Tulip is Perplexity’s lightweight Rust gRPC inference server that sits between Ivy and the ROSE engine. It collects incoming requests, batches them, and sends them to the GPU. For small embedding models, runtime depends on tokens, not query count, so ~512 tokens fills the GPU.
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How Perplexity Splits Inference Across Ivy, Tulip, and ROSE
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Perplexity exposes inference via standardized APIs. Ivy (Rust HTTP) does CPU work—parsing, tokenization, templating—and translates to gRPC. Tulip (Rust gRPC) schedules batches for the ROSE engine. ROSE (Python) implements forward passes and CUDA graph management.
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LangChain Adds Support for the Stateless MCP Specification
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You won't want to miss this — @sydneyrunkle with a detailed breakdown of LangChain's MCP revamp and support for the new, stateless spec!
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Screen, Keyboard, and Mouse Become Interfaces for Computer-Using AI
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The screen becomes the API and the keyboard and mouse are the actuators. Any software can become intelligent without even incorporating a single line of AI code. You can't even imagine the consequences this is going to have; it's wild. When we [Traduit de FR vers EN]
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Agent Harness Failures Can Be Mistaken for Model Failures
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I’ve seen that we typically assign failures to the model, even when the surrounding code is asking it to emit XML, parsing that from a text stream, retrying broken calls, and eventually stopping after three mistakes. A lot can go wrong before the model’s actual capability is
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Building a Math Application With LangChain
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Building Math App with LangChain! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #Books #100DaysofCode https://
geni.us/Building-LangC
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Remote Computer Control as a Milestone for AI Agents
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Read this carefully. As I've already written, we will reach a genuinely new stage with artificial intelligence when we can control a computer remotely with AI. In other words, an application like TeamViewer or AnyDesk with an AI that controls all actions at [Traduit de FR vers EN]
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A Learning Roadmap for vLLM, SGLang, and TensorRT-LLM
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Some ideas about how to get started learning about all of this Inference Engines & Topics – vLLM: PagedAttention, continuous batching, prefix caching, CUDA graphs – SGLang: RadixAttention/prefix reuse, speculative decoding, MoE, structured/agent workloads – TensorRT-LLM:
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Introducing GPT-6 Astra, our most intelligent and aligned model yet
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Introducing GPT-6 Astra, our most intelligent and aligned model yet. ✨ 💻 State-of-the-art computer use and software engineering
🔬 New breakthroughs in math and science
✨ Polished documents, spreadsheets and presentations that follow your templates and style Astra scores -
GPT-6 Astra Extends Interactive Computer Use by Agents
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Clearly, the approach of the new GPT-6 Astra is interactive, agentic computer use. It isn't really new—it was already starting to work with previous versions—but with a more agile and intelligent model, it can [Traduit de FR vers EN]