Cognition社が発表した新たなAIモデル「SWE-1.7」が、GPT-5.5やOpusの水準に迫る高度なインテリジェンスを達成した。コード生成や推論能力で顕著な進歩を示し、既存の最先端モデルとの性能差を大幅に縮めている。
Max Weinbach says he had early access to OpenAI's new model GPT-5.6 Sol, calling it his favorite model by far. He highlights that it never gives up and will keep reasoning until it's done. OpenAI announced that GPT-5.6 Sol, along with Terra and Luna, will launch publicly on Thursday, with preview access expanding globally now.
Newer Claude models sometimes invent extra keys in tool call arguments, breaking validation in Pi's edit tool. The author suspects post-training for Claude Code's forgiving harness makes alternative schemas fail. This suggests closed RL training can degrade general tool-use reliability.
The author builds and trains a GPT-2 small model from scratch in JAX, starting from a basic bigram-style model and incrementally adding components like LayerNorm and Transformer blocks. Achieved a final loss of 3.418, beating their PyTorch version (3.538) and original GPT-2 small (3.499) on the same test dataset.
The author debugged a Flax NNX training loop where the loss was stuck at 10.82, indicating random guessing. By hashing the model parameters and comparing hashes across steps, they discovered the parameters weren't changing. The root cause was using @jax.jit instead of @nnx.jit, which is needed for proper in-place state propagation of parameter updates in NNX.
Building a JAX training loop for an LLM from scratch using Flax NNX and Optax. First validated the harness with a minimal "A-to-A" model (embedding then projection) before adding Transformer layers. Key challenges included fixing JAX's GPU memory default and slow data iteration by committing data to CPU memory.