Cybercriminals have been struggling to adopt AI in their work, reports the first-of-its-kind study that analyzed a dataset of 100 million posts from underground cybercrime communities. The study is published on the arXiv preprint server.
In reality, most cybercriminals—often referred to as hackers—lack the skills or resources to support real innovation within their criminal activities, experts say.
A research team led by Virginia Tech cybersecurity expert Bimal Viswanath has found a critical blind spot in today’s image protection techniques designed to prevent bad actors from stealing online content for unauthorized artificial intelligence training, style mimicry, and deepfake manipulations. The study is published on the arXiv preprint server.
The research team found that attackers can defeat existing security using off-the-shelf artificial intelligence (AI) models and simple commands. Furthermore, “There is currently no foolproof, mathematically guaranteed way for users to protect publicly posted images against an adversary using off-the-shelf GenAI models,” Viswanath said.
The work was presented at the fourth IEEE Conference on Secure and Trustworthy Machine Learning, in Munich, Germany. The authors include Viswanath, doctoral students Xavier Pleimling and Sifat Muhammad Abdullah, Assistant Professor Peng Gao, Murtuza Jadliwala of the University of Texas at San Antonio, and Gunjan Balde and Mainack Mondal of the Indian Institute of Technology, Kharagpur.
A malicious version of the PyTorch Lightning package published on the Python Package Index (PyPI) delivers a credential-stealing payload targeting browsers, environment files, and cloud services.
The developer disclosed the supply-chain attack on April 30, saying that version 2.6.3 of the package included a hidden execution chain that downloads and executes a JavaScript payload.
PyTorch Lightning is a deep learning framework used for pretraining and fine-tuning AI models. It is a popular package, amassing more than 11 million downloads last month.
Hosted by the european conference on artificial intelligence.
Sponsored by Google DeepMind.
In August 1970, six chess-playing programs and their developers gathered in New York to compete in the 1st United States Computer Chess Championship. This important event in the history of AI research began a series of annual competitions that continues to this day, longer than any other experiment in computer science history.
There’s a very specific reason the tech giants are suddenly racing to get AI running locally on your phone, watch, and smart glasses.
The traditional Operating System (OS) is quietly being retired. Soon, the OS as you know it will be replaced entirely by an omnipresent AI hub.
But if the OS becomes an AI, what happens to that grid of static apps we rely on every day? And when the friction of swiping and searching disappears, how does the underlying economy of the Internet shift?
In my latest piece, I explore what happens next: the death of the app, the rise of dynamic AI “Sparks,” and a hidden token economy where your device doesn’t just cost you money—it generates it.
Want a glimpse at what your digital life looks like when you stop swiping and start orchestrating?
I have been on a breathtaking journey, for decades I have been watching how we connect with the world and each other. If you’ve been around tech long enough, you remember the humble hum of single twisted-pair copper wires, and the sheer, brick-like weight of early cell phones. Fast forward to today, and we are streaming the entirety of human knowledge over millimeter-wave antennas onto super-thin slabs of glass in our pockets.
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REFERENCES
How the 4 fundamental forces work • Why & How do the 4 fundamental forces of n…
History of atom • The Quantum Mechanical model of an atom. W…
Strong Force • Why Don’t Protons Fly Apart in the Nucleus… https://tinyurl.com/2bqv3b9y
Source of mass • How Can MASS and ENERGY be the Same Thing?… https://tinyurl.com/29crnzy2
Medium article https://tinyurl.com/2by2sdbq
Weak Force https://tinyurl.com/25gp9ty7
CHAPTERS
0:00 Why Universe is inside an Atom
1:29 What is an atom?
4:44 Louis de Broglie finds waves!
6:28 Electromagnetic force explained
7:24-Sponsor InVideo
8:35 Strong Force explained, color charges!
12:33 Weak Force explained
14:58 Why is Weak Force called a \.
In a previous article, I traced Adversarial Convergence (AC) through 2,500 years of human intellectual history — from Sun Tzu’s unsentimental assessment of self and enemy, through Socrates’ elenchus, through Hegel’s dialectic, and to Kant’s critical method. The argument was that AC isn’t a novel prompt engineering technique. It’s a formalization of something human cognition has been doing naturally whenever it operates at points of tension and resolution.
This raises a deeper question: why does structured adversarial reasoning consistently produce more refined analysis and conclusions? What is it about human cognitive architecture that makes this particular structure the natural shape of rigorous truth-seeking? The answer appears to live, at least in part, in a small but remarkably important region of the brain.
I called it, and said it for decades in here. ASI will be lead in to LEV.
Also, expect people and corpos in medical industry to freak out, and suddenly turn Anti Ai, once realized we are now about 9 years, (2035), from day Disease is no longer a Cash Cow to center careers and industries around. its already started, Doctors tryin to say AI is harmful and cant be trusted.
Derya Unutmaz, professor of immunology, is blown away by AI’s potential to improve healthcare. Here he lays out how he envisions the technology transforming drug discovery and disease eradication.