Cracking the AI Code: ROI, Challenges, and Insights with Luke Arrigoni | Part 2
Aug 24, 2023
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Luke Arrigoni, CEO at Arricor, discusses the practical problems and ROI of AI, emphasizing the need for engagement and preserving top talent. He explores the future implications of AI and its limitations in artistic creativity. The importance of role models and mentors in making human decisions is also highlighted.
The challenge in implementing AI lies in finding practical and cost-effective solutions that allow companies to reap the benefits without breaking the bank.
Building trust in AI models is crucial for their widespread adoption, and transparency, accountability, and ongoing education are key to ensuring responsible use of AI.
Deep dives
The challenge of taking AI models to production
One of the most common enterprise problems today is the difficulty of taking AI models to production. Many companies are building advanced models that work well in theory but struggle to be implemented in a functional and cost-effective way. Companies like Microsoft are losing millions of dollars each day just to host their models. The challenge lies in finding a solution that is both practical and affordable, allowing companies to reap the benefits of AI without breaking the bank. Ericor has excelled in this area by building systems that are not only advanced but also practical and able to solve real problems while making money.
The importance of framing and trust in AI adoption
One of the key blockers for companies adopting AI is trust. Many organizations fear the potential negative impacts of AI, such as biased outputs or hallucinations. Building trust in AI models is crucial for their widespread adoption. It is important for businesses to frame the challenges and risks appropriately. Rather than dismissing AI as a whole due to a single incident, it is essential to identify specific areas for improvement and consider the overall value AI can bring. Transparency, accountability, and ongoing education are key to building trust and ensuring AI is used responsibly.
The future of AI and the need for adaptability
The future of AI is both transformative and adaptive. As technology continues to evolve rapidly, it is essential for individuals and businesses to be adaptable to change. The pace of innovation and the compression of time between advancements means that staying ahead requires a constant focus on improvement. Mathematics and art are areas where AI currently falls short, as they require original thought and creativity. However, as AI progresses, these areas may also see advancements. To thrive in the AI era, individuals and organizations should strive to be in the top percentile of their respective fields and embrace change as a core competency.
Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin,WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
Want to be featured as a guest on Making Data Simple? Reach out to us at almartintalksdata@gmail.com and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
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