Key research and product announcements at the AI Native Conf

What this post added

This post introduces several significant technical advancements that enhance AI infrastructure and performance. Key contributions include: FlashAttention-4, a new attention algorithm optimized for NVIDIA Blackwell GPUs, offering substantial speedups over existing solutions. Together Megakernel, a single-kernel implementation for running entire models, achieving significant latency reduction for real-time voice agents. together.compile, an automation tool for generating optimized GPU kernels, improving generation speed for video and image models. The Reinforcement Learning API is enhanced with infrastructure for RL training, focusing on efficient weight distribution and rollout optimization. ThunderAgent is introduced as a program-aware abstraction for agentic workloads, addressing KV cache thrashing, cross-node memory imbalance, and tool lifecycle issues, leading to improved throughput and memory savings. ATLAS-2 provides an online training flywheel for speculative decoding, continuously updating speculators from live traffic for sustained performance gains. Cache-aware prefill–decode disaggregation (CPD) introduces a three-tier serving stack to optimize long-context inference by intelligently routing requests based on cache hit rates, significantly increasing sustainable throughput.