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AI News Digest: July 29, 2026

Daily roundup of AI and ML news - 8 curated stories on security, research, and industry developments.

Here's your daily roundup of the most relevant AI and ML news for July 29, 2026. Today's digest includes 1 security-focused story. We're also covering 6 research developments. Click through to read the full articles from our curated sources.

Security & Safety

1. Claude AI Just Cracked a Post-Quantum Test Scheme and Found a Faster 7-Round AES Attack

Anthropic says Claude Mythos Preview helped derive an end-to-end key-recovery attack against HAWK-256 and a 200- to 800-fold speedup for an attack on seven-round AES-128.

The HAWK attack exploits a previously unused symmetry in the lattice behind the signature scheme. Anthropic's released implem...

Source: The Hacker News (Security) | 19 hours ago

Research & Papers

2. Robustness Certificates for Neural Networks Against Data Poisoning and Evasion Attacks

arXiv:2512.20865v3 Announce Type: replace Abstract: The increasing use of machine learning in safety-critical domains amplifies the risk of adversarial threats, especially data poisoning attacks that corrupt training data to degrade performance or induce unsafe behavior. Most existing defenses l...

Source: arXiv - Machine Learning | 10 hours ago

3. WALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders

arXiv:2607.25763v1 Announce Type: cross Abstract: This paper proposes a multitask wireless foundation model via adaptive low-rank masked autoencoders (WALoMA), a unified multi-task foundation model for sixth-generation (6G) wireless physical layer architectures, to address the limitations of spe...

Source: arXiv - Machine Learning | 10 hours ago

4. Benchmarking Deep Learning Models for Raman Spectroscopy Across Open-Source Datasets

arXiv:2601.16107v2 Announce Type: replace Abstract: Deep learning classifiers for Raman spectroscopy are increasingly reported to outperform classical chemometric approaches. However, their evaluations are often conducted in isolation or compared against traditional machine learning methods or t...

Source: arXiv - Machine Learning | 10 hours ago

5. A Human-in-the-Loop Corpus for LLM-Based Simplification of Scientific Summaries

arXiv:2607.25630v1 Announce Type: cross Abstract: Interdisciplinary research is accelerating, yet scientific papers remain difficult to understand outside their home fields. We study large language model (LLM)-based simplification of scientific texts and present a human-in-the-loop workflow that...

Source: arXiv - AI | 10 hours ago

6. Device Invariance using Domain Adaptation on Acoustic Scene Classification

arXiv:2607.25887v1 Announce Type: cross Abstract: This paper explores the effectiveness of domain adaptation techniques when using convolutional neural network (CNN)-based and transformer-based feature representations for acoustic scene classification. Two well-known domain adaptation techniques...

Source: arXiv - AI | 10 hours ago

7. AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation

arXiv:2602.17071v4 Announce Type: replace Abstract: Graph neural networks frequently encounter significant performance degradation when confronted with structural noise or non-homophilous topologies. To address these systemic vulnerabilities, we present AdvSynGNN, a comprehensive architecture de...

Source: arXiv - Machine Learning | 10 hours ago

Tech & Development

8. We’re running out of reasons to ignore AI safety

Earlier this month, OpenAI gave several of its AI models a task: complete a test designed to measure their cybersecurity capabilities. It put the systems in a sandboxed environment without an internet connection and set them off to work. What happened next is almost laughably silly - but also, as...

Source: The Verge - AI | 3 hours ago


About This Digest

This digest is automatically curated from leading AI and tech news sources, filtered for relevance to AI security and the ML ecosystem. Stories are scored and ranked based on their relevance to model security, supply chain safety, and the broader AI landscape.

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