@NullableX: If this model's real-world experience turns out to be as good as the current benchmark data, it's actually a positive for the AI profitability side, not a negative. It's quite different from the "DeepSeek shock" on 2025/1/20 that broke the monopoly — the environment has changed, and the version is different. The three major cloud providers essentially connect downstream to large, medium, and small companies building AI apps and AI services at the application layer...

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Summary

A commenter analyzes the release of DeepSeek-V4.1-Flash-1017 as a positive for the AI industry's profitability: improved token cost-efficiency will drive up AI penetration and demand for cloud providers' infrastructure. Unlike the earlier DeepSeek shock, market conditions have since changed.

If this model's real-world experience turns out to be as good as the current benchmark data, it's actually a positive for the AI profitability side, not a negative. It's quite different from the "DeepSeek shock" on 2025/1/20 that broke the monopoly — the environment has changed, and the version is different. The three major cloud providers essentially connect downstream to large, medium, and small companies building AI apps and AI services. How well their infrastructure sells directly reflects real token demand, which is to say, AI penetration. For AI penetration to go up, token cost-efficiency has to keep improving. Take an extreme hypothetical: if OPUS 5.5 tokens were free, how many enterprises and individuals who never wanted to use AI would start giving it a try? Take a simple everyday office example: type in a few prompts and a presentation deck is generated. Not satisfied? Type in feedback and the next version is updated right away. Don't like the style? Screenshot a colleague's presentation, send it to the model, and ask it to restyle the deck to match. A few minutes later you have a new version. After a few rounds, you have a ready-to-use deck of dozens of slides — the whole process might take less than two hours. And the biggest blocker preventing this very smooth workflow from going mainstream isn't how hard it is to implement, but the massive token bill. And the faster that "bill" comes down, the faster profitability will grow for the entire AI industry.
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If the real-world experience of this model matches its current test results, it’s actually bullish rather than bearish for overall AI profitability. It’s not quite the same as the “DeepSeek shock” of 2025/1/20 that broke the monopoly — the environment has changed, and so has the landscape.

The major cloud providers behind the big three cloud platforms mostly serve downstream customers that are building AI apps and AI services — from large enterprises down to small startups. How well cloud providers sell their infrastructure is a direct reflection of real token demand, which in turn is a proxy for AI penetration. For AI penetration to grow, the cost-performance ratio of tokens has to keep improving. Take an extreme hypothetical: if Opus 5.5 tokens were free, how many businesses and individuals who previously had no interest in AI would start giving it a try?

Here’s a simple everyday office example: you type in a few prompts and a presentation deck gets generated right away. Not satisfied? You type in some feedback and the next version is ready almost immediately. Don’t like the style? Just screenshot a colleague’s deck, send it to the model, and ask it to restyle yours to match. A few minutes later you have a new version. After a few rounds, you’ve got a ready-to-use deck with dozens of pages — the whole process might take under two hours. The biggest blocker preventing this smooth workflow from going mainstream isn’t how hard it is to implement, but rather the enormous token bill. And the faster that “bill” comes down, the faster the entire AI industry’s profitability will grow.

DeepSeek (@deepseek_ai): 🚀 DeepSeek-V4.1-Flash-1017 is here!

Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.

🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy,

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@mikotossd0106: It feels like DeepSeek's performance is always near top-tier, always just a bit behind the top three, but not by much, forcing the top three to invest heavily in compute to widen the gap, only to have DeepSeek catch up again shortly after with a bunch of scrap parts.

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The comment points out that DeepSeek's model performance is always close to the top AI companies (the top three), forcing them to invest heavily in compute to stay ahead, but DeepSeek then manages to catch up again with low-cost solutions.

@oran_ge: https://x.com/oran_ge/status/2116337749171360048

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A Chinese-language in-depth opinion piece exploring whether AI has truly created incremental value. Drawing on the recent sharp selloff in US equities (Intel down 28.6%, Google down 12.6%, Reddit down 29%) alongside rising hardware prices, collapsing token prices, and disappearing traffic, the author argues that AI is destroying value by making intelligence no longer scarce, and believes we are on the eve of an AI bubble bursting, with companies like ByteDance and Microsoft reinvesting nearly all of their profits into AI infrastructure.