Join Logan Kilpatrick and Nolan Fortman as we dive deep into how having an AI-first mindset is one of the key enablers for the broad adoption of AI. Conor has trained hundreds of thousands of people to use AI and currently serves as the head of generative AI at NYU Stern. Takeaways - Stay out of the AI bubble and understand how people outside of the tech industry think. - Simplify technical terms and focus on real-life applications when explaining AI to non-technical individuals. - Grennan's AI productivity stack includes tools like perplexity and fine-tuned models. - He is excited about the personalization capabilities of AI and its potential to transform content creation. - Grennan expresses concern about the challenges posed by deepfakes and the need to educate vulnerable populations about AI. Demystifying AI is crucial for successful implementation, and leadership and culture play a significant role in this process. - Non-technical backgrounds can provide an advantage in understanding the potential of AI and breaking down preconceived notions. - Staying informed about AI requires reading newsletters, listening to podcasts, and following experts on platforms like Twitter. - AI implementation in academia faces challenges, but faculty can adapt their teaching methods to incorporate AI effectively. - Small teams and organizations with a strong learning and trust culture tend to see tangible returns from AI implementation. - Integrating AI in organizations requires reframing the mindset and setting new benchmarks for productivity and quality.
