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DjangoCon Europe 2024 | KEYNOTE: AI, away from the hype
Explore the reality of AI beyond the hype, discussing its limitations, challenges, and potential uses in various industries, from healthcare to agriculture, education, and more.
- AI is a tool, not a strategy, and companies should be aware of this.
- AI needs model health, just like humans need mental health.
- The blockchain-based internet could solve many problems, but first, we need to solve the energy problem.
- Data is the lifeblood of AI, and it’s essential to have good data governance and data privacy.
- AI is not always transparent, and it can be difficult to understand how it makes decisions.
- Generative AI is the future, but it’s also the source of many concerns, such as bias, hate speech, and intellectual property issues.
- AI can be used to automate tasks, but it’s not always clear what tasks are worth automating.
- AI can be used to make predictions, but it’s not always accurate.
- AI can be used to create art, music, and literature, but these creations may not be genuinely creative.
- AI can be used to improve healthcare, but it’s not a substitute for human expertise and judgment.
- AI can be used to improve agriculture, but it’s not a substitute for human labor and effort.
- AI needs security, and it’s vulnerable to attacks and misuse.
- The Dunning-Kruger effect is a bias that affects how we perceive and interact with AI.
- The hype cycle is a phenomenon where AI technology goes through a cycle of overhyping and disillusionment.
- There are many AI models, including transformers, that can be used for various tasks, but it’s essential to understand how they work and what they can do.
- AI can be used to create new business models, but it’s essential to understand the ethics and implications of these models.
- AI can be used to improve education, but it’s essential to ensure that it’s inclusive and accessible to all.
- AI can be used to improve transportation, but it’s essential to ensure that it’s safe and reliable.