Riyadh is quickly emerging into a dynamic hub of global influence and innovation. Guided by Vision 2030, Saudi Arabia is embracing forward-thinking policies, entrepreneurship, and technology to expand its economy and promote a creativity culture. Known for its commercial and political significance primarily, Riyadh now redefines its personality as an innovation center, attracting global startups, investors, and talent. Now, the city stands as a testament to the power of planning, progress, and ambition to shape a futuristic, dynamic […]

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In the high-stakes world of AI, ‘Context Engineering’ has emerged as the latest frontier for squeezing performance out of LLMs. Industry leaders have touted AGENTS.md (and its cousins like CLAUDE.md) as the ultimate configuration point for coding agents—a repository-level ‘North Star’ injected into every conversation to guide the AI through complex codebases. But a recent study from researchers at ETH Zurich just dropped a massive reality check. The findings are quite clear: if you aren’t deliberate with your […]

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In Part 1, we built the engine. A small set of EODHD-backed tools, an agent with strict rules, and a single run_brief() function that returns two outputs: the markdown brief and the structured artifacts. This part is about turning that into something you can actually demo. We’ll build a simple Streamlit app that feels like a real feature: a query box on the left, a brief in the main view, and the tool-backed numbers rendered next to it. […]

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The AI industry’s scramble for licensable content is heating up, and Microsoft, being at the center of it, is already looking ahead with Publisher Content Marketplace (PCM). For those unaware, Microsoft’s PCM is designed to offer publishers a transparent framework for licensing, allowing AI developers to use their material legally and efficiently. Now, Amazon appears to be lining up with the same idea, at least according to a report by The Information. Amazon is exploring a new marketplace […]

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This study presents a quantitative evaluation of the EMBA firmware security analysis tool applied to Internet of Things (IoT) and embedded device firmware in two deployment environments: a standalone personal computer and a Microsoft Azure cloud-based virtual machine. The study addresses a gap in existing research regarding how deployment choices affect performance, cost, and operational characteristics of firmware security analysis. Using identical EMBA configurations and analysis modules, firmware images of varying sizes were analyzed, while execution time, detected […]

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Centralized training with decentralized execution (CTDE) has been the dominant paradigm in multi-agent reinforcement learning (MARL), but its reliance on global state information during training introduces scalability, robustness, and generalization bottlenecks. Moreover, in practical scenarios such as adding/dropping teammates or facing environment dynamics that differ from the training, CTDE methods can be brittle and costly to retrain, whereas distributed approaches allow agents to adapt using only local information and peer-to-peer communication. We present a distributed MARL framework that […]

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Reinforcement learning (RL) has improved the reasoning abilities of large language models (LLMs), yet state-of-the-art methods still fail to learn on many training problems. On hard problems, on-policy RL rarely explores even a single correct rollout, yielding zero reward and no learning signal for driving improvement. We find that natural solutions to remedy this exploration problem from classical RL, such as entropy bonuses, more permissive clipping of the importance ratio, or direct optimization of pass@k objectives, do not […]

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Scaling modern deep learning workloads demands coordinated placement of data and compute across device meshes, memory hierarchies, and heterogeneous accelerators. We present Axe Layout, a hardware-aware abstraction that maps logical tensor coordinates to a multi-axis physical space via named axes. Axe unifies tiling, sharding, replication, and offsets across inter-device distribution and on-device layouts, enabling collective primitives to be expressed consistently from device meshes to threads. Building on Axe, we design a multi-granularity, distribution-aware DSL and compiler that composes […]

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arXiv:2601.07989v1 Announce Type: new Abstract: This paper identifies the Stein-exponent of distributed detection when the sensor communicates to the decision center over a discrete memoryless channel (DMC) subject to one of three stringent communication constraints: 1) The number of channel uses of the DMC grows sublinearly in the number of source observations n; 2) The number of channel uses is n but a block-input cost constraint is imposed almost surely, which grows sublinearly in n; 3) The block-input […]

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arXiv:2601.08885v1 Announce Type: new Abstract: Two-photon lithography (TPL) is an advanced additive manufacturing (AM) technique for fabricating high-precision micro-structures. While computer vision (CV) is proofed for automated quality control, existing models are often static, rendering them ineffective in dynamic manufacturing environments. These models typically cannot detect new, unseen defect classes, be efficiently updated from scarce data, or adapt to new part geometries. To address this gap, this paper presents an adaptive CV framework for the entire life-cycle of […]

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