AI Reading List #17: Multimodality, Voice integration into ChatGPT, Gen AI Flywheel and bias.

I am curious about multimodality and its opportunities to bring artificial intelligence to the next step making our interactions with generative AI more human-like.

Multimodal generative AI refers to models that can process information from diverse sources, including images, voices, videos, and text. These models integrate and support multiple data types and formats within single frameworks, enhancing user experience and improving business processes. Companies like ChatGPT and Google Gemini are already implementing multimodality in AI.

“As artificial intelligence goes multimodal, medical applications multiply” (featured article)

Today’s featured research paper discusses Gen AI and multimodal medical applications, highlighting a shift towards using self-supervised and unsupervised data as complements to the traditionally dominant supervised learning.

Although multimodal AI is revolutionizing medicine by analyzing diverse data layers such as genomic, biomarker, and environmental information in real-time, supporting innovative applications like virtual health assistants and remote patient monitoring that could transform homes into care settings, it still faces significant challenges. These include data privacy concerns, embedded biases, and the lack of robust regulatory frameworks. Moreover, the integration of various data forms by this technology requires further development to fully harness its potential in healthcare.

Looking forward, the integration of massive computing power with multimodal AI capabilities is expected to revolutionize personalized medicine, offering more precise and predictive healthcare solutions through technologies like virtual health assistants and enhanced diagnostic tools.

If you are interested in AI applications in the Health sector Jan Beger is a notable AI advocate with a direct professional approach to the topic and is worth following.

Additional articles and resources to explore AI in the enterprise

• Voice Integration in ChatGPT. Given today's discussion on multimodality, I thought it would be insightful to share my experiences with incorporating voice functionality into ChatGPT.

• The path to generative AI value: Setting the flywheel in motion(By PWC). This article explains how different industries can use the flywheel concept to increase and realize the benefits of generative AI, helping them make the most of this technology's advantages. It includes an interactive value-realization flywheel to start prioritizing GenAI deployments. Worth exploring.

• Why Large Language Models Like ChatGPT Treat Black- and White-Sounding Names Differently (By Stanford HAI) This study shows systemic issues in some of the most popular language models. Gen AI technologies can potentially amplify societal biases based on the way they process racially associated names. A must-read for those interested in the intersection of technology and bias.

Follow me for more exciting insights into the world of generative AI. Have a great week!