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GENERATIVE AI
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AI Co-Creation Studios Turn Consumers Into Product Builders
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AI-Powered Co-Creation Studios
— Yohei (@yoheinakajima) 29 avril 2026
Consumers become co-builders of products, not just buyers. AI translates intent into production, collapsing the gap between idea and execution.
This drives hyper-personalization, but more importantly, emotional ownership. People value what they… pic.twitter.com/ARnwZBraJjAI-Powered Co-Creation Studios Consumers become co-builders of products, not just buyers. AI translates intent into production, collapsing the gap between idea and execution. This drives hyper-personalization, but more importantly, emotional ownership. People value what they
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AI-Generated IP Becomes Mass-Scale Licensable Asset Class
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AI-Generated IP & Virtual Asset Licensors
— Yohei (@yoheinakajima) 29 avril 2026
Mass-scale generation of characters, designs, music, and worlds becomes a licensable asset class. Instead of a few blockbuster IPs, there are millions of niche, dynamically evolving ones.
The key shift is from scarcity-driven IP to… pic.twitter.com/GMILei45ykAI-Generated IP & Virtual Asset Licensors Mass-scale generation of characters, designs, music, and worlds becomes a licensable asset class. Instead of a few blockbuster IPs, there are millions of niche, dynamically evolving ones. The key shift is from scarcity-driven IP to
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DeepSeek v4 Demonstrates SOTA Long Context Efficiency Without Benchmarking
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IMO DeepSeek v4 demonstrated utter confidence and competence by not benchmaxxing, not focusing on some BS final run cost, not even spending inference-optimal compute. just showed up, demonstrated SOTA long context efficiency techniques (CSA, HCA, mHC, flash at 8% cost of pro,
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Professional comparison of Claude and GPT-5.5 capabilities
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The definitive ranking doesn't exist. Here's what does: → Complex reasoning, code review, multi-file refactoring: Claude Opus 4.7
→ Agentic execution, terminal workflows, tool orchestration: GPT-5.5
→ Interactive speed: Claude
→ Cost at scale: GPT-5.5 The professionals -
Claude wins 7 tests but GPT-5.5 leads in OpenAI’s table
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Tom's Guide ran 7 head-to-head tests. Claude won all 7. OpenAI's own benchmark table shows GPT-5.5 leading on 14 categories. But that table includes tests where only OpenAI published a Claude score. Anthropic's own numbers tell a different story on several of those. The
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Token efficiency: GPT-5.5 vs Claude Opus 4.7 cost and speed
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Token efficiency is where things get interesting. GPT-5.5 uses 72% fewer output tokens than Opus 4.7 on the same coding tasks. Fewer tokens means lower cost per task, even though GPT-5.5 costs $30/M output vs Claude's $25/M. But Claude's time-to-first-token is roughly 0.5s vs
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Claude Opus 4.7 dominates reasoning and code benchmarks
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Deep reasoning and code precision: Claude Opus 4.7 → SWE-Bench Pro: 64.3% → GPT-5.5: 58.6% → MCP Atlas: 79.1% → GPT-5.5: 75.3% → GPQA Diamond, HLE (with and without tools), FinanceAgent v1.1: all Opus 4.7 When the task requires architectural thinking
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Claude Opus 4.7 leads GPT-5.5 on 6 of 10 benchmarks by category
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On the 10 benchmarks where both OpenAI and Anthropic report scores, here's the split: Claude Opus 4.7 leads on 6. GPT-5.5 leads on 4. But the leads aren't random. They cluster by category. And that changes what "winning" means entirely.
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GPT-5.5 vs Claude Opus 4.7: The real benchmark story
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GPT-5.5 shipped 7 days after Claude Opus 4.7. Everyone picked a winner based on headlines. I looked at every benchmark both labs published. The real story isn't what most people are reporting: