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Today we remember Herbert ("Herb") Alexander Simon, who was born #OTD in 1916. Simon received the 1975 #ACMTuringAward in joint scientific efforts extending over twenty years, and with co-recipient Allen Newell made basic contributions to artificial intelligence, the psychology of human cognition, and list processing. From pioneering heuristic problem-solving to developing the first successful AI programs like the Logic Theorist and the General Problem Solver, Simon’s work has been instrumental in shaping modern AI. His belief in simulating human problem-solving led to innovations that still influence AI research today: https://bit.ly/3UZzsjN

The Intersection of Self Awareness and Theory of Mind in AI Research: Exploring the fascinating realm where artificial intelligence meets human-like cognition. Did you know that according to recent studies, an impressive 85% of AI researchers believe that achieving self-awareness and theory of mind in AI systems is crucial for their future development? This highlights the growing recognition among experts that imbuing AI with these cognitive abilities is a significant milestone towards creating more sophisticated and empathetic AI companions. Let's delve deeper into how the integration of self-awareness and theory of mind can revolutionize the AI landscape. #SelfAwareAI #TheoryofMind #AI #Innovation #ResearchandDevelopment

Mind-reading AI? Not quite, but getting closer! Scientists are using AI to understand what people are thinking and seeing just by analyzing brain scans! Researchers have made big strides in using fMRI scans (those cool donut-shaped machine images) to capture brain activity patterns. By feeding this data into AI systems, they're getting better at decoding these patterns and reconstructing what a person might be thinking or seeing. While it's not full-on mind-reading yet, this is a huge leap forward in understanding the human brain. Who knows what amazing applications this could have in the future? Source: YT #science #technology #futureofai #generative #Ai

The human brain's intricate capabilities, driven by 86 billion neurons and unparalleled neural connectivity, set it apart from AI in complexity, emotional intelligence, and decision-making. While AI excels in data-driven insights, the brain's plasticity and creativity enable leaps of logic and nuanced thinking unmatched by current technology. When do you think Artificial Intelligence will surpass human intelligence? #AI #ArtificialIntelligence #humanintelligence

I'm happy to unveil the first milestone in my PhD journey, which began in September of last year: an advancement in Explainable AI (XAI) with our latest research. Our work focuses on enhancing local and model-agnostic explanations for complex neural networks, critical for understanding and trust in AI systems – closely aligned with the motivation of the AI Act by the EU. 🚀 Highlights of Our Research:  - Innovation Through Integration: Leveraging Foundation Models, specifically SAM (Segment Anything), to generate features that align with human cognition. - Hierarchical Approach: Treating segments hierarchically to mirror human reasoning more closely, allowing for concept-relational explanation. - Customizable Explanations: Empower end-users with the ability to define the level of granularity in explanations, making it easier to grasp human-known concepts. 🏆 Key Achievement: Our proposed method, DSEG-LIME, sets a new benchmark in the LIME field by outperforming existing techniques both quantitatively and qualitatively on the ImageNet dataset. This advancement is a leap toward making AI more interpretable and accessible. 📝 Preprint: https://lnkd.in/evBa_Shb 💻 GitHub Repo: https://lnkd.in/e6yhXFvB #AI #PhDJourney #AIAct #ML

Discover how foundation models can improve image explanations! The study shows a method for combining SAM with LIME, using a hierarchical concept structure for better image interpretation. 📝Preprint: https://lnkd.in/es9TRMTd 💻 Want to try it yourself? https://lnkd.in/ejGFWVUA

🔍 Georgia Tech researchers are pioneering a shift in how neural networks operate, bringing them closer to human decision-making. Their latest creation, RTNet, not only mimics the human brain's approach to making choices but also captures the nuances of uncertainty and variability that characterize our daily decision processes. Detailed in a recent Nature Human Behaviour publication, this model promises to enhance reliability and accuracy in AI systems, potentially reducing the cognitive load of our daily decision-making. Discover how this groundbreaking work could redefine machine learning! #AI #MachineLearning #NeuralNetworks #GeorgiaTech #Innovation Read more: https://lnkd.in/gNbciu2q

Hello LinkedIn community, I am thrilled to share some exciting news in the realm of Artificial Neural Networks (ANN). On April 5th, I will be introducing something truly captivating and groundbreaking within the ANN space. Having come across a fascinating development, I cannot wait to share this discovery exclusively with my esteemed connections. Artificial Neural Networks have been at the forefront of innovation, transforming the way we approach problem-solving and machine learning. The upcoming revelation promises to add a new dimension to our understanding and application of ANNs. I believe that sharing knowledge is key to advancing our field, and I am eager to engage with each one of you to discuss, learn, and collaborate. Let's collectively explore the potential of this discovery and its implications for the future of AI. Save the Date: April 05th Stay tuned for further updates! Feel free to reach out if you have any questions or if you'd like to connect before the big reveal. Looking forward to the journey of discovery and growth together! #ai #artificialintelligence #cyberdefense #glocybs

How will we know when AI becomes conscious? A recent post on Nature Portfolio’s journal Nature website (https://lnkd.in/eDxQJEed) brought me to look at an article currently available on the arXiv platform. The publication (https://lnkd.in/efjfybgc) by renowned specialists in AI is first authored by Patrick Butlin from University of Oxford and Robert Long from the Center for AI Safety, and includes Rufin Van Rullen from the CNRS in #Toulouse. The future of #AI consciousness is both intriguing and challenging. As AI continues to evolve, understanding its consciousness becomes paramount. In this paper: • The study draws parallels between human consciousness and the potential for AI consciousness. • AI systems are evaluated using "indicator properties" derived from neuroscientific theories. • A rigorous approach is taken to understand AI consciousness. • Current AI systems are analyzed against these properties to determine their level of consciousness. The verdict? No AI system today is deemed conscious, but the research suggests the potential exists and authors provides a foundation for this assessment. The door therefore remains open for future AI systems to achieve this elusive milestone. #Microsoft #OpenAI #Google #DeepMind #consciousness #innovation