1 option
AI superstream : AI engineering / Fabiana Clemente [and 8 others]
- Format:
- Video
- Author/Creator:
- Clemente, Fabiana, author.
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Physical Description:
- 1 online resource (1 video file (03 hr., 49 min.)) : sound, color.
- Edition:
- [First edition].
- Place of Publication:
- [Sebastopol, California] : O'Reilly Media, Inc., 2025.
- Summary:
- With the development of "model as a service," the powers of AI are now accessible to anyone with a solid set of prompting skills. However, leveraging the capabilities of AI models has its own set of challenges and requires new skills and techniques to ensure the reliability of AI applications in production. Fabiana Clemente welcomes a panel of speakers who are exploring the frontier of AI engineering and building the skills to meet this moment. They'll share the current state of this subdiscipline and what it demands of AI practitioners and software engineers who are transitioning to AI engineering. They'll also discuss emerging and established technologies, such as the leading AI models and agent frameworks as well as new agent protocols, and they'll examine the challenges of moving from simple prototypes to production-ready AI systems. What you'll learn and how you can apply it Learn the current state of the main subfields of AI engineering, from prompting engineering and fine-tuning to AI agents Explore emerging and established technologies such as leading AI models, agent frameworks, and new agent protocols Examine the challenges of moving from simple prototypes to production-ready AI systems Recommended follow-up: Read AI Engineering (book) Read AI Systems Performance Engineering (book) Listen to Generative AI in the Real World (podcast) Take Demystifying Generative AI: A Practical Look Under the Hood (live course with Thomas Nield) Watch GenAI Prompt to Product Showdown: Choosing the Best AI Tools (event video).
- Notes:
- OCLC-licensed vendor bibliographic record.
- OCLC:
- 1550495407
- Publisher Number:
- 0642572020243
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.