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The integration of large language models (LLMs) into peer review raises a concern beyond authorship and detection: the potential cascading automation of the entire editorial process. As reviews become partially or fully machine-generated, it becomes plausible that editorial decisions may also be delegated to algorithmic systems, leading to a fully automated evaluation pipeline. They risk reshaping the criteria by which scientific work is assessed. This paper argues that machine-driven assessment may systematically favor standardized, pattern-conforming research while penalizing […]

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For years, we’ve treated coding interviews as the gateway to software engineering. Solve a few algorithm problems under pressure, and you’re “in.” Struggle with them, and suddenly your ability as an engineer is questioned. But here’s the uncomfortable truth: LeetCode-style interviews have never been a reliable measure of engineering skill. At best, they’re a hit-or-miss signal. Sometimes you’re in the zone. Sometimes the pressure gets to you. Sometimes you’ve seen a similar problem before. Sometimes you blank out […]

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Efficient ground state search is fundamental to advancing combinatorial optimization problems and quantum chemistry. While the Variational Imaginary Time Evolution (VITE) method offers a useful alternative to Variational Quantum Eigensolver (VQE), and Quantum Approximate Optimization Algorithm (QAOA), its implementation on Noisy Intermediate-Scale Quantum (NISQ) devices is severely limited by the gate counts and depth of manually designed ansatz. Here, we present an automated framework for VITE circuit design using Double Deep-Q Networks (DDQN). Our approach treats circuit construction […]

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Being over 20 years old in the sphere of enterprise technology is a reality that can no longer be ignored: the very thing that once made enterprises stable—legacy systems—has now become a significant challenge. These systems were designed and built with accuracy and reliability in mind, and over the years they have effectively supported business operations. However, their limitations have become more evident as business needs have evolved and digital transformation has accelerated. As a result, legacy systems […]

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As AI agents begin executing trades, managing risk, and interacting with markets through natural language, exchanges are quietly undergoing one of their most significant architectural shifts since the invention of the order book itself. The platforms that win the next cycle may not be the ones with the deepest order books, they may be the ones that are the most programmable, the most interoperable, and the most agent-ready. Victor Wu is building that shift from the inside at […]

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Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervised fine-tuning (SFT), preference optimization, reinforcement learning (RL), process supervision, verifier-guided methods, distillation, and multi-stage pipelines. Yet these methods are often discussed in fragmented ways, organized by labels or objective families rather than by the behavioral bottlenecks they address. This survey argues that LLM post-training is best understood as structured intervention on model behavior. We organize the field first […]

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London, UK Busha, a Nigerian SEC-licensed digital asset exchange, expands to the UK to serve families with connections across both regions   Busha selected Uphold as its platform partner thanks to experience in delivering on-chain infrastructure services in the UK   Busha, a crypto platform focused on building the future of money in Africa, has selected Uphold, the modern infrastructure provider for on-chain finance, to support the launch of its services in the UK. Busha serves more than a million […]

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Spatiotemporal neural dynamics and oscillatory synchronization are widely implicated in biological information processing and have been hypothesized to support flexible coordination such as feature binding. By contrast, most deep learning architectures represent and propagate information through activation values, neglecting the joint dynamics of rate and phase. In this work, we introduce Kuramoto oscillatory Phase Encoding (KoPE) as an additional, evolving phase state to Vision Transformers, incorporating a neuro-inspired synchronization mechanism to advance learning efficiency. We show that KoPE […]

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Learning rules plays a crucial role in deep learning, particularly in explainable artificial intelligence and enhancing the reasoning capabilities of large language models. While existing rule learning methods are primarily designed for symbolic data, learning rules from image data without supporting image labels and automatically inventing predicates remains a challenge. In this paper, we tackle these inductive rule learning problems from images with a framework called γILP, which provides a fully differentiable pipeline from image constant substitution to […]

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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. ## ClickFix Attacks Are Targeting VC and Fintech Talent with New Multi-Stage Loader Techniques By @moonlock [ 11 Min read ] New ClickFix attacks target crypto pros via fake LinkedIn job offers. Learn how multi-stage loaders steal assets and how to protect yourself from these […]

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