Key insights

• ⚙️ Generative AI, like chatGPT, seems human-like but falls short in understanding and value compared to humans.
• 📝 AI can produce first drafts of letters or syllabi but needs to be proofread for accuracy.
• 🔮 Predictive AI and enterprise machine learning are used to improve large-scale operations by learning from data to make predictions.
• 📦 UPS uses predictive AI to streamline delivery efficiency, saving millions of dollars and reducing emissions.
• 💼 AI can help with marketing, fraud detection, and maintenance decisions to improve efficiencies and benefit the economy.
• 🏭 Machine learning generates models to improve large-scale operations across industries.
• 🚚 Augmenting known package information with predicted deliveries using a predictive model, optimizing delivery routes for better planning and loading of packages.
• 🧠 Generative AI is progressing towards AGI, Artificial General Intelligence, which can perform tasks like a person.

Q&A

• Is Generative AI aiming for Artificial General Intelligence (AGI)?

  Generative AI is progressing towards AGI, which can perform tasks like a person. However, the focus should be on concrete value and practical applications, rather than replicating human capabilities, to avoid mismanaged expectations and hype.

• How can a company use predictive models to optimize delivery routes?

  A company can augment known package information with predicted deliveries using a predictive model to optimize delivery routes, improve large-scale operations, and enhance efficiencies by assigning likelihood to outcomes and acting on the results for effective implementation.

• What are the applications of Predictive AI?

  Predictive AI is applied in prioritizing building inspections for fire risk, identifying at-risk patients in healthcare, and optimizing delivery operations. Machine learning, a part of Predictive AI, generates models to improve large-scale operations across industries, such as streamlining delivery efficiency and saving costs.

• How can AI be used for predictive analysis?

  AI is used for predictive analysis to improve large-scale operations in various industries by learning from data and making predictions. However, the produced outputs, like first drafts of letters or syllabi, need to be proofread for accuracy before being utilized.

• What is the difference between Generative AI and Predictive AI?

  Generative AI, like chatGPT, can seem human-like but lacks true understanding and value compared to humans, while Predictive AI, used in enterprise machine learning, improves large-scale operations by making predictions based on data, such as in marketing, fraud detection, and maintenance decisions.

• 00:00 Generative AI is hyped as a solution to all business problems but is limited in its capabilities. Predictive AI, on the other hand, still holds untapped value. Eric Siegel shares his journey and expertise in the field of artificial intelligence.
• 01:24 Generative AI, like chatGPT, seems human-like but falls short in understanding and value compared to humans.
• 02:42 Using AI for predictive analysis can improve large-scale operations, but it must be proofread for accuracy. This type of technology has the potential to benefit the economy and improve efficiencies.
• 03:56 Predictive AI has various applications such as predicting fire risk for buildings, identifying patients at risk of readmission, and optimizing delivery operations. Machine learning generates models to improve large-scale operations across industries.
• 05:21 A company augments known package information with predicted deliveries using a predictive model to optimize delivery routes and improve large-scale operations.
• 06:35 Generative AI is advancing towards AGI, but the focus should be on concrete value and practical applications rather than replicating human capabilities.