Jonathon Belotti thundergolfer

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!

\

AGENTS

AGENTS - PERSONAL

amazon alexa
Cortana
Allo
Facebook
Siri
Replika

Success Stories of Fine-Tuning LLMs Across Industries

Below is a summary of diverse use cases where companies fine-tuned large language models (LLMs) to solve business challenges that previous methods struggled with. Each case highlights the challenge, the fine-tuning approach, and the key results achieved.

Summary of Fine-Tuning Success Cases

Use Case	Key Results	Source Link
Wealth Management Assistant (Finance)	98% advisor adoption; document access up from 20% to 80%	OpenAI & Morgan Stanley
Insurance Claims AI (Insurance)	30% accuracy improvement vs. generic LLMs	[Insurance News (EXL)](https://www.insurancenews.c

	package tm;

	public final class MachinesLibrary
	{
	private MachinesLibrary() {}

	public static TuringMachine EqualBinaryWords()
	{
	TuringMachine newTM = new TuringMachine();
	newTM.addState("q1");

	import abc
	import time

	import boto
	from boto.emr.connection import EmrConnection
	from boto.regioninfo import RegionInfo
	from boto.emr.step import InstallPigStep

	import luigi
	from luigi.s3 import S3Target, S3PathTask

	a4b.amazonaws.com
	access-analyzer.amazonaws.com
	account.amazonaws.com
	acm-pca.amazonaws.com
	acm.amazonaws.com
	airflow-env.amazonaws.com
	airflow.amazonaws.com
	alexa-appkit.amazon.com
	alexa-connectedhome.amazon.com
	amazonmq.amazonaws.com

	load("@rules_python//python:defs.bzl", "py_runtime", "py_runtime_pair")
	load(":venv.bzl", "py_venv")
	load(":wrapper.bzl", "py_wrapper")

	py_venv(
	name = "py3_venv",
	# caching the venv interpreter doesn't work for two reasons:
	#
	# * there are no platform dependencies on this target: the cache will contain binaries for the wrong OS
	# * there are no dependencies on the interpreter binary or standard library: the cache may contain stale versions