Why the seeds of the next civilization are already growing, and how to see them. What if the chaos around us isn’t collapse, but transformation? Michel Bauwens has spent decades mapping the edges of change. From peer-to-peer networks to the commons, from medieval guilds to distributed autonomous organizations, he’s been tracking something most people miss: the seeds of a new civilization, already growing underneath the noise. Some people might call Bauwens a unicorn, because he does not fit […]

Ver mais

arXiv:2601.22315v1 Announce Type: new Abstract: Many real-world optimization problems involve an expensive ground-truth oracle (e.g., human evaluation, physical experiments) and a cheap, low-fidelity prediction oracle (e.g., machine learning models, simulations). Meanwhile, abundant offline data (e.g., past experiments and predictions) are often available and can be used to pretrain powerful predictive models, as well as to provide an informative prior. We propose Prediction-Augmented Gaussian Process Upper Confidence Bound (PA-GP-UCB), a novel Bayesian optimization algorithm that leverages both oracles and […]

Ver mais

arXiv:2603.02417v1 Announce Type: new Abstract: We develop a Fisher-geometric theory of stochastic gradient descent (SGD) in which mini-batch noise is an intrinsic, loss-induced matrix — not an exogenous scalar variance. Under exchangeable sampling, the mini-batch gradient covariance is pinned down (to leading order) by the projected covariance of per-sample gradients: it equals projected Fisher information for well-specified likelihood losses and the projected Godambe (sandwich) matrix for general M-estimation losses. This identification forces a diffusion approximation with Fisher/Godambe-structured volatility […]

Ver mais

For two decades, product design has revolved around a stable premise: users initiate, software responds. Even as AI crept into products such as recommendation engines, predictive text, and fraud detection, the interface still framed intelligence as reactive. AI agents break that contract. An agent does not wait for instruction. It monitors context, forms intentions, takes actions, and adapts its strategy over time. It delegates to APIs, coordinates across systems, and sometimes executes decisions without asking first. In other […]

Ver mais

Open-pit mining relies heavily on visual inspection to identify indicators of slope instability such as surface cracks. Early identification of these geotechnical hazards allows for the implementation of safety interventions to protect both workers and assets in the event of slope failures or landslides. While computer vision (CV) approaches offer a promising avenue for autonomous crack detection, their effectiveness remains constrained by the scarcity of labelled geotechnical datasets. Deep learning (DL) models require large amounts of representative training […]

Ver mais

arXiv:2601.09729v1 Announce Type: new Abstract: Financial reports and earnings communications contain large volumes of structured and semi structured information, making detailed manual analysis inefficient. Earnings conference calls provide valuable evidence about a firm’s performance, outlook, and strategic priorities. The manual analysis of lengthy call transcripts requires substantial effort and is susceptible to interpretive bias and unintentional error. In this work, we present a hybrid summarization framework that combines extractive and abstractive techniques to produce concise and factually reliable […]

Ver mais

If you apply what’s on this email to the T, you can rebuild yourself in six months. Bold statement? Yes. But give me a few minutes and I’ll gift you the EXACT blueprint for: A different body. A different mind. A different baseline of energy. A different standard for what you tolerate. A different life altogether. And this is not manifestation. This is engineering, and this is what we do here. We will work on: identity, body, skills, environment, […]

Ver mais

arXiv:2406.07746v3 Announce Type: replace Abstract: We propose a computationally efficient algorithm that achieves anytime regret of order $mathcal{O}(sqrt{t})$, with explicit dependence on the system dimensions and on the solution of the Discrete Algebraic Riccati Equation (DARE). Our approach builds on the SDP-based framework of cite{cohen2019learning}, using an appropriately tuned regularization and a sufficiently accurate initial estimate to construct confidence ellipsoids for control design. A carefully designed input-perturbation mechanism is incorporated to ensure anytime performance. We develop two variants […]

Ver mais

Diminished Reality (DR)—the ability to visually remove real-world objects from a live Augmented Reality (AR) feed—is essential for reducing cognitive load and decluttering workspaces. However, existing techniques face a critical challenge: removing an object creates a visual void (“hole”) that must be filled with a plausible background. Traditional 2D inpainting methods lack temporal consistency, causing the background to flicker or slide as the user moves. In this paper, we propose Clean-Splat, a novel framework for real-time, multi-view consistent […]

Ver mais

With homemade instruments and radical patience, Bose forces matter to betray itself: plants pulse, feel shock, crave stimulants, writhe, and die; metals, too, fatigue and respond. What we called “inanimate” merely hid its vitality. Life was never imported into matter—it was always there, waiting for eyes sensitive enough to see it.

Ver mais