The Federal Reserve's SR 11-7 model risk guidance, designed for traditional quantitative models, is inadequate for governing AI systems like LLMs, RAG pipelines, and agentic AI deployed in banking. SR…
Recoverflow spent four days on architecture design before writing any code for its AI collections system, prioritizing what the system should not do over what it can do. The team shifted the design ce…
Generative AI coding assistants are making programming language popularity less relevant, as tools like Claude Code can work with older languages like Perl if sufficient documentation exists. The auth…
MLOps Data Engineer traces unreliable AI agent failures to poor knowledge retrieval, arguing that Retrieval-Augmented Generation (RAG) is the foundation for reliable agents. The article explains why c…
Researchers propose AgenticRei, a deontic policy framework for runtime governance of LLM-driven autonomous AI agents, addressing obligations, dispensations, conflict resolution, and ontological reason…
Manticore Search released version 27.1.5 with built-in authentication and authorization, sharded tables, conversational search, and faster vector search. The update also includes improvements to HNSW …
Integer quantization reduces neural network memory and energy costs by converting high-precision values to lower-bit integers, with INT8 additions consuming 30 times less energy than FP32. The techniq…
Auriko's cache-aware cost-arbitrage engine reduced LLM inference costs by 32.8% against a routing peer and 7.7–38.3% across five single-provider baselines in a benchmark of over 80,000 API requests ac…
A Search Engine Journal article reports that feeding the same query to a search engine and a large language model produces numerically similar but fundamentally different metrics, as search indexes ma…
Coding agents are becoming highly capable at software development tasks with effective feedback loops, such as those with clear error messages or benchmarks, while struggling with tasks lacking clear …
A team building a production assistant for financial advisors found that prompt editing rarely fixed LLM failures; architectural changes, such as removing abstract routing categories and adding missin…
Researchers from DiDi introduced ProfiLLM, an agentic LLM data pipeline that generates utility-aligned user profiles for industrial ride-hailing dispatch. Deployed on DiDi's production system, ProfiLL…
A developer detailed a 7-layer prompt-injection challenge, explaining how each defense layer works and where it breaks. The core issue is that LLMs have no hard boundary between instructions and data,…
A new reverse-engineering pipeline called ISA_recovery automatically generates Ghidra SLEIGH processor specifications for undocumented instruction set architectures by using an agentic workflow of lar…
The Joint Development Foundation and LF AI & Data announced DocLang, a new open standard for machine-readable documents designed to replace PDF and DOCX in AI pipelines. DocLang encodes semantic tags,…
A developer draws parallels between coding with Claude Code and playing video games like Civilization, Dota 2, and StarCraft, noting that the loop of prompting and responding in LLM conversations mirr…
A developer found that adding more parallel subagents to an ad-creative analysis pipeline increased latency rather than decreasing it, because context assembly before the LLM call became the bottlenec…
Polar is building a new design system called Orbit to enforce brand consistency when LLMs generate UI code, moving away from Tailwind's string-based classes to a prop-based system that makes off-brand…
Researchers at Indiana University found that AI rewriting of radiology reports causes a 'slop paradox' where tasks that produce cleaner text for multimodal training actually degrade image-text alignme…
Researchers introduced RAD3D-Prefix, a lightweight diagnostic-prior conditioning framework for volumetric CT report generation that keeps large language models frozen to minimize overfitting and clini…