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The most Insightful Stories About Deepseek V3 - Medium

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작성자 Anh
댓글 0건 조회 12회 작성일 25-02-01 10:09

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28China-Deepseek-01-whbl-videoSixteenByNine3000.jpg Multiple estimates put DeepSeek within the 20K (on ChinaTalk) to 50K (Dylan Patel) A100 equivalent of GPUs. Training one model for multiple months is extraordinarily dangerous in allocating an organization’s most dear property - the GPUs. A true price of possession of the GPUs - to be clear, we don’t know if DeepSeek owns or rents the GPUs - would comply with an analysis just like the SemiAnalysis total price of possession model (paid feature on top of the newsletter) that incorporates prices along with the actual GPUs. The total compute used for the DeepSeek V3 model for pretraining experiments would likely be 2-4 times the reported quantity within the paper. The cumulative question of how much whole compute is utilized in experimentation for a model like this is way trickier. We’ll get into the specific numbers beneath, however the question is, which of the various technical improvements listed within the DeepSeek V3 report contributed most to its learning efficiency - i.e. mannequin performance relative to compute used. It will permit us to construct the subsequent iteration of DEEPSEEK to swimsuit the particular wants of agricultural companies resembling yours.


kushikurage.jpg Now that we know they exist, many teams will construct what OpenAI did with 1/10th the fee. And there is a few incentive to proceed placing things out in open supply, but it should clearly change into increasingly competitive as the cost of these things goes up. Lots of the techniques free deepseek describes of their paper are issues that our OLMo staff at Ai2 would benefit from getting access to and is taking direct inspiration from. For one instance, consider evaluating how the DeepSeek V3 paper has 139 technical authors. Given the above finest practices on how to supply the mannequin its context, and the immediate engineering techniques that the authors instructed have positive outcomes on consequence. Why this issues - asymmetric warfare involves the ocean: "Overall, the challenges offered at MaCVi 2025 featured sturdy entries throughout the board, pushing the boundaries of what is feasible in maritime imaginative and prescient in a number of totally different facets," the authors write. Drawing on intensive safety and intelligence experience and advanced analytical capabilities, DeepSeek arms decisionmakers with accessible intelligence and insights that empower them to grab opportunities earlier, anticipate dangers, and strategize to meet a variety of challenges. The usage of compute benchmarks, nevertheless, especially in the context of national security dangers, is considerably arbitrary.


Before we start, we would like to mention that there are an enormous amount of proprietary "AI as a Service" companies comparable to chatgpt, claude and so on. We solely want to make use of datasets that we can download and run locally, no black magic. However, to solve advanced proofs, these models must be wonderful-tuned on curated datasets of formal proof languages. The prices to practice fashions will proceed to fall with open weight models, particularly when accompanied by detailed technical reports, but the tempo of diffusion is bottlenecked by the necessity for difficult reverse engineering / reproduction efforts. This publish revisits the technical details of DeepSeek V3, however focuses on how finest to view the associated fee of training models on the frontier of AI and how these costs could also be altering. These costs aren't essentially all borne directly by DeepSeek, i.e. they may very well be working with a cloud supplier, but their value on compute alone (earlier than something like electricity) is at the least $100M’s per 12 months. The CapEx on the GPUs themselves, at the very least for H100s, is probably over $1B (primarily based on a market price of $30K for a single H100). 16,000 graphics processing models (GPUs), if not more, deepseek ai claims to have needed solely about 2,000 GPUs, namely the H800 series chip from Nvidia.


For reference, the Nvidia H800 is a "nerfed" model of the H100 chip. For Chinese corporations which are feeling the strain of substantial chip export controls, it can't be seen as particularly surprising to have the angle be "Wow we are able to do means more than you with less." I’d probably do the same of their shoes, it's much more motivating than "my cluster is bigger than yours." This goes to say that we'd like to understand how necessary the narrative of compute numbers is to their reporting. The fact that the mannequin of this quality is distilled from DeepSeek’s reasoning mannequin series, R1, makes me more optimistic concerning the reasoning mannequin being the actual deal. Some of the noteworthy enhancements in DeepSeek’s coaching stack embrace the next. deepseek ai china carried out many tricks to optimize their stack that has solely been achieved nicely at 3-5 other AI laboratories on the planet. Reproducing this isn't impossible and bodes properly for a future where AI skill is distributed throughout more gamers. The put up-coaching side is less innovative, however gives more credence to those optimizing for online RL coaching as DeepSeek did this (with a type of Constitutional AI, as pioneered by Anthropic)4.

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