How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The Long Now of the Web: Inside the Internet Archive’s Fight Against Forgetting By @zbruceli [ 18 Min read ] A deep dive into the Internet Archive’s custom tech stack. Read More. Why Kubernetes Outages Are Usually Human Failures, Not Platform Bugs By @davidiyanu […]

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arXiv:2602.16721v1 Announce Type: new Abstract: Numerous models have shown great success in the fields of speech recognition as well as speech synthesis, but models for speech to speech processing have not been heavily explored. We propose Speech to Speech Synthesis Network (STSSN), a model based on current state of the art systems that fuses the two disciplines in order to perform effective speech to speech style transfer for the purpose of voice impersonation. We show that our proposed […]

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arXiv:2406.01552v2 Announce Type: replace Abstract: Tensors are a fundamental data structure for many scientific contexts, such as time series analysis, materials science, and physics, among many others. Improving our ability to produce and handle tensors is essential to efficiently address problems in these domains. In this paper, we show how to exploit the underlying symmetries of functions that map tensors to tensors. More concretely, we develop universally expressive equivariant machine learning architectures on tensors that exploit that, in […]

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arXiv:2601.20051v1 Announce Type: new Abstract: The rise of chronic diseases related to diet, such as obesity and diabetes, emphasizes the need for accurate monitoring of food intake. While AI-driven dietary assessment has made strides in recent years, the ill-posed nature of recovering size (portion) information from monocular images for accurate estimation of “how much did you eat?” is a pressing challenge. Some 3D reconstruction methods have achieved impressive geometric reconstruction but fail to recover the crucial real-world scale […]

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arXiv:2510.02514v2 Announce Type: replace-cross Abstract: We introduce the Information-Estimation Metric (IEM), a novel form of distance function derived from an underlying continuous probability density over a domain of signals. The IEM is rooted in a fundamental relationship between information theory and estimation theory, which links the log-probability of a signal with the errors of an optimal denoiser, applied to noisy observations of the signal. In particular, the IEM between a pair of signals is obtained by comparing their […]

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arXiv:2408.12739v2 Announce Type: replace-cross Abstract: Quantum Convolutional Neural Networks (QCNNs) are widely regarded as a promising model for Quantum Machine Learning (QML). In this work we tie their heuristic success to two facts. First, that when randomly initialized, they can only operate on the information encoded in low-bodyness measurements of their input states. And second, that they are commonly benchmarked on “locally-easy” datasets whose states are precisely classifiable by the information encoded in these low-bodyness observables subspace. We […]

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The debate between reading physically or digitally is never-ending; both have their pros and cons. However, for those who like reading digitally, a great service to use is Marvel Unlimited. It’s Marvel’s own subscription service that allows you to read a ton of old and new comics. It does seem, though, that a lot of people either have never heard of Marvel Unlimited or have completely forgotten about it. There are others who know about it but don’t […]

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arXiv:2402.04177v3 Announce Type: replace-cross Abstract: Scaling laws provide important insights that can guide the design of large language models (LLMs). Existing work has primarily focused on studying scaling laws for pretraining (upstream) loss. However, in transfer learning settings, in which LLMs are pretrained on an unsupervised dataset and then finetuned on a downstream task, we often also care about the downstream performance. In this work, we study the scaling behavior in a transfer learning setting, where LLMs are […]

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CLIP is a single thermometer taped to the outside of a house. It tells you something about the temperature, but it can’t tell you whether the furnace is on, whether a window is open, or whether the house is on fire in the kitchen. In my pipeline, CLIP-only ranking produced the same kind of failure: candidates that “looked similar” in embedding space but violated constraints that mattered for continuity. (See Radford et al. for the original CLIP formulation […]

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Hi technicians, I be in my graduation semester and did sign up for a exploration project on Edge AI reinforcement learning. When I did dive into the literature I did discover that there are not so much resources out there. So to gain some knowledges and some point of views I want to share with you this technique and put some questions in this chat hopefully you can challenge me and give me some new insights :). Thank […]

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