🔐 New EIP-8250: Keyed Nonces for Frame Transactions 🔐 by @soispoke, @nero_eth, @lightclients and @VitalikButerin This replaces the single sender nonce with (nonce_key, nonce_seq), giving frame transactions independent replay domains. For privacy protocols, the key can be derived from a nullifier: concurrent withdrawals from a shared sender become possible, with inclusion atomically marking the nullifier spent. Target fork: Hegota Links below 👇

Creator of C , Bjarne Stroustrup: AI-generated code isn't ready — it generates more bugs, more bloat, more security holes, and is nearly impossible to validate "senior developers are already retiring rather than deal with it" The problem is that even a small prompt change can shift the entire codebase in unpredictable ways

I added KV caching and INT8 KV quantization to our transformer inference, improving throughput by 35x. All of this was done from scratch in Rust CUDA, on top of a homemade ML framework. On a 4-token prompt with 252 generated tokens: - Original: 0.76 tok/s - KV cache fp32: 27.21 tok/s - KV cache int8 (quantized): 27.29 tok/s Try it out yourself here: mni-ml.github.io/demos/kv-ca… In practice: - KV caching gave us about a 35x end-to-end speedup - INT8 KV cache kept roughly the same speed as fp32 but cut KV cache memory by 3.78x FP32 cache used 4.5 MB in this run while the INT8 cache used only 1.19 MB This simple change to inference created a huge impact on performance. To learn more about the KV cache and other optimizations like this, check out the blog at mni.ml!

Last week, we released a preview of memories in Codex. Today, we’re expanding the experiment with Chronicle, which improves memories using recent screen context. Now, Codex can help with what you’ve been working on without you restating context.