Z.ai's latest AI model release could help companies secure their systems--or find its way into the hands of hackers. Last Friday, the Chinese AI company Z.ai announced a powerful open-weight model that it says is capable of automating cutting-edge coding and cybersecurity tasks almost as well as the best publicly available models from Anthropic and OpenAI . The new model, GLM 5.3, could be a gift for companies looking to secure their systems against attacks, providing a cheaper way to scan for hidden bugs and other weaknesses. Open-weight--or free-to-download--models can be run on one's own hardware and are often significantly less costly than closed models like Claude and GPT. Alongside the new model, Z.ai released OpenVuln, a service for scanning code repositories for vulnerabilities using GLM 5.3.

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Nvidia's open Nemotron 3.5 Lightning model is all about specialized, local agentic AI Our AI Model Release Tracker keeps new models in context with their peers, so you know which are worth your time. AI labs are shipping new models nonstop. Besides being better and faster than their predecessors, not every new model is guaranteed to be a major step change, despite how the company's PR may wax poetic about them. Model strengths really emerge in context: Where are competitor models lacking or excelling? Which models have outstanding specialties, and which are just catching up to industry standards? Our Model Release Tracker helps you make sense of where models stand relative to each other and whether they're worth a deeper look. While we don't test every model or model update on this list, we'll always include the key elements you need to know, along with our hands-on expert test, where applicable.

OpenAI is giving some members of its Daybreak cybersecurity program access to a new model that's less likely to refuse higher-risk tasks. The company is also expanding access to Daybreak to more partners, including Accenture, IBM, CrowdStrike, Cisco, Sophos and Cloudflare. OpenAI says the companies will use the cyber models available through Daybreak to protect their customers. Under the expanded program, Daybreak is available to partners in two tiers. Daybreak Blue gives them access to frontier general-purpose models, including GPT‑5.6 Sol, OpenAI's most advanced one yet.

Meta has released a new slimmed down "open source" AI model that's light enough to run on a single computer, the company announced today. Called Muse Glimmer, it's based on Meta's Spark 1.2 closed model, but is small enough to require just a single GPU for agent-oriented tasks like scheduling and file management. "We designed Muse Glimmer to balance capability against the memory and compute constraints of local hardware," the company wrote. Facebook said that it's making the "weights" that AI systems use to choose responses available to everyone on Hugging Face along with developer documentation. The download is available for free, and users can run the model on their own PCs.

Retrieval systems rely on representations learned by increasingly powerful models. However, due to the high training cost and inconsistencies in learned representations, there is significant interest in facilitating communication between representations and ensuring compatibility across independently trained neural networks. In the literature, two primary approaches are commonly used to adapt different learned representations: affine transformations, which adapt well to specific distributions but can significantly alter the original representation, and orthogonal transformations, which preserve the original structure with strict geometric constraints but limit adaptability. A key challenge is adapting the latent spaces of updated models to align with those of previous models on downstream distributions while preserving the newly learned representation spaces. In this paper, we impose a relaxed orthogonality constraint, namely λ-Orthogonality regularization, while learning an affine transformation, to obtain distribution-specific adaptation while retaining the original learned representations. Extensive experiments across various architectures and datasets validate our approach, demonstrating that it preserves the model's zero-shot performance and ensures compatibility across model updates.

Large language model (LLM) evaluation is increasingly costly, prompting interest in methods that speed up evaluation by shrinking benchmark datasets. Benchmark prediction (also called efficient LLM evaluation) aims to select a small subset of evaluation points and predict overall benchmark performance from that subset. In this paper, we systematically assess the strengths and limitations of 11 benchmark prediction methods across 19 diverse benchmarks. First, we identify a highly competitive baseline: Take a random sample and fit a regression model on the sample to predict missing entries. Outperforming most existing methods, this baseline challenges the assumption that careful subset selection is necessary for benchmark prediction.

The rest of Dyson's promised 2026 vacuum lineup is here, from the new Dyson V16 Piston Animal to an updated version of the favored Dyson V8 Cyclone. Dyson's vacuum lineup had a new look planned for this year . Some of the vacuums have already arrived, like the Dyson PencilVac and Dyson Spot+Scrub robot vacuum, but others we've still been waiting to see. That wait is over as of this month, as Dyson has finally dropped the rest of its anticipated models. Dyson now has three new cordless vacuums you can shop, plus one with a Submarine head variant: the Dyson V16 Piston Animal ($980) and Dyson V16 Piston Animal Submarine ($1,100), the Dyson V10 Konical ($500), and the Dyson V8 Cyclone ($400) .

The ChatGPT Images 2.0 model is here. Our testing shows it's better at creating more detailed images and rendering text, but it still struggles with languages other than English. OpenAI launched a new image generation AI model on Tuesday, dubbed ChatGPT Images 2.0. This model can generate more than one image from a single prompt, like an entire study booklet, as well as output text, including in non-English languages, like Chinese and Hindi. This release is available globally for ChatGPT and Codex users, with a more powerful version available for paying subscribers.

ChatGPT Images 2.0 is better at rendering non-Latin text OpenAI describes it as a step change for image generation models. OpenAI's new ChatGPT Images 2.0 model is now available. A little more than a year after OpenAI gave ChatGPT users the option to create images and designs directly from its chatbot, it's now releasing ChatGPT Images 2.0 . OpenAI describes the new system as a "step change" for image generation models, particularly when it comes to the tool's ability to follow instructions in detail, render dense text and place and relate objects in a scene. For the first time, OpenAI has also built an image model with reasoning capabilities, giving the system the ability to do things like search the web and verify its outputs.

We investigate the space of weights spanned by a large collection of customized diffusion models. We populate this space by creating a dataset of over 60,000 models, each of which is a base model fine-tuned to insert a different person's visual identity.