Your AI Injection

This week our guest was Pindar Van Arman. Pindar is an established artist who uses AI-driven robotic arms to paint. We talked with Pindar about his creative process and background, and  broke down the AI technology that he uses for his paintings. We also discussed the role of the robot as both a tool and a creative collaborator. 

To look at Pindar's work and learn about his creative and technological process, check out his website here:

• Cloudpainter.com

This week we had the chance to talk with Dr. Dennis Tenen, an associate professor of English and Comparative Lit at Columbia University. Dennis has been studying vaccine-hesitant language online, a project that is leveraging AI to better understand the various social and cultural explanations for vaccine-hesitancy. 

We chatted with Dennis about his unique background in the intersection of AI and literature, and about the machine learning that is helping bring his research to life. 

To learn more about Dennis' work, check out:

• https://denten.plaintext.in/

What if you could monitor your baby’s development with just your phone?

In this episode of Your AI Injection, Deep Dhillon talks to Bharath Modayur about Early Markers’ vision to bring developmental screening into every nursery. Their system helps parents identify delays in motor skills and other milestones by coming AI with clinically validated tools. Bharath shares how real-time feedback and targeted activities may enhance outcomes for infants, while reducing anxiety for parents. 

Learn more about Bharath here: https://www.linkedin.com/in/bmodayur/
and Early Markers here: https://earlymarkers.com/index

To find out more about how to use pose analysis to analyze activities, visit our website: Human Pose Analysis

Or check out our related content: 

• Using AI to Improve Sports Performance & Achieve Better Running Efficiency
• Unlocking At-Home Orthopedic Care through AI Imagery Analysis with Artem Semjanow
• Does AI Know Better Than Doctors? Our New Healthcare Reality with Oded Cohen

Has AI already replaced your favorite musician?

In this episode of Your AI Injection, host Deep Dhillon sits down with Jay Bartot, tech innovator and musician, to debate whether AI-generated music is empowering artists or erasing their relevance entirely. Jay reflects on how through his life digital tools have transformed his musical creativity, from his punk-rock roots to his later MIDI experiments. Now, as AI mimics iconic musicians and even completes unfinished Nirvana tracks, are we witnessing the end of authentic human musicianship? Join the conversation and discover how AI is rewriting the rules of music-making, and whether that's something to celebrate or fear.

Learn more about Jay here: https://www.linkedin.com/in/jay-bartot/

Check out the article on our website about this topic: How AI is Transforming Music Composition

Or check out our related content:

• AI's Evolving Role in Music Production with Dr. Hans-Martin Will
• AI's Potential Impact on Art Curation and Design with Gavi Wolf
• Streamlining the Film Production Process with AI featuring Ruslan Khamidullin

This week we interviewed Dr. Werner Koepf, a successful organization leader and AI Practitioner. Currently the Senior Vice President Of Engineering at Karat, Dr. Koepf has served as a tech. executive and CTO at numerous companies, including Expedia, Ticketmaster, and Conversica.

We chatted with Dr. Koepf about his background in theoretical physics, and how he transitioned to working in software and product development. Dr. Koepf shared some of his experiences that have shaped his approach to AI and what successful companies should do—and not do—to integrate AI into their business models. 

This week, our data scientists discuss how AI-driven body pose estimation technology can be used by athletes to improve sports performance. 

Too often, athletes face injuries that could have been prevented by better technique and body positioning. When running, impact at each step, overtraining and poor form can promote undue strain on muscles, joints, and tendons and the cumulative effect can lead to serious injury. Getting professional feedback from physical trainers to prevent these injuries can be costly, tedious, and ineffective. 

After facing a major injury while training for a marathon, one of Xyonix's own data scientists created a machine-learning algorithm that relies on body pose estimation technology to assess and correct his running form. The device measures the motions of key body parts based on videos of the runner to assess for inefficiencies such as asymmetrical technique or poor cadence. 

If you're interested in reading about this topic, visit our blog article here:

• Using AI to Improve Sports Performance & Achieve Better Running Efficiency

AI models are now being used to make life altering decisions in areas such as healthcare, hiring, lending, university admissions and criminal justice. The stakes of AI models to make decisions fairly could never be higher and yet there are many high profile examples where AI 
has been shown to produce unfair, inequitable and exclusive decisions.

In this episode of our podcast, data scientists at Xyonix talk about how to prevent societal biases from creeping into machine learning models, and why it's so important to be aware of these biases.

Read the article on our website:

• https://www.xyonix.com/blog/how-to-detect-and-mitigate-harmful-societal-bias-in-your-organizations-ai 

Artificial Intelligence is transforming industries around you every day, but all too often great opportunities to apply AI in business fail. 

In this episode, data scientists at Xyonix explain some of the most common reasons why AI fails and walk through ways to prevent it. Ranging from a lack of support from the broader company to a poorly structured team, these reasons can stifle AI innovation and if left unchecked, completely prevent eager businesses from successfully applying AI. 

To read more about this topic, visit the article on our website:

• https://www.xyonix.com/blog/10-reasons-why-ai-innovation-fails-according-to-an-ai-consultant

AI is increasingly used to make important decisions in our lives like predicting the onset of a disease, the suitability of a job candidate, the likelihood of a criminal to reoffend, or the next president of the United States. In such cases, having AI model outcomes that are explainable, or interpretable, is often just as important as having model outcomes that are accurate. In this episode, Xyonix Data Scientists engage in a robust discussion where we explore model interpretability and discuss why you should care.

Want to dig in more? Some of our related articles:

• Inside the Black Box, Developing Explainable AI Models
• Explaining a Passenger Survival AI Model Using SHAP for the RMS Titanic
  
  

Have an AI problem you need help with? Reach out to us at www.XyoniX.com