Fellow AI researchers - let's be real. We're stuck in a rut.
Problems: - Single modality is dead. Real intelligence isn't just text/image/audio in isolation - Another day, another LLM with 0.1% better benchmarks. Yawn - Where's the novel architecture? All I see is parameter tuning - Transfer learning still sucks - Real-time adaptation? More like real-time hallucination
The Challenge: 1. Build systems that handle 3+ modalities in real-time. No more stitching modules together 2. Create models that learn from raw sensory input without massive pre-training 3. Push beyond transformers. What's the next paradigm shift? 4. Make models that can actually explain cross-modal reasoning 5. Solve spatial reasoning without brute force
Bonus Points: - Few-shot learning that actually works - Sublinear scaling with task complexity - Physical world interaction that isn't a joke
Stop celebrating incremental gains. Start building revolutionary systems.
Share your projects below. Let's make AI development exciting again.
If your answer is "just scale up bro" - you're part of the problem.
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