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Nov 8
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ProductsBuildersMulti-sourceSelected00:28
Together Compiler Boosts Inference Speed for AI Deployments

Kernel-level optimization running continuously as an agent means inference costs and latency can keep improving without hand-tuned engineering work. Teams running high-traffic inference deployments can apply it directly to existing endpoints rather than rebuilding them. It positions Together against hand-tuned serving stacks from rivals like vLLM-based providers, where such gains typically require specialist engineers.

Event
Official accountTogether AI@togethercomputeSource
ProductsBuildersSelected00:01
StepFun Showcases Step 5 Preview and Step Code at AI Engineer Shanghai 2026

The pairing of Step 5 Preview with an open-source Agent Harness signals that StepFun is treating agent reliability over long task horizons as a product-level problem, not just a model problem. Developers building agentic workflows can examine Step Code as an open alternative to proprietary agent frameworks from labs like OpenAI or Anthropic. The event also underscores StepFun's push to build a developer community around its stack.

Official account阶跃星辰 Stepfun@Stepfun_AISource
Nov 7
ProductsBuildersMulti-sourceSelected21:58
Vork engine lets AI agents write shaders with a 2,500-token API

Vork reframes engine design around machine-readable APIs instead of human-centric graphics interfaces, a shift that could reshape how agents handle 3D and VFX work. Builders working on agent pipelines for rendering, simulation or generative content can compare it directly against token costs in Blender or Unreal workflows. It runs on NVIDIA GPUs via Metal and Vulkan, so teams can test it on standard cloud instances.

Event
小互@imxiaohuSource
ProductsBuildersSelected76°09:42
LlamaIndex maps two-tier document OCR with liteparse and OCRia-1

The two-tier split matters because most agent pipelines overpay for accuracy on bulk digitisation, or underinvest on the documents that feed finance and insurance workflows. Teams building RAG over PDFs can pair liteparse as a cheap first pass with LlamaParse or OCRia-1 for the complex subset. OpenBMB is a Chinese lab, so the liteparse integration is also a practical example of open-weight China models plugging into Western tooling.

Jerry Liu@jerryjliu0Source

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