OpenAI's ChatGPT showed left-leaning bias 80% of the time, according to a new study testing AI chatbots including Google Gemini, Anthropic Claude, and Grok for political bias.

A wiggly robot in Japan could help explain why we find eating certain foods so taboo. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. The edible agent in the study was made from edible materials and designed to sway from side to side in synchrony with vocalizations. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

OpenAI had been working with the US government over a preview of the GPT 5.6 model. OpenAI had been working with the US government over a preview of the GPT 5.6 model. Sam Altman announces limited preview of GPT 5.6 in move that echoes launch of Anthropic's Mythos OpenAI is staggering the release of its latest AI model after a request from the US government, in a move echoing the launch of Anthropic's Mythos product. Sam Altman, the chief executive of the company behind ChatGPT, told staff this week that GPT 5.6 would be released in a limited preview to a small group of partners, according to the tech publication The Information. Altman said the federal government had asked for a staggered release.

Since the first robot-assisted surgery was performed, over 40 years ago, major advances in robotics, computer vision and artificial intelligence have fundamentally changed medicine and healthcare. Innovative new technologies are already aiding skilled medical professionals in diagnosis, surgery, rehabilitation and beyond. But many questions remain: What ethical issues arise as medical tools become increasingly autonomous? How do we regulate technologies that can learn and change over time? And how can we ensure that cutting-edge medical devices are accessible to all?

Children and people with mental health disorders are especially vulnerable.

Large language model (LLM) agents for web interfaces have advanced rapidly, yet open-source systems still lag behind proprietary agents. Bridging this gap is key to enabling customizable, efficient, and privacy-preserving agents. Two challenges hinder progress: the reproducibility issues in RL and LLM agent training, where results often depend on sensitive factors like seeds and decoding parameters, and the focus of prior work on single-step tasks, overlooking the complexities of web-based, multi-step decision-making. We address these gaps by providing a statistically driven study of training LLM agents for web tasks. Our two-stage pipeline combines imitation learning from a Llama 3.3 70B teacher with on-policy fine-tuning via Group Relative Policy Optimization (GRPO) on a Llama 3.1 8B student. Through 240 configuration sweeps and rigorous bootstrapping, we chart the first compute allocation curve for open-source LLM web agents. Our findings show that dedicating one-third of compute to teacher traces and the rest to RL improves MiniWoB++ success by 6 points and closes 60\% of the gap to GPT-4o on WorkArena, while cutting GPU costs by 45\%. We introduce a principled hyperparameter sensitivity analysis, offering actionable guidelines for robust and cost-effective agent training.

Elie observed and recorded the sounds the zebra finches made and classified the calls according to the situation and the bird that made them. Elie observed and recorded the sounds the zebra finches made and classified the calls according to the situation and the bird that made them. A scientist who decoded the dictionary that a bird uses to communicate has won a $100,000 prize for making progress towards a world in which humans can talk to the animals - without being met with a blank response. Dr Julie Elie at the University of California, Berkeley, was awarded the 2026 Coller-Dolittle prize for two-way interspecies communication after working out the 11 core calls in the zebra finch vocabulary and their meanings. Her work revealed how the birds announce who they are and what they are doing, and recognise one another regardless of what they are saying by using individual signatures.

Takeda Pharmaceutical is targeting a return on equity of at least 5% over that time, the company's newly appointed Chief Executive Officer Julie Kim said at her first news conference after assuming the top job this week. Takeda Pharmaceutical's newly appointed Chief Executive Officer Julie Kim says the company will return to growth in two to three years as it gears up for a wave of product launches. The company is targeting a return on equity of at least 5% over that time, Kim said at her first news conference after assuming the top job this week. Takeda is planning three major launches, including narcolepsy drug Oveporexton and psoriasis medication Zasocitinib in the next 12 months, while advancing a pipeline of five additional late-stage assets. It will ensure resiliency of its core therapeutic and business areas, which makes up more than half of its revenue. The company is also looking to leverage artificial intelligence, particularly in research and development, where it can accelerate the time it takes to run through pre-clinical work and improve decision making, according to Kim.

Incomplete multi-view data, where certain views are entirely missing for some samples, poses significant challenges for traditional multi-view clustering methods. Existing deep incomplete multi-view clustering approaches often rely on static fusion strategies or two-stage pipelines, leading to suboptimal fusion results and error propagation issues. To address these limitations, this paper proposes a novel incomplete multi-view clustering framework based on Hierarchical Semantic Alignment and Cooperative Completion (HSACC). HSACC achieves robust cross-view fusion through a dual-level semantic space design. In the low-level semantic space, consistency alignment is ensured by maximizing mutual information across views. In the high-level semantic space, adaptive view weights are dynamically assigned based on the distributional affinity between individual views and an initial fused representation, followed by weighted fusion to generate a unified global representation. Additionally, HSACC implicitly recovers missing views by projecting aligned latent representations into high-dimensional semantic spaces and jointly optimizes reconstruction and clustering objectives, enabling cooperative learning of completion and clustering. Experimental results demonstrate that HSACC significantly outperforms state-of-the-art methods on five benchmark datasets. Ablation studies validate the effectiveness of the hierarchical alignment and dynamic weighting mechanisms, while parameter analysis confirms the model's robustness to hyperparameter variations.

Nick Cave and Kylie Minogue are among Australian artists reportedly found in datasets used to train artificial intelligence. Nick Cave and Kylie Minogue are among Australian artists reportedly found in datasets used to train artificial intelligence. 'It's all just rendered useless', Something For Kate's Paul Dempsey says as AI scrapes millions of songs to learn how to make music Paul Dempsey and Bernard Fanning are among big-name Australian musicians upset that their original songs have been found in datasets used to train artificial intelligence. A dataset search tool recently created by US publication The Atlantic reveals millions of creative works have been scraped from the internet to train the disruptive technology. It includes a vast catalogue of work by Australian artists, with tunes by Kylie Minogue, Powderfinger, Nick Cave and Jimmy Barnes, and novels by Thomas Keneally and Peter Carey.