Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
LLM Evaluation and Alignment, the Foundational Ideas: Building Trustworthy AI Applications

LLM Evaluation and Alignment, the Foundational Ideas: Building Trustworthy AI Applications

Lee, Han

Paperback

General Computers

PREORDER - Expected ship date January 26, 2027

ISBN10: 1633434249
ISBN13: 9781633434240
Publisher: Manning Publications
Published: Jan 26 2027
Pages: 275
Weight: 0.72
Language: English
Get the eBook free when you register your print book at Manning.

It's a fundamental truth that all software--even AI systems--is broken. AI engineers who can diagnose faults and refine systems to align with business needs are in high demand. This book expands the foundational research into judging and adapting AI systems into a collection of practical techniques you can use on the job. As you trace the progression from surface-level text matching to semantic similarity to judgment-based evaluation, you'll build the mental models necessary to choose the right metrics, detect failure modes, and close the loop from evaluation to alignment.

This book teaches you to think of evaluation as a design constraint. You'll employ a working backwards methodology that begins with what your system must get right, which directs you to the appropriate evaluation approach. As you internalize the define > evaluate > analysis > align cycle, you'll start making more informed tradeoffs and expertly balancing helpfulness, safety, and brand voice in your models.

What's inside

- BLEU, ROUGE, BERTScore, COMET, and LLM-as-a-judge methods

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