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Article Sep 29, 2026

NESS, the Neural-Symbolic Sandwich

A new direction for making transformers AGI-friendly—via judiciously mixing continuous symbolic program learning into open-weights transformers.

Ben Goertzel 43 min read

Community Jun 8, 2026

Beyond Digital Amnesia: How AI Agents are Learning to Evolve

AI agents no longer forget. EvoSC’s self-consolidation lets them learn from successes and failures, turning experience into lasting intuition — without memory overload.

Fethulmubin Ahmed 4 min read

Community Jun 8, 2026

LEAPS: Teaching AI to Evolve Solution Like Nature

Why just ask AI for answers when it can evolve them? LEAPS blends LLMs and evolutionary algorithms to generate, mutate, and refine solutions like nature.

Aryam Tesfay 3 min read

Article Sep 15, 2025

Anthropic will include user interactions in Claude's training data

By including interactions with users in training data, AI models could gain improved statistics on how people actually interact and an improved ability to resolve imprecisions and capture shifting language patterns.

Giulio Prisco 5 min read

Community Feb 6, 2025

Bias Whispers: The Untold Story of Learning Without Synaptic Change

Forget synaptic weight changes—what if learning happens differently? A new study shows neural networks can adapt by adjusting only biases, reshaping our understanding of AI and the brain.

Alazar Workneh 4 min read