The amount of factually incorrect information and hyperventilating...
Dean W. Ball@deanwball
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Jan 27, 2025
~3 min read
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The amount of factually incorrect information and hyperventilating takes on deepseek on this website is truly astounding. I assumed that an object-level analysis was unnecessary but apparently I was wrong. Here you go:
1. DeepSeek is an extremely talented team and has been producing some of the most interesting public papers in ML for a year. I first wrote about them in May 2024, though was tracking them earlier. They did not “come out of nowhere,” at all.
2. v3 and r1 are impressive models. v3 did not, however, “cost $5m.” That reported figure is almost surely their *marginal* cost. It does not include the fixed cost of building a cluster (and deepseek builds their own, from what I understand), nor does it include the cost of having a staff.
3. Part of the reason DeepSeek looks so impressive (apart from just being impressive!) is that they are among the only truly cracked teams releasing detailed frontier AI research. This is a soft power loss on America’s part, and is directly downstream of the culture of secrecy that we foster in a thousand implicit and explicit ways, including by ceaselessly analogizing AI to nuclear weapons. Maybe you believe that’s a good culture to have! Perhaps secrecy is in fact the correct long term strategy. But it is the obvious and inevitable tradeoff of such a culture; I and many others have been arguing this for a long time.
4. Deepseek’s r1 is not an indicator that export controls are failing (again, I say this as a skeptic of the export controls!), nor is it an indicator that “compute doesn’t matter,” nor does it mean “America’s lead is over.”
5. Lots of people’s hyperbolic commentary on this topic, in all different directions, is driven by their broader policy agenda rather than a desire to illuminate reality. Caveat emptor.
6. With that said, DeepSeek does mean that open source AI is going to be an important part of AI dynamics and competition for at least the foreseeable future, and probably forever.
7. r1 especially should not be a surprise (if anything, v3 is in fact the bigger surprise, though it too is not so big of a surprise). The reasoning approach is an algorithm—lines of code! There is no moat in such things. Obviously it was going to be replicated quickly. I personally made bets that a Chinese replication would occur within 3 months of o1’s release.
8. Competition is going to be fierce, and complacency is our enemy. So is getting regulation wrong. We need to reverse course rapidly from the torrent of state-based regulation that is coming that will be *awful* for AI. A simple federal law can preempt all of the most damaging stuff, and this is a national security and economic competitiveness priority. The second best option is to find a state law that can serve as a light touch national standard and see to it that it becomes a nationwide standard. Both are exceptionally difficult paths to walk. Unfortunately it’s where we are.
1. DeepSeek is an extremely talented team and has been producing some of the most interesting public papers in ML for a year. I first wrote about them in May 2024, though was tracking them earlier. They did not “come out of nowhere,” at all.
2. v3 and r1 are impressive models. v3 did not, however, “cost $5m.” That reported figure is almost surely their *marginal* cost. It does not include the fixed cost of building a cluster (and deepseek builds their own, from what I understand), nor does it include the cost of having a staff.
3. Part of the reason DeepSeek looks so impressive (apart from just being impressive!) is that they are among the only truly cracked teams releasing detailed frontier AI research. This is a soft power loss on America’s part, and is directly downstream of the culture of secrecy that we foster in a thousand implicit and explicit ways, including by ceaselessly analogizing AI to nuclear weapons. Maybe you believe that’s a good culture to have! Perhaps secrecy is in fact the correct long term strategy. But it is the obvious and inevitable tradeoff of such a culture; I and many others have been arguing this for a long time.
4. Deepseek’s r1 is not an indicator that export controls are failing (again, I say this as a skeptic of the export controls!), nor is it an indicator that “compute doesn’t matter,” nor does it mean “America’s lead is over.”
5. Lots of people’s hyperbolic commentary on this topic, in all different directions, is driven by their broader policy agenda rather than a desire to illuminate reality. Caveat emptor.
6. With that said, DeepSeek does mean that open source AI is going to be an important part of AI dynamics and competition for at least the foreseeable future, and probably forever.
7. r1 especially should not be a surprise (if anything, v3 is in fact the bigger surprise, though it too is not so big of a surprise). The reasoning approach is an algorithm—lines of code! There is no moat in such things. Obviously it was going to be replicated quickly. I personally made bets that a Chinese replication would occur within 3 months of o1’s release.
8. Competition is going to be fierce, and complacency is our enemy. So is getting regulation wrong. We need to reverse course rapidly from the torrent of state-based regulation that is coming that will be *awful* for AI. A simple federal law can preempt all of the most damaging stuff, and this is a national security and economic competitiveness priority. The second best option is to find a state law that can serve as a light touch national standard and see to it that it becomes a nationwide standard. Both are exceptionally difficult paths to walk. Unfortunately it’s where we are.
