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Show HN: AI Facial Attractiveness Model Aligned with Human Preferencesfaceanalysisai.com

Reproducing, disclosing, and fixing the libheif vulnerability with Hacktron and the maintainersvercel.com

Hacktron reported an RCE in libheif, an AVIF decoder used by Next.js image optimization. Vercel and Hacktron reproduced the issue, then coordinated with upstream maintainers (sharp, libvips, libheif) to deploy platform-wide mitigations and release fixes across the ecosystem.

Union vs sum typesviralinstruction.com

From Memory-Hungry HNSW to Quantized SPANN: The Technical Evolution of Pinterest's Manas Platforminfoq.com

Pinterest reengineered its Manas search platform to replace memory‑heavy HNSW with scalar and product quantization, cutting index size by up to 93% while keeping recall above 70% and achieving 20‑30% cost savings. They also moved ANN storage to SSD using SPANN, gaining 3× query throughput over DiskANN with modest latency and recall impact.

Shopify Drops React Native for Swift and Kotlin as AI Changes Cross-Platform Development Tradeoffsinfoq.com

Shopify is abandoning React Native for native Swift and Kotlin development, driven by the improved quality of AI coding models and a looming refactor to React Native's New Architecture. This shift resulted in significant performance and stability gains for their flagship app, challenging previous cross-platform development tradeoffs.

Trust, but benchmark: How we let an AI agent optimize Elasticsearchelastic.co

MilleMiglia: A realistic instance generator for middle-mile logisticsresearch.google

MilleMiglia is an open‑source C++ generator that creates realistic, privacy‑preserving middle‑mile logistics instances (space‑time graphs with fixed schedules, throughput limits, and synchronization constraints). It uses data‑driven spatial, demand, and rotation distributions, serializes with protobuf, and ships small files for small‑toy to continent‑scale problems, enabling both exact/heuristic…

Writing Rust code that's fast by asking agents to make the code fasterminimaxir.com

Building AI Agents got easier; managing them didn’t: Managing agent sprawl with Blocks Enterprisepubnub.com

Building AI agents is now easy, but as deployments grow into dozens or hundreds, companies lose visibility into ownership, usage, and cost—a problem called agent sprawl. Blocks Enterprise offers a private network that lets heterogeneous agents be discovered, permissioned, and audited across clouds without forcing a single framework.

GSoC 2026: Improving HLSL Support in clangdllvm.org

The GSoC 2026 project identified and closed numerous gaps in clangd’s HLSL support. By performing a systematic gap analysis, the author authored an RFC, opened 11 GitHub issues, and landed multiple PRs that improve hover (semantic annotations, out/inout parameters, swizzles, RootSignature, register ranges) and code‑completion (attributes, register, semantic annotations, swizzle). The work also ex…

Uber Redesigns M3DB Sharding with Subclusters to Limit Failure Impactinfoq.com

Uber reworked M3DB's shard placement by grouping nodes into fixed-size subclusters, each owning a disjoint shard range, to bound the blast radius of node failures. A greedy shard‑move algorithm (O(S log S) + O(S×N)) handles scaling while preserving existing placement tooling.

GPT-Live 1 now available on AI Gatewayvercel.com

Vercel AI Gateway now offers OpenAI’s GPT‑Live 1, a full‑duplex voice model that can listen and speak simultaneously. The SDK lets you start a voice session and optionally delegate work to any text model, with code examples for both patterns.

Knowledge cutoff is a poor proxy for model capabilitymicrosoft.com

A study found that an LLM's stated knowledge cutoff date is a poor indicator of its actual capability regarding specific product versions. Models showed inconsistent knowledge, failing on older features while sometimes inferring correctly about newer, post-cutoff features.

How LLMs Can Find a Needle in a Haystackbytebytego.com

The post explains how retrieval‑augmented generation (RAG) lets LLM‑based assistants answer questions from private corpora. It covers chunking documents into passages, embedding queries and chunks, similarity metrics, and the trade‑offs of different vector indexes (flat, IVF, HNSW). The focus is on practical design choices rather than new research.

Gemini Live audiosimonwillison.net

Simon Willison shows a minimal JavaScript UI that talks to Google’s Gemini 3.8 Live speech‑to‑speech models via a WebSocket API, using the Web Audio API for capture/playback and no external libraries.

More dirty coding tricks from game developers (2015)archive.org

Google Agent Development Kit for Kotlin Reaches Feature Parity with Python, Supports On-Device AIinfoq.com

Google's ADK for Kotlin 1.0 is a production-ready framework for building AI agents across Kotlin, Android, and JVM applications. It achieves feature parity with Python ADK, offering idiomatic Kotlin APIs for orchestration, tools, and memory, alongside new Android-specific on-device and hybrid AI capabilities.

A First Futamura Projectionveitheller.de

Write End-to-End Tests in Your Backend’s Languageatomicobject.com

This article advocates writing end-to-end tests in the backend's language to leverage domain models and persistence tools for efficient test data setup. It details a strategy for structuring E2E tests with inline data creation, small helpers, and parallel execution considerations.

Mapsnap: Automated Georeferencing for Historic Sanborn Insurance Mapsdanvk.org

Dropbox Outlines How Focusing on Existing Infrastructure Efficiency Can Create Headroom for AIinfoq.com

Dropbox details how a decade‑long program of infrastructure efficiency—forecasting, deep‑sleep servers, workload rebalancing, higher‑density storage, reliability‑based hardware refresh, and rack‑level power upgrades—has cut storage power use by >50% and created headroom for AI workloads without new data‑center builds.

From alert to resolution: Manage incidents with Bits Chat in Slackdatadoghq.com

Datadog’s Bits Chat adds a natural‑language interface to Slack, letting responders start investigations, get root‑cause analysis, generate code fixes, and close incidents without leaving the channel. The post walks through a sample e‑commerce outage to show the end‑to‑end workflow.

Improving synthesis prediction of small molecules at scale with RetroChimeramicrosoft.com

RetroChimera is an open‑source retrosynthesis system that ensembles a Transformer‑based de‑novo model and a GNN template selector with a learned ranking layer. In blind expert evaluations it achieved a 90 % route acceptance rate, far above prior models.

Show HN: Jev vs. GPT-5.6 and Claude Haiku at Pongably.dev

Authenticity's Triumphsmalleycreative.com

Fearless Concurrency on the GPUarxiv.org

Diagnosing PostgreSQL Index Bloat, Write Amplification, and Buffer Cache Hit Ratiossitepoint.com

This article details how to diagnose PostgreSQL index bloat, write amplification, and buffer cache inefficiency using SQL tools like pgstattuple and pg_buffercache. It provides a reusable SQL toolbox and a Docker environment to identify and understand performance bottlenecks caused by MVCC-related index fragmentation.

Vibe coding security: How to be sure your vibe-coded apps are safe to usezapier.com

This article addresses common security vulnerabilities in AI-generated "vibe-coded" applications, such as exposed API keys and data breaches. It provides practical steps and agent skills to build securely from the start, perform security reviews, and protect sensitive data and keys.

What We Know About Laravel 14laravel-news.com

Laravel 14 (Q1 2027) raises the PHP minimum to 8.4 and adds several concrete API changes: a new `Route::query()` method, `$user->authorize()`, context support for `report()`, `Storage::fake()` for on‑demand disks, extended `whereKey*()` helpers, and fixes to queue‑pause signatures, non‑mutating `lazy()`/`chunk()`, array handling in `Cache::has/forget`, and `MassPrunable` soft‑delete behavior. The…

Advancing AI for biology: Teaching models to design and characterize antibodiesamazon.science

Amazon Bio Discovery developed three AI models: MochiBind for fast, sequence-based antibody binding ranking, CA-MAP for context-aware developability prediction robust to batch effects, and an agent-guided system for de novo antibody design. These advancements aim to accelerate and improve the accuracy of antibody drug discovery, with experimental validation for a novel cancer target.