By: Thomas Stahura
If it wasn’t clear already, open source won the AI race.
To recap: Deepseek R1 is an open-source reasoning model that was quietly launched during the 14 hours TikTok was banned. The reasoning version of Deepseek V3, Deepseek R1 performs at o1 levels on most benchmarks. Very impressive and was reportedly trained for just $6 million, though many are skeptical on those numbers.
By Monday, a week after R1 launched, the model caused a massive market selloff. Nvidia lost $500 billion in value (-17%), the biggest one-day selloff in US history, as the market adjusts to our new open-source reality.
So, what does this mean?
For starters, models have been commoditized. Well-performing open-source models at every scale are available. But that’s besides the point. Deepseek is trained on synthetic data generated by ChatGPT. Essentially extracting the weights of a closed model and open sourcing them. This eliminates the moats of OpenAI, Anthropic, and the other closed source AI labs.
What perplexes me is why Nvidia got hit the hardest. The takes I’ve heard seem to suggest it’s the lower costs it took to train Deepseek that spooked the market. The thinking goes: LLMs become cheaper to train, so hyperscalers need fewer GPUs.
The bulls, on the other hand, cite Jevons’ paradox. Wherein, the cheaper a valuable commodity becomes, the more it gets used.
I seem to be somewhere in the middle. Lower costs are great for developers! But I have yet to see a useful token-heavy application. Well maybe web agents… I’ll cover those in another edition!
I suspect the simple fact the model came out of China is what caused it to blow up. After all, there seems to be such moral panic over the implications on US AI sovereignty. And for good reasons.
Over the weekend, I attended a hackathon hosted by Menlo where I built a browser agent. I had different LLMs take the pew research center political topology quiz.
Anthropic’s claude-sonnet-3.5, gpt-4o, o1, and llama got outsider left. Deepseek R1 and V3 got establishment liberals. Notably, R1 answered, “It would be acceptable if another country became as militarily powerful as the U.S.”
During my testing, I found that Deepseek’s models would refuse to answer questions about Taiwan or Tiananmen square. In all fairness, most American models won’t answer questions about Palestine. Still, as these models are open and widely used and used by developers, there is fear that these biases will leak into AI products and services.
I’d like to think that this problem is solvable with fine-tuning. I suppose developers are playing with Deepseek’s weights as we speak! We’ll just have to find out in the next few weeks…