AWS Machine Learning

NOVEMBER 29, 2023

Each trained model needs to be benchmarked against many tasks not only to assess its performances but also to compare it with other existing models, to identify areas that needs improvements and finally, to keep track of advancements in the field. Evaluating these models allows continuous model improvement, calibration and debugging.

Benchmark 78

Benchmark Metrics Engineering APIs 78

AWS Machine Learning

APRIL 8, 2024

In this post, we explore the latest features introduced in this release, examine performance benchmarks, and provide a detailed guide on deploying new LLMs with LMI DLCs at high performance. Be mindful that LLM token probabilities are generally overconfident without calibration. Qing Lan is a Software Development Engineer in AWS.

Engineering 80

Engineering Calibration APIs Enterprise 80

Callminer

AUGUST 1, 2017

With more than 15 years of experience in business, finance and accounting, she is also responsible for implementing financial controls and processes. Going from 50% first time resolution to 100% first time resolution might sound like a great target, but getting to 60% is already a 20% improvement over the benchmark. Scott Nazareth.

Contact Center 334

Contact Center Call Center Average Handle Time Real estate 334