AMD silently removes memory encryption from consumer Ryzen CPUs

API Credentials from Your Terminal, and OpenAPI on GitHub

In May we opened self-service app registration for Artist Pro subscribers. That fixed the browser flow. Two requests kept coming up anyway…

Bcachefs 1.38.6 - the performance release

Sogen – High-performance Windows and Linux userspace emulator

I Could've Rickrolled the Entire FIFA World Cup. All I Needed Was My ID

How to Become a Person After Smartphones Have Rotted Your Brain

DeepSeek Introduces Vision

The Australian Government to Require SMS/MMS Sender ID Registraion

CLI Authentication, the Right Way

Monkey: Optimal Navigable Key-Value Store (2017)

NASA picks Eric Schmidt’s rocket company for Mars mission, setting up a race with SpaceX

Apple boss Tim Cook says prices to rise due to memory chip costs

Christophe Pettus: All Your GUCs in a Row: default_transaction_isolation and default_transaction_read_only

PostgreSQL's isolation levels hold surprises: read uncommitted silently becomes read committed, repeatable read forbids phantom reads the standard permits, and…

I hate compilers

Magic Buffers and io_uring Registered Buffers

Scaling opencomputer from 1 VM to 1 million sandboxes

Show HN: Local personal data redaction for any AI tools

Local Qwen isn't a worse Opus, it's a different tool

I restarted a 10 year old Xeon 174 times to delete 12 flags and gain 4 TPS

How Well Do Large Language Models Capture Human Personality?

arXiv:2606.18263v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate human populations via persona prompting, often under the assumptions that richer persona descriptions improve behavioral fidelity, similarly sized attribute combinations are equally simulatable, and persona definitions generalize across tasks. In this work, we formalize these assumptions and systematically evaluate them across multiple architectures, scales, and simulation settings....

When Prompts Mislead: Textual Dominance and Diagnostic Bias in MLLMs

arXiv:2606.18262v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly being evaluated for medical applications, where computational constraints often make prompting strategies the only practical alternative to fine-tuning. Such strategies are generally assumed to support diagnostic reasoning, yet their potential failure modes in medical MLLMs remain poorly characterized. We analyze FundusExpert-1B, an open-source ophthalmology MLLM, on a hemorrhage versus ...

"Are you an AI?" Analyzing Client Suspicion of AI Use in Crisis Counseling

arXiv:2606.18261v1 Announce Type: new Abstract: As artificial intelligence (AI) tools get increasingly deployed for mental healthcare, public trust in these systems remains uncertain. It is unclear how clients perceive AI involvement in counseling interactions, particularly in moments of crisis that require empathy and connection. To address this gap, we analyzed 75,777 crisis counseling conversations from a human-staffed WhatsApp helpline in India to characterize how often clients suspected...

FluidViews: Adaptive Drag-and-Drop Token Filters for Heterogeneous Multi-View Visual Analytics

arXiv:2606.18260v1 Announce Type: new Abstract: Interactive visual analytics workflows are often disrupted by rigid filter panels and context switches that break analysts' cognitive flow. We introduce FluidViews, a web-based framework that elevates filters to first-class, manipulable objects through two novel direct-manipulation interactions. Copy-as-Highlight enables users to duplicate any visual mark into a persistent highlight token for rapid, transient cross-view comparison, while Drag-a...

Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaboration

arXiv:2606.18259v1 Announce Type: new Abstract: AI agents that plan, retain memory across sessions, invoke external tools and act with partial autonomy are transforming human--AI collaboration. Research on affective computing, simulated empathy in large language models, trust in automation and AI safety has illuminated important design principles, yet these literatures remain fragmented. No integrated account explains how affective cues operate within agentic collaboration -- settings in whi...

Examining Human-Like Behaviors in LLMs: A Multi-Dimensional Analysis of Model Behaviors, User Factors, and System Prompts

arXiv:2606.18258v1 Announce Type: new Abstract: Large language models (LLMs) exhibit a wide range of human-like behaviors, from expressing thoughts and emotions, to engaging in relationship-building with users, to refusing requests and maintaining boundaries. Despite their prevalence, researchers and practitioners lack methods and empirical insights to make informed decisions about when and what types of human-like behaviors LLMs should exhibit. To fill this gap, we present a multi-dimension...

From Memorization to Creation: Evaluating the Cognitive Depth of LLM-Generated Educational Questions

arXiv:2606.18257v1 Announce Type: new Abstract: While LLMs show promise in automating educational content creation, their ability to generate questions that stimulate higher-order thinking remains understudied. This work evaluates six widely-used LLMs through a Bloom's Taxonomy lens, focusing on their capacity to transcend rote memorization and achieve cognitive leaps. Using a hybrid human--AI evaluation protocol, we generate and analyze 20{,}700 questions across computer science, K--12 math...

Dynamic In-Group Persona Generation for Enhancing Human-AI Rapport

arXiv:2606.18256v1 Announce Type: new Abstract: LLM-based chatbots are increasingly applied in interpersonal domains such as counseling and peer support, where establishing human-AI rapport is crucial yet remains challenging. In this work, we introduce a novel approach for conditioning LLMs with in-group personas, which (i) first identifies a user's primary concern and brief personal context (e.g., a computer science undergraduate worried about future career prospects), and (ii) generates a ...

Human-Machine Bidirectional Trust-Aware Analysis and Design for Human-Led Truck Platooning

arXiv:2606.18255v1 Announce Type: new Abstract: Human-led truck platooning, where a human-driven truck leads one or more autonomous followers, offers significant benefits in fuel efficiency, safety, and traffic flow. However, its successful deployment hinges on trust between the human driver and the automated systems. Unlike conventional automation, trust in this context is inherently bidirectional: the human must trust the autonomous followers, and the followers must reliably interpret and ...

ATIM: An ACT-R-Based Task Interface Model for Predicting Operator Action Time in Digital Nuclear Control Rooms

arXiv:2606.18254v1 Announce Type: new Abstract: Human performance in digital control rooms is strongly influenced by interface characteristics, which shape visual search, cognitive processing, and motor execution. Accurate prediction of operator action time is therefore essential for ergonomic evaluation, interface design, and performance optimization in safety critical systems. However, existing approaches typically rely on extensive experimental data or black box models, limiting their int...

Continue has been acquired by Cursor

Meta head of product for 'AI for work' transformation is leaving company

[x86] AI Compute Extensions (ACE) Specification

Show HN: BlitzGraph – Supabase for graphs, built for LLM agents

Midjourney Ultrasonic CT Scanner

Brad Feld – Does the Rule of 40 Work for Hardware?

How to turn off AI in your Google Docs

ChatGPT Spontaneously Generates Sexual Violence and Hardcore Snuff Imagery

Noam Shazeer is joining OpenAI

Clojure Hosted on Go

Show HN: We built an 8-bit CPU as 2nd year EE students

License Plate Cameras Will Soon Track Phones, Wearables, Infotainment and Pets

AI is hurting Apple in more ways than one: it may force iPhone price increases

The Free and Open Web Is Under Attack at the IETF

The (real) dead economy theory

A World of First Drafts

Leaked financial docs show OpenAI is losing billions of dollars a year

Apple Intelligence may become mandatory in iOS and macOS 27

Loreline – Tools for writing interactive fiction

Chi-Hua Chien saw Facebook coming; now he says the real AI winners won’t be selling AI

Apple to Raise Prices Due to Memory Chip Crunch

BaraDB multimodal database engine written in Nim — 100% native

BaraDB combines document, graph, vector, columnar, and full-text search storage in a single engine with a SQL query language submitted by /u/Loud_Possibility_203 [link] [comments]

Tesco moving 40k server workloads off VMware amid Broadcom's abusive conduct

A Robot Is Sprinting Towards You: Do You Want It Running on Claude or Grok?

I scored 200 blockchain NPM packages for deprecation and hijack risk

FortiBleed – 75k Fortinet firewalls have admin passwords cracked

The Return of Rigorous Full-System Timing Simulation

Bcachefs 1.38.6 Brings Many Performance Improvements

The World is Waiting for the Next Adam Smith

AI has given us a new developmental engine. We still lack the economic model that fits it.

Roelof Botha joins SpaceX’s board of directors

After unveiling ridiculously expensive AR glasses, Snap’s stock takes a dive

Lore – Open source version control system designed for scalability

Krugman: Musk, a Human Ponzi Scheme

There's No Place Like $HOME: A 10 Journey of Vim, Then VS Code, and Back to Vim

How a Filesystem Beat Vector Search: 99.9% AR, 77.2% BEAM — No RAG, No Embeddings, No Tricks

[Proof: AR 99.9% results](https://github.com/CEM888AI/CEM888.AI-Site/blob/main/benchmarks/AR-Results-99.9pct.md) · [Proof: BEAM 77.2% results](https://github.com/CEM888AI/CEM888.AI-Site/blob/main/benchmarks/Vetta-BEAM-Honest-77.2pct.md) --- **The scores:** - **AR Retrieval: 99.9%** (1,998/2,000) — best public baseline is GPT-4.1-mini at 71.8% - **BEAM-10M Memory: 77.2%** — SOTA is Hindsight at 64.1% --- **Here's the controversial part: we achieved this with zero RAG, zero vectors, zero e...

Introducing the Cloudflare One stack: agent-powered deployment

The Cloudflare One stack is a library of agent skills that gives any AI agent the knowledge it needs to plan, deploy, and manage a Zero Trust environment — no migration calls required.

zkit: provider agnostic Agent toolkit

Windows 11 25H2 – I'm so happy to not be using this

The hacker sent by Anthropic to calm the government's nerves about AI safety

The feedback loops behind Kubernetes

World leaders want American AI. They just don’t want America to be able to turn it off.

UK's Social Media Ban: The Monumental Pretext for Total Digital Surveillance

Bringing down my ZSH load times from ~3.1s to ~230ms

Anthropic becomes first AI startup to join the Frontier carbon removal coalition

Social media’s next evolution: user-controlled algorithms

Cybercriminals allegedly hacked tens of thousands of Fortinet firewalls used by major companies all over the world

Migrating Etsy’s database sharding to Vitess

Etsy has maintained a sharded MySQL architecture since around 2010. This database cluster contains most of Etsy’s online data and is made up of ~1,000 tables distributed across ~1,000 shards. Over the last 16 years, it has grown significantly: combined, these tables have over 425 TB of data and receive roughly 1.7 million requests per second. Etsy engineers access our MySQL data through a proprietary object-relational mapping (ORM). The ORM has a corresponding model for each MySQL table. W...

Making Ads Count: Using MMoE and Auxiliary Tasks to Better Connect Buyers & Sellers

When buyers search on Etsy, they need to quickly and easily find the perfect item. At the same time, sellers need to be confident their unique products are being seen by the right customers. Our Ads Search ranking model, which is built on a multitask learning foundation, is the critical link in this connection. Recently, we identified an opportunity to drive more meaningful buyer engagement by enhancing our model’s ability to predict purchase intent. We achieved this via a dual-pronged impr...

Shaping Product Understanding with Contrastive Reinforcement Learning

Etsy’s marketplace is defined by the creativity and craftsmanship of our sellers and the hundreds of millions of highly diverse products they offer. You can find silversmiths who cold-forge recycled sterling silver, weavers who dye raw fleece with indigo and black walnut, and ceramicists who throw stoneware on a kick wheel. These details define each product and often determine whether it matches a buyer’s taste, style, and interests. Sometimes buyers know exactly what they want, searching...

AI chemist improves a challenging reaction in medicinal chemistry

The Competitive Moat That AI Can't Replicate