16 July 2025
Topic: Research And Papers
Can AI really code? Study maps the roadblocks to autonomous software engineering
A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward....
Google’s AI agent ‘Big Sleep’ just stopped a cyberattack before it started
Google’s AI agent, dubbed Big Sleep, has achieved a cybersecurity milestone by detecting and blocking an imminent exploit in the wild—marking the …...
TL;DR
Google's Big Sleep AI agent has successfully detected and blocked an imminent exploit in the wild, marking a major breakthrough in AI-driven cybersecurity.
Key Takeaways:
Key Takeaways:
- Big Sleep has identified a critical vulnerability in SQLite (CVE-2025-6965) before it was exploited.
- This breakthrough shifts the defense from reactive patching to AI-driven prediction and prevention, potentially saving devices and data worldwide.
- Google's AI security efforts are expanding, with initiatives like Timesketch, FACADE, and partnerships like the AI Cyber Challenge with DARPA aimed at crowd-sourcing innovations.
GenAI Meets Quantum: How GenAI and Quantum Computing Are Transforming Our Future
Join us on 28 August at the Fairfield Inn & Suites – Houston Memorial City Area for an energizing, two-hour session where two distinguished industry …...
TL;DR
GenAI and Quantum Computing experts will share cutting-edge convergence insights at a two-hour session on August 28.
Key Takeaways:
Key Takeaways:
- Experts will discuss practical strategies for overcoming deployment challenges and revolutionizing finance, healthcare, and space with quantum algorithms.
- Attendees will see real-world case studies and participate in a 15-minute Q&A session on pragmatic approaches in GenAI and Quantum Computing.
- Speakers Shenson Joseph and Parth Saxena are leaders in AI and Machine Learning, with expertise in ethical and explainable AI, and practical AI applications in healthcare and finance.
University students feel ‘anxious, confused and distrustful’ about AI in the classroom and among their peers
The advent of generative AI has elicited waves of frustration and worry across academia for all the reasons one might expect: Early studies are …...
TL;DR
University students report feelings of anxiety, confusion, and distrust about AI use in the classroom due to unclear expectations and perceptions of unfairness.
Key Takeaways:
Key Takeaways:
- Students feel guilty or ashamed about using AI due to environmental, ethical concerns, or perceptions of laziness.
- Distrust and frustration among students lead to avoidance of peers and learning interactions, potentially undermining academic engagement and student success.
- Institutions of higher education should prioritize clear guidelines, faculty-student relationships, and peer-to-peer connections to mitigate AI-related anxiety and foster a more supportive learning environment.
Join Our Livestream: Inside the AI Copyright Battles
Curious about generative AI and copyright? Subscribers can join WIRED live on July 16 as we answer your questions about this critical topic....
Incoming late summer: 8B and 70B models trained on 15T tokens, fluent in 1000+ languages, open weights and code, Apache 2.0. Thanks Switzerland!
Support for diffusion models (Dream 7B) has been merged into llama.cpp
[R][D] Interpretability as a Side Effect? Are Activation Functions Biasing Your Models?
OpenAI Built Codex in Just 7 Weeks From Scratch
Anyone having luck with Hunyuan 80B A13B?
[R] Is the Two-Tower Model Hitting Its Limits for RecSys Retrieval?
I tested Opus 4 against Grok 4 and Opus is still the most tasteful model
Is there any realistic theory that AGI is "near" (i.e. within a decade)?
Would AI potentially cause a “reverse migration”?
[R] Interesting paper on cost-aware prompt optimization (CAPO)
So Grok 4 and not Grok 3 was "MechaHitler"?