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DTSTART;VALUE=DATE:20240428
DTEND;VALUE=DATE:20240513
DTSTAMP:20260416T120558
CREATED:20240105T081216Z
LAST-MODIFIED:20240105T081343Z
UID:10000276-1714262400-1715558399@www.neuropac.info
SUMMARY:CapoCaccia 2024: Workshop toward Neuromorphic Intelligence
DESCRIPTION:Theme for 2024: “Do robots dream of evolving sheep?”\nDuring the last couple of years we have experienced groundbreaking advances in AI. Transformer architectures are revolutionizing the way we deal with today’s vast amount of available data\, and are having a massive impact in our society. Despite these advancements\, AI systems still fall short of replicating the most basic yet highly sophisticated capabilities inherent in biological organisms: the effortless ability to sense\, navigate and interact efficiently with our environment. \nIn this workshop we will center our discussions on exploring which bio-inspired principles could be incorporated into neuromorphic “brains” to successfully guide future robots in noisy and unpredictable environments. Towards the end of the workshop we will revolve around one of the most fundamental distinctions between biological organisms and current AI systems: that biological intelligence emerges in the absence of any external designer. Biological brains evolved sophisticated algorithms to build themselves into powerful computational devices. Will this be the key to the future of robotics?. \nThe mission of the CapoCaccia Workshops for Neuromorphic Intelligence is to understand the principles of biological intelligence and apply this knowledge in technologies\, for the good of all mankind.\nThe workshop features open and highly interactive discussion sessions in the morning; hands-on projects\, tutorials\, and hardware and software jamming sessions during the day; and free-form discussions in the evenings. \nThe workshop is open to everyone\, but since resources are limited\, we can accept only a limited number of registrations. Due to the limited number of hotel rooms\, Ph.D. students are expected to pair up and share rooms. All participants are encouraged to stay for the full two week period\, but can stay for less if necessary. \nParticipants are expected to use their own sources of funding to pay their travel\, accommodation\, and registration expenses. \n\n\n\nThe registration will be open from Jan 08 until Jan 31\, 2024.
URL:https://www.neuropac.info/event/capocaccia-2024-workshop-toward-neuromorphic-intelligence/
LOCATION:Alghero\, Sardinia\, Italy\, Alghero\, Sardinia\, Italy
CATEGORIES:Workshop
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20240430
DTEND;VALUE=DATE:20240501
DTSTAMP:20260416T120558
CREATED:20240219T093217Z
LAST-MODIFIED:20240219T093217Z
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SUMMARY:ICONS 2024 Paper Deadline
DESCRIPTION:CALL FOR PAPERS: International Conference on Neuromorphic Systems (ICONS) 2024\nImportant Dates:\nApril 30\, 2024: Submissions due \nMay 15\, 2024: Reviews due \nJune 6\, 2024: Decision notification \nJuly 30-August 2\, 2024: Conference \nWith the looming end of the “Moore’s Law” era\, there is an emerging challenge to “create a new type of computer that can proactively interpret and learn from data\, solve unfamiliar problems using what it has learned\, and operate with the energy efficiency of the human brain.” \nNeuromorphic computing will play a major role in this challenge and has the potential to transform the way we use computers through new materials\, new brain-inspired chips\, greater understanding of neuroscience\, and breakthroughs in machine understanding/intelligence. Neuromorphic computing systems have the potential to mimic the functionality of neural systems in the brain\, which we believe will lead to more powerful and efficient computing paradigms. The goal of this conference is to bring together leading researchers in neuromorphic computing to present new research\, develop new collaborations\, and provide a forum to publish work in this area. \nRESEARCH PAPERS ARE REQUESTED FOR TOPICS ON NEUROMORPHIC COMPUTING\, SPECIFICALLY IN FOUR FOCUS AREAS:\n\nSystems\, architectures\, and circuits\n\nNetwork\, neuron\, and synapse models\nNon-von Neumann computing architectures and models\nEmerging devices and hardware implementations\nEvent or spike-based systems\nNeuromorphic circuits\nNovel brain-inspired system architectures\n\n\nMachine intelligence algorithms for programming or training neuromorphic devices\n\nSupervised\, unsupervised and self-supervised learning methods\nBiologically-inspired algorithms\nAdaptations to existing algorithms for use on or with neuromorphic systems\n\n\nApplications for and use-cases of neuromorphic systems\n\nApplications where neuromorphic systems have the potential to outperform state-of-the-art techniques\nSuggestions for benchmark tasks for neuromorphic computing\nNeuromorphic datasets\n\n\nSupporting software and systems for neuromorphic systems\n\nEfficient simulation techniques for hardware and large-scale networks\nCompilers and programming frameworks\nVisualization tools\n\n\n\nNote: Submissions outside the scope of these areas\, including materials science and neuroscience\, will also be considered (especially for lightning talks and posters)\, although they are not the focus of this conference. \nWE ARE ACCEPTING SUBMISSIONS IN THE FOLLOWING FORMATS:\n\nFull papers (6-8 pages)\, which will be considered for full (20 minute) presentations. Full papers should present original research and will be included in the conference proceedings. The page limit includes references\, appendix and any other material that would accompany the paper.\nShort papers (3-4 pages)\, which will be considered for full presentations and/or lightning talks. Short papers can be position papers or present preliminary results and will be included in the conference proceedings. The page limit includes references\, appendix and any other material that would accompany the paper.\nExtended abstracts (1 page) for lightning talks and/or poster presentations. Extended abstracts will not be included in the conference proceedings.\nTutorial submissions (2-3 pages) for 1-2 hour tutorial sessions. Tutorials should include a hands-on component for tutorial attendees to work on or interact with neuromorphic software or hardware. Tutorials should be led by no more than three facilitators. Unlike paper and abstract submissions\, tutorial submissions should be submitted via email to Melika Payvand and Maryam Parsa at melika [at] ini.uzh.ch and mparsa [at] gmu.edu.\nSpecial session submissions (2-3 pages) for 1-2 hour special sessions. Special sessions should include invited presentations on a specific topic. Special session submissions will not be included in the conference proceedings. Unlike paper and abstract submissions\, special session submissions should be submitted via email to Melika Payvand and Maryam Parsa at melika [at] ini.uzh.ch and mparsa [at] gmu.edu\n\nProgram Co-Chairs:\nMelika Payvand\, Institute of Neuroinformatics\, University of Zurich and ETH Zurich \nMaryam Parsa\, George Mason University \nSubmission Website: Coming soon
URL:https://www.neuropac.info/event/icons-2024-paper-deadline/
LOCATION:Online
CATEGORIES:Conference,Deadline
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DTSTART;TZID=America/New_York:20240504T110000
DTEND;TZID=America/New_York:20240504T121500
DTSTAMP:20260416T120558
CREATED:20240428T081014Z
LAST-MODIFIED:20240428T081014Z
UID:10000285-1714820400-1714824900@www.neuropac.info
SUMMARY:Sangyeob Kim @ ONM - C-DNN and C-Transformer: Mixing ANNs and SNNs for the Best of Both Worlds
DESCRIPTION:From the Open Neuromorphic website. \nSangyeob and his team have developed a C-DNN processor that effectively processes object recognition workloads\, achieving 51.3% higher energy efficiency compared to the previous state-of-the-art processor. Subsequently\, they have applied C-DNN not only to image classification but also to other applications\, and have developed the C-Transformer\, which applies this technique to a Large Language Model (LLM). As a result\, they demonstrate that the energy consumed in LLM can be reduced by 30% to 72% using the C-DNN technique\, compared to the previous state-of-the-art processor. In this talk\, we will introduce the processor developed for C-DNN and C-Transformer\, and discuss how neuromorphic computing can be used in actual applications in the future. \n\n\nAbout the Speaker\nSangyeob Kim (Student Member\, IEEE) received the B.S.\, M.S. and Ph.D. degrees from the School of Electrical Engineering\, Korea Advanced Institute of Science and Technology (KAIST)\, Daejeon\, South Korea\, in 2018\, 2020 and 2023\, respectively. He is currently a Post-Doctoral Associate with the KAIST. His current research interests include energy-efficient system-on-chip design\, especially focused on deep neural network accelerators\, neuromorphic hardware\, and computing-in-memory accelerators.
URL:https://www.neuropac.info/event/sangyeob-kim-onm-c-dnn-and-c-transformer-mixing-anns-and-snns-for-the-best-of-both-worlds/
LOCATION:Online
CATEGORIES:Talk,Workshop
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