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Let's set aside the geopolitics involved with China for a minute, just enough for us to appreciate what just happened.
This has been a long time coming. As engineers, we should know better than to throw as much money, energy, and resources there is on a problem, which has been the case in this AI hype cycle. As many have already pointed out, including myself (more on this later), the current AI status quo of going bigger and badder at every iteration is unsustainable and destructive. I hope this pushes everything into the opposite direction, where everyone starts placing larger focus on optimization and efficiency, which is at the very core of scalable computer science.
On the flip side, since this is open source, everyone benefits from the discoveries, even a certain "Open Artificial Intelligence" company that closed the source of their models. 🙄 As a matter of fact, Microsoft has already integrated DeepSeek in their products! Let's expect--nay--let's demand for more efficient AI models from here on out!
If anyone is like me who doesn't have the time to really dive deep into each and every AI advancement, here's a good quick primer on what DeepSeek does differently vs. major Western LLMs.
Pretty sure they're not the first to do it, but the technique of having a larger LLM teaching a smaller LLM to be better than itself is the very definition of what mentorship is. 😂
Still on the AI sustainably topic, my TEDx talk finally got uploaded on YouTube, on the TEDx official channel no less! I discussed how colonialism has creeped into society once again, this time disguised as the technological advancement we've come to know as Artificial Intelligence and Big Data. Emerging economies like us are the most vulnerable to the exploitative practices of this new form of colonialism.
I still can't get myself to watch my TEDx video. I cringe at the thought of it, especially knowing what happened leading up to my time at the stage. But I'll do muster up the courage one of these days, probably via a reaction video. 😂
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