Nvidia Just Paid $20 Billion for a Company That Missed Its Revenue Target by 75%

Nvidia Just Paid $20 Billion for a Company That Missed Its Revenue Target by 75% Panic buying, plain and simple. If anything indicates that this AI bubble is about to pop, it’s this. First, Let’s Clear Up the Groq Confusion If you’ve heard “Grok” thrown around lately, you’re probably thinking of Elon’s chatbot from xAI. We’re not talking about that one. That model isn’t particularly good, but its whole value prop is being politically incorrect so you can get it to say edgy things. My default Zellij layout so I can parallelize Claude Code tasks. The company Nvidia bought is Groq (with a Q). Totally different beast. What Groq Actually Does If you’ve used any high quality LLM, you’ve noticed it takes a while to generate a response. Especially for something rapid fire like a conversation, you want high quality AND speed. But speed is often what gets sacrificed. There’s always that “thinking... gathering my notes... taking some time to form the best response” delay. Groq specialized in hardware and software that makes this way faster. They created a new type of chip called an LPU (Language Processing Unit). It’s based on an ASIC, an application specific integrated circuit. If that’s confusing, don’t worry about it. It’s just a processor that does a specific type of task really well. So imagine you’re talking to Gemini and it takes a couple seconds to respond. Now imagine it responded instantly, like 10 or 100 times faster. That’s the problem Groq was solving. I Explain LPUs vs GPUs So That Anyone Can Understand Them In One Minute To go one level deeper on LPUs versus GPUs (the processors most LLMs run on, typically Nvidia cards): those GPU calculations have to access a lot of things in memory. Nvidia’s chips depend on HBM, high bandwidth memory. But LPUs use something called SRAM that’s much faster to reference. Think about it like this. Your wife has a grocery list for you. You go to the store but forget the list. Every time you’re in an aisle, you have to call her on the phone: “Hey, do I need anything from the bread aisle?” Get the bread. Put the phone down. Go to the next aisle. “Hey, do I need anything from canned goods?” And so on through produce, meat, pick up the beer, check out, get home. Very inefficient. Groq’s approach is like you just took the list to the store. Get to a new aisle, look at the list. Next aisle, look at the list. Much faster than a phone call. That’s the key difference. Nvidia GPUs are phoning out every time they hit a new aisle. Groq’s LPUs mean the shopper has the list in their pocket. Groq’s Business Model Groq’s main offering is GroqCloud. An engineer like me isn’t going to go out and buy an LPU (I don’t even know if they’re commercially available). What I’m going to do is, if I need lightning fast response in an application I’m building,...

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