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EchoJEPA: Latent Predictive Foundation Model for Echocardiography

https://github.com/bowang-lab/EchoJEPA
1•euvin•6m ago•0 comments

Disablling Go Telemetry

https://go.dev/doc/telemetry
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Effective Nihilism

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The UK government didn't want you to see this report on ecosystem collapse

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No 10 blocks report on impact of rainforest collapse on food prices

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Seedance 2.0 Is Coming

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Dexterous robotic hands: 2009 – 2014 – 2025

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Interop 2025: A Year of Convergence

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JobArena – Human Intuition vs. Artificial Intelligence

https://www.jobarena.ai/
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Concept Artists Say Generative AI References Only Make Their Jobs Harder

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https://github.com/mkmkkkkk/paysentry
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https://moli-green.is/
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The Crumbling Workflow Moat: Aggregation Theory's Final Chapter

https://twitter.com/nicbstme/status/2019149771706102022
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Pax Historia – User and AI powered gaming platform

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Show HN: I built a RAG engine to search Singaporean laws

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Scams, Fraud, and Fake Apps: How to Protect Your Money in a Mobile-First Economy

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Porting Doom to My WebAssembly VM

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Cognitive Style and Visual Attention in Multimodal Museum Exhibitions

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Full-Blown Cross-Assembler in a Bash Script

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Logic Puzzles: Why the Liar Is the Helpful One

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Forcing Rust: How Big Tech Lobbied the Government into a Language Mandate

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Make Trust Irrelevant: A Gamer's Take on Agentic AI Safety

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Show HN: Sem – Semantic diffs and patches for Git

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1•rs545837•1h ago•1 comments
Open in hackernews

Show HN: Pebble Falcon–autonomous right-sizer and carbon-aware K8s scheduler

1•kevalshah90•7mo ago
Hi HN — I’m Keval, part of the AI team behind Pebble Falcon.

What it Pebble Falcon:

Two long-running agents you deploy inside your k8s cluster.

> PerfectFit:

- Streams pod / VM / GPU utilization

- Calculates head-room

- Generates JSON patches to right-size CPU, memory and storage

- Optional human-approval step

> EcoAgent

- Polls real-time grid-carbon feed and re-configures GPU nodes and pods to maximize clean energy use.

- Re-queues batch jobs to the region with the lowest gCO₂/kWh that still meets your latency SLA

A lightweight web UI shows cost saved, watts avoided and a 30-day projection.

No data leaves the cluster; the only inbound feed is public carbon intensity.

Why we built it:

We kept seeing GPU nodes idling below 20 % while ETL jobs ran in high-carbon regions. Manual “rightsizing sprints” never caught up.

Pilot result (40-node GPU cluster, 30 days) 70% idle compute removed

4160 kg CO₂ avoided (≈ six NYC→London flights)

Pebble Falcon needs access to clusters so no public sandbox yet. Instead we recorded a 3-min overview of the agents.

Video Demo: https://youtu.be/DTpHxAmVrAo

However if you’re interested in trying it out, comment and we’ll get in contact and can add you to our pilot test: https://www.gopebble.com/sign-up

AMA about energy, cost and compute aware scheduling for AI workloads.

Comments

JojoFatsani•7mo ago
It’s neat but I’m sure it would kill something important before too long.

Hopefully this is “just built in” to kube within the next few years..

Thomas2419•7mo ago
Yeah hopefully we just get acquired our tech get's integrated into k8s