[KongchangAI]

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Integrating WorkOS AuthKit Authentication in Rust axum: A Practical Guide
·2 min

Integrating WorkOS AuthKit Authentication in Rust axum: A Practical Guide

Based on WorkOS's official blog, this article explains how to integrate WorkOS AuthKit into a Rust axum app: use the Rust SDK for login, validate user sessions on every request, and verify webhook signatures, with integration insights and practical tips.

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Pushing the Limits of Extreme Sudoku on a 16GB GPU: Insights from Depth and Flow Matching
Tech Frontiers
·4 min

Pushing the Limits of Extreme Sudoku on a 16GB GPU: Insights from Depth and Flow Matching

A researcher trained a 16.54M-parameter model on a 16GB GPU to solve extreme Sudoku, finding effective depth breaks the 60% plateau and flow matching with improved sampling pushes accuracy past 99% with ~50× lower layer-evaluation budget.

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A New Proof on the Closedness of ReLU Network Sets: Single Hidden Layer is Weakly Closed, Two Hidden Layers is Not Closed
·2 min

A New Proof on the Closedness of ReLU Network Sets: Single Hidden Layer is Weakly Closed, Two Hidden Layers is Not Closed

New research proves single-hidden-layer ReLU network sets are weakly closed in W^{1,p}, ensuring existence of solutions for Deep Ritz and similar methods; two-hidden-layer network sets are not closed, refuting an existing conjecture.

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FlowMoP: A New Framework for Stochastic Multi-Person Motion Prediction
·2 min

FlowMoP: A New Framework for Stochastic Multi-Person Motion Prediction

FlowMoP introduces a conditional flow matching framework that jointly generates diverse future motions for multiple agents, using B-spline reparameterization and a dual-stream Transformer for interaction-aware prediction. It outperforms deterministic baselines on CMU-Mocap and 3DPW and establishes the first motion prediction baseline on WorldPose.

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Computer-Using Agents: A New General-Purpose Paradigm for Embodied AI
·2 min

Computer-Using Agents: A New General-Purpose Paradigm for Embodied AI

ECCV workshop competitions show computer-using agents (CUAs) can win multiple contests by turning embodied tasks into software interaction, without specialized tuning—revealing their potential as embodied generalists and a new path to general embodied AI.

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Graded Convolutional Networks: Scale Invariance and Blur Robustness Without Scale Parameters
·2 min

Graded Convolutional Networks: Scale Invariance and Blur Robustness Without Scale Parameters

Graded Convolutional Networks leverage the graded vector space structure of Gaussian jets to achieve scale invariance via retraction without scale parameters, significantly improving robustness under unknown Gaussian blur. MNIST experiments show 88.4% accuracy under two-pixel blur, outperforming scale-normalized derivatives at 66.2%.

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UCR Archive Exposed? 52 Pigs Reveal the Truth About TSC Benchmarks
·2 min

UCR Archive Exposed? 52 Pigs Reveal the Truth About TSC Benchmarks

Audit of the UCR time series classification archive: multiple datasets have repurposed tasks and flawed test splits. The 52-pig dataset reveals TSC benchmarks are disconnected from real problems, urging cautious interpretation of archive scores.

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How to Design Effective Monitor-Based Interventions to Curb Reward Hacking in RL
·3 min

How to Design Effective Monitor-Based Interventions to Curb Reward Hacking in RL

Research reveals design principles for monitor-based interventions against reward hacking in RL: models can evade high-precision monitors; monitors that leak more learning signal suppress hacking better but are easier to evade; mixing simpler problems into training reduces reward hacking. Three open-source environments—coding, medical chat, and biography generation—show findings transfer to new settings.

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The 19-Year-Old PayPal Mafia Dream: How Competition Kids Became the Backbone of AI
·2 min

The 19-Year-Old PayPal Mafia Dream: How Competition Kids Became the Backbone of AI

A tweet recalls a 2017 San Francisco lunch where 19-year-old Scott Wu and friends imagined the competition circle becoming the next PayPal Mafia. Nearly a decade later, these kids from MATHCOUNTS and AoPS are scattered across AI's core, showing how high-density peer communities cultivate top talent.

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RIP Harvest: The End of Distributed Tracing and a Rethink of Observability
·2 min

RIP Harvest: The End of Distributed Tracing and a Rethink of Observability

Aphyr's 'RIP, Harvest' sparks Hacker News debate. We analyze the maintenance costs, high-cardinality challenges, and alert fatigue behind observability tool exits.

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Is Jensen Huang's CEO Seat at Risk? Yale Scholar Puts His Odds of Staying at Roughly 50-50
·2 min

Is Jensen Huang's CEO Seat at Risk? Yale Scholar Puts His Odds of Staying at Roughly 50-50

NVIDIA's board is investigating CEO Jensen Huang's ties to an alleged Chinese spy. Yale professor Sonnenfeld puts his odds of staying at about 50-50. This article analyzes the investigation, founder-CEO governance risks, and the potential impact on NVIDIA and the AI supply chain.

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Apple Caps Engineers at $200 Daily AI Budget
·2 min

Apple Caps Engineers at $200 Daily AI Budget

Apple sets a $200 daily AI budget cap for engineers. Hacker News discussion highlights the tension between cost control and individual usage differences. This article analyzes the management logic of daily caps, the real friction points of enterprise AI adoption, and what it means for developers using AI tools.

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How Hackers Can Unlock Any Car from Brand X Worldwide
·2 min

How Hackers Can Unlock Any Car from Brand X Worldwide

A Hacker News hot article reveals a remote unlock vulnerability in a car brand: attackers can unlock vehicles across most of the world via the cloud communication link, bypassing physical contact. This analysis examines the attack surface, global impact, and structural issues in connected-car security.

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The AI Bubble Debate: Why Some Insist There Is No Bubble
·3 min

The AI Bubble Debate: Why Some Insist There Is No Bubble

Matteo Raso challenges the AI bubble theory, citing revenue growth, long-term infrastructure value, and early adoption. Hacker News debates capex and productivity gains.

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Amazon Applied Science Intern Interview: How PhDs Can Tackle Both ML and DSA Challenges
·2 min

Amazon Applied Science Intern Interview: How PhDs Can Tackle Both ML and DSA Challenges

An EU PhD student receives an Amazon Applied Science Intern interview with ML and DSA coding rounds. This article analyzes the interview content, short-term sprint strategies, and long-term coding advice to help candidates decide whether to cancel or prepare fully.

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HN Buzz: What Are Developers Working On Lately?
·1 min

HN Buzz: What Are Developers Working On Lately?

The Hacker News monthly "What are you working on?" thread drew 188 upvotes and 631 comments as developers shared projects and technical curiosities. This analysis explores why such open discussions thrive in tech communities and their value for sensing trends and preserving community memory.

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4x R9700 Benchmark: Qwen3.8 Long-Context Concurrent Inference Performance
·3 min

4x R9700 Benchmark: Qwen3.8 Long-Context Concurrent Inference Performance

A Reddit user shares a 4x R9700 inference server benchmark: Qwen3.8-Flash-Next under tp4 sustains ~6800 tok/s prefill, with 8-user 128K follow-up turns getting first token in just 0.2-2.5s, plus key lessons on prefix cache and host-pool parameters.

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No Skin, But a Stroller First: Éloi's Unconventional Office Stroll
·2 min

No Skin, But a Stroller First: Éloi's Unconventional Office Stroll

Animotion Robotics' robot Éloi, still without skin or a complete face, is taken for walks in a stroller around the office. This "parenting-style" development approach uses temporary solutions to get the robot into human environments early, sparking reflection on robot testing priorities.

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