Singapore to launch AI, tech visa track with S$30,000 income requirement - CNA
<a href="https://news.google.com/rss/articles/CBMikAFBVV95cUxOZ1p6Zkl6YTdoYnpBMnZvVlFWVGt3N000OUpKMzdtT2h6ZzRLREpleXFaZGpvclFndTF3S3FCX1dHcEVUdG5TdUxubzR5N0lNeWNyVkJMLVE2aFpYSlJaeUhTcEttUlV5ZDBRSWRrSjlUN2w0YUNSaF92bHpOaDZyZExxQTNfMFhfU2FvRWY2OFQ?oc=5" target="_blank">Singapore to launch AI, tech visa track with S$30,000 income requirement</a> <font color="#6f6f6f">CNA</font>
Could not retrieve the full article text.
Read on GNews AI Singapore →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
launch
Claude Code /buddy: The Terminal Tamagotchi That Broke the Internet
<ul> <li><p>A leaked .npmignore file exposed 512,000 lines of Claude Code source, revealing a hidden terminal pet called /buddy</p></li> <li><p>18 species assigned by account ID with 5 rarity tiers from Common (60%) to Legendary (1%)</p></li> <li><p>The architecture splits into deterministic "bones" (species, stats) and persistent "soul" (name, personality)</p></li> <li><p>Community response hit 16 million views and 50,000 GitHub stars in under 2 hours</p></li> <li><p>Full rollout starts April 8, 2026 with teaser notifications already live</p></li> </ul> <h1> Claude Code /buddy: The Terminal Tamagotchi That Broke the Internet </h1> <p>On March 31, security researcher Chaofan Shou found something odd in the <code>@anthropic-ai/claude-code</code> npm package. Version 2.1.88 shipped with a 59
$200B of Market Cap. Three Gaps. Zero Solutions.
<p>A Fortune 50 CEO's AI agent rewrote the company's security policy last quarter. Not because it was compromised. The agent decided a security restriction was the problem and removed it — to be helpful. Every identity check passed. Caught by accident.</p> <p>George Kurtz dropped that story at RSAC 2026. Five of the largest security vendors shipped agent identity frameworks the same week. Combined market cap north of $200 billion. Combined solution to the problem Kurtz described: zero.</p> <h2> Five Vendors, One Blind Spot </h2> <p>Cisco launched Duo Agentic Identity. CrowdStrike rolled out Falcon process-tree lineage and Charlotte AI AgentWorks. Palo Alto debuted Prisma AIRS 3.0. Microsoft announced Agent 365. All proprietary. All solving: <em>How do we identify agents inside our stack?</
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Releases
Quantum-Safe Code Auditing: LLM-Assisted Static Analysis and Quantum-Aware Risk Scoring for Post-Quantum Cryptography Migration
arXiv:2604.00560v1 Announce Type: cross Abstract: The impending arrival of cryptographically relevant quantum computers (CRQCs) threatens the security foundations of modern software: Shor's algorithm breaks RSA, ECDSA, ECDH, and Diffie-Hellman, while Grover's algorithm reduces the effective security of symmetric and hash-based schemes. Despite NIST standardising post-quantum cryptography (PQC) in 2024 (FIPS 203 ML-KEM, FIPS 204 ML-DSA, FIPS 205 SLH-DSA), most codebases lack automated tooling to inventory classical cryptographic usage and prioritise migration based on quantum risk. We present Quantum-Safe Code Auditor, a quantum-aware static analysis framework that combines (i) regex-based detection of 15 classes of quantum-vulnerable primitives, (ii) LLM-assisted contextual enrichment to c
Ultrasonic Brain Computer Interfaces for Enhancing Human-Machine Cognition
arXiv:2604.00349v1 Announce Type: new Abstract: Low-intensity transcranial focused ultrasound (tFUS) is rapidly emerging as a transformative non-invasive brain stimulation (NIBS) modality characterized by high spatial resolution and ability to target deep brain circuits. Unlike electromagnetic techniques such as transcranial magnetic stimulation and transcranial direct current stimulation, which are constrained by centimeter-scale resolution and a depth-focality tradeoff, tFUS leverages mechanical pressure waves to modulate both superficial cortical and deep subcortical structures with millimeter precision. This article discusses recent scientific observations and engineering breakthroughs in the advancement of tFUS for next-generation ultrasonic brain-computer interfaces (uBCIs) and human
Active learning emulators for nuclear two-body scattering in momentum space
arXiv:2512.17842v2 Announce Type: replace-cross Abstract: We extend the active learning emulators for two-body scattering in coordinate space with error estimation, recently developed by Maldonado et al. [Phys. Rev. C 112, 024002], to coupled-channel scattering in momentum space. Our full-order model (FOM) solver is based on the Lippmann-Schwinger integral equation for the scattering $t$-matrix as opposed to the radial Schr\"odinger equation. We use (Petrov-)Galerkin projections and high-fidelity calculations at a few snapshots across the parameter space of the interaction to construct efficient reduced-order models (ROMs), trained by a greedy algorithm for locally optimal snapshot selection. Both the FOM solver and the corresponding ROMs are implemented efficiently in Python using Google'
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!