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Strategies & Market Trends : 2026 TeoTwawKi ... 2032 Darkest Interregnum -- Ignore unavailable to you. Want to Upgrade?

To: Julius Wong who wrote (212948)	4/7/2025 1:36:29 AM
From: TobagoJack	1 Recommendation Recommended By Julius Wong Respond to of 218505

the fat Jack loves Grand Theft Auto, eagerly awaiting GTA6, should go insane on the map feature-able Every alley, every flat, even every manhole cover is mirrored, the researchers said. scmp.com Grand Theft Auto Shanghai? Chinese scientists build a super virtual city – for police A hyperrealistic rendering of China’s largest city may look like a video game setting, but it has a much more serious purpose Stephen Chen in Beijing Published: 12:00pm, 7 Apr 2025 As the gaming world eagerly awaits Grand Theft Auto VI, rumoured to allow players to enter over 40 per cent of its virtual buildings, scientists in Shanghai have quietly achieved something far more ambitious: a hyperrealistic digital twin of China’s largest metropolis, built not for role-playing criminals but for policing. With an accuracy of under 3cm (1.2 inches), this “virtual Shanghai” enables officers to navigate every street, scan interior layouts of skyscrapers and even access real-time data such as property occupancy records – all through a mobile terminal. Developed by the Shanghai Surveying and Mapping Institute and the Ministry of Natural Resources’ key lab for megacity data analytics, the system combines airborne laser scans, street-level lidar (light detection and ranging), and AI-powered 3D modelling to recreate the city down to individual bedrooms and fire hydrants. Patrol officers can now “enter” buildings virtually, viewing floor plans, tenant registries and utility lines – a capability that blurs the line between physical and digital realms, according to the project team led by government engineer Zeng Lingfang in a peer-reviewed paper published this month in the Chinese-language Journal of Geomatics. Built by Chinese scientists, the virtual version of Shanghai has been created using vehicles, drones and backpack-mounted sensors to map the city. Photo: Shanghai Surveying and Mapping Institute During emergencies, metropolitan police headquarters can overlay live surveillance feeds, vehicle movements and heat maps onto the virtual city, orchestrating responses with surgical precision, according to Zeng and her colleagues. Every alley, every flat, even every manhole cover is mirrored, the researchers said.

To: Julius Wong who wrote (212948)	4/7/2025 1:39:54 AM
From: TobagoJack	Respond to of 218505

back to usual programming, as market plunge only matter to when-bottom-when-buy bloomberg.com DeepSeek and Tsinghua Developing Self-Improving AI Models By Saritha Rai 7 April 2025 at 13:00 GMT+8 DeepSeek is working with Tsinghua University to reduce the training needed for its AI models, aiming to lower operational costs. Summary by Bloomberg AI The collaboration has resulted in a novel approach to reinforcement learning, which offers rewards for more accurate and understandable responses, and has outperformed existing methods on various benchmarks. Summary by Bloomberg AI DeepSeek will release its new models, called DeepSeek-GRM, on an open source basis, and other companies, including Alibaba and OpenAI, are also working on improving reasoning and self-refining capabilities in AI models. Summary by Bloomberg AI DeepSeek is working with Tsinghua University on reducing the training its AI models need in an effort to lower operational costs. The Chinese startup, which roiled markets with its low-cost reasoning model that emerged in January, collaborated with researchers from the Beijing institution on a paper detailing a novel approach to reinforcement learning to make models more efficient. The new method aims to help artificial intelligence models better adhere to human preferences by offering rewards for more accurate and understandable responses, the researchers wrote. Reinforcement learning has proven effective in speeding up AI tasks in narrow applications and spheres. However, expanding it to more general applications has proven challenging — and that’s the problem that DeepSeek’s team is trying to solve with something it calls self-principled critique tuning. The strategy outperformed existing methods and models on various benchmarks and the result showed better performance with fewer computing resources, according to the paper. DeepSeek is calling these new models DeepSeek-GRM — short for “generalist reward modeling” — and will release them on an open source basis, the company said. Other AI developers, including Chinese tech giant Alibaba Group Holding Ltd. and San Francisco-based OpenAI, are also pushing into a new frontier of improving reasoning and self-refining capabilities while an AI model is performing tasks in real time. Menlo Park, California-based Meta Platforms Inc. released its latest family of AI models, Llama 4, over the weekend and marked them as its first to use the Mixture of Experts (MoE) architecture. DeepSeek’s models rely significantly on MoE to make more efficient use of resources, and Meta benchmarked its new release against the Hangzhou-based startup. DeepSeek hasn’t specified when it might release its next flagship model.