AI-Yi-AI: We Know Where This Is Heading or Gimme Some Moore
August 28, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
Every once in a while I read an output from Semi Analysis (please, don’t confuse this consulting firm with Artificial Analysis). I have learned that my blood pressure ticks up, and I need a break to water the flowers. “Are Open Models Catching Up?” The assumptions underlying the write up, in my opinion as an official dinobaby, are:
Assumption 1: The US is the world’s leader in proprietary closed (proprietary) frontier models
Assumption 2: Open models deliver results on benchmark tests that show the frontier faces an encroaching suburbia of smart software
Assumption 3: Assume that the US will be the big winner in opening up the Wild West frontier of artificial intelligence
Assumption 4: Writing blue-chip thinking and giving it away for free will generate sales leads
Assumption 5: Open models have to catch up. (Spoiler: No, open models only have to be good enough, available, and cheap.)
You and Semi Analysis won’t agree, but just for fun, suspend your doubt, and let’s think about what is happening in the “if we build it, they will come” world of smart software.
The write up says:
The past two months have been a breakout period for open source AI. Yes, there was the “Deepseek moment” back in January 2025, but no one actually used R1 to do any economically valuable work. In contrast, models like GLM 5.3 and Kimi K3 are genuinely capable of many of the same coding and agentic tasks that rocketed Anthropic to $65B+ ARR. Unlike others who inflated ARR, our figures were much closer to reality.
Let’s accept the statement about “no one actually used R1 to do any economically valuable work” and “our figures were much closer to reality.”
The “killer chart” is this one:
Sure, it is black and hard to read. The idea the chart is supposed to make is that Semi Analysis has discovered a chart that someday soon will look like this one from Wikipedia:
By golly, Semi Analysis and “their figures were much closer to reality” appears to suggest that open AI models are improving in the same way chips were. The swizzle in this some Moore law is that the open models are improving from “below.” The idea is that open models are catching up with the frontier pioneers’ trailblazing innovations.
But wait! The future of smart software is agentic. That means that new players will enter the fray and use the existing models as an installed base of capabilities. Agents will become the next big thing. Is this a new insight? My answer: Nope. Agents are the next big thing. If the Semi Analysis-type thinkers take a look at what outfits like Alibaba have been doing for months, the progress is rapid. Depending upon what a user wants to do, one can look at Alibaba, its deal with Google, and the distributed innovation method in use. The conclusion could be phrased this way: “Let the open models catch up. We will use wrapper software and agents to create a different type of system and user interaction method.”
Why is this important? In my upcoming Ciffer lecture about the future of online crime, I point out:
- Open tools and systems are good enough
- Improvement in these tools and systems allow bureaucracy-free actors to select, test, discard, learn, and use what works
- Cyber security professionals have to figure out what has happened, pinpoint the agent, and the figure out how to prevent the action from taking place again.
Bad actors have been tapping LLM capabilities since the systems became available. This means that the assertion the early open models were not economically viable. Sorry, Semi Analysis, your semi analysis is dead wrong. You are looking at the corporate sector which is still trying to figure out a use case that delivers a payoff. The open models work just fine for the ransomware folks, the data suckers, and the systemic disruption people.
What’s the future look like? Unlike Semi Analysis I don’t have a big orange button so you can buy the answer to the question. I will go through what’s coming from within the US and from non-US players at the Ciffer event. Let me hint at what’s happening: Frontier models are struggling to improve. Open models are good enough. Economic evidence that open models work is available. But that’s not the story. The nascent attempt to create a Moore’s Law for AI has to look beyond what BAIT outfits are doing (BAIT is my lingo for big AI tech and “ai tech” rhymes with “train wreck”).
Stephen E Arnold, August 28, 2026
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