Generative AI @Google

The Columbia University Emerging Technology Consortium is pleased to host a discussion with Google on an overview of cutting-edge research and applications of generative AI, including utilizing various AI/ML toolsets on the Google Cloud Platform.

Highlights of the discussion include key trends for guiding AI principles, the concept of generative AI, a large language model, and the considerations of AI like this and other applications in higher institutions for advancing teaching, learning, and research. 

Google experts shared their views about education and learning that will transform and accelerate as the ecosystem of users adapts and adjusts to its technology. Along the way, users build the guard rails and tools and incorporate innovation into the ecosystem. 

For educators and learners, generative AI can be an incredible lab assistant capable of delivering information and details at a fast pace. Google and other industry leaders aim to ensure those details are both accurate and close to the state of the world. 

Five trends that guide the principles of Generative AI at Google consist of:

1. Highly capable, general-purpose machine learning models
2. More improvements in the efficiency of machine learning models 
3. Shifting from a human-computer interaction mode to a human-computer collaboration mode
4. Growing impact of these models in engineering, science, health, and sustainability
5. Building AI tools and peripheral technologies for safety grounding, reliability, and responsibilities 

Organizations and higher education institutions seeking to build large language models can leverage existing models trained with their private information. These generative AI models can generate new artifacts in text, image, or video forms. In addition to a large language model, organizations will soon need high-quality search capabilities and conversational AI platforms embedded in the large language models.

For students thinking about the future of work, there has been a shift in AI exercise, and new jobs have been created with the concept of prompt design and engineering. Enterprises and organizations will require new skills and creativity to work with prompt engineering. These careers may grow quickly and become high in demand as these models and technology are here to help us be more productive and provide more value.

Google has been a pioneer in AI and leading research on fundamental and applied large language models. The organization applies and actively innovates this research into all dimensions, such as hardware, frameworks, services and different types of artifacts that can create to meet the needs of generative AI today.

About Speakers

Hamidou Dia, VP of Global Head Solutions Engineering at Google Cloud, leads designing Google Cloud solutions for customers on a path to digital transformation. Hamidou is a highly regarded technologist across the cloud technology sector and helps Google Cloud customers harness the power of data, analytics, artificial intelligence, and machine learning when solving their digital transformation challenges.

Dan Banga, Product Manager of Core Machine Learning Engineering at Google, builds products to accelerate fundamental machine learning research and applied machine learning innovations into Google products such as assistance, cloud, labs, maps, photos and Youtube. Dan leads initiatives in close collaboration with researchers, applied scientists, domain solutions, engineers, platform and compiler engineers to identify evolving technology needs, then design and deliver machine learning capabilities that would meet those needs at a large scale.

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