BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20240304T155901Z UID:4F039FC6-07E1-4919-9862-E8778A8123AD DTSTART;TZID=Etc/UTC:20240321T120000 DTEND;TZID=Etc/UTC:20240321T130000 DESCRIPTION:Special Presentation by Prof. Walid Saad (Virginia Tech\, USA)\ nHosted by Future Networks Artificial Intelligence & Machine Learning (AIM L) Working Group\nDate/Time: Thursday\, March 21st\, 2024 @ 12:00 UTC\n\n[ ]\n\nTopic:\nArtificial General Intelligence (AGI)-Native Wireless Systems with Common Sense\n\nAbstract:\nNext-generation wireless systems\, such a s 6G and beyond\, are expected to tightly embed artificial intelligence (A I) into their design\, giving rise to what is termed AI-native wireless sy stems. Remarkably\, despite significant academic\, industrial\, and standa rdization efforts dedicated to AI-native wireless systems in the past few years\, even the very definition of such systems remains ambiguous. Presen tly\, most endeavors in this domain represent incremental extensions of co nventional "AI for wireless" paradigms\, employing classical tools like au toencoders\, diffusion models\, or large-language models to replicate esta blished wireless functionalities. However\, such approaches suffer from in herent limitations\, including the opaque nature of the adopted AI models\ , their tendency toward curve-fitting\, reliance on extensive training dat a\, energy inefficiency\, and limited generalizability to novel new\, unse en scenarios and out-of-domain/out-of-distribution data points. To surmoun t these challenges\, in this talk\, we unveil a bold\, pioneering framewor k for the development of artificial general intelligence (AGI)-native wire less systems. We particularly show how the fusion of wireless systems\, di gital twins\, and AI can catalyze a transformative\, revolutionary paradig m shift in both wireless and AI technologies by conceptualizing a next-gen eration AGI architecture imbued with "common sense" capabilities\, akin to human cognition. This architecture is envisioned to empower networks with reasoning\, planning\, and other human-like cognitive faculties such as i magination and deep thinking. We first define the technical tenets of comm on sense and\, subsequently\, we demonstrate how the proposed AGI architec ture can instill a new level of generalizability\, explainability\, and re asoning into tomorrow’s wireless networks\, liberating them from their c onventional physical constraints. We then discuss how AGI-native wireless systems can unleash novel use cases such as digital twins with analogical reasoning\, resilient experiences for cognitive avatars\, and brain-level holographic experiences. Following the establishment of the foundational p rinciples and components of AGI-native wireless systems\, we take a signif icant stride forward by forging a link with the emerging concept of semant ic communications. In doing so\, we demonstrate how the integration of cau sal reasoning (a key component of our AGI vision) with semantic communicat ion can usher in a new era of knowledge-driven\, reasoning AGI-native wire less systems. These systems represent a major departure from today’s dat a-driven\, knowledge-agnostic models\, offering enhanced sustainability an d resilience in their design and operation. We present our recent key resu lts\, rooted in AI\, theory of mind\, digital twins\, and game theory\, la ying the groundwork for the realization of AGI-native wireless systems\, a nd illustrating how our designed framework reduces data volume in networks while enhancing reliability\, crucial for next-generation wireless servic es like connected intelligence and holography. We conclude with a discussi on on the exciting opportunities in this field that can help redefine the intersection of wireless communications and AI.\n\nCo-sponsored by: IEEE F uture Networks\n\nSpeaker(s): Prof. Walid Saad\n\nVirtual: https://events. vtools.ieee.org/m/409919 LOCATION:Virtual: https://events.vtools.ieee.org/m/409919 ORGANIZER:c.polk@comsoc.org SEQUENCE:5 SUMMARY:Artificial General Intelligence (AGI)-Native Wireless Systems with Common Sense URL;VALUE=URI:https://events.vtools.ieee.org/m/409919 X-ALT-DESC:Description: <br /><p>Special Presentation by <strong>Prof. Wali d Saad (Virginia Tech\, USA)</strong><br>Hosted by <strong>Future Networks Artificial Intelligence &amp\; Machine Learning (AIML) Working Group</str ong><br>Date/Time: <strong>Thursday\, March 21st\, 2024 @ 12:00 UTC</stron g></p>\n<p><img src="https://events.vtools.ieee.org/vtools_ui/media/displa y/dcce1c50-2ebb-46d9-9924-e448eaceed89" alt="" width="1146" height="300">< /p>\n<p><br><span style="text-decoration: underline\;"><strong>Topic:</str ong></span><br>Artificial General Intelligence (AGI)-Native Wireless Syste ms with Common Sense</p>\n<p><br><span style="text-decoration: underline\; "><strong>Abstract:</strong></span><br>Next-generation wireless systems\, such as 6G and beyond\, are expected to tightly embed artificial intellige nce (AI) into their design\, giving rise to what is termed AI-native wirel ess systems. Remarkably\, despite significant academic\, industrial\, and standardization efforts dedicated to AI-native wireless systems in the pas t few years\, even the very definition of such systems remains ambiguous. Presently\, most endeavors in this domain represent incremental extensions of conventional "AI for wireless" paradigms\, employing classical tools l ike autoencoders\, diffusion models\, or large-language models to replicat e established wireless functionalities. However\, such approaches suffer f rom inherent limitations\, including the opaque nature of the adopted AI m odels\, their tendency toward curve-fitting\, reliance on extensive traini ng data\, energy inefficiency\, and limited generalizability to novel new\ , unseen scenarios and out-of-domain/out-of-distribution data points. To s urmount these challenges\, in this talk\, we unveil a bold\, pioneering fr amework for the development of artificial general intelligence (AGI)-nativ e wireless systems. We particularly show how the fusion of wireless system s\, digital twins\, and AI can catalyze a transformative\, revolutionary p aradigm shift in both wireless and AI technologies by conceptualizing a ne xt-generation AGI architecture imbued with "common sense" capabilities\, a kin to human cognition. This architecture is envisioned to empower network s with reasoning\, planning\, and other human-like cognitive faculties suc h as imagination and deep thinking. We first define the technical tenets o f common sense and\, subsequently\, we demonstrate how the proposed AGI ar chitecture can instill a new level of generalizability\, explainability\, and reasoning into tomorrow&rsquo\;s wireless networks\, liberating them f rom their conventional physical constraints. &nbsp\;We then discuss how AG I-native wireless systems can unleash novel use cases such as digital twin s with analogical reasoning\, resilient experiences for cognitive avatars\ , and brain-level holographic experiences. Following the establishment of the foundational principles and components of AGI-native wireless systems\ , we take a significant stride forward by forging a link with the emerging concept of semantic communications. In doing so\, we demonstrate how the integration of causal reasoning (a key component of our AGI vision) with s emantic communication can usher in a new era of knowledge-driven\, reasoni ng AGI-native wireless systems. These systems represent a major departure from today&rsquo\;s data-driven\, knowledge-agnostic models\, offering enh anced sustainability and resilience in their design and operation. We pres ent our recent key results\, rooted in AI\, theory of mind\, digital twins \, and game theory\, laying the groundwork for the realization of AGI-nati ve wireless systems\, and illustrating how our designed framework reduces data volume in networks while enhancing reliability\, crucial for next-gen eration wireless services like connected intelligence and holography. We c onclude with a discussion on the exciting opportunities in this field that can help redefine the intersection of wireless communications and AI.</p> END:VEVENT END:VCALENDAR