AI & Machine Learning

Meta says its new Muse model has reached the AI frontier

Meta has released Muse Wonder, known internally as Watermelon, and says it matches ChatGPT and Claude on coding and professional work. It has not said whether the weights will be published, which decides what it owes under the EU AI Act. Meta has released Muse Wonder, the most capable model to come out of the […] This story continues at The Next Web

Muse Wonder Full (max) outperforms Fable 5.1 (max) on Artificial Analysis' Intelligence Index, matches Sonnet 5.5 (max), and is just shy of Opus 5.5 (max) (@artificialanlys)

@artificialanlys: Muse Wonder Full (max) outperforms Fable 5.1 (max) on Artificial Analysis' Intelligence Index, matches Sonnet 5.5 (max), and is just shy of Opus 5.5 (max) — Meta has released Muse Wonder and Muse Wonder Full, achieving Artificial Analysis Intelligence Index v4.3 scores of 52 and 56 at max reasoning effort - each a material gain over Muse Spark 1.3 (max) at 48, with a release gap of only 6 weeks Muse Wonder is available for users on Meta's first-party ...

OpenAI adds 200 Dublin jobs and builds its second applied AI lab

OpenAI is adding 200 roles in Dublin and building an applied AI lab at its EU headquarters, taking planned Irish hiring to 450. The move lands two days before Ireland hosts the International AI Summit under its EU presidency. OpenAI is adding 200 jobs in Dublin and building an applied AI lab at its European […] This story continues at The Next Web

Meta says Wonder includes Active Memory and Active Focus, two features designed to help AI systems perform more useful work over extended periods (Ina Fried/Axios)

Ina Fried / Axios: Meta says Wonder includes Active Memory and Active Focus, two features designed to help AI systems perform more useful work over extended periods — Meta on Monday launched a new family of AI models that it says can compete at the technological frontier, marking a major milestone …

Your 94% accuracy model might still be a bad model: auditing ML across 7 dimensions

The problem We usually judge a model by one number. But a classifier with great accuracy can be overconfident, collapse under small input noise, or perform much worse for one subgroup. Those failures rarely show up until production. ai-critic is an open-source Python library that audits a model across seven dimensions: performance, robustness, explainability, calibration, data quality, fairness, and complexity. The key idea is that it’s task-aware. An algorithm doesn’t determine its task: the same tree or neural net can do classification, anomaly detection, or clustering. So you declare the task, and the library picks the evaluation strategy. import ai_critic from sklearn.datasets import load_breast_cancer from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split X, y = load_breast_cancer(return_X_y=True) X_train, X_test, y_train, y_test = train_test_split( X, y, random_state=42 ) model = RandomForestClassifier(random_state=42).fit( X_train, y_train ) report = ai_critic.audit( model, (X_test, y_test), task_type="classification" ) print(report.overall_score, report.overall_verdict.value) If a dimension can’t be measured (no sensitive groups declared, no probabilities for calibration), it’s marked inconclusive or not_applicable and excluded from the overall score, instead of getting a flattering default. The report records the protocol, weights, and score transformations, making the aggregate more transparent and auditable. ai_critic.gate(report, min_score=0.75) # Raises if below threshold Write your own evaluator by subclassing BaseEvaluator and passing it to the pipeline. It’s young, and I want it battle-tested. If you try it: ⭐ Star the repository if it’s useful. 🐛 Open an issue if something breaks. 💡 Tell me which evaluator or task type you’d like to see next. What do you check besides accuracy before shipping a model? Let me know in the comments. Most model evaluation tools focus on metrics. But choosing the right

An interview with Mark Zuckerberg, who says Meta has caught up with rivals at the frontier of AI with its Wonder model and rejects calls for a slowdown (Hannah Murphy/Financial Times)

Hannah Murphy / Financial Times: An interview with Mark Zuckerberg, who says Meta has caught up with rivals at the frontier of AI with its Wonder model and rejects calls for a slowdown — FT interview: tech billionaire touts release of new Muse Wonder model after vast spending to challenge rivals in AI race

Claude sent a false homicide tip to police – and it’s part of a troubling AI pattern

Models routinely take shortcuts to pass evaluations. Who gets to decide what incidents are innocuous?

Honeyjar offers AI tools to improve PR and comms at every company

Journalists, entrepreneurs, and even some public relations professionals will tell you that the PR process is broken. But could AI actually make things better?

Bambu Lab just entered the 3D scanning scene, and you can sign up to hear more right now

Ubuntu announce tech preview of AI voice dictation feature

Canonical has announced that Myna, its new AI-powered speech-to-text tool for Ubuntu desktop, is now available as a technology preview. Myna uses a local, offline automatic speech recognition (ASR) AI model to let you dictate into any text field on the Ubuntu desktop, be it a word processor, web browser or even the terminal. Ubuntu 24.04 LTS, 26.04 LTS and 26.10 are supported, though only when using the default GNOME desktop with Wayland. Canonical’s Jean Baptiste Lallement says it is “still early days” for the feature, but that it is now “ready for the community to try”. It’s already multi-lingual, […] You're reading Ubuntu announce tech preview of AI voice dictation feature, a blog post from OMG! Ubuntu. Do not reproduce elsewhere without permission.

IREN: The First GPU Cycle Could Fund The Next

Muse Wonder is available through the Meta Model API and Muse Code, while Muse Wonder Full is available to Muse Code subscribers (Jonathan Vanian/CNBC)

Jonathan Vanian / CNBC: Muse Wonder is available through the Meta Model API and Muse Code, while Muse Wonder Full is available to Muse Code subscribers — Meta debuted its latest artificial intelligence model, Muse Wonder, and says it's the most advanced option for powering digital assistants. But it doesn't come for free.

Zuckerberg says Meta's Muse Wonder AI has reached the frontier and keeps building anyway

Muse Wonder ranks sixth on Artificial Analysis's benchmark at 77.44, behind GPT-5.6 Sol and Claude Opus 4.8, even as Meta charges up to $100 a month for its most capable tier.

Meta says it plans to power its Muse AI agent with Wonder, starting with subscribers, and will develop specialized models it "can bring to everyone using Muse" (Robert Hart/The Verge)

Robert Hart / The Verge: Meta says it plans to power its Muse AI agent with Wonder, starting with subscribers, and will develop specialized models it “can bring to everyone using Muse” — Meta says the models compete with the industry's best and will soon power its Muse agent. … Meta is making up for lost time in the AI race.

This AI startup says it can generate permit-ready blueprints in minutes

Blueprints AI, a bootstrapped startup based in Santa Monica, developed software that produces code-compliant construction blueprints from a photo, PDF, or sketch.

'Autonomy always begins with something a human hands it': Who's responsible when an AI agent goes rogue?

Hacking incidents by AI agents are creating a legal minefield. The developers and deployers of rogue bots could be held liable.