](), [coding](), [coding-agent](), [controller](), [cost](), [costs](), [cs-ai](), [cs-ro](), [data](), [farm](), [independent](), [labour](), [light](), [llm](), [model](), [north-america](), [robot]() ### AI overview PyRUA-DataFarm uses a coding agent to turn a data request and one real-robot calibration episode into simulation scenes, expert controllers, and success judges. Simulation provides exact actions; a video model conditioned on real images renders synchronized camera views, and independent judges screen the expert and each episode. Policies trained only on the resulting data matched policies trained on an equal number of teleoperated episodes across five tasks (93 versus 84 successes in 100 trials) and scored 87 versus 46 successes under an unseen tablecloth and coloured light. The excerpt reports an average $21 in API usage per task plus $5 for a render contract, then $0.80 per additional episode. One hour of three-view data averaged $107, compared with a $117 teleoperation quote in China and $290 in North American labour alone. ### Source excerpt arXiv:2611.05320v1 Announce Type: cross Abstract: Teleoperation remains the default way to collect robot demonstrations, but every episode costs robot and operator time, and every new task starts from scratch. We ask whether a coding agent can take over the teleoperator's job. In our DataFarm, the agent receives a data request and one calibration episode of the robot in the target scene and rebuilds the task in simulation: it writes the scene, an expert controller, and a success judge. The simulator supplies exact actions, and a video model conditioned on real images renders each rollout as photographic video, generating all camera views together consistently. The output is real-ready data: synchronized camera views labelled with the robot's actions, on which a policy can be trained directly and deployed on the real robot. Independent judges certify the expert and every rendered episode before admission. On five real-robot tasks, policies trained only on farm data match policies trained on as many teleoperated episodes (93 vs. 84 successes in 100 trials), and under an unseen tablecloth and coloured light they keep 87 successes where the teleoperation-trained policies fall to 46. Adapting a task is fully automatic and costs \$21 of API usage on average, paid once per task, plus \$5 for a render contract; every further episode costs \$0.80 on average for simulation, rendering, and review, with no robot or operator. One hour of three-view data for a task costs \$107 on average, these costs included, slightly below a quote of \$117 for teleoperation in China and below \$290 in labour alone in North America. ## Maswao: An automatically collected, prepared, and benchmarked dataset for the South African Sign language DevFeed: [Maswao: An automatically collected, prepared, and benchmarked dataset for the South African Sign language]() Original publisher: [Read original article]() Author: Thapelo Sindane, Unarine Netshifhefhe, Vukosi Marivate, Abiodun Modupe, Herkulaas Combrink, Ketro Sithole Published: 2026-11-03T05:00:00Z Content type: article Language: en Sources: [arXiv: Artificial Intelligence]() Topics: [Language Engineering](), [machine-translation](), [asr](), [Artificial Intelligence](), [managing large-scale text data in AI]() Tags: [asr](), [audio](), [automatically](), [benchmark](), [bleu](), [collect](), [collection](), [crop](), [cs-ai](), [cs-cl](), [dataset](), [datasets](), [framework](), [gradient](), [gradient-descent](), [labour](), [language](), [languages](), [model](), [models](), [motion](), [sign]() ### AI overview Maswao is a weakly sentence-aligned South African Sign Language dataset built with minimal human intervention. The framework collects public SASL videos, including news broadcasts, converts accompanying audio to text with available ASR tools, crops the signing area, and uses gradient descent to detect non-motion valleys as sentence boundaries. On sign-to-text translation, Transformer models outperformed the recurrent baselines tested. The best Transformer scored BLEU-1 through BLEU-4 of 13.78, 5.21, 2.52, and 1.54, with ChrF 18.09 and ROUGE-L 10.51. The reported scores suggest the task remains open for further investigation. ### Source excerpt arXiv:2611.02903v1 Announce Type: cross Abstract: Recent advancements in sign language processing can be attributed to developments in both large-scale dataset collection and algorithmic complexity in areas such as pose estimation techniques, signal processing through Transformer models, and model optimization. However, only a handful of sign languages, such as the American, British, and German, from over 200 globally recognized sign languages, reap the benefits of such advancements, while the rest lag behind. In this study, we aim to address this technological disparity by proposing a framework for the automatic collection and preparation of sign language datasets, with very minimal human-labour intervention, using the South African Sign Language (SASL) as a testbed. Specifically, we automatically collect SASL video content using public resources such as news broadcasts. Additionally, we convert their accompanying audio streams into text using available Automatic Speech Recognition (ASR) tools. Furthermore, we crop the sign language area in the videos and use gradient descent to locate valleys of non-motion to determine end-of-sentence points within long videos to create our weakly sentence-aligned parallel corpora -- the Maswao (Signs) dataset. Finally, we benchmark the weakly aligned dataset on the task of Sign-to-text Translation using Recurrent Neural Networks and Transformer models to compare their individual intricacies. Our results show that Transformer models proposed in the literature outperform recurrent baselines, with the best-performing Transformer achieving BLEU-1 to BLEU-4 scores of 13.78, 5.21, 2.52, and 1.54, respectively, as well as ChrF = 18.09 and ROUGE-L = 10.51. These results indicate that the task remains promising and warrants further investigations. ## AI firms say UK has a year to head off datacentre protests before construction is threatened DevFeed: [AI firms say UK has a year to head off datacentre protests before construction is threatened]() Original publisher: [Read original article]() Author: Robert Booth Published: 2026-10-22T05:00:08Z Content type: news Language: en Sources: [The Guardian | Technology]() Topics: [AI Infrastructure](), [clean energy data centers]() Tags: [ai](), [ai-artificial-intelligence](), [ai-companies](), [ai-infrastructure](), [cisco](), [datacentres](), [datacentres-uk](), [datacentres-uk-uk-news-ai-artificial-intelligence-microsoft-nvidia-cisco](), [energy](), [government](), [infrastructure](), [labour](), [microsoft](), [nvidia](), [public](), [risk](), [run](), [run-ai](), [submission](), [tech](), [train](), [uk](), [uk-news](), [us]() ### AI overview The SAIL taskforce, including Nvidia, Microsoft and Cisco, warns that the UK has roughly 12 months to secure public consent for datacentre expansion before opposition could threaten projects. It proposes a government framework for "prosperity compacts," with local benefits such as financial contributions or facilities scaled to site size, and allowing host councils to retain more business-rate revenue. The companies say distrust, energy costs and fears of stranded assets are driving opposition in the US and beginning to surface in Britain. Critics argue that incentives could shift costs to central government services and will not undo community opposition; Scotland campaigners say local resistance is already established. The government says communities should receive investment, jobs and supply chains, while prioritising clean power and responsible water use, and notes that councils in English AI growth zones can already retain additional business rates. The taskforce has not estimated the central-government cost of allowing councils to keep all datacentre business rates. ### Source excerpt Exclusive: Nvidia, Microsoft and Cisco taskforce urges ministers to offer areas greater benefits from tech infrastructure amid fears of US-style opposition AI companies have told ministers they have 12 months to head off public opposition to datacentres in the UK or risk US-style protests that could threaten their construction. Successive dry summers and rising energy bills are increasing public scrutiny of plans for the huge computer warehouses that are used to train and run AI models, says a submission to the Labour government from a group including the AI infrastructure companies Nvidia, Microsoft and Cisco. Continue reading... ## The power of AI is worrying senior Labour figures - as is the fear of 'falling behind the public' DevFeed: [The power of AI is worrying senior Labour figures - as is the fear of 'falling behind the public']() Original publisher: [Read original article]() Author: Rowena Mason and Dan Milmo Published: 2026-10-17T11:33:20Z Content type: news Language: en Sources: [The Guardian | Technology]() Topics: [ai security](), [Cybersecurity](), [Machine learning](), [Open Source](), [Critical Infrastructure]() Tags: [ai](), [ai-artificial-intelligence](), [ai-artificial-intelligence-uk-security-and-counter-terrorism-defence-policy-data-and-computer-secu](), [ai-safety](), [ai-security](), [ai-technology](), [all](), [andy-burnham](), [anthropic](), [artificial-intelligence](), [attacks](), [big-tech](), [bio](), [bioweapons](), [computing](), [conference](), [cybercrime](), [cybersecurity](), [data-and-computer-security](), [data-protection](), [death](), [defence-policy](), [democrats](), [disease](), [donald-trump](), [ed-miliband](), [labour](), [leader](), [mi5](), [openai](), [politics](), [technology](), [uk-news](), [uk-security-and-counter-terrorism](), [worrying]() ### AI overview The article reports growing concern among UK Labour figures and security officials about AI risks, including cyberattacks, extremist use, and potential AI-enabled bioweapons. It describes debate over model testing, regulation, international cooperation, and balancing safeguards against the use of AI in public services and defence. Experts differ on the immediacy and evidence for existential risks. ### Source excerpt Westminster appears to be waking up to warnings over AI safety, with concerns over its use by extremist groups and bad actors "I have this sense that, within a few months, AI is going to be all anyone is talking about," said one cabinet minister, with an ominous stare. It was Labour conference, with everyone from ministers to activists jubilant at Andy Burnham's takeover and a bounce in the polls after the change of leader. Continue reading...