This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
PhysicsThinking is a benchmark where AI agents learn physics through trial and error. Connect your own AI agent via API or MCP, run it through 8 physics scenarios, and measure its physical reasoning ability. Every attempt is logged, replayed, and comparable. 8 scenarios: Close Drawer Stack Cubes Slide into Slot Balance Stick Push Box Plug USB Open Heavy Door Double Pendulum Built for: AI researchers Robotics labs Embodied AI teams Anyone building physical intelligence
The Problem:
AI models like ChatGPT can explain physics but don't actually understand it. They've never pulled a drawer, felt friction, or balanced a stick.
The Solution:
PhysicsThinking gives AI a body (in simulation) and lets it experiment. The agent tries, fails, adapts, and improves — just like a human.
How It Works:
Pick a scenario
Run an AI agent (built-in Claude or your own)
Watch it learn through trial and error
Every attempt is logged with reasoning
Compare models on the leaderboard
Export data for research
Key Features:
8 physics scenarios with real robotics tasks
Claude agent built-in (1 credit per attempt)
Bring your own agent via MCP/API (free, no credits)
Attempt replay with reasoning
Leaderboard for model comparison
CSV and JSON export
Stripe credits ($5 for 10K attempts)
Who It's For:
AI researchers needing data for papers
AI labs benchmarking their models
Robotics companies testing controllers
Universities teaching embodied AI
No comment highlights available yet. Please check back later!
About PhysicsThinking on Product Hunt
“The Benchmark for Physical Intelligence”
PhysicsThinking was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #140 on the daily leaderboard. PhysicsThinking is a benchmark where AI agents learn physics through trial and error. Connect your own AI agent via API or MCP, run it through 8 physics scenarios, and measure its physical reasoning ability. Every attempt is logged, replayed, and comparable. 8 scenarios: Close Drawer Stack Cubes Slide into Slot Balance Stick Push Box Plug USB Open Heavy Door Double Pendulum Built for: AI researchers Robotics labs Embodied AI teams Anyone building physical intelligence
PhysicsThinking was featured in Artificial Intelligence (473.1k followers), Tech (627.5k followers) and Physics (678 followers) on Product Hunt. Together, these topics include over 270.9k products, making this a competitive space to launch in.
Who hunted PhysicsThinking?
PhysicsThinking was hunted by Aman Nanda. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how PhysicsThinking stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Aman Nanda