SLMs: The Future of AI or Just a Cheap Trick? Nvidia Thinks You’re a Fool for LLMs 😂

Experts at Nvidia are like, “Hey, maybe we should stop spending billions on AI that costs more than your firstborn and try this cheaper option instead.” Groundbreaking. Who knew?

But no, everyone’s still obsessed with these overpriced, bloated LLMs. If this continues, the AI industry might slow down. Or maybe the U.S. economy will collapse. Either way, we’re doomed. 🤷♂️

  • Investors are throwing money at LLMs like they’re the last buffet in Vegas. Classic.
  • SLMs are the AI equivalent of a used car – cheaper, less flashy, but they get the job done without needing a loan.
  • Nvidia’s like, “SLMs are the future,” while secretly wondering why anyone still uses a Tesla when a rusty Prius works fine.

SLMs vs. LLMs

SLMs are trained on up to 40 billion parameters. They’re like the “I’ll just do one task and pretend I care” version of AI. Cheaper? Check. Less confusing? Double check.

“We’re not all geniuses.”

LLMs can train SLMs, but why waste time when you can just copy and paste? Efficiency, baby. 💸

The tiniest SLMs run on regular CPUs. They’re like the “I don’t need a supercomputer to send you a receipt” version of AI.

Companies don’t need AI that knows everything. They need a tool that does one thing without making you cry over electricity bills. Priorities, people.

Even GPT-5 uses SLMs for basic tasks. It’s like your phone using a calculator app instead of a quantum computer to add 2+2. 🤦♂️

Nothing more humiliating than when GPT-5 router decides your request was too low IQ and reroutes you to the small model

– andrew gao (@itsandrewgao) September 2, 2025

What happens if an AI sector takes a setback?

Crypto companies are using LLMs to summarize trades. Because nothing says “financial stability” like letting a robot decide if you’re a good investor. 🤡

Trading firms are combining LLMs with other AI tools. Great! Now we’re all going to be replaced by a team of overpriced robots. Yay!

Big projects like Gemini and GPT require data centers the size of cities. They’re like the “I need a mansion for my cat” of AI. 💀

The U.S. AI sector raised $109 billion in 2024. That’s enough to buy 10,000 Teslas or one functioning healthcare system. Your call.

OpenAI is selling $500 billion in stock. Because why not? We’ve all got spare change for a company that charges millions to say “please.”

If we don’t build enough data centers, the economy might crash. Or maybe it’ll just make everyone realize we’ve been funding a digital version of a goldfish. Either way, we’re doomed.

High interest rates, trade wars, and the growing popularity of SLMs could all kill the LLM hype. Classic. Who knew?

Data centers are a bubble. They use chips that’ll be obsolete in a few years. Because nothing says “future-proof” like buying tech that’ll be useless by 2030. 🤪

How to avoid collapse

Nvidia suggests using SLMs to save resources. Because nothing says “efficient” like telling investors they’ve been wasting money on AI that costs more than a small country.

Specialize SLM agents. Because who needs versatility when you can just hire a team of one-trick ponies?

Modular agent systems are the way to go. Use LLMs only when you have to. Like using a sledgehammer to crack a nut. 💣

Read More

2025-09-14 00:46