daily digest
monday 15 june 2026
curated daily from across the web, filtered and summarised by gemini.
01 ai
▸ Why AI hasn’t replaced software engineers, and won’t
★ highThis essay explores why software engineering remains resilient to AI disruption despite high expectations for automation. It provides a nuanced look at the limitations of current LLMs in handling complex, end-to-end software development tasks.
▸ Rio de Janeiro's "homegrown" LLM appears to be a merge of an existing model
A community investigation reveals that a purportedly novel LLM is likely a derivative merge of existing open-source models. This highlights the ongoing challenge of verifying the originality and provenance of new AI model releases.
02 quantum
03 dev tools
▸ The only scalable delete in Postgres is DROP TABLE
★ highThis article discusses the performance implications of large-scale data deletion in PostgreSQL and why standard DELETE operations often fail at scale. It offers practical architectural alternatives for managing high-volume data lifecycle.
▸ Jinx: Meta-build-system for bootstrapping operating system distributions
Jinx provides a structured approach to bootstrapping OS distributions, simplifying complex build dependencies. It is a useful tool for developers working on custom Linux environments or reproducible builds.
▸ Comparison and Benchmarking of Rust Decimal Crates
This technical comparison evaluates various Rust crates for high-precision decimal arithmetic, essential for financial and scientific applications. It provides clear benchmarks to help developers choose the right library for performance-critical tasks.
04 applied tech
▸ Efficient On-Device Diffusion LLM Inference with Mobile NPU
★ highThis paper addresses the computational challenges of running diffusion-based large language models on mobile hardware by optimizing denoising processes. It offers a path toward lower-latency, on-device generative AI applications.
▸ A fully GPU-based workflow for building physics emulators of hypersonic flows
This research introduces a high-performance workflow for simulating complex hypersonic flow physics using GPU acceleration. It demonstrates significant computational gains over traditional CPU-bound simulation methods.
05 open source
06 research
last updated: 8:03pm aest · 10 items · curated by gemini