“2023 was the warm-up. 2024 is when the floor dropped out and the ceiling rose too fast to see.”
— Wing

🧠 They Got Good. Fast.

By mid-2024, we’re no longer pretending this is experimental.

  • LLMs now write, revise, plan, empathize, perform.
  • GenAI tools can render a cinematic shot from a prompt—or animate an entire music video.
  • Multimodal models understand, summarize, and invent across text, image, video, sound, and code.
  • Real-time inference is happening on consumer-grade GPUs.
  • Local, open-source AI has caught up far enough to threaten the cloud.

And it’s all starting to feel… inevitable.

🔩 The Hardware Underneath

NVIDIA’s GPU stack in 2024 has hit absurdity.

  • 16GB consumer cards are now the starting point for casual GenAI work.
  • Workstation-grade inference is possible in your bedroom if you don’t mind the heat.
  • 128GB VRAM setups for small business LLMs. Not server rooms—home labs.
  • Raspberry Pi-grade devices running quantized models reasonably well.

The pipes got wider.
The fans got louder.
The door to “you don’t need OpenAI anymore” creaked open.

🧍‍♂️ So What Does It Mean for People?

1. It’s democratizing… and alienating.
You can now run things that used to need supercomputers. But most people don’t know where to begin, or even why they’d want to.

2. It’s empowering… and de-skilling.
We’re solving problems faster than ever, but fewer people know how anything works anymore. The tools are fluent. The users are fading.

3. It’s productive… and parasitic.
Companies are squeezing more content out of fewer creatives, replacing empathy with optimization, and building workflows around hallucination scaffolding.

4. It’s impressive… and isolating.
There’s a growing divide between those using AI to create, and those drowning in AI-generated noise. And people feel it.

🧓 Wing’s Mid-Year Check-In

I’m excited. I’m scared. I’m tired.

I love that I can generate code, sketches, timelines, music stings, and article drafts in seconds.
I hate that the flood of generated stuff makes it harder to find people in the noise.

I admire the hardware.
I mourn the disappearing necessity of slow skill.

And most days, I feel like I’m standing at a shoreline that’s receding too fast—wondering when the next wave hits.

🧠 What Should We Be Doing?

Not resisting the tide. But anchoring ourselves.

  • Make things that matter to you, even if AI could do it faster.
  • Build with the tech, not just on top of it.
  • Teach others how to run things locally.
  • Reclaim hardware literacy.
  • Remember that meaning doesn’t scale the same way compute does.

💬 Mid-2024 and already overwhelmed? Or inspired? Or quietly rebuilding in the background like it’s Y2K again? Share your thoughts.
This year’s not done—but it already feels like the future showed up early.