Tech Pulse 2030 is more than an event series—it's a global movement. With 12 events last year, it fuels collaboration, sparks bold ideas, and drives real-world impact across AI, FinTech, Web3, and beyond. Why Attend:

• Discover cutting-edge AI use cases driving positive impact
• Gain insights from global thought leaders and startup disruptors
• Build meaningful connections with peers across sectors

Host

Xiaochen Zhang, Executive Director & Chief AI Officer, AI 2030 Moderator: Uvika Sharma, Founder & Managing Partner INTLDA Speakers:

• Jie Li, Director, Lair East Labs
• Saurav Pandit, Founder, 2nd Set AI
• Anubha Kabra, Senior ML Research Engineer (Conversational AI), Bloomberg
• Daniel Sieberg, Founder and CEO, ScreenGeni.us

About AI 2030 AI 2030 is a global initiative committed to harnessing AI’s transformative power to benefit humanity.Focused on Responsible AI, AI for All, and AI for Good, we empower individuals and organizations with the knowledge, tools, and networks needed to lead in Responsible AI, closing key gaps in awareness, talent, and solutions to enable responsible AI adoption across public and private sectors globally. www.ai2030.org

About FinTech4Good FinTech4Good is a global network focused on emerging technologies. We collaborate with startups, industrial leaders, NPOs, and investors to develop solutions for a better world. https://www.fintech4good.co/

About 1871 The Chicagoland Entrepreneurial Center, dba 1871 is a 501c3 organization that exists to inspire, equip, and support people from all backgrounds to build and innovate extraordinary businesses. https://1871.com/

When March 21, 2024 – 10:00 AM Pacific

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/march-2024-ai-machine-learning-data-science-meetup/

Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Images that change their appearance under a transformation, such as a rotation or a flip, have long fascinated students of perception, from Salvador Dalli to M. C. Escher. The appeal of these multi-view optical illusions lies partly in the challenge of arranging visual elements such that they may be understood in multiple different ways. Creating these illusions requires accurately modeling—and then subverting—visual perception. We propose a simple, zero-shot method for obtaining these illusions from off-the-shelf text-to-image diffusion models. During the reverse diffusion process, we estimate the noise from different views of a noisy image. We then combine these noise estimates together and denoise the image. A theoretical analysis suggests that this method works precisely for views that can be written as orthogonal transformations. An important special case of these transformations are permutations of an image's pixels, which we use to create a variety of "anagram" illusions, such as jigsaw puzzles that can be solved in two different ways.

Speaker: Andrew Owens is an assistant professor at The University of Michigan in the department of Electrical Engineering and Computer Science. Prior to that, he was a postdoctoral scholar at UC Berkeley. He received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016. He is a recipient of a Computer Vision and Pattern Recognition (CVPR) Best Paper Honorable Mention Award, and a Microsoft Research Ph.D. Fellowship.

Omnidirectional Computer Vision

Omnidirectional cameras are a different camera modality than what we are typically used to, where we sacrifice nice geometry for significantly larger fields-of-view. Ciarán will discuss Omnidirectional cameras, how to represent them geometrically, optical effects of using omnidirectional cameras, neural networks on omnidirectional cameras, and applications that use omnidirectional cameras.

Speaker: Ciaran Eising is an Associate Professor of Artificial Intelligence and Computer Vision at the University of Limerick, Ireland and co-founder of the D2iCE Research Group. Prior to joining the University of Limerick, Ciarán was a Senior Expert of Computer Vision (director level) at Valeo, designing omnidirectional vision algorithms for low-speed vehicle automation.

Illuminating the Underground World with Multimodal Algorithms

Dive deep into the future of underground exploration! This talk introduces a groundbreaking approach that leverages the power of multimodal algorithms, combining advanced computer vision techniques, SLAM algorithms, sensor metadata, and GIS data. By integrating diverse data streams, we unlock unprecedented levels of detail and accuracy in underground inspections, paving the way for safer, more efficient, and insightful subterranean analyses. About the Speaker

Speaker: Adonaí Vera is a Machine Learning Engineer with expertise in computer vision and AI algorithms, specializing in AI solutions for underground inspections using TensorFlow and OpenCV. Recognized by Google as a top TensorFlow developer in Colombia, he is also the founder of a company focused on AI innovations and currently contributes his expertise to Subterra AI.

The Role of AI in Fixing Hiring

From writing job descriptions, to sourcing candidates, to interviews and evaluation – our current hiring practices are often rife with human bias. Even when such bias is unconscious, it can result in expensive mis-hires. This talk explores the types of biases and the pivotal role of AI in mitigating them. We will discuss the common sources of bias in hiring, the current AI landscape that attempts to address these issues and further opportunities.

Speaker: Saurav Pandit is a seasoned AI leader with expertise in natural language understanding, search and language models. He is on the advisory board of AI 2030, an initiative that promotes AI for good.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.

When March 21, 2024 – 10:00 AM Pacific

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/march-2024-ai-machine-learning-data-science-meetup/

Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Images that change their appearance under a transformation, such as a rotation or a flip, have long fascinated students of perception, from Salvador Dalli to M. C. Escher. The appeal of these multi-view optical illusions lies partly in the challenge of arranging visual elements such that they may be understood in multiple different ways. Creating these illusions requires accurately modeling—and then subverting—visual perception. We propose a simple, zero-shot method for obtaining these illusions from off-the-shelf text-to-image diffusion models. During the reverse diffusion process, we estimate the noise from different views of a noisy image. We then combine these noise estimates together and denoise the image. A theoretical analysis suggests that this method works precisely for views that can be written as orthogonal transformations. An important special case of these transformations are permutations of an image's pixels, which we use to create a variety of "anagram" illusions, such as jigsaw puzzles that can be solved in two different ways.

Speaker: Andrew Owens is an assistant professor at The University of Michigan in the department of Electrical Engineering and Computer Science. Prior to that, he was a postdoctoral scholar at UC Berkeley. He received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016. He is a recipient of a Computer Vision and Pattern Recognition (CVPR) Best Paper Honorable Mention Award, and a Microsoft Research Ph.D. Fellowship.

Omnidirectional Computer Vision

Omnidirectional cameras are a different camera modality than what we are typically used to, where we sacrifice nice geometry for significantly larger fields-of-view. Ciarán will discuss Omnidirectional cameras, how to represent them geometrically, optical effects of using omnidirectional cameras, neural networks on omnidirectional cameras, and applications that use omnidirectional cameras.

Speaker: Ciaran Eising is an Associate Professor of Artificial Intelligence and Computer Vision at the University of Limerick, Ireland and co-founder of the D2iCE Research Group. Prior to joining the University of Limerick, Ciarán was a Senior Expert of Computer Vision (director level) at Valeo, designing omnidirectional vision algorithms for low-speed vehicle automation.

Illuminating the Underground World with Multimodal Algorithms

Dive deep into the future of underground exploration! This talk introduces a groundbreaking approach that leverages the power of multimodal algorithms, combining advanced computer vision techniques, SLAM algorithms, sensor metadata, and GIS data. By integrating diverse data streams, we unlock unprecedented levels of detail and accuracy in underground inspections, paving the way for safer, more efficient, and insightful subterranean analyses. About the Speaker

Speaker: Adonaí Vera is a Machine Learning Engineer with expertise in computer vision and AI algorithms, specializing in AI solutions for underground inspections using TensorFlow and OpenCV. Recognized by Google as a top TensorFlow developer in Colombia, he is also the founder of a company focused on AI innovations and currently contributes his expertise to Subterra AI.

The Role of AI in Fixing Hiring

From writing job descriptions, to sourcing candidates, to interviews and evaluation – our current hiring practices are often rife with human bias. Even when such bias is unconscious, it can result in expensive mis-hires. This talk explores the types of biases and the pivotal role of AI in mitigating them. We will discuss the common sources of bias in hiring, the current AI landscape that attempts to address these issues and further opportunities.

Speaker: Saurav Pandit is a seasoned AI leader with expertise in natural language understanding, search and language models. He is on the advisory board of AI 2030, an initiative that promotes AI for good.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.

When March 21, 2024 – 10:00 AM Pacific

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/march-2024-ai-machine-learning-data-science-meetup/

Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Images that change their appearance under a transformation, such as a rotation or a flip, have long fascinated students of perception, from Salvador Dalli to M. C. Escher. The appeal of these multi-view optical illusions lies partly in the challenge of arranging visual elements such that they may be understood in multiple different ways. Creating these illusions requires accurately modeling—and then subverting—visual perception. We propose a simple, zero-shot method for obtaining these illusions from off-the-shelf text-to-image diffusion models. During the reverse diffusion process, we estimate the noise from different views of a noisy image. We then combine these noise estimates together and denoise the image. A theoretical analysis suggests that this method works precisely for views that can be written as orthogonal transformations. An important special case of these transformations are permutations of an image's pixels, which we use to create a variety of "anagram" illusions, such as jigsaw puzzles that can be solved in two different ways.

Speaker: Andrew Owens is an assistant professor at The University of Michigan in the department of Electrical Engineering and Computer Science. Prior to that, he was a postdoctoral scholar at UC Berkeley. He received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016. He is a recipient of a Computer Vision and Pattern Recognition (CVPR) Best Paper Honorable Mention Award, and a Microsoft Research Ph.D. Fellowship.

Omnidirectional Computer Vision

Omnidirectional cameras are a different camera modality than what we are typically used to, where we sacrifice nice geometry for significantly larger fields-of-view. Ciarán will discuss Omnidirectional cameras, how to represent them geometrically, optical effects of using omnidirectional cameras, neural networks on omnidirectional cameras, and applications that use omnidirectional cameras.

Speaker: Ciaran Eising is an Associate Professor of Artificial Intelligence and Computer Vision at the University of Limerick, Ireland and co-founder of the D2iCE Research Group. Prior to joining the University of Limerick, Ciarán was a Senior Expert of Computer Vision (director level) at Valeo, designing omnidirectional vision algorithms for low-speed vehicle automation.

Illuminating the Underground World with Multimodal Algorithms

Dive deep into the future of underground exploration! This talk introduces a groundbreaking approach that leverages the power of multimodal algorithms, combining advanced computer vision techniques, SLAM algorithms, sensor metadata, and GIS data. By integrating diverse data streams, we unlock unprecedented levels of detail and accuracy in underground inspections, paving the way for safer, more efficient, and insightful subterranean analyses. About the Speaker

Speaker: Adonaí Vera is a Machine Learning Engineer with expertise in computer vision and AI algorithms, specializing in AI solutions for underground inspections using TensorFlow and OpenCV. Recognized by Google as a top TensorFlow developer in Colombia, he is also the founder of a company focused on AI innovations and currently contributes his expertise to Subterra AI.

The Role of AI in Fixing Hiring

From writing job descriptions, to sourcing candidates, to interviews and evaluation – our current hiring practices are often rife with human bias. Even when such bias is unconscious, it can result in expensive mis-hires. This talk explores the types of biases and the pivotal role of AI in mitigating them. We will discuss the common sources of bias in hiring, the current AI landscape that attempts to address these issues and further opportunities.

Speaker: Saurav Pandit is a seasoned AI leader with expertise in natural language understanding, search and language models. He is on the advisory board of AI 2030, an initiative that promotes AI for good.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.

When March 21, 2024 – 10:00 AM Pacific

Where Virtual / Zoom - https://voxel51.com/computer-vision-events/march-2024-ai-machine-learning-data-science-meetup/

Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models

Images that change their appearance under a transformation, such as a rotation or a flip, have long fascinated students of perception, from Salvador Dalli to M. C. Escher. The appeal of these multi-view optical illusions lies partly in the challenge of arranging visual elements such that they may be understood in multiple different ways. Creating these illusions requires accurately modeling—and then subverting—visual perception. We propose a simple, zero-shot method for obtaining these illusions from off-the-shelf text-to-image diffusion models. During the reverse diffusion process, we estimate the noise from different views of a noisy image. We then combine these noise estimates together and denoise the image. A theoretical analysis suggests that this method works precisely for views that can be written as orthogonal transformations. An important special case of these transformations are permutations of an image's pixels, which we use to create a variety of "anagram" illusions, such as jigsaw puzzles that can be solved in two different ways.

Speaker: Andrew Owens is an assistant professor at The University of Michigan in the department of Electrical Engineering and Computer Science. Prior to that, he was a postdoctoral scholar at UC Berkeley. He received a Ph.D. in Electrical Engineering and Computer Science from MIT in 2016. He is a recipient of a Computer Vision and Pattern Recognition (CVPR) Best Paper Honorable Mention Award, and a Microsoft Research Ph.D. Fellowship.

Omnidirectional Computer Vision

Omnidirectional cameras are a different camera modality than what we are typically used to, where we sacrifice nice geometry for significantly larger fields-of-view. Ciarán will discuss Omnidirectional cameras, how to represent them geometrically, optical effects of using omnidirectional cameras, neural networks on omnidirectional cameras, and applications that use omnidirectional cameras.

Speaker: Ciaran Eising is an Associate Professor of Artificial Intelligence and Computer Vision at the University of Limerick, Ireland and co-founder of the D2iCE Research Group. Prior to joining the University of Limerick, Ciarán was a Senior Expert of Computer Vision (director level) at Valeo, designing omnidirectional vision algorithms for low-speed vehicle automation.

Illuminating the Underground World with Multimodal Algorithms

Dive deep into the future of underground exploration! This talk introduces a groundbreaking approach that leverages the power of multimodal algorithms, combining advanced computer vision techniques, SLAM algorithms, sensor metadata, and GIS data. By integrating diverse data streams, we unlock unprecedented levels of detail and accuracy in underground inspections, paving the way for safer, more efficient, and insightful subterranean analyses. About the Speaker

Speaker: Adonaí Vera is a Machine Learning Engineer with expertise in computer vision and AI algorithms, specializing in AI solutions for underground inspections using TensorFlow and OpenCV. Recognized by Google as a top TensorFlow developer in Colombia, he is also the founder of a company focused on AI innovations and currently contributes his expertise to Subterra AI.

The Role of AI in Fixing Hiring

From writing job descriptions, to sourcing candidates, to interviews and evaluation – our current hiring practices are often rife with human bias. Even when such bias is unconscious, it can result in expensive mis-hires. This talk explores the types of biases and the pivotal role of AI in mitigating them. We will discuss the common sources of bias in hiring, the current AI landscape that attempts to address these issues and further opportunities.

Speaker: Saurav Pandit is a seasoned AI leader with expertise in natural language understanding, search and language models. He is on the advisory board of AI 2030, an initiative that promotes AI for good.

Don’t Forget

• Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.
• Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.