Robots winning marathons!

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🤖 Robot Runners Take the Lead in Beijing’s First Humanoid Half-Marathon

China hosted the world’s first half-marathon featuring humanoid robots running alongside thousands of human athletes. With only 4 out of 21 robots finishing the race, the event became both a test of engineering and a showcase of national ambition in robotics.

The Decode:

• Tiangong Ultra Sets the Pace - The winning robot, Tiangong Ultra, finished in 2 hours and 40 minutes, aided by long legs and advanced running algorithms. It needed three battery swaps and even took a fall mid-race. Despite the challenges, it beat 17 other bots that couldn’t make the cutoff.
  
• Real-World Stress Test for Robotics - Many robots struggled, one crashed into a fence, another smoked from the head, and several fell flat at the start. With only four completing the extended 4-hour limit, the race exposed critical design limitations in today’s humanoid robotics.
  
• High-Stakes Public Demonstration - The event was backed by Beijing’s ambition to dominate humanoid robotics, with support from companies like Xiaomi and subsidies from the state. Officials likened it to a race car competition, where engineers navigated both hardware and AI challenges in real time.
  
• Skeptics Warn of Overhype - Experts argue that walking and running demos don’t reflect true intelligence or utility in industrial settings. While eye-catching, such feats don't solve actual productivity challenges. However, the ability to run and adapt under pressure is still an essential step toward factory-ready bots.

This wasn’t about who won the race, it was a signal of global competition in AI and robotics. With China ramping up public tests and industrial funding, the US and others may be pushed to accelerate humanoid development. The finish line isn’t just physical, it’s strategic, economic, and geopolitical.

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🎥 How to Use ReelFarm to Automatically Create and Publish TikTok Videos

ReelFarm is an AI-powered platform that creates and publishes TikTok-style UGC videos promoting your product, all without filming, editing, or posting manually.

✅ Step-by-Step Guide

1. Sign Up and Choose a Plan

Go to reel.farm and click Start Now. Choose from:

• Starter ($19/month) – 10 videos, access to 200+ UGC avatars, generate viral hooks, create up to 25 image and 5 video AI avatars, TikTok publishing and automation
• Growth ($49/month) – 50 videos, slideshow video access, 100 image and 25 video avatars
• Scale ($95/month) – 150 videos, all features, 200 image and 50 video avatars

2. Generate Viral Hooks: Use the Hook Generator to instantly create and save viral openers for your videos.

3. Create UGC Avatars: Use the UGC Avatar Generator to turn your product images and clips into custom AI avatars. All plans include access to 200+ prebuilt avatars.

4. Choose Your Video Format

You can create:

• Hook + Demo UGC videos
• Greenscreen Meme Videos
• Slideshow Videos (Growth and Scale only)

5. Launch an Automated Campaign: Use the Automated Campaigns feature to auto-create and auto-publish videos directly to your TikTok account — fully hands-off.

👨‍💻 Mechanize Wants to Fully Automate the Workforce

Mechanize, a new AI startup from Epoch co-founder Tamay Besiroglu, aims to accelerate the complete automation of human labor. With support from investors like Jeff Dean and Nat Friedman, the company is creating simulated digital workspaces to train agents on real-world job tasks.

The Decode:

• Simulating Real Work - Mechanize is developing virtual environments that mirror real office tasks, long, complex, interrupted workflows requiring decision-making, coordination, and persistence. These simulations will help train AI models to handle tasks like a human would in a real job setting.
• Targeting a $60 Trillion Market - The team estimates the global labor market value at $60 trillion annually and believes most of that can be automated. By focusing on ordinary labor instead of rare “super-intelligence,” they plan to unlock economic scale through automation of white-collar jobs.
• Fixing AI’s Limits - Current models fail at long-horizon planning, context retention, and multi-modal reasoning. Mechanize hopes to overcome this by combining reinforcement learning with targeted benchmarks and training data, effectively building the “data gym” for work-ready AI agents.
• Raising Eyebrows - The announcement drew early backlash, both for the unsettling goal of full labor automation and for conflict-of-interest concerns with Besiroglu’s Epoch role. Critics worry that proclaiming “AI will take your job” may accelerate resistance in an already anxious economy.

Mechanize represents a bold and controversial push toward a future where AI doesn’t just assist workers, it replaces them entirely. If they succeed, it could spark massive economic growth and social upheaval in equal measure, bringing forward difficult questions about jobs, purpose, and the structure of society itself.

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📝 AI Essay Grader – Save hours by grading essays with AI-powered feedback that students can actually learn from.

📈 Balzac – Get fresh, SEO-optimized blog content done for you without agencies or writers.

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📽️ OpenAI’s latest AI models hallucinate more often than older ones, raising concerns about their reliability. Internal tests show o3 hallucinated on 33% of PersonQA questions, while o4-mini did so 48% of the time.

🎫 Experts raise concerns over Google’s latest Gemini 2.5 Pro technical report, citing a lack of transparency and missing safety details. Despite prior commitments, the report omits key findings from Google’s own Frontier Safety Framework.

🛍️ OpenAI’s o3 model claimed a 25% math benchmark score, but independent tests show just 10%. The public model is smaller, tuned for speed, sparking transparency concerns and AI benchmarking doubts.

🛒 OpenAI has introduced Flex processing, a cost-saving API option offering slower speeds and occasional unavailability. Aimed at non-critical tasks, it cuts token costs by 50% for o3 and o4-mini models.

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