Could the next great novel be written by AI (and would you even be able to tell)? Can you tell which, if any, were AI generated? "The hotel is in a great location for everything. Lots of places to eat and drink. The hotel itself is always abuzz. The tavern located on the ground floor is definitely a must. Food, service, prices and atmosphere were great." "A good hotel, though the room had the proportions of a well-appointed lift.

During negotiations on Wednesday, employees voiced frustrations with what they consider an unwillingness among senior DeepMind executives to engage meaningfully with the prospect of unionization. Negotiations between Google DeepMind and its London-based employees over the possibility of unionization stumbled this week, after initial talks left union representatives feeling they had wasted their time, WIRED has learned. In May, DeepMind employees asked Google to recognize the Communication Workers Union and Unite the Union as joint representatives. The company later denied that request, but agreed to participate in negotiations arbitrated by a third-party body. An initial meeting on Wednesday was attended by union officers, DeepMind employees involved in the unionization push, the third-party arbitrator, and DeepMind HR representatives.

OpenAI has partnered with datacentre operator NextDC to build a multibillion dollar computing cluster in Sydney. The NSW environment minister, Penny Sharpe, says the city is'a highly desirable location'. OpenAI has partnered with datacentre operator NextDC to build a multibillion dollar computing cluster in Sydney. The NSW environment minister, Penny Sharpe, says the city is'a highly desirable location'. NSW government'absolutely thrilled' to welcome OpenAI ... until someone mentioned the Terminator films Emails sent between MP Anoulak Chanthivong's staff take cautious approach to AI giant arriving in Sydney - despite the government's encouragement The NSW technology minister's office removed a reference to being "absolutely thrilled" about OpenAI opening a Sydney office after staffers joked a dystopian Skynet could be headed for the city within five years.

PCWorld reports that AI subscription providers are implementing new restrictions on flat-rate plans due to financial unsustainability, with users previously accessing $14,000 worth of API tokens for just $200 monthly. Anthropic is limiting Claude subscribers' access to Fable features, while OpenAI's new GPT-5.6

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Large language models (LLMs) have demonstrated remarkable progress in generating functional code, leading to numerous AI-based coding program tools. However, their reliance on the perplexity objective during both training and inference primarily emphasizes functionality, often at the expense of efficiency--an essential consideration for real-world coding tasks. Perhaps interestingly, we observed that well-trained LLMs inherently possess knowledge about code efficiency, but this potential remains underutilized with standard decoding approaches. To address this, we design strategic prompts to activate the model's embedded efficiency understanding, effectively using LLMs as \textit{efficiency critiques} to guide code generation toward higher efficiency without sacrificing--and sometimes even improving--functionality, all without the need for costly real code execution. Extensive experiments on benchmark datasets (EffiBench, HumanEval+) across multiple representative code models demonstrate up to a 70.6\% reduction in average execution time and a 13.6\% decrease in maximum memory usage, highlighting the computational efficiency and practicality of our approach compared to existing alternatives.

OpenAI proposes handing U.S. government a 5% stake, report says OpenAI has discussed giving the U.S. government a 5% stake as artificial intelligence firms face scrutiny in Washington. OpenAI has discussed giving the U.S. government a 5% stake, the Financial Times reported on Thursday, as artificial intelligence firms face scrutiny in Washington over the likely misuse of advanced models and whether Americans would benefit from the industry's massive valuations. The ChatGPT creator has proposed that other U.S. AI firms also give Washington similar stakes, although it is unclear whether they would agree, the report said, citing two people familiar with the talks. The move follows growing public backlash in the U.S. over AI's potential to cause economic upheaval, including layoffs, and could help OpenAI sweeten ties with an administration that is increasingly taking an active role in regulating the technology. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Zhipu's AI service on the web, dubbed Z.ai. BEIJING/BENGALURU - Since DeepSeek shocked markets early last year with its cheap but powerful artificial intelligence model, global consumers have been faced with a choice: Chinese offerings with lower prices and less capability or OpenAI or Anthropic, which have poured billions into development. A model called GLM-5.2, launched last month by Beijing-based startup Z.ai, may finally be closing that gap in terms of Western interest. GLM-5.2 has Silicon Valley buzzing with its coding and agent capabilities, or the ability to execute complex tasks with minimal prompting, that almost rival leading U.S. offerings at a fraction of the cost, in what some experts are calling a "mini DeepSeek moment." In a time of both misinformation and too much information, quality journalism is more crucial than ever.

We propose a scaling law that takes into account model size and training data while explicitly splitting the latter into training steps and batch size (called three-term law). Fitting the proposed law on a large set of training runs, we find that it correctly recovers the scaling of the optimal batch size. Moreover, because it makes use of training runs with suboptimal batch size, our proposed law can be robustly fit with a significantly smaller amount of training runs. We further show that the three-term law can be used to derive scaling laws for suboptimal batch sizes, and that it matches previous empirical findings related to the critical batch size.

Evaluations of LLM personas via psychometric questionnaires typically rely on aggregate scores, discarding within-instance correlation structure. We test whether this geometric structure is intrinsic or frame-dependent. Constructing within-instance correlation matrices from IPIP-50 responses, we analyze geometry on SPD manifolds under manipulated question orderings in GPT-4o simulating American and Chinese-American personas. We find that persona expression comprises two dissociable components: aggregated features (Big Five scores) degrade under randomization (21% drop) but are frame-robust; geometric features (SPD manifold) collapse under frame misalignment (42% drop) but recover substantially (to 84%) under shared frames, surpassing aggregated features (76%). This collapse-recovery pattern reveals that persona geometry is not intrinsic but a frame-dependent coordination pattern encoding information invisible to aggregation. Our findings establish a dual-nature framework for LLM personas, frame-dependent geometry versus frame-robust aggregates, necessitating frame-aware evaluation and challenging static trait conceptions.