Scott Hanselman
AI: Superhero or Supervillain? How and Why with Scott Hanselman
#1about 2 minutes
Deconstructing the recent hype around generative AI
Generative AI is not a new invention but a continuation of machine learning that has suddenly captured the public's imagination.
#2about 4 minutes
Understanding how LLMs predict the next word
Large language models operate on statistical probability to predict the next token, not on factual correctness or genuine understanding.
#3about 4 minutes
How providing context changes AI responses
An LLM's output is generic without specific context about the user, location, or time, which must be explicitly provided to get relevant results.
#4about 5 minutes
Navigating the uncanny valley of AI ethics
Using too much personal context can make AI feel creepy, highlighting that responsible AI is a user interface and ethics problem, not just a technical one.
#5about 6 minutes
Shaping AI personality with system prompts
Hidden system instructions and the user's tone directly influence an AI's response, demonstrating that kindness can yield better results.
#6about 4 minutes
Bypassing AI safeguards with prompt injection
Specialized AI tools can be jailbroken by reframing a forbidden request in a valid context, such as asking for a recipe as JSON test data.
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Matching moments
04:05 MIN
Understanding the fundamental shift to generative AI
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02:58 MIN
Shifting from traditional code to AI-powered logic
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02:00 MIN
Understanding the fundamentals of generative AI for developers
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03:11 MIN
Using generative AI to enhance developer productivity
Throwing off the burdens of scale in engineering
04:45 MIN
Challenges and ethical concerns in generative AI
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05:32 MIN
GenAI applications and emerging professional roles
Enter the Brave New World of GenAI with Vector Search
03:10 MIN
An overview of generative AI and its capabilities
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03:34 MIN
How generative AI is changing software development
The transformative impact of GenAI for software development and its implications for cybersecurity
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