Detralytics’ Post

"Recurrent quantum embedding neural network and its application in #vulnerability #detection" Interesting paper about Innovating Vulnerability Detection with #Quantum #NLP 🌐 The integration of deep learning has the potential to propel vulnerability detection to unprecedented heights. This latest paper presents a pioneering approach, merging #QuantumComputing and Natural Language Processing (NLP) to enhance the efficiency and effectiveness of these methods: Introducing the Recurrent Quantum Embedding Neural Network (RQENN), designed to significantly reduce the memory consumption traditionally associated with vulnerability detection tasks while leveraging the unique capabilities of quantum computing to refine the performance of NLP methods. According to the researchers, the findings underscore the potential of quantum technologies in practical applications and set a new standard in #cybersecurity. I have attached the paper to explore how RQENN is reshaping vulnerability detection through the power of quantum computing. Citation: Song, Z., Zhou, X., Xu, J. et al. Recurrent quantum embedding neural network and its application in vulnerability detection. Sci Rep 14, 13642 (2024). https://lnkd.in/d7QguCrR #QuantumComputing #Cybersecurity #NLP #Innovation #Technology

Facts About The Origin Of Artificial Intelligence – How It All Started? Artificial Intelligence amazing facts untold: 1956 Conference at Dartmouth College. In the summer of 1956, Dartmouth hosted a scientific conference where a young brain and ambitious mind defined the term “Artificial Intelligence “later known as the Father of Artificial Intelligence “Sir John McCarthy. There are proven facts in AI that prior to these historical conferences, scientists had already framed natural language and neural network concepts lacking a more natural and universally accepted term for the stunning concept of machine “Mind”. #AIforCybersecurity#CyberAIDefense #FutureofCybersecurity #AIforGood #FutureofAI #ResponsibleA #MachineLearning #DeepLearning #NLP For more information, kindly contact me. ☎ ☎ ☎ ☎ https://lnkd.in/gFTfy6SQ  

🔍 Delighted to unveil my latest project in AI and natural language processing! 🚀 I've developed a sophisticated model to automatically classify SMS messages as spam or legitimate. Leveraging advanced techniques such as TF-IDF for feature extraction and employing powerful classifiers like Naive Bayes, Logistic Regression, and Support Vector Machines, our model achieves high accuracy in identifying spam messages with precision. This project has been a fantastic opportunity to deepen my expertise in machine learning, particularly in text classification and data preprocessing. It underscores the pivotal role of AI in enhancing cybersecurity measures and optimizing communication channels. Excited to continue exploring new frontiers in AI and applying these insights to real-world challenges! 🌐💡 #AI #MachineLearning #NLP #SpamDetection #DataScience #TechInnovation #Cybersecurity CodSoft

🔍 AI in Fraud Detection🔍 In today's digital world, protecting against fraud has never been more crucial. With the help of Artificial Intelligence (AI), we're seeing incredible strides in how we detect and prevent fraudulent activities. Here’s how AI is changing the game: ➡️Anomaly Detection: Spotting those unusual patterns that just don’t fit the norm. ➡️Ensemble Learning: Combining different models to boost accuracy in predictions. ➡️Natural Language Processing (NLP): Analyzing text data to find hidden signs of fraud. ➡️Deep Learning: Using advanced neural networks to uncover complex fraud schemes. ➡️Machine Vision: Understanding visual data to detect fraud. ➡️Predictive Analysis: Predicting fraudulent behavior before it happens. These technologies are more than just buzzwords—they’re powerful tools that can help businesses stay one step ahead of fraudsters. As AI continues to evolve, our ability to protect ourselves and our customers will only get better. What are your thoughts on AI in fraud detection? Do you see these technologies changing the landscape of digital security? Let’s discuss! #AIFraudDetection #MachineLearning #DeepLearning #NLP #PredictiveAnalytics #TechInnovation #CyberSecurity #DataScience #BusinessSecurity #AI #ArtificialIntelligence

#artificialintelligence and #quantumcomputing can help each other 👇 These are some of the areas where #ai and quantum computing complement each other: 🖊️ Enhanced optimization 🖊️ Pattern recognition 🖊️ Simulation and modelling 🖊️ Speeding up #machinelearning 🖊️ Handling #bigdata 🖊️ Improved natural language processing (#nlp ) 🖊️ #cybersecurity and encryption 🖊️ Quantum machine learning Which other areas would you add to this list? Read the full "Quantum Computing in Web3" deck here 👉[https://lnkd.in/dJVknpX5] Txs Giorgio Torre (SFC)™ 🔺 🔺 for the great share Tino Herold

The NLP IL - Natural Language Processing Israel April meetup is next week (Monday, 8/4)! Our next meetup at Dream will focus on creating and maintaining custom LLMs. We will hear 2 in-depth lectures - Elad Ben-Zaken 🎗️ from Dream will talk about the training process of a domain-specific cybersecurity LLM and all the lessons learned from that project. Then, Nadav Barak from Deepchecks will show us how we can more effectively evaluate our LLMs performance without requiring a fleet of manual annotators. Link to the meetup event in the first comment! Please register in advance (attendance is free as always). For more events and updates, please join our Whatsapp community! Link in the second comment. And as always, looking for more speakers and hosting companies - if you’re interested, please fill the form on the third comment. #meetup #nlp #datascience #llm

Unlock the Power of AI in OSINT Research! Are you curious about how Artificial Intelligence is transforming Open Source Intelligence (OSINT) research? Dive my report to discover the numerous benefits AI brings to this critical field: 🔍 Speed and Efficiency: AI automates data collection and analysis, saving researchers significant time and enabling work with larger data sets. 📈 Accuracy and Reliability: Advanced AI techniques like machine learning and Natural Language Processing (NLP) enhance the accuracy and depth of OSINT findings. 🌐 Scalability and Scope: AI handles large volumes of data from diverse sources and languages, providing a global perspective. 🤖 Enhanced Decision Making: AI supports better decision-making with data-driven insights and predictive analytics. 💰 Cost-Effectiveness: AI reduces labor costs and optimizes resource allocation, making OSINT research more efficient. #ArtificialIntelligence #OSINT #Research #AIinOSINT #DataAnalysis #MachineLearning #CyberSecurity #FutureTech #Innovation

How is #NaturalLanguageProcessing Revolutionizing the Arms Industry? The integration of Natural Language Processing (#NLP) in the arms industry signifies a significant advancement in defense technology. It enables automated threat analysis, improves communication through speech recognition and language translation, and enhances #cybersecurity capabilities. NLP's role extends to crisis response, psychological warfare applications, and disinformation detection, highlighting its pivotal role in shaping future defense strategies and operations. #AMR #NLPinDefense #MilitaryTechnology #SecurityInnovation #DefenseRevolution #AIinArmsIndustry #FutureOfDefense

In recent years, deep learning has shown remarkable results in identifying vulnerabilities using natural language processing (NLP). However, NLP's heavy computing demands are paving the way for quantum computing innovations. Researchers have created a Recurrent Quantum Embedding Neural Network (RQENN) for this purpose. RQENN significantly reduces memory consumption and enhances performance, using fewer qubits and achieving 15.7% higher accuracy in vulnerability detection compared to classic models. This leap forward demonstrates the powerful synergy of AI and quantum computing in cybersecurity. https://lnkd.in/g9hgi_j4 #AI #QuantumComputing #Cybersecurity #IP #VC #Patents #DeepTech

#artificialintelligence and #quantumcomputing can help each other 👇 These are some of the areas where #ai and quantum computing complement each other: 🖊️ Enhanced optimization 🖊️ Pattern recognition 🖊️ Simulation and modelling 🖊️ Speeding up #machinelearning 🖊️ Handling #bigdata 🖊️ Improved natural language processing (#nlp ) 🖊️ #cybersecurity and encryption 🖊️ Quantum machine learning Which other areas would you add to this list? Read the full "Quantum Computing in Web3" deck here 👉[https://lnkd.in/dJVknpX5] Tino Herold