The applications of AI are numerous,
yet they suffer from vulnerabilities.
The importance of this is even greater in safety-critical systems,
where AI-based decisions can have a significant effect on users or operators.
We solve these problems.
keepn.ai maximizes the potential of your product by minimizing risk related to AI safety.
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Using our first generation solution, stakeholders, product, and R&D can define static and dynamic policies to govern the product’s behavior.
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Yesterday, I visited the AWS floor 28 in Azrieli Sarona, Tel Aviv. There was a really fun event called How To Secure Your Generative AI Application.
This workshop was a great opportunity to learn mor...
Can copyright be protected by diffusion models (DMs)? The CVPR 2024 paper suggests watermarks.
It is impressive how well DMs generate images.
However, DMs replicating unauthorized creations may viol...
Machine-learning-based Windows PE malware detectors can significantly be improved with explainability techniques.
In malware, it has become increasingly apparent that crafting optimal adversarial per...
Possibly the most influential figure in adversarial examples research ever.
Interested? Keep up with us 🖖
#research #neuralnetworks #deeplearning #adversarialexamples
Did you know? On-device deep learning models are being used in finance, social media, and driving assistance.
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On-device models on Android smartphones were proven to be extremely vulnerable becaus...
An informative post we post on behalf of. Hope you find it useful 🙂⚡️🙌
#ml #safety #mlsafety #machinelearning The `SB 1047` is a new bill in the California Legislature. It generally states that if...
Did you know? Compression using neural networks can reduce storage space by a factor of 1000.
As an example, a 2Gb hash-table can be compressed into a 2Mb neural network.
You can learn more by readi...
The Lasso (L1), Ridge (L2), and Elastic Net (L1+L2) techniques are regularization methods (and feature selection methods) in Machine Learning.
Obviously, each technique has pros and cons. The illustr...
JailbreakBench is an open robustness benchmark for jailbreaking language models.
Language models can generate harmful, unethical, or otherwise unwanted content as a result of jailbreak attacks.
The ...
Anyone who has studied Machine Learning knows the “No-Free-Lunch theorem” and why prior knowledge is essential. This paragraph from Understanding Machine Learning: From Theory to Algorithms by Shai Sh...
Need open-source LLM guardrails? Check out this post by Dor, our founder, from 4 months ago.
Want to stay up to date? Follow keepn.ai
#llm #guardrails #safety #security #mlops Securing your LLM sys...
Some more bits from our founder, we hope you find it useful.
Keep it up, and follow keepn.ai 🙏 Quantization of neural networks (NN) is a technique to reduce the NN required computational resources....
When Sam Altman and Ilya Sutskever were in Tel Aviv last year, Sam explained why ChatGPT was useful to him - Wikipedia is his favorite website.
#chatgpt #llm #attentionnetworks --> Dear ChatGPT, des...