cartero Thursday, August 13, 2026 · No. 25967
Search Engines

Search engine internals: how to win "Search Benchmark, The Game"

Back in March, we entered the Search Benchmark, The Game with a search engine we’ve been working on called IResearch. It’s a C++ native alternative to Lucene or Tantivy that isn’t widely known yet, but we actually ended up winning it. The cool part for us was that the Tantivy maintainers validated the results and approved the commit themselves. We appreciate this competition and treat it as a way to contribute our findings back to the search and information retrieval community, so we’...

PostgreSQL

Annie Ghazali: PostgreSQL’s Growing Role in AI Infrastructure

PostgreSQL, often through platforms like Supabase, is increasingly becoming part of the default stack for many AI applications. That level of adoption says something important about where engineering teams are placing their trust.Supabase has become one of the most common starting points for AI products. Most AI frameworks support PostgreSQL and pgvector directly. For many teams, PostgreSQL is already part of the stack before the AI layer is even introduced.  ...

Database Internals

Built a DBMS from scratch in C to study buffer pool behavior on real SQL workloads

I’m a third-year CS student and over the past year I’ve been building minidbms — a database engine written from scratch in C and Python — to study buffer pool replacement policies experimentally. Current features: - slotted-page heap storage - direct pread/pwrite I/O - LRU / Clock / NoCache / OPT - trace-based telemetry replay - benchmark + sweep analysis tools - interactive cache inspector - B+ tree indexes (in progress) Some interesting results so far: - Bélády-related behavior re...

AI Agents

A new EDIT tool for LLM agents

Right now I'm working to an agent for my DS4 project. Local inference is token-poor, it's a battlefield where optimizations count. I was quite surprised by the fact the EDIT tool everybody is using right now forces the LLM to emit the old version of the text verbatim. This CAS (check and set) mode of operation, where I say EDIT old="foo" new="bar", is needed because there are often colliding edits (the user is editing as well, or checked out a different branch, and so forth) and because the L...

AI Coding Tools

Codex-Maxxing

Web Application Security

Your fridge could be a threat to national security

On the floor of HumanX, Ryan is joined by Adam Meyers,  Senior VP of Counter Adversary Operations at Crowdstrike, for a deep dive on their latest Global Threat Report that tracks over 281 adversaries across nation states, e-crime, and hacktivist organizations.

Artificial Intelligence

D$^2$Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning

arXiv:2605.17037v1 Announce Type: new Abstract: Reinforcement learning (RL) has demonstrated potential for enhancing reasoning in large language models (LLMs). However, effective RL training, which requires medium-difficulty training samples, faces two fundamental challenges: Effective Data Scarcity and Dynamic Difficulty Shifts, where medium-difficulty samples are scarce and become trivial as models improve. Existing methods mitigate this scarcity to some extent by generating training sampl...

Artificial Intelligence

Reliability and Effectiveness of Autonomous AI Agents in Supply Chain Management

arXiv:2605.17036v1 Announce Type: new Abstract: This paper studies autonomous generative AI agents in multi-echelon supply chains using the MIT Beer Game. We identify four inference-time levers that shape performance: model selection, policies and guardrails, centralized data sharing, and prompt engineering. Model capability is the dominant factor: an out-of-the-box reasoning model exceeds human-level performance, and optimized reasoning models reduce costs by up to 67% relative to human tea...

Privacy

Privacy Policy Enforcement Guardrails for Data-Sensitive Retrieval-Augmented Generation

arXiv:2605.17034v1 Announce Type: new Abstract: Standard PII filters often miss contextual data leakage in RAG systems, such as non-regulated attribute clusters that collectively identify individuals. We introduce a Privacy Policy Enforcement (PPE) framework using dual one-class density estimators with fused text embeddings and a calibrated abstain region for out-of-distribution inputs. Using an axis-stratified, multi-LLM synthetic data pipeline across medicine, finance, and law, we found th...

Robotics

Generalizable and Actionable Parts Pose Estimation with Symmetry Annotation-Free Learning Strategy

arXiv:2605.17033v1 Announce Type: new Abstract: Urgently needed generalizable robot object interaction and manipulation requires high-quality Cross-Category object perception. As a pioneer of this area, Generalizable and Actionable Parts (GAParts) understanding has attracted increasing attention from relevant researchers. However, most recent works either have insufficient design regarding the symmetry issue or require rich symmetry annotation, which severely impedes precise GAPart pose esti...

Large Language Models

Task Abstention for Large Language Models in Code Generation

arXiv:2605.17029v1 Announce Type: new Abstract: Large language models (LLMs) have revolutionized automated code generation. One serious concern, however, is the so-called ``hallucination'', i.e., LLMs may generate seemingly plausible but functionally incorrect code. In this paper, we study the task abstention problem, i.e., determining whether a given LLM should abstain from performing a specific code generation task to avoid likely hallucination. Our approach features a calibrated abstentio...

LLM Evaluation

PARALLAX: Separating Genuine Hallucination Detection from Benchmark Construction Artifacts

arXiv:2605.17028v1 Announce Type: new Abstract: Large language models (LLMs) hallucinate with confidence: their outputs can be fluent, authoritative, and simply wrong. In medical, legal, and scientific applications this failure causes direct harm, and detecting it from internal model states offers a path to safer deployment. A growing body of work reports that this problem is increasingly tractable, with recent methods achieving high detection performance on widely used benchmarks. We show, ...

Fine-tuning and PEFT

Why Do Reasoning Models Lose Coverage? The Role of Data and Forks in the Road

arXiv:2605.17026v1 Announce Type: new Abstract: Recent progress in large language models has led to the emergence of reasoning models, which have shown strong performance on complex tasks through specialized fine-tuning procedures. While these methods reliably improve pass@1 accuracy, prior works have observed that they show a coverage shrinkage behavior, where pass@k degrades relative to the base model. In this paper, we investigate the reasoning shrinkage arise under SFT-based post-trainin...

Computational Complexity

Intermediate Constacyclic Codes and Scalar-Residue Reed--Muller Layers

arXiv:2605.17022v1 Announce Type: new Abstract: A 2024 paper of Sun, Ding and Wang introduced a second class of constacyclic codes over finite fields, denoted $C(q,m,r,\ell)$, with length $(q^m-1)/r$, where $r\mid(q-1)$ and the defining monomials have total $q$-ary degree congruent to $r-1$ modulo $r$. In the non-projective intermediate range $2

xAI

Here’s why Elon Musk lost his suit against OpenAI

On Monday, the jury in Musk v. Altman dealt Elon Musk a major blow—reaching a unanimous advisory verdict that Musk sued OpenAI too late and, as a result, his claims are barred by the applicable statutes of limitations. US District Judge Yvonne Gonzalez Rogers immediately accepted it.  Musk announced on X that he will be…

Software Engineering

Coding on Paper

Artificial Intelligence

Vibhor Kumar: Beyond Vector Search: Why PostgreSQL Could Become the Memory Layer for Enterprise AI Systems

The conversation around AI infrastructure today is heavily focused on models, GPUs, inference speed, and vector databases. These are important building blocks, but they often distract from a deeper architectural challenge that is beginning to emerge as enterprises move from experimentation toward operational AI systems. The challenge is memory. Not memory in the simplistic sense of storing chat history or embeddings, but memory in the broader sense of maintaining durable context, operat...