A lot of the skills robots need to learn already exist in real workplaces.
Machine Age is bringing skilled businesses and robotics teams together so robots can learn from real tasks, practical experience and the people who do this work every day.
Its new marketplace is opening the door for businesses from anywhere in the world, whether that's India, South America, Europe, the US or anywhere else, to contribute to the future of robotics.
Interesting to see how this develops.
Checkout here: https://t.co/9XfLpLksIP
The future belongs to those who never stop learning! 🚀
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November 17–19 at BIEC, Bengaluru
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AI agents shouldn't need you to keep checking on them while they wait for emails or Slack replies.
Strawberry Browser is solving this with Jev, powered by @typesafeai
It monitors app events and lets your AI companion take action when something happens, from handling emails to managing files.
A simple but useful step toward truly autonomous AI agents.
Test your AI video model's ability to interact in real time with StreamEval.
Here are 5 resources to explore the benchmark:
1. Leaderboard: https://t.co/Whola5D5Pm
2. Research Paper: https://t.co/2MDY1TgXWC
3. GitHub Repository: https://t.co/MvCwMLDejL
4. Benchmark Dataset (Hugging Face): https://t.co/PmGFtHYmg3
5. Benchmark Dataset (ModelScope): https://t.co/kWanmnnkxL
Explore the benchmark, access the code and datasets, and reproduce the evaluations yourself.
Run your own tests with StreamEval and see how your model compares on the leaderboard.
AI video generation is moving beyond just creating clips.
The next challenge? Making videos respond to you while they're being generated.
StreamEval is an open-source benchmark designed to test exactly that.
Instead of focusing only on video quality, it evaluates whether AI models can handle real-time interactions across three categories spanning five tasks:
→ Avatar Interaction: Handle conversations and follow movement commands as a session unfolds.
→ World Generation: Change environments, camera views or actions based on incoming instructions.
→ Real-Time Video Editing: Modify specific elements in a video while preserving unaffected content.
What makes this particularly interesting is that StreamEval allows AI developers to evaluate their models using publicly available code and datasets, with support for submitting models through API endpoints.
This could become an important benchmark for understanding how close we are to truly interactive AI video systems.
Curious to see which models perform best, especially when it comes to precise real-time editing.
Paper, GitHub, and datasets in the comments 👇
#StreamEval #AI #VideoGeneration #StreamEvalBenchmark