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A summit pitch on building reliable AI agents

A post says NVIDIA, Hugging Face and OpenHands will attend, pitching the summit as a learning opportunity.

Graham NeubigGN
Boris PowerBP
elvisEL
5 Sources, 1h ago, first seen 1h ago

TLDR

A post promotes a summit as a chance to learn about the decisions involved in building reliable AI agents, from models and data to tools, security, infrastructure and ongoing improvement. It says NVIDIA, Hugging Face and OpenHands will be there.

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5 Sources, first seen 1h ago

— likes— comments— saves— reposts

Combined views

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5 Sources, first seen 1h ago

— likes— comments— saves— reposts

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5 Sources

Santiago@svpinoSoftware Engineering has never been more alive. If you care about building reliable agents, you'll need to make 1,000 decisions about models, data, tools, security, infrastructure, and how to improve them over time. The industry's cream of the crop will be at this summit: NVIDIA, Hugging Face, OpenHands... Great chance to learn about all that matters.1h
elvis@omarsar0Own your intelligence stack, folks! Open models, open data, and open harnesses are where a lot of the real agent building is happening right now. Here's a great opportunity to catch up on the latest. @digitalocean's Open Intelligence Summit today features talks on building an agent with an open harness, when it's worth post-training an open model for your agents, and how to keep a post-training loop running without idle GPUs. Great lineup from Nous Research, OpenHands, NVIDIA, Hugging Face, and more. The keynote is at 1 PM PT.1h
Boris Power@BorisMPowerA great opportunity to learn what it takes to effectively deploy super intelligence in the enterprise setting to deliver clear business value32m
Graham Neubig@gneubigI now use digital ocean VMs to host my personal cloud agents that automate a bunch of my daily tasks, so really excited to have OpenHands participate in this event!26m
Rohan Paul@rohanpaul_aiAgent traffic is a strange workload for an inference server. Each turn resends a long, nearly identical prefix (system prompt, tool schemas, history) and asks for a short tool call back. At DigitalOcean’s Open Intelligence Summit, Yifan Qiao of Inferact is giving a Serve track session on running vLLM on agentic production workloads. That shape of traffic is why prefix caching and KV-cache reuse matter more for agents than raw tokens per second. A cache miss on a long prefix means paying for the full prefill again, on every turn of a long task.24m
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    5 Sources

    Santiago@svpinoSoftware Engineering has never been more alive. If you care about building reliable agents, you'll need to make 1,000 decisions about models, data, tools, security, infrastructure, and how to improve them over time. The industry's cream of the crop will be at this summit: NVIDIA, Hugging Face, OpenHands... Great chance to learn about all that matters.1h
    elvis@omarsar0Own your intelligence stack, folks! Open models, open data, and open harnesses are where a lot of the real agent building is happening right now. Here's a great opportunity to catch up on the latest. @digitalocean's Open Intelligence Summit today features talks on building an agent with an open harness, when it's worth post-training an open model for your agents, and how to keep a post-training loop running without idle GPUs. Great lineup from Nous Research, OpenHands, NVIDIA, Hugging Face, and more. The keynote is at 1 PM PT.1h
    Boris Power@BorisMPowerA great opportunity to learn what it takes to effectively deploy super intelligence in the enterprise setting to deliver clear business value32m
    Graham Neubig@gneubigI now use digital ocean VMs to host my personal cloud agents that automate a bunch of my daily tasks, so really excited to have OpenHands participate in this event!26m
    Rohan Paul@rohanpaul_aiAgent traffic is a strange workload for an inference server. Each turn resends a long, nearly identical prefix (system prompt, tool schemas, history) and asks for a short tool call back. At DigitalOcean’s Open Intelligence Summit, Yifan Qiao of Inferact is giving a Serve track session on running vLLM on agentic production workloads. That shape of traffic is why prefix caching and KV-cache reuse matter more for agents than raw tokens per second. A cache miss on a long prefix means paying for the full prefill again, on every turn of a long task.24m
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