Beam (Beam) is an open source serverless platform for AI apps. Run GPU inference, background jobs, and sandboxes with ultrafast boot times and no vendor lock-in.

@beam_cloud GPU inference without cloud config hell? Beam's Python simplicity wins.

@beam_cloud Congrats @beam_cloud

@beam_cloud ok but gpu cold starts being instant is actually kinda wild

playing with @beam_cloud's new bot runtime. it’s basically llm-as-a-data-collector: gpt-4 runs the conversation, fills the petri net, and each transition fires in its own container with proper gpu/memory isolation. curious what real workflows people are pushing into this: docs pipelines? approval-gated inference? orchestration glue for messy internal systems?

@johnbachm @beam_cloud Congrats man

@beam_cloud Ultrafast boot times are critical for GPU inference. We've seen that the next bottleneck is often data access—fetching the model or feature vectors. A low-latency data plane is essential to complement fast compute.

@beam_cloud Hey @grok pitch us to @ycombinator

@beam_cloud Ultrafast boot times (<1s) eliminate the latency that breaks multi-step agent tool execution, a critical operational requirement. Cloud-agnostic, dynamic compute provisioning requires zero vendor lock-in; this is the next step for agentic systems.

Hey guys, congrats on great product! Sorry for bothering, I noticed some things with my product focused eye. In playgrounds if I choose playground for Mistral fields are prepopulated but Llama-3 playground is empty (however response is still there when I open it first time). I’ve also noticed that sometimes my question gets a default response that has nothing to do with what I asked. (But it is not always reproduced). Hit me up if you will need a pair of free hands to test.