PODCAST:The AI in Business Podcast
TITLE:Driving Infrastructure Transformations for New Generative AI Use Cases - with Steve Astorino of IBM
DATE:2024-01-30 00:00:00
URL:
MODEL:gpt-4-gizmo
The episode of the AI in Business podcast features Steve Astorino, director of the Canada Lab and VP of development in data and AI at IBM. The discussion centers on the infrastructure challenges enterprises face when leveraging new AI use cases, particularly with data-intensive generative AI tools. Astorino highlights several key challenges:
GPU Availability: The primary challenge is the availability of GPUs necessary for training large language models and executing them efficiently. This shortage is slowing the adoption of new AI capabilities but is also seen as an opportunity to address the technology's risks responsibly.
Selection of the Right Tools: Businesses often find themselves overwhelmed by the plethora of AI tools available, making it crucial to choose the right ones for successful implementation. This selection process has become even more critical with the rapid advancements in AI and the potential risks associated with its misuse.
Skills Gap: There's a noticeable lack of skills in the workforce to effectively utilize AI technologies. Astorino discusses IBM's efforts in education and training to address this gap, emphasizing the importance of industry-wide collaboration to enhance AI skills among professionals.
Data Challenges: Clean, accessible, and private data is essential for the effective use of AI. Astorino points out the difficulties in accessing clean data, the importance of privacy, and the need for comprehensive governance around data and AI models to ensure ethical and secure use.
The conversation also touches on the cultural and ethical considerations of AI adoption, suggesting that the rapid pace of AI development necessitates a more mature and cautious approach. Astorino emphasizes the need for better governance, regulations, and tools to manage AI's risks while harnessing its transformative potential. The discussion concludes with a look forward to a future episode focused on AI ethics, highlighting the interconnectedness of data governance and ethical AI deployment.
