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Technology Engineering The world's first nuclear clocks are ticking Nuclear clocks may surpass their atomic forebears and help solve the universe's most difficult mysteries. 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. Timekeeping has officially entered its nuclear age. Two independent teams, one in Vienna, Austria and another in Beijing, China have built working thorium-229 nuclear clock prototypes . Rather than track changes in an atom's electrons the way that current atomic clocks do, these nuclear versions use a laser that's tuned to the frequency where a thorium nucleus flips between two energy states for potentially even more accurate time keeping.

The 2026 IEEE International Conference on Robotics & Automation (ICRA) was held in Vienna from the 1 - 5 June. The event brought together researchers and industry professionals with expertise spanning many different aspects of robotics. IEEE have made the keynote and plenary talk recordings available to watch . You can also catch the panel discussions and keynote tutorials. Panel 4 - Publish or Perish: Surviving the Paper Deluge - Is AI the solution?

Kamala Harris is being mocked after a resurfaced clip of her rambling AI explanation followed her post calling on Donald Trump to pursue a treaty with China on artificial intelligence.

Christine Lagarde spoke in Vienna about Europe and AI on Monday. Christine Lagarde spoke in Vienna about Europe and AI on Monday. Europe must build own AI or risk getting cut off by US or China, says ECB's Lagarde Central bank chief says continent's AI dependency could give trade partners unprecedented leverage in negotiations Europe must develop its own AI technology and build more datacentres in order to nullify the threat of being cut off by the US or China, according to the president of the European Central Bank . Christine Lagarde said the continent needed AI models - the technology that powers AI tools such as chatbots - that were "good enough" to carry out most tasks and run from domestic datacentres. If Europe invests in its own AI tech, said Lagarde, "the threat of being cut off loses its force".

Sam Altman and Elon Musk have backed calls from Anthropic's Dario Amodei to put brakes on'reckless' AI development

The AI-based program AlphaFold predicts a protein's 3D structure with remarkable accuracy. However, it tends to reduce heterogeneous structures to a single dominant conformation, or shape, and overlooks experimental conditions that can alter local structure. Researchers at the Institute of Science and Technology Austria (ISTA) and international collaborators have now developed a way to guide AlphaFold with experimental data. Their approach, published in, paves the way for improved future predictive models. Our understanding of molecular structures is considerably influenced by X-ray crystallography--a technique that has served as structural biology's central pillar for many decades.

From the 1st-5th June, the robots descended on Vienna. The 2026 IEEE International Conference on Robotics & Automation (ICRA) brought together the top minds in robotics for one short week to showcase the latest technologies, form new collaborations, and exchange ideas. Held at the Messe Wien, a stone's throw from the bank of the Danube, ICRA proved to be equal parts technological marvel and thought-provoking discussion. The host venue for ICRA 2026: Messe Wien, also known as VIECON. My week at ICRA began with the 2nd ICRA 2026 Workshop on Robot Ethics: Ethical, Legal and User Perspectives in Robotics & Automation (WOROBET) .

Speculative decoding accelerates language model inference by using a fast drafter to propose candidate tokens that are then verified by a larger target model. Existing theory largely studies the stochastic, distribution-preserving setting, where the goal is to exactly sample from the target distribution. In contrast, many practical systems use greedy decoding, relaxed acceptance rules, or tree-based candidate sets, where success is governed by local ranking and threshold events rather than exact distributional equality. We develop a theory for these regimes. We identify that many common acceptance criteria have rejection regions that can be characterized as lower level sets of the target distribution. For these, we characterize the exact KL divergence required for rejection yielding exact certificates and sharp margin-based bounds for strict greedy decoding, additive and multiplicative relaxed acceptance, top-(m) relaxed criteria, and entropy-thresholded acceptance. We then extend the framework to greedy tree decoding, deriving exact and margin-only certificates for when the target greedy token remains covered by the drafter's top-(m) candidates. Finally, we evaluate the resulting certificates on Qwen3 models, showing that relaxed and tree-based criteria substantially enlarge the region of certified acceptance, especially on decoding steps with low target model distribution margin. These results complement existing distribution-preserving analyses of speculative decoding by characterizing the deterministic local acceptance events common in practical inference systems.

Visual assessment of residual plots is a common approach for diagnosing linear models, but it relies on manual evaluation, which does not scale well and can lead to inconsistent decisions across analysts. The lineup protocol, which embeds the observed plot among null plots, can reduce subjectivity but requires even more human effort. In today's data-driven world, such tasks are well suited for automation. We present a new R package that uses a computer vision model to automate the evaluation of residual plots. An accompanying Shiny application is provided for ease of use. Given a sample of residuals, the model predicts a visual signal strength (VSS) and offers supporting information to help analysts assess model fit.