AI Bubble Burst? Companies Are Seeing The Problems With AI! Ron Baron [CkZvFjDKUKZ]

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AI was supposed to make companies cheaper to run. Instead it created a brand-new cost crisis called Tokenmaxxing.

As bosses push every employee to use AI for everything, AI bills are quietly exploding. Some companies now spend crores a month on tokens. Others burned through their entire annual AI budget in just four months. And this mess is opening up an entirely new business opportunity most people haven't spotted yet.

In this deep dive you'll learn:

What AI tokens actually are, in plain English

Why token costs went from cents to real money almost overnight

What Jensen Huang really meant by "spend $250,000 on tokens"

4 practical ways companies the amazing spider-man 2 are cutting AI costs: cheaper default models, model routing, caching, and lean context

How to run free open-source models on your own laptop, phone, or a Mac Studio

Why AI hardware and inference rigs are becoming a massive industry

3 real business opportunities you can build in the Tokenmaxxing era

Whether you're an employee who wants to become the person who does more with fewer tokens, a founder watching your AI bill climb, a developer, an investor, or just someone trying to understand the real economics of AI, this case study breaks down one of the biggest shifts happening in artificial intelligence right nifty 50 now.

CHAPTERS

0:00 The AI job panic everyone got wrong

0:30 How "Tokenmaxxing" actually started

1:43 What is an AI token

2:17 Why tokens went from cents to dollars

3:41 Jensen Huang's $250,000 token argument

4:52 Fix 1: Use a cheaper default model

5:44 Fix 2: Model routing explained

7:31 Fix 3: Caching

8:31 Fix 4: Keep your context lean

10:16 The hardware side: inference rigs

11:37 A Mac Studio as your own AI rig

11:53 Why AI hardware demand is exploding

13:04 How employees can cash in

14:09 3 business ideas for founders

14:59 The bigger picture

#Tokenmaxxing #AICost #ArtificialIntelligence #AITools #AIforBusiness

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