arXiv:2603.23302v1 Announce Type: cross Abstract: We study nonparametric covariance function estimation for functional data observed with noise at discrete locations on a $d$-dimensional domain. Estimating the covariance function from discretely observed data is a challenging nonparametric problem, particularly in multidimensional settings, since the covariance function is defined on a product domain and thus suffers from the curse of dimensionality. This motivates the use of adaptive estimators, such as deep learning estimators. However, existing theoretical results are largely limited […]

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Riyadh, Saudi Arabia, will host the Global Blockchain Show on June 29 and 30, 2026. The show will bring together some of the world’s most influential and widely recognized voices shaping blockchain, Web3, and the global digital assets ecosystem. The Global Blockchain Show is produced by VAP Group with support from The Times of Blockchain and represents the world’s foremost Global Blockchain Show, highlighting blockchain innovation, investment, and collaboration among industry leaders in both blockchain and Web3. The […]

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In this quiz, you’ll test your understanding of AI Coding Agents Guide: A Map of the Four Workflow Types. By working through this quiz, you’ll revisit the four common workflow types for AI coding agents: IDE, terminal, pull request, and cloud. You’ll also get a chance to review how to match the right workflow to the task in front of you. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick […]

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arXiv:2603.28992v1 Announce Type: new Abstract: We study training-free flow matching between two Gaussian mixture models (GMMs) using explicit velocity fields that transport one mixture into the other over time. Our baseline approach constructs component-wise Gaussian paths with affine velocity fields satisfying the continuity equation, which yields to a closed-form surrogate for the pairwise kinetic transport cost. In contrast to the exact Gaussian Wasserstein cost, which relies on matrix square-root computations, the surrogate admits a simple analytic expression derived […]

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We are entering a strange era of technology where the creators of our most advanced machines are no longer entirely sure what is happening inside them. Recently, Anthropic CEO Dario Amodei admitted that while they don’t know if their AI models are conscious, they are “open to the idea.” Anthropic has even noticed internal activations within their models that mimic human anxiety, prompting them to implement “Model Welfare Assessments.” When the engineers building the future start worrying about […]

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Key Highlights: Countries in the Middle East are increasingly working to bolster plans for future innovations in advanced technology, AI, and other areas. One such example is the UAE. The country is partnering with some of the top tech giants from the U.S., like Microsoft and OpenAI, to make it more efficient in the AI sector. More recently, Microsoft announced $15.2 billion investment in the UAE to expand its AI footprint in the country. That’s not all; the […]

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Prediction markets reported their strongest week, with Kalshi hitting a notional volume of $3.54 billion while Polymarket recorded $2.48 billion; the industry’s combined notional volume crossed $6.5 billion, setting a new overall high, according to DeFi Rate. Image source: DeFi Rate This surge coincides with a positive outlook on the industry by Bank of America Analysts who expect sports-related events contracts to hit $1.1 trillion per year. Bernstein also estimates that total market volumes will reach $240 billion […]

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A recurring concern I’ve seen regarding LLMs for programming is that they will push our technology choices towards the tools that are best represented in their training data, making it harder for new, better tools to break through the noise. This was certainly the case a couple of years ago, when asking models for help with Python or JavaScript appeared to give much better results than questions about less widely used languages. With the latest models running in […]

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