We’re living in a new world now — one where it’s an AI-powered penetration tester that “now tops an eminent US security industry leaderboard that ranks red teamers based on reputation.” CSO Online reports:
On HackerOne, which connects organizations with ethical hackers to participate in their bug bounty programs, “Xbow” scored notably higher than 99 other hackers in identifying and reporting enterprise software vulnerabilities. It’s a first in bug bounty history, according to the company that operates the eponymous bot…
Xbow is a fully autonomous AI-driven penetration tester (pentester) that requires no human input, but, its creators said, “operates much like a human pentester” that can scale rapidly and complete comprehensive penetration tests in just a few hours. According to its website, it passes 75% of web security benchmarks, accurately finding and exploiting vulnerabilities. — Read More
Monthly Archives: July 2025
hypercapitalism and the AI talent wars
Meta’s multi-hundred million dollar comp offers and Google’s multi-billion dollar Character AI and Windsurf deals signal that we are in a crazy AI talent bubble.
The talent mania could fizzle out as the winners and losers of the AI war emerge, but it represents a new normal for the foreseeable future. If the top 1% of companies drive the majority of VC returns, why shouldn’t the same apply to talent? Our natural egalitarian bias makes this unpalatable to accept, but the 10x engineer meme doesn’t go far enough – there are clearly people that are 1,000x the baseline impact.
This inequality certainly manifests at the founder level (Founders Fund exists for a reason), but applies to employees too. Key people have driven billions of dollars in value – look at Jony Ive’s contribution to the iPhone, or Jeff Dean’s implementation of distributed systems at Google, or Andy Jassy’s incubation of AWS. — Read More
No Code Is Dead
Once again, the software development landscape is experiencing another big shift. After years of drag-and-drop, no-code platforms democratizing app creation, generative AI (GenAI) is eliminating the need for no-code platforms in many cases.
Mind you, I said “no code” not “low code” — there are key differences. (More on this later.)
GenAI has introduced the ability for nontechnical users to use natural language to build apps just by telling the system what they want done. Call it “vibe coding” — the ability to describe what you want and watch AI generate working applications, or whatever. But will this new paradigm enhance existing no-code tools or render them obsolete?
I sought out insights from industry veterans to explore this pivotal question, revealing a broad spectrum of perspectives on where the intersection of AI and visual development is heading. — Read More
The hidden cost of AI reliance
I want to be clear: I’m a software engineer who uses LLMs ‘heavily’ in my daily work. They have undeniably been a good productivity tool, helping me solve problems and tackle projects faster. This post isn’t about how we should reject LLMs and progress but rather my reflection on what we might be losing in our haste to embrace them.
The rise of AI coding assistants has brought in what many call a new age of productivity. LLMs excel at several key areas that genuinely improve developer workflows: writing isolated functions; scaffolding boilerplate code like test cases, configuration files, explaining unfamiliar code or complex algorithms, generating documentation and comments, and helping with syntax in unfamiliar languages or frameworks. These capabilities allow us to work ‘faster’.
But beneath this image of enhanced efficiency, I find myself wondering if there’s a more troubling affect: Are we trading our hard-earned intelligence for short-term convenience? — Read More
Andrew Ng: Building Faster with AI
Inside a neuroscientist’s quest to cure coma
Locked inside their minds, thousands await a cure. Neuroscientist Daniel Toker is racing to find it.
The study of consciousness is a field crowded with scientists, philosophers, and gurus. But neuroscientist Daniel Toker is focused on its shadow twin: unconsciousness.
His path to this research began with a tragedy — one he witnessed firsthand. While at a music festival, a young concertgoer near Toker dove headfirst into a shallow lake. He quickly surfaced, his body limp and still. Toker, along with others, rushed to help. He performed CPR, but it soon became apparent that the young person’s neck had snapped. There was nothing to be done. — Read More
Introducing warmwind OS : The AI Operating System That Works Smarter
What if your operating system didn’t just run your computer but actively worked alongside you, anticipating your needs, learning your habits, and automating your most tedious tasks? Enter warmwind OS, the world’s first AI-driven operating system, a bold leap into the future of human-computer interaction. Unlike traditional systems that passively wait for your commands, warmwind OS operates as a proactive partner, seamlessly blending into your workflows to eliminate inefficiencies and free up your time for what truly matters. Imagine an OS that not only understands your goals but actively helps you achieve them—this isn’t science fiction; it’s here.
In this introduction of warmwind OS, its development team explain how it redefines the relationship between humans and technology. From its new teaching mode that allows the AI to learn directly from your actions to its ability to integrate with even the most outdated legacy software, this operating system is designed to adapt to your unique needs. Whether you’re looking to streamline customer support, enhance HR processes, or simply reclaim hours lost to repetitive tasks, warmwind OS offers a glimpse into a smarter, more intuitive future. As you read on, consider this: what could you achieve if your technology worked as hard as you do? — Read More
Lean and Mean: How We Fine-Tuned a Small Language Model for Secret Detection in Code
We fine-tuned a small language model (Llama 3.2 1B) for detecting secrets in code, achieving 86% precision and 82% recall—significantly outperforming traditional regex-based methods. Our approach addresses the limitations of both regex patterns (limited context understanding) and large language models (high computational costs and privacy concerns) by creating a lean, efficient model that can run on standard CPU hardware. This blog post details our journey from data preparation to model training and deployment, demonstrating how Small Language Models can solve specific cybersecurity challenges without the overhead of massive LLMs.
This research is now one of Wiz’s core Secret Security efforts, adding fast, accurate secret detection as part of our solution. — Read More
‘Positive review only’: Researchers hide AI prompts in papers
Research papers from 14 academic institutions in eight countries — including Japan, South Korea and China — contained hidden prompts directing artificial intelligence tools to give them good reviews, Nikkei has found.
Nikkei looked at English-language preprints — manuscripts that have yet to undergo formal peer review — on the academic research platform arXiv.
It discovered such prompts in 17 articles, whose lead authors are affiliated with 14 institutions including Japan’s Waseda University, South Korea’s KAIST, China’s Peking University and the National University of Singapore, as well as the University of Washington and Columbia University in the U.S. Most of the papers involve the field of computer science. — Read More
LiteLLM
LiteLLM is a LLM gateway that lets you Call all LLM APIs using the OpenAI format [Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, Groq etc.]. Support for missing a providers or LLM Platform can be requested via a feature request. — Read More
Rick's Cafe AI 