[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ admin_label=”Features” module_id=”about” _builder_version=”4.21.0″ _module_preset=”default” background_color=”#dbdbdb” background_image=”https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/05\/rm380-10.jpg” background_blend=”overlay” custom_padding=”3.9%||||false|false” use_background_color_gradient_phone=”on” background_color_gradient_stops_phone=”#001528 0%|rgba(255, 255, 255, 0) 10%|rgba(255,255,255,0) 70%|#0f0122 100%” collapsed=”on” global_colors_info=”{}”][et_pb_row column_structure=”2_3,1_3″ _builder_version=”4.21.0″ _module_preset=”default” custom_padding=”27px||43px|||” global_colors_info=”{}”][et_pb_column type=”2_3″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
Recent progress in generative models have resulted in models that can produce realistic text, images and video that can potentially revolutionize the way humans work, create content and interact with machines. The workshop on Generative AI at AIMLSystems will focus on the entire life-cycle of building and deploying such Generative AI systems, including data collection and processing, developing systems and requisite infrastructure, applications it enables, and the ethics associated with such technology covering concerns related to fairness, transparency and accountability. We invite original, unpublished work on Artificial Intelligence with a focus on generative AI and their use cases. Specifically, the topics of interest include but are not limited to:<\/p>\n
- \n
- Systems, architecture and infrastructure for Generative AI<\/li>\n
- Machine learning and Modeling using LLMs and Diffusion models<\/li>\n
- Large Language Models and its applications<\/li>\n
- Multi-modal Generative AI and its applications<\/li>\n
- Gen AI based Plugins and agents<\/li>\n
- Deployment of Generative AI solutions<\/li>\n
- Evaluation of Language and Diffusion based models<\/li>\n
- Responsible use of Gen AI<\/li>\n<\/ul>\n
<\/span><\/p>\n
[\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_tabs active_tab_background_color=”#1c1b3a” inactive_tab_background_color=”#0b91c6″ _builder_version=”4.21.0″ _module_preset=”default” tab_text_color=”#FFFFFF” background_color=”rgba(0,0,0,0)” custom_padding=”||0px||false|false” border_radii=”on|11px|11px|11px|11px” global_colors_info=”{%22gcid-f1f9244b-c8ab-43e1-95c3-c0bdf69ac7b5%22:%91%22active_tab_background_color%22,%22active_tab_background_color%22%93}”][et_pb_tab title=”Program Committee” _builder_version=”4.21.0″ _module_preset=”default” body_line_height=”1.4em” global_colors_info=”{}”]<\/p>\n
- \n
- Anupam Purwar, Senior Research Scientist, Amazon<\/span><\/li>\n
- Danish Pruthi, Indian Institute of Science (IISC), Bangalore<\/span><\/li>\n
- Sunayana Sitaram, Principal Researcher<\/span>, Microsoft Research\u00a0<\/li>\n<\/ul>\n
[\/et_pb_tab][\/et_pb_tabs][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.21.0″ _module_preset=”default” hover_enabled=”0″ locked=”off” global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n
Schedule<\/b><\/h2>\n
\n<\/p>\n
- Danish Pruthi, Indian Institute of Science (IISC), Bangalore<\/span><\/li>\n
- Anupam Purwar, Senior Research Scientist, Amazon<\/span><\/li>\n
<\/span><\/strong><\/span><\/p>\n
<\/span><\/span><\/p>\n![\"\"](\"https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/10\/mausam-head_cropped-300x300.jpg\")
<\/span><\/strong><\/span><\/p>\n![\"\"](\"https:\/\/www.aimlsystems.org\/2023\/wp-content\/uploads\/2023\/10\/mitesh-300x300.jpg\")
<\/span><\/span><\/p>\n