Artificial Intelligence, and more specifically, Generative AI, is emerging as an important technology. Over the past few years a number of prominent generative AI technologies have been developed and have received widespread attention; ranging from text generation via large language models (ChatGPT, Claude, Llama, Gemini, DeepSeek, Qwen, etc), image generation via diffusion models (Dall-E, Stable Diffusion, etc), to scientific generative AI techniques used for protein generation (e.g., Watson et al. 2023, etc), DNA sequence editing (e.g., Ruffolo et al. 2025, etc), among others. Such methods have been quickly adopted by end users and institutions, both via direct usage, as well as integrated in other tools such as code assistants and web search agents. The scientific community has shown significant interest in using generative AI models, achieving a number of breakthrough results (see e.g., Davies et al. 2021, Hayes et al. 2025, etc), culminating in a 2024 Nobel Prize in Chemistry awarded in part for work with a significant component in protein structure design and generation (The Royal Swedish Academy of Sciences 2024). Yet, the adoption of generative AI (GenAI) methods more generally is hindered by their lack of reliability (see e.g., Farquhar et al. 2024, Strauss et al. 2025, Manduchi et al. 2025, etc).

Today on, we talk about why the AI industry is investing in the development of humanoid robots, and what that means for us non-robots. This week, WIRED learned that OpenAI is ramping up its efforts in robotics--specifically, by hiring researchers who work on AI systems for humanoid robots. Humanoids, robots built to resemble us and perform daily tasks, were famous for their clumsiness just a few years ago. Senior writer Will Knight tells us about how that's rapidly changing on today's episode cohosted by Michael Calore and senior correspondent Kylie Robison. Write to us at uncannyvalley@wired.com . You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link . My Lord and Savior Lauren Goode, I'm so happy to fill in for her, but I miss her dearly. Also on the show this week, we have Will Knight, our AI expert at WIRED. Welcome back to the show, Will. Given the topic of today's episode, I want to ask you both. Do you have a favorite robot movie? Mine is The Iron Giant. I was just looking up when that came out because I swear I watched it on VHS as a kid. Yeah, I loved that movie. It's got a very sad ending. The robot is no longer.

Jon Stewart leads defense of Jimmy Kimmel as late night hosts unite to mock Trump's'censorship' Trump just humiliated Harry and Meghan with two brutal words... but even more embarrassing is the reason they're having to stay silent: MAUREEN CALLAHAN Disturbing full story of singer D4vd's relationship with girl, 13, found dismembered in his Tesla... as creepy messages, songs and links to stars are exposed Utter chaos breaks out backstage at The View over Jimmy Kimmel: Hosts at war and staff in fear... as network bosses impose strict new'rule' The strain shows on Jimmy Kimmel as he emerges for first time after show's shock cancellation Queen Camilla appears to'pull rank' as Kate chats animatedly with Melania during State visit - and ushers Princess back towards William Seth Meyers responds to Jimmy Kimmel cancellation with dose of mockery for Trump: 'A great president, an even better golfer' President of America's biggest university forced to step down over'transgender indoctrination' Starbucks responds after barista refuses to write'Charlie Kirk' on customer's cup due to'policy' Millions under tsunami threat as fallout from monster 7.8 earthquake threatens US Woman, 84, horrified after stomach-churning discovery in Morrisons juice: 'Dead snake' slithered out of carton Two elderly women were left horrified and upset when they found a'dead snake' in a carton of fruit juice--and refuse to believe supermarket bosses' claim that the foot-long gelatinous entity is merely a string of mould. Betty Richards, 84, bought a carton of apple and mango juice from the Armthorpe branch of Morrisons as a treat for her best friend of twenty years, Julie Bircumshaw, also 84. The BBC reports that Ms Bircumshaw noticed some'bits of black' around the opening of the 1L carton, but after tasting the juice, thought it was fine to drink. When Ms Richards popped over to see her friend at home in Doncaster a week later, she was told about the discolouration around the nozzle. She was concerned, and decided to take a closer look at the £1.35 carton--which was almost empty.

In 1907, Duncan MacDougall put dying patients on a scale. William Blake's 1805 illustration for Scottish poet Robert Blair's poem The Grave imagines the soul rising from the body at death. Breakthroughs, discoveries, and DIY tips sent every weekday. It's a little complicated to weigh a dying person on a hospital bed, but that didn't matter to Duncan MacDougall. In the early 20th century, MacDougall's unique, purpose-built scale was ready to receive test subjects.

Not only that, but information is suddenly everywhere, people are losing trust in news outlets and there is a growing exhaustion with crisis reporting. Serious journalism is under greater pressure than ever before. How is DER SPIEGEL reacting? Quite some time ago, an email landed in my inbox from a former DER SPIEGEL editor. He wanted to pitch me a story and, as I quickly realized, stir things up a bit. Then, a couple of months ago, he approached me personally on the sidelines of an event in Hamburg, perhaps because I still hadn't shown much interest. He said we should meet up for a tea or something harder." He is plagued, he told me, each and every week by the wrenching, agonizing decision as to whether he should cancel his subscription to DER SPIEGEL - dismayed by what he described as an incipient decline under the dictates of late-capitalist sales imperatives" he had observed at his former employer.

Located in China, Juno is a 17-country collaboration that will try to detect neutrinos and antineutrinos to learn more about their mass. Juno's sphere (bottom left) and photomultipliers (top right) for neutrino detection. Located 700 meters underground near the city of Jiangmen in southern China, a giant sphere--35 meters in diameter and filled with more than 20,000 tons of liquid--has just started a mission that will last for decades. This is Juno, the Jiangmen Underground Neutrino Observatory, a new, large-scale experiment studying some of the most mysterious and elusive particles known to science. Neutrinos are the most abundant particles in the universe with mass.

Trump claims Biden administration investigation into Turning Point tried to force Charlie Kirk'out of business' Dem-run city's iconic mall teeters on collapse as 93% of stores vacant after crime-wave causes stores to flee Extraordinary measures jail put in motion to keep Charlie Kirk assassin suspect alive: 'It's severe' Texas AG's mistress' shock new life after sex scandal was exposed Airbnb guest says he was'shaken down' for $10K after selfie inside California's viral'Invisible House' Astonishing moment Charlie Kirk's wife Erika loses Miss USA pageant to pro-trans rival... as Trump watches on Christian Brueckner walks free: Madeleine McCann chief suspect leaves prison... with prosecutors fearing he will immediately flee the country and never be seen again Psychiatrist reveals bombshell'motive' for Charlie Kirk's assassination: 'Fits the profile' The raging jealousy that destroyed Nashville's hottest young couple: 'Up to no good' Air Force One jumbo carrying Donald Trump to Britain'is involved in close encounter mid-air drama with jet on same altitude ordered to change course by frantic air controllers' Charlie Kirk's final video message is released as top conservatives prepare to speak at his memorial this weekend Dancing with the Stars descends into CHAOS: Foul-mouthed backstage rants erupt over'trainwreck' celebs... as one star goes'missing' and ugly rape allegations resurface Rapper DaBaby ignites backlash with music video depicting slain Ukrainian refugee's fatal Charlotte stabbing in controversial reenactment'Give me a f***ing break': Searing response of Elon Musk's trans daughter Vivian to my questions about Charlie Kirk's assassination... in an interview that takes a tearful turn ABC News reporter Matt Gutman blasted for hailing'very touching' texts between Charlie Kirk suspect and trans lover Meet the'world's cutest sea monster': Scientists discover an adorable snailfish nearly 10,800ft underwater - as amazed viewers compare it to a Pokémon When you go this deep, you'd expect any sign of life to be pretty terrifying. So scientists were delighted to discover an adorable new species of snailfish thousands of feet below the ocean's surface. The large-eyed pink creature was first detected in 2019 by researchers who were exploring the seafloor off California using a remotely operated vehicle at a depth of 3,268m (10,722ft). They came across this individual, an adult female 9.2cm (3.6 inches) long, happily swimming along amongst the crushing pressure, frigid cold and perpetual darkness. New analysis now reveals this animal was a species previously unknown to science - and has been named the bumpy snailfish (Careproctus colliculi).

Large Language Models (LLMs) are increasingly deployed in roles requiring nuanced psychological understanding, such as emotional support agents, counselors, and decision-making assistants. However, their ability to interpret human personality traits, a critical aspect of such applications, remains unexplored, particularly in ecologically valid conversational settings. While prior work has simulated LLM "personas" using discrete Big Five labels on social media data, the alignment of LLMs with continuous, ground-truth personality assessments derived from natural interactions is largely unexamined. To address this gap, we introduce a novel benchmark comprising semi-structured interview transcripts paired with validated continuous Big Five trait scores. Using this dataset, we systematically evaluate LLM performance across three paradigms: (1) zero-shot and chain-of-thought prompting with GPT-4.1 Mini, (2) LoRA-based fine-tuning applied to both RoBERTa and Meta-LLaMA architectures, and (3) regression using static embeddings from pretrained BERT and OpenAI's text-embedding-3-small. Our results reveal that all Pearson correlations between model predictions and ground-truth personality traits remain below 0.26, highlighting the limited alignment of current LLMs with validated psychological constructs. Chain-of-thought prompting offers minimal gains over zero-shot, suggesting that personality inference relies more on latent semantic representation than explicit reasoning. These findings underscore the challenges of aligning LLMs with complex human attributes and motivate future work on trait-specific prompting, context-aware modeling, and alignment-oriented fine-tuning.

The detection and grounding of manipulated content in multimodal data has emerged as a critical challenge in media forensics. While existing benchmarks demonstrate technical progress, they suffer from misalignment artifacts that poorly reflect real-world manipulation patterns: practical attacks typically maintain semantic consistency across modalities, whereas current datasets artificially disrupt cross-modal alignment, creating easily detectable anomalies. To bridge this gap, we pioneer the detection of semantically-coordinated manipulations where visual edits are systematically paired with semantically consistent textual descriptions. Our approach begins with constructing the first Semantic-Aligned Multimodal Manipulation (SAMM) dataset, generated through a two-stage pipeline: 1) applying state-of-the-art image manipulations, followed by 2) generation of contextually-plausible textual narratives that reinforce the visual deception. Building on this foundation, we propose a Retrieval-Augmented Manipulation Detection and Grounding (RamDG) framework. RamDG commences by harnessing external knowledge repositories to retrieve contextual evidence, which serves as the auxiliary texts and encoded together with the inputs through our image forgery grounding and deep manipulation detection modules to trace all manipulations. Extensive experiments demonstrate our framework significantly outperforms existing methods, achieving 2.06\% higher detection accuracy on SAMM compared to state-of-the-art approaches. The dataset and code are publicly available at https://github.com/shen8424/SAMM-RamDG-CAP.

As large language models (LLMs) become increasingly embedded in products used by millions, their outputs may influence individual beliefs and, cumulatively, shape public opinion. If the behavior of LLMs can be intentionally steered toward specific ideological positions, such as political or religious views, then those who control these systems could gain disproportionate influence over public discourse. Although it remains an open question whether LLMs can reliably be guided toward coherent ideological stances and whether such steering can be effectively prevented, a crucial first step is to develop methods for detecting when such steering attempts occur. In this work, we adapt a previously proposed statistical method to the new context of ideological bias auditing. Our approach carries over the model-agnostic design of the original framework, which does not require access to the internals of the language model. Instead, it identifies potential ideological steering by analyzing distributional shifts in model outputs across prompts that are thematically related to a chosen topic. This design makes the method particularly suitable for auditing proprietary black-box systems. We validate our approach through a series of experiments, demonstrating its practical applicability and its potential to support independent post hoc audits of LLM behavior.