During this glimpse into the space station we will be joined by representatives from the NASA ISS Program Science Office and ISS U.S. As part of NASA’s Destination Station, this is a unique opportunity to understand the space-based orbiting laboratory that enables innovative research capable of pushing the boundaries of exploration, and benefitting life on Earth. Join us for an exciting opportunity to learn about the world’s only crewed, multinational research laboratory and technology test bed in orbit: the International Space Station (ISS). The future of AI meets the future of space. Topics of interest include both systems for AI and AI for systems, including but not limited to: AutoAI algorithms, HCI of AutoAI and AI, AI lifecycle management, AI platforms, AI programming languages, algorithm toolkits and frameworks, distributed learning, GPU processing, data visualization, AI lifecycle acceleration, AI application composition, automated ML and synthesis, HCI of AI, security and ethics, hardware for AI.
This workshop has expanded this year to include two parallel tracks and a morning and afternoon session: AI Systems, AI Lifecycle Management, AutoAI Algorithms, and HCI for AutoAI.
Machine learning also feeds back into systems research to provide novel techniques and approaches. As machine learning techniques rapidly grow in popularity, the design, implementation, and deployment of systems that enable machine learning applications also rapidly grow in importance. This workshop builds on the success of last year’s AI Systems Day workshop targeting the intersection of machine learning and systems. This workshop will foster a discussion of major challenges in applying AI to mental health and neurological disorders and consider novel strategies to overcome them. AI has great potential to develop digital phenotypes based on behaviors, redefine neuropsychiatric assessment, increase understanding of mental illnesses, and personalize treatment. Their clinical data are often in the form of subjective and qualitative patient statements and written notes. Mental health practitioners are more hands-on and patient-centered in their clinical practice than most non-psychiatric practitioners, relying more on “softer” skills, like forming relationships with patients and directly observing patient behaviors and emotions. While AI technology is becoming more prevalent in medical practice, the discipline of mental health has been slower to adopt AI. One in five Americans suffers from a mental illness that requires care but there is a severe shortage healthcare experts.
#Ihbm 2018 human brain mapping driver#
Mental illness is prevalent and a major driver of high costs of overall healthcare. This session will include lightening talks from featured posters and researchers, and awards for the Best Posters. All AI Research Week participants are welcome to join! Projects cover a variety of topics in AI including fundamental advances in machine learning and reasoning algorithms (deep learning, reinforcement learning, generative adversarial networks, novel NN techniques for program induction, causal structure learning and inference, and many more) AI for healthcare, life sciences, cybersecurity mapping AI algorithms to quantum and analog architectures and AI for social good, including ethics and avoiding bias in AI, economics and workforce implications of AI, and AI applied to broad societal challenges. Posters from over 80 collaborative AI research projects will be presented in a social setting with food and drinks provided to promote networking and collaboration building. Check out cutting-edge research from the MIT-IBM Watson AI Lab and AI Horizons Network's world-class universities, network with the researchers, and discuss how their work will shape the future of AI.
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