DeepSeek

I dont have much to say about your last two points, but 1-3 are pretty off base in a few different ways. Its important to differentiate between Deepseek (the company) and Deepseek V3 (model released on Christmas), and Deepseek R1 (model released Jan 20) While Deepseek is indeed a Chinese company, they released V3 and R1 (and technically R0 but thats not relevant) opensource. Meaning anyone can run, iterate, exmine etc that application. An opensource model like this just categorically cannot do what you are describing. Its maybe better to imagine an Opensource LLM as a really really complex math equation. So complex that unless people tell you specifically what it looks like you could never guess. When they release it, they're simply telling you what the math equation is. It doesn't suddenly do all sorts of new stuff. If you have a big enough computer you can run something like this without internet access. You have to consciously do a lot of work to make changes to a model or continue training it. *Note*: This is different than their chat product, deepseek.chat.com or whatever. That does have the concerns you mention. But this is the same concern with all non-personal services. 2. I also doubt the claim that V3 was trained for 5.5m, I DO believe it was much much cheaper than US firms could do, but likely much more than 5.5m. As for reverse engineering, there isn't really anything to discover. They released some pretty in-depth papers explaining how they made some important efficiencies which contributed to the saved money. But outside of those, its not exactly new information. Also agree that the lasting impact of this is downward price pressure. 3. My earlier point about V3 and R1 is important here. V3 is a standard chat model, that is impressive and nearly SOTA (non-reasoning), but was not quite the bombshell that R1 was. Biggest deal is indeed its Price to Performance, being an Opensourced model (and MoE, but thats beyond the scope of this) it means that the price for this is going to end up basically being the cost of electricity to use. You'll have dozens of providers competing to provide the model as cheaply as possible, in fact you already do. The real bombshell that happened was the release of R1. This is the Deepsek Reasoning model. Similar to O1 from OpenAI. Reasoning models are new classifications of LLMs, you can very generally consider them like regular LLMs but with a lot of work to make them better and problem solving and reasoning. The how of this isn't super important here. Previously OpenAI, and kind of Google, had the only impressive reasoning models. And it was assumed that it was very computationally expensive to create them. Deepseek R1 proved, that atleast for current state of the art performance, its not terribly expensive and certainly not terribly complex to make these style of models. Previously the only reasoning model was O1, which is very expensive. R1 being opensource will again drive pressure down on these types of models. More on reddit.com

My wallet says yes More on reddit.com

Who guarantees me that the text isn't generated by deep seek to simulate someone who knows the subject? What if it's deep seek itself posing as a reddit user? More on reddit.com

Don't run it through the DeepSeek app. Run it through a U.S. provider like Perplexity or Kagi. I use Kagi and they provide access to ChatGPT 4o, Claude, Mistral, Gemini Pro, LLama, Qwen, Nova, and DeepSeek. More on reddit.com