The Illusion of "AI Innovation Slowing"
???Happy Birthday to the Second Generation of AI!??? November 30, 2022, marked a pivotal moment in technology history. OpenAI introduced ChatGPT, powered by GPT-3.5, as part of a free research preview. Was it a polished production product? Not at all. It wasn’t even an alpha version of one. But it was?mind-blowingly COOL?and sparked a revolution that’s still reshaping the world today.
Fast forward two years, and now the tech world is buzzing with claims that AI innovation has "slowed down." Article after article sounds the alarm. But are they right? Let’s dig into the reasons they give and see if the hype (or the skepticism) holds up.
The "Evidence" of a Slowdown
Here are the common reasons cited by skeptics, along with why they might be missing the bigger picture:
1. Diminishing Returns from Scaling It’s true: doubling down on bigger models, more data, and insane compute power isn’t delivering the same leaps forward it used to. Industry leaders like OpenAI and Anthropic admit that just making things?bigger?no longer works as well. Does this mean innovation is slowing? No—it means we’re at a pivot point, where creativity and efficiency will outpace brute force. ??
2. Hardware and Data Limitations Hardware constraints are real, as seen with Nvidia’s overheating Blackwell GPUs, and high-quality training data is becoming scarce. But if history teaches us anything, it’s that necessity drives innovation. Think we’ll stop here? Think again. ??
3. Economic and Market Pressures Monetizing AI is no small task, and it’s true that some companies, like Baidu, have stumbled in finding profitability for AI search. But setbacks in?business strategy?are not the same as slowing?technological progress. These challenges are signs of a maturing market, not one grinding to a halt. ??
4. Shifts in Research Focus Yes, companies like Microsoft are doubling down on applying existing AI to practical tools like Copilot. But does that mean innovation is over? Hardly. It means we’re entering the?Beta phase?of AI’s evolution, where maturing tools become reliable, scalable, and useful in the real world. This is the foundation for the?next big leap. ??
Putting It in Context
Let’s remember:?ChatGPT’s debut was just two years ago.
In the world of software, meaningful releases don’t happen overnight. They go through lengthy?Alpha?and?Beta?cycles—typically 18 months each—for a total of three years from functional prototype to polished, production-ready product. Some examples:
Now, think about AI.?OpenAI is just entering Beta.?Anthropic? Still in Alpha. And the others? Many wouldn’t have even launched in a world of traditional standards (remember Google’s early Bard misstep?). Siri, anyone? Definitely not ready for prime time.
The Road Ahead
AI isn’t slowing—it’s maturing. And just like any groundbreaking technology, it needs time to iron out the rough edges. Meanwhile, the major players are racing ahead with?new capabilities, even as they let their current systems catch up in usability and reliability.
Here’s where the famous?S-curve of technology adoption?comes into play. In reality, we’re not dealing with just one S-curve; we’re on the cusp of?multiple overlapping curves.
A New AI Timeline (According to Me - the Alpha version of what "they" are calling a world-famous AI Expert!)
Let’s look at what’s coming:
The illusion of slowing, is a perspective of technology, moving faster than anything in the history of humankind!