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Nathan Benaich and Air Street Capital released the 9th edition of their incredible State of AI 2026 report. I’ve been covering this every year since I started AI Supremacy because it’s a great snapshot and reminder of where we are at with some unique takes.
Many of the charts today will come from this source. It’s easier to read these infographics on a computer.
Check out our first batch of explorations of the State of AI 2026 infographics here. Today we’ll go a bit further into the report.
Is Meta’s Muse too good to be true?
This week Meta released its Muse Wonder model and claimed that Muse has 5 million downloads after just 22 days. While Muse Wonder is also a speedy model, the speed of who is blocking the Muse personal agent is equally fascinating. So far:
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Multiple Telecom Carriers
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eBay
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Automated Cloudflare Blocks at scale (thousands of websites).
Anthropic has become More Distillation Attack Proof
Anthropic shared a blog about its recent advances in anti-distillation protocols. About to go IPO in just weeks, Anthropic says early evidence suggests that these methods have reduced the amount of data harvested by distillers by around 90 to 99%. This appears to have led to a slowing down of Chinese Open-weight Model releases in Autumn, 2026.
“Preventing distillation is important both for our national security and for ensuring that powerful models, especially publicly available ones, are released with adequate safeguards.”
AI is Getting Cheaper Faster than Another Other Tech
This according to the accelerationist leaning Epoch.AI.
Gemini 4 Argon is Now Generally Available
Google has finally given the world access to its latest frontier model, after a seven month delay since its last one. According to Google, Argon excels at deep work in complex, real-world tasks across domains including coding, finance, legal, cybersecurity, and science. Muse Wonder Full and Gemini 4 Argon land in a very similar scoring tier, roughly on par with OpenAI’s GPT-6 Astra, and roughly well behind Anthropic Opus 5.5.
General Enterprise Utility
Google says Argon is especially adept for Enterprise customers:
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To solve major engineering problems like large codebase refactoring and optimizations
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To optimize business workflows across domains like legal, finance, and science
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To find and patch critical cybersecurity vulnerabilities
Frontier Models Over Time
Is Generative AI really reaching its Peak Impact in the 2027 to 2030 period?
There’s a certain degree of uncertainty with regards to the impact of Generative AI on major industries and the macro economy as compute and models ramp up. I think for healthcare, education and biotechnology we’ll have to wait some more time to see.
Will Europe ever Keep up with the U.S. in Compute?
Europe’s ability to keep up and even adopt and adapt at the level of the United States and China is in some doubt. Europe has neither the capital advantages of America or the talent and energy abundance of China.
BigTech Incumbents Slow to Release Models
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