We simplify space binding by focusing on two core components, a single encoder per modality and high-quality data; enabling training state-of-the-art models on a single GPU in a few hours as opposed to multiple days. We present EBind, an Easy, data-centric, and parameter-efficient method to Bind the embedding spaces of multiple contrastive models. We demonstrate that a simple 1.8B-parameter image-text-video-audio-3D model can outperform models 4 to 17x the size. The key to achieving this is a carefully curated dataset of three complementary data sources: i) 6.7M fully-automated multimodal quintuples sourced via SOTA retrieval models, ii) 1M diverse, semi-automated triples annotated by humans as negative, partial, or positive matches, and iii) 3.4M pre-existing captioned data items. We use 13 different evaluations to demonstrate the value of each data source. Due to limitations with existing benchmarks, we further introduce the first high-quality, consensus-annotated zero-shot classification benchmark between audio and PCs. In contrast to related work, we will open-source our code, model weights, and datasets.

Reliable behavior control is central to deploying Large Language Models (LLMs) on the web. Activation steering offers a tuning-free route to align attributes (e.g., truthfulness) that ensure trustworthy generation. Prevailing approaches rely on coarse heuristics and lack a principled account of where to steer and how strongly to intervene. To this end, we propose P osition-wise I njection with eX act E stimated L evels (PIXEL), a position-wise activation steering framework that, in contrast to prior work, learns a property-aligned subspace from dual views (tail-averaged and end-token) and selects intervention strength via a constrained geometric objective with a closed-form solution, thereby adapting to token-level sensitivity without global hyperparameter tuning. PIXEL further performs sample-level orthogonal residual calibration to refine the global attribute direction and employs a lightweight position-scanning routine to identify receptive injection sites. We additionally provide representation-level guarantees for the minimal-intervention rule, supporting reliable alignment. Across diverse models and evaluation paradigms, PIXEL consistently improves attribute alignment while preserving model general capabilities, offering a practical and principled method for LLMs' controllable generation. To meet this need, a growing body of work has focused on post-training control mechanisms, which aim to adjust model behavior without retraining the entire model.

Stranger Things actress Sadie Sink will make her West End debut in a new production of Romeo & Juliet. British actor Noah Jupe, best known for his role in horror series A Quiet Place, will play the Romeo to her Juliet. They will portray the star-crossed lovers on stage at the Harold Pinter Theatre in London from March 2026, as first reported by US outlet Deadline. Award-winning writer and director Robert Icke, who has previously adapted George Orwell's 1984 and Chekhov's Uncle Vanya, will direct the project. US actress Sadie, 23, rose to fame after joining the cast of Stranger Things in series two as as Max Mayfield.

Neural networks are capable of translating between languages--in some cases even between two languages where there is little or no access to parallel translations, in what is known as Unsupervised Machine Translation (UMT).

'Palantir is the embodiment, in a lot of ways, of him' Alex Karp. 'Palantir is the embodiment, in a lot of ways, of him' Alex Karp. 'Fear really drives him': is Alex Karp of Palantir the world's scariest CEO? His company is potentially creating the ultimate state surveillance tool, and Karp has recently been on a striking political and philosophical journey. I n a recent interview, Alex Karp said that his company Palantir was "the most important software company in America and therefore in the world". He may well be right.

A natural way to unlock particular capabilities is to improve this training data.

Former Harvard president Larry Summers has said he will step back from public commitments after his emails with disgraced financier Jeffrey Epstein were made public. I am deeply ashamed of my actions and recognise the pain they have caused, he said in a statement to CBS News, the BBC's US partner. I take full responsibility for my misguided decision to continue communicating with Mr Epstein. Emails released by Congress last week show Summers, a former US treasury secretary, communicated with Epstein until the day before the paedophile's 2019 arrest for sex trafficking minors. On Tuesday, House members are expected to vote on releasing all files related to the late sex offender.

The UK is to use artificial intelligence (AI) to tackle the rising numbers of infections that have become resistant to treatment. The project - a collaboration between the Fleming Initiative and the pharmaceutical company GSK - is a battle between superbugs and supercomputers. It aims to speed up the discovery of fresh antibiotics and deliver new ways of killing other threats, including deadly fungal infections. Overusing antibiotics drives bacteria to evolve resistance to infections, which means new drugs are a priority. Drug-resistant infections are a growing problem - one known as the silent pandemic.