When AI Slop Outpaces Quality
Plus, 👨💻 Meta teaches AI to code via self-play, How to Recreate Realistic Actions and Lip-Sync with DomoAI, and more!
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📺 AI slop is scaling faster than quality video
Kapwing released a report on the global rise of AI slop, defined as low-quality auto-generated content made to farm views and distinct from thoughtful AI-assisted videos. The study analyzed trending channels and new user feeds to measure scale and exposure.
The Decode:
1. Where slop viewership concentrates - South Korea led AI slop viewership with 8.45B views, followed by Pakistan at 5.34B and the U.S. at 3.39B, while Spain topped subscriber counts, showing regional differences in how slop scales.
2. Algorithm exposure starts early - On a brand new YouTube account, 21% of the first 500 recommended Shorts were classified as AI slop, indicating that low-quality AI content reaches new users almost immediately.
3. Slop pays at the top - India’s Bandar Apna Dost ( an anthropomorphic monkey) crossed 2B views with estimated annual earnings of $4.25M, proving that even repetitive low effort AI content can generate significant revenue.
YouTube prioritizes watch time and engagement over production quality, allowing AI slop to compete directly with handcrafted videos as long as it sustains viewer attention. AI slop is not fringe content; it is economically rewarded at scale.
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🎭 How to Recreate Realistic Actions and Lip-Sync with DomoAI
DomoAI lets you transfer real human motion onto any character using just one image and one video. No animation skills, no editing timeline.
How it works
- Open DomoAI: Go to AI Video → Image to Video → Character to Video.
- Upload your inputs: Add one reference video for the motion and one character image for the look.
- Generate instantly: DomoAI transfers body movement, facial expressions, and lip-sync with impressive realism.
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🧠 Meta teaches AI to code via self-play
Meta’s FAIR published research on Self-play SWE-RL, a new reinforcement learning framework for software agents. The system removes reliance on human-written issues or tests. Instead, models improve by breaking and fixing code themselves.
The Decode:
1. One model, two roles - A single LLM alternates between acting as a bug injector and a bug solver in sandboxed repositories, learning both how to create challenging failures and how to repair them.
2. No human-curated data - The framework only requires access to code repositories and dependencies, eliminating the need for human issue descriptions or test suites that typically limit scaling.
3. Emergent difficulty curriculum - Failed fixes are recycled into harder bugs, creating higher-order challenges that automatically scale with the model’s skill level over time.
4. Strong benchmark gains - On SWE-bench Verified and Pro, the approach delivered 7–10 point absolute improvements and outperformed baselines trained on human data.
Most coding agents are capped by finite human-labeled data. Self-play SWE-RL unlocks unlimited training from existing codebases, applying an AlphaZero-style loop to software engineering. This points toward more autonomous and continuously improving coding agents.
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🤖 Meta has acquired Manus, a “general-purpose” AI agent startup built for autonomous end-to-end task execution, marking another move in Zuckerberg’s massive 2025 AI spending spree as Meta pushes toward real-world, scalable agent systems.
⚠️ Polls from Gallup and Pew show 80% of Americans want strict AI regulation even if progress slows, making unchecked AI one of the lowest-polling issues and a growing political wedge for both parties.
🚀 Three years after ChatGPT, 95% of enterprises still see no ROI, but VCs insist 2026 will be the true AI adoption year, with budgets rising, agents emerging, and winners defined by real workflow impact.
🛡️ China proposes strict new AI rules to protect kids, requiring guardian consent, human takeover on self-harm chats, usage limits, and bans on violent, gambling, or manipulative chatbot content.
✨ New SimilarWeb data shows a dramatic AI traffic reshuffle in 2025, with ChatGPT’s dominance dropping from 87% to 68% while Google’s Gemini triples its share to 18% in just one year.
🧩 Prompt of the Day
How to Create Interactive Content That People Actually Engage With
Turn passive scrolling into clicks, participation, and shares using simple interactive formats that invite action.
Paste the prompt: Drop this into ChatGPT, then fill the placeholders with your brand, audience, and the goal you want the interaction to drive.
Prompt to paste:
Brainstorm 5 interactive content ideas for [Brand or Product]. For each idea, include Format: [Quiz, poll, challenge, calculator, swipe, etc.]. Topic: [Specific subject tied to the audience’s problem or curiosity]. CTA: [Clear next step like subscribe, share, download, or shop]. Make each idea simple to execute, easy to understand in under 3 seconds, and designed to encourage sharing or repeat interaction rather than passive consumption.
🤳AI Nugget of the Day
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