L1 instruction cache set conflicts, associativity, and code alignment in Go

Hark raises $700M Series A for its secretive “universal” AI interface

The Path, founded by Tony Robbins and Calm alums, hopes to offer safer AI therapy

1-Wire

Google is pitching an AI agent ecosystem to consumers who may not buy it

A Bipartisan Amendment Would End Police License Plate Tracking Nationwide

AI is just unauthorised plagiarism at a bigger scale

Wayve’s self-driving tech is headed to US cars made by Stellantis

Anthropic to open Milan office, expanding push into Europe

Hating AI Is Good

FatGid: FreeBSD 14.x kernel local privilege escalation

Antony Pegg: From Managed PostgreSQL to Production RAG: Build Your Own Ellie in pgEdge Cloud

If you've used docs.pgedge.com recently, you've probably met Ellie. Ask her how to set up multi-master replication, or what port the MCP Server listens on, and she pulls the relevant documentation, assembles it into context, and gives you a grounded answer with source citations. She doesn't guess or hallucinate. She finds the actual docs and synthesizes an answer from them.Ellie is a RAG Server deployment. The pgEdge RAG Server is an API server for retrieval-augmented generation that runs hyb...

Flipper unveils a Linux-powered networking gadget built for hackers and tinkerers

Gemini randomly dumped its system prompt

Large-Scale High-Quality 3D Gaussian Head Reconstruction from Multiview Captures

IBM invented semiconductor manufacturing automation

The Download: online safety’s future and climate tech’s big pivot

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Tech researchers are suing the Trump administration over the future of online safety For months, the Trump administration has been going after researchers who study and try to counter hate speech,…

Bliki: Vibe Coding

Vibe coding is building a software application by prompting an LLM, telling it what to build, trying it out, prompting for changes - but without looking at any of the code that the LLM generates. This technique can be used by people without any knowledge of programming. However the resulting software often shows problems with maintainability, correctness, and security - so is best used for disposable software written for a limited audience. The term was coined in February 2025 by A...

Denmark's wind and solar investments shield it from global energy turmoil

Flipper One – we need your help

Python 3.15: features that didn't make the headlines

Test-Driving the Lance Lakehouse Format in DuckDB

Lance is an open lakehouse format with a design geared toward AI workloads. LanceDB and DuckDB Labs have partnered to bring you fast vector and hybrid search directly from DuckDB SQL, without leaving your analytical workflow. In this post, we explain what Lance is, how to use it in DuckDB, and, of course, show some benchmark results.

semab tariq: How to Cut Over After a PostgreSQL Migration

One Database at a Time, or All at Once? You have deployed your new cluster. Now comes the work of moving your data and cutting over to it. Reading that sentence, you might assume cutover is something you figure out at the end, after the migration is done. And in practice, that is the order in which things happen. But technically, it is your cutover strategy that decides how you migrate, not the other way around.  The strategy you pick determines how you configure replication, how many slots ...

Lazydiff: Terminal PR Review with AST-Aware Semantic Diff Rendering

Comparing Objective Caml and Standard ML

Google officially announces that ads will be included in AI Mode search results

No Slop Grenade

Kubernetes In Anger

Show HN: Rmux – A programmable terminal multiplexer with a Playwright-style SDK

Numexpr: Fast numerical array expression evaluator for Python, NumPy, Pandas

DiffsHub

Tech researchers are suing the Trump administration over the future of online safety

Since its earliest days back in office, the Trump administration has been going after researchers who study and try to counter hate speech, harassment, propaganda, and disinformation online.  Now, some of those researchers are fighting back. Last week their lawsuit—which could have global repercussions for online safety and free speech—made its first appearance in court. …

Testing the Lance Lakehouse Format in DuckDB

The famous O3 "GeoGuessr" prompt did not work

Vivaldi 8.0: our biggest design overhaul

All the Bugs They Found

[RFC] LLVM Foundation statement in favor of open access to standards documents

General Catalyst just led a $63M bet on India’s travel payments market

Simulating Infinity in Conway's Game of Life with Modern C++

Imperagen raises £5 million to use quantum physics, AI on enzyme engineering

Data Scaling as Progressive Coverage of a Predictive Contribution Spectrum

arXiv:2605.20196v1 Announce Type: new Abstract: We investigate the hypothesis that real-data scaling laws are governed by progressive coverage of a latent predictive contribution spectrum rather than by token-frequency tails alone. We work with a suffix-automaton representation of text corpora and define a data-intrinsic global-KL predictive contribution spectrum, in which each state contributes according to its empirical mass times its KL deviation from a global next-token baseline. Across ...

Pseudo-Siamese Network for Planning in Target-Oriented Proactive Dialogues

arXiv:2605.20195v1 Announce Type: new Abstract: A target-oriented proactive dialogue system is designed to steer conversations toward predefined targets while actively providing suggestions. The core paradigm of such a system is to plan a reasonable dialogue path and subsequently guide language models (e.g., pre-trained or large language models) to generate responses, where dialogue path planning serves as the central component-a novel yet under-explored problem. In this work, we propose a F...

Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction

arXiv:2605.20194v1 Announce Type: new Abstract: Large language models (LLMs) have been increasingly used to analyze text. However, they are often plagued with contextual reasoning limitations when analyzing long documents. When long documents are processed sequentially, early or dominant concepts can overshadow less visible but meaningful interpretations, leading to cumulative analytical bias, omission error, and over-generalization. Additionally, independently generated outputs are often me...

Improving Quantized Model Performance in Qualitative Analysis with Multi-Pass Prompt Verification

arXiv:2605.20193v1 Announce Type: new Abstract: Quantized Large Language Models (LLMs) are used more often in qualitative analysis because they run fast and need fewer computing resources. This study examines how different lower bits quantization levels (8-bit, 4-bit, 3-bit, and 2-bit) and quantization types affect the performance of LLaMA-3.1 (8B) on qualitative analysis. The study uses expert and non-expert responses from 82 interview transcripts. Low-bit models often produce higher levels...

Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token

arXiv:2605.20192v1 Announce Type: new Abstract: Decentraland, a decentralized virtual reality platform operating within the expanding Metaverse ecosystem, utilizes its native MANA token to facilitate virtual asset transactions and governance. This study investigates the integration of Discord community sentiment with multi-modal financial data to enhance cryptocurrency price prediction within virtual world economies. We address: (1) identifying sentiment patterns within Decentraland's Discor...

Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs

arXiv:2605.20191v1 Announce Type: new Abstract: Modern Large Language Models (LLMs) have recently attracted much attention for their ability to simulate human behavior and generate text that reflects personas and demographic groups. While these capabilities can open up a multitude of diverse applications across fields, it is crucial to examine how such models represent various target groups since LLMs can perpetuate and amplify biases or discrimination against historically marginalized commu...

Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration

arXiv:2605.20190v1 Announce Type: new Abstract: Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric edits under diverse, coupled constraints. To fill this gap, we propose COSMO-Agent (Closed-loop Optimization, Simulation, and Modeling Orchestration), a tool-augmented reinforcement learning (RL) framework that teaches LLMs to complete the closed-loop CAD-CAE process. Specifically, we cast CAD gen...

SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation

arXiv:2605.20189v1 Announce Type: new Abstract: Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with primary challenges being concept drift and the high cost of gradient-based adaptation. Traditional fine-tuning (FT) struggles to adapt to non-stationary data streams without resulting in catastrophic for getting or requiring extensive manual data curation. To address these limitations within the stream...

GraphDiffMed: Knowledge-Constrained Differential Attention with Pharmacological Graph Priors for Medication Recommendation

arXiv:2605.20188v1 Announce Type: new Abstract: Recommending safe and effective medication combinations from electronic health records (EHRs) is a core clinical AI problem, yet it remains difficult because patient trajectories are long, noisy, and clinically heterogeneous. Existing methods typically excel at either temporal modeling across visits or pharmacological knowledge integration (e.g., drug-drug interactions, DDIs), but rarely achieve both while robustly suppressing noise. We present...

Neural Estimation of Pairwise Mutual Information in Masked Discrete Sequence Models

arXiv:2605.20187v1 Announce Type: new Abstract: Understanding dependencies between variables is critical for interpretability and efficient generation in masked diffusion models (MDMs), yet these models primarily expose marginal conditional distributions and do not explicitly represent inter-variable dependence. We propose a neural framework for estimating pairwise conditional mutual information (MI) directly from the hidden states of a pretrained MDM, using ground-truth MI computed from the...

New features in GCC 16: Improved error messages and SARIF output

OpenAI to confidentially file for IPO as soon as Friday

Haskell Foundation 2026 Update

A Markdown-based test suite

Not alive, but not dead: disembodied human brains used for drug testing

Jensen Huang says he’s found a ‘brand new’ $200B market for Nvidia

I reverse engineered Apple's video wallpapers

Anthropic says it’s about to have its first profitable quarter

Deep – CLI/REPL for generating and iterating on codebases using DeepSeek

Kaarel Moppel: Data analyst vs width_bucket()

After helping out a buddy with the job title of Data Analyst, who experienced some light Postgres “bucketing” woes - and given the fact that this was not the first such occasion in that area over the years, though I’d help future googlers / LLM-ers out a bit as well,...

Anthropic is expanding to Colossus2. Will use GB200

The OEIS meta sequence and subway stations

Staged publishing for npm packages

The SpaceX IPO filing is filled with AI bets, Starship dreams, and Elon Musk at the center

Clouted wants to take the guesswork out of making short videos go viral

xAI burned $6.4B last year. SpaceX’s IPO filing shows why the spending is far from over

GitHub's take on age assurance for developers

Nvidia posts another record quarter, reveals $43 billion of holdings in startups

Musk’s xAI is being sued over its data center generators. Now, it’s buying $2.8B more.

How Partition Access Visualizations Reduced our Data Lake S3 Cost by 33%

Introduction In large analytics environments, data teams often struggle to answer deceptively simple questions, like who their stakeholders are and how their data is being used. At Yelp, we address this by visualizing access patterns, plotting time-based partition key values against access event timestamps. These visualizations reveal distinct usage signatures – ad hoc queries, daily batch jobs, and periodic backfills – allowing data owners to understand their stakeholders and use cases. ...

Google Declaring War on the Web

America Turned Against AI According to the Poll Data: A Very Big Compilation

Anthropic will pay xAI $1.25 billion per month for compute

GPU Memory Math for LLMs: Formula That Tells You What Fits on Your GPU

Sam Altman makes ‘mic drop’ offer to every Y Combinator startup

Show HN: Dari-docs – Optimize your docs using parallel coding agents

Christophe Pettus: All Your GUCs in a Row: check_function_bodies

PostgreSQL validates function bodies at creation time by default, catching syntax errors early.

In Yesterday's IO Keynote Google Declared War on the Remnants of the Web

PopuLoRA: Co-Evolving LLM Populations for Reasoning Self- Play

Declining America