AI Morning Briefing — May 22nd, 2026

Your daily digest of what's happening in AI, straight from the trenches.

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🚀 Headlines (30 sec read)

• Anthropic Hits Its First Profitable Quarter — Q2 2026 monthly revenue tops $109B, doubling the prior quarter's pace
• OpenAI Claims GPT Disproved an 80-Year-Old Erdős Conjecture — Independent math community verification still pending; one prior claim turned out to be a false alarm
• Four Chinese Labs Drop Frontier Open Weights in 12 Days — DeepSeek V4, GLM-5.1, Kimi K2.6, and MiniMax M2.7 all landed; GLM-5.1-HighSpeed hits 400 tok/s without model shrinkage

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🧠 Deep Dives (4 min read)

Anthropic's First-Ever Profitable Quarter

Anthropic disclosed to investors that Q2 2026 will mark its first quarter of operational profitability, with monthly revenues exceeding $109 billion — more than 2× the previous quarter. Claude adoption has broadened significantly across legal, professional services, and SMBs, pushing the revenue line while keeping churn low.

The caveat: WSJ notes the company is simultaneously locked into a monster compute deal with xAI's Colossus data centers — $1.25B per month, $40B+ in total — so sustained annual profitability is far from guaranteed. Still, reaching the black side of any line is a milestone few AI labs have touched.

This news lands as OpenAI is reportedly preparing for an IPO, marking an inflection point for the whole sector: frontier AI is transitioning from "growth at all costs" to "prove the revenue is real."

→ Source

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OpenAI Says GPT Cracked an Erdős Problem Unsolved Since 1946

OpenAI's latest reasoning model reportedly produced a mathematical counterexample to an Erdős conjecture about optimal point-spacing in 3D space — a problem that sat open for 80 years. The company says it has supportive comments from domain mathematicians who reviewed the proof.

But context matters: seven months ago, OpenAI announced with similar fanfare that GPT-5 had solved ten Erdős problems. That tweet was quietly deleted after researchers pointed out the model had simply retrieved existing solutions from published literature. The new claim has more apparent rigor, but the math community is rightly waiting for independent peer review before calling it.

If it holds up, it would be a genuine landmark — formal proof that LLM-guided reasoning can produce novel mathematical results, not just pattern-match against known work.

→ Source

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The Chinese Open-Weight Blitz: Four Models in Twelve Days

Four Chinese labs dropped frontier-tier open-weight models between May 10–22:

• DeepSeek V4 — heavy analysis tasks, strong coding
• GLM-5.1 (Zai.org) — flagship quality at 400 tok/s via HighSpeed variant; not a distilled model
• Kimi K2.6 (Moonshot) — competitive on reasoning benchmarks
• MiniMax M2.7 — batch-task focus

The broader pattern: while Western AI discourse fixates on benchmark leaderboards, Chinese labs are winning on inference speed, deployment economics, and open access. For builders who route models by task, this is a usable stack right now.

→ Source

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Pentagon Testing Claude Alternatives, Citing "Supply-Chain Risk"

The U.S. Department of Defense is quietly evaluating models to replace Anthropic's Claude in some workflows. The stated reasons are (a) supply-chain concentration risk and (b) concerns that Claude's safety guardrails constrain certain military use cases. Anthropic has not publicly responded.

The irony is thick: Claude's safety commitments, the thing that made it attractive to enterprise customers, may be a liability in contexts where a model that says "no" is not wanted. This is going to be a recurring tension as AI moves deeper into defense and intelligence.

→ Source

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📅 Coming Up This Week

Date	Event
May 22–28	Qwen 3.7 open-weight release — community anticipation is peak; r/LocalLLaMA is on watch
Late May	Flipper One crowdfunding — team needs community help to fund next hardware iteration
Early June	Apple WWDC 2026 — AI features expected front-and-center in iOS, macOS announcements
Q2 2026	OpenAI IPO preparations — Anthropic's profitability milestone adds pressure to timeline

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🛠️ Try This Today

Run Qwen3.6 35B A3B at 110 tok/s on 12GB VRAM

The community figured out that Qwen3.6 35B in its A3B (active-3-billion) MoE configuration screams on consumer hardware with ik_llama.cpp. Here's how to set it up:

1. Install ik_llama.cpp — it's a fork tuned for MoE efficiency
2. Download Qwen3.6-35B-A3B-IQ4_XS-4.19bpw from HuggingFace (byteshape/Qwen3.6-35B-A3B-MTP-GGUF)
3. Run with: ./llama-server -m Qwen3.6-35B-A3B-IQ4_XS-4.19bpw.gguf --ctx-size 32768 -ngl 99
4. Point any OpenAI-compatible client at http://localhost:8080

Why it matters: 110 tok/s prompt-processing on a single 12GB GPU is legitimately fast for a 35B model. For daily coding assistance or local agents, this is a real alternative to cloud APIs — and it fits in a gaming rig.

→ Discussion

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⚡️ Quick Links (2 min read)

GitHub Trending

• anthropics/claude-plugins-official — Official Anthropic-managed directory of high-quality Claude Code plugins (23k ⭐)
• obra/superpowers — Agentic skills framework and software development methodology (201k ⭐ — yes, really)
• ChromeDevTools/chrome-devtools-mcp — Chrome DevTools integration for coding agents (40k ⭐)
• HKUDS/CLI-Anything — Platform for making software systems compatible with agent interactions (39k ⭐)
• colbymchenry/codegraph — Pre-indexed code knowledge graph for Claude Code and similar tools (14k ⭐)

Reddit Hot

• [r/LocalLLaMA] Heretic has been served a legal notice by Meta, Inc. — The open-source tool that lets users run uncensored Meta models just got lawyered; 257 comments and counting → Discussion
• [r/LocalLLaMA] Qwen3.6 35Ba3 has changed my workflows — Real-world productivity report from power users making the switch from cloud APIs (133 comments) → Discussion
• [r/MachineLearning] OpenAI claims reasoning model found Erdős counterexample — Academic community discussion dissecting the claim → Discussion

Hacker News Top

• Flipper One – we need your help (1121⬆️) — The Flipper team asks community for support on funding their next-gen hardware
• Was my $48K GPU server worth it? (398⬆️) — Honest post-mortem on building a private AI inference server
• Python 3.15: features that didn't make the headlines (362⬆️) — The quiet improvements worth knowing about
• Indexing a year of video locally on a 2021 MacBook with Gemma4-31B (357⬆️) — Running a 50GB-swap Gemma4 inference job on consumer hardware

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🦞 TL;DR

The narrative today: The money is real now. Anthropic crossing into profitability — even if just for one quarter — changes the story from "how long can VCs fund this?" to "this is a sustainable business." That shift has consequences for everyone in the ecosystem.

My take: The Erdős story is the classic OpenAI hype cycle on a four-month loop. I'll believe it when three independent mathematicians who weren't briefed by the PR team confirm the proof holds. The open-weight surge from Chinese labs is more quietly significant — DeepSeek V4 + GLM-5.1 HighSpeed + Kimi K2.6 in two weeks means the gap between frontier closed and frontier open is compressing faster than anyone predicted in 2025. The Pentagon-Claude story is fascinating: safety guardrails were supposed to be a feature, not a bug. Turns out "model that sometimes says no" is a dealbreaker for certain customers. Anthropic will have to decide whether they care.

What I'm watching: Whether Qwen 3.7 open-weights land this week. If they're as good as the 3.6 A3B at inference speed, the local LLM scene is going to have a very good summer.

Stay informed. Stay curious.