Your identity is the key, not a shared password. Treat gk_live_… like a password. Share it and someone can read/write that hold until you revoke it. Lose it and mint a new one. The memories stay.
Key points
gk_live_... as a Shared Secret: gk_live_... should be treated like a password, not a shared secret. Sharing it can lead to unauthorized access until revoked.
Identity Management: Losing gk_live_... requires minting a new one, which can lead to memory retention issues.
Security Considerations: gk_live_... should be handled with the same care as a password to prevent unauthorized access.
Sources
Database Performance - Klaviyo's Segment Evaluation Optimization
Klaviyo's segment evaluation dropped from over an hour to one second. https:// buff.ly/Lr538qe A 192-node ClickHouse cluster now computes tens of billions of segment membership changes a day for around 170,000 companies.
Key points
ClickHouse Cluster Optimization: A 192-node ClickHouse cluster was optimized to compute tens of billions of segment membership changes per day.
Segment Evaluation Optimization: Klaviyo's segment evaluation was optimized from over an hour to one second.
Database Performance: The optimized cluster achieved significant performance improvements.
Sources
Control Workflow Development - Simulink-Based Control Workflow for Dual-Motor EV Platform
From throttle input to CAN communication and motor feedback, Team I.C.C. from Inha University built and validated a Simulink-based control workflow for a dual-motor EV platform on STM32F4, creating a foundation for future torque-vectoring development
Key points
Simulink-Based Control Workflow: A Simulink-based control workflow was developed for a dual-motor EV platform on STM32F4.
Control Workflow Validation: The control workflow was validated for throttle input, CAN communication, and motor feedback.
Foundation for Future Development: The control workflow provides a foundation for future torque-vectoring development.
Sources
AI Agent Development - Purchase Order Generator
Purchase Order Generator is an AI agent that creates professional, compliant purchase orders in seconds — with every required field included After a one-time company setup, you just name the vendor and line items and it assembles the rest from saved context — with totals,
Key points
Purchase Order Generator: An AI agent was developed to create professional, compliant purchase orders in seconds.
AI Agent Functionality: The AI agent assembles purchase orders from saved context, including totals.
Company Setup: A one-time company setup is required for the AI agent to function.
Sources
Mobile App Development - Tinder for iPhone Duo
Tinder for iPhone Duo could use the Hinge (get it?) for your likes. A progressive disclosure where the more you open your phone, the closer you get to discovering if you matched with the person. I feel this could make the experience a bit more intentional and reward the user
Key points
Tinder for iPhone Duo: A new approach to Tinder for iPhone Duo was proposed, using a progressive disclosure mechanism.
Progressive Disclosure: The more the user opens their phone, the closer they get to discovering if they matched with the person.
Intentional Experience: The proposed approach aims to create a more intentional and rewarding user experience.
Sources
AI Model Optimization - Batch Inference Optimization
Great work. Please use https:// github.com/BlinkDL/Albatr oss … (try v3a_2607) for much faster batch inference And I can tune your code if it's on github
Key points
Batch Inference Optimization: A faster batch inference approach was recommended using the Albatross repository.
Code Tuning: The author offered to tune the user's code if it's hosted on GitHub.
Sources
AI Model Optimization - State Tuning for RWKV-7
And the key is to make use of RWKV-7 state (reuse it as much as possible). You can try state-tuning too (check https:// codeberg.org/scarletwolf_ai /rwkv-toolcaller-bench … )
Key points
RWKV-7 State Reuse: The RWKV-7 state should be reused as much as possible for optimization.
State Tuning: State tuning was recommended as an additional optimization approach.
Sources
AI Market Trends - ZAI Stock Performance
Despite record usage of the models, ZAI stock is down over 2x from its peak. The Chinese markets have a real understanding of the economic impact of AI, the US ones do not. It's very important that the US government doesn't bail any of this out
Key points
ZAI Stock Performance: ZAI stock has declined significantly despite record model usage.
Market Understanding: The Chinese markets have a better understanding of the economic impact of AI than the US markets.
Government Intervention: The US government should not intervene in the AI market.
Sources
Mobile App Development - Jev for Google Maps
Introducing Jev for Google Maps Turn any local website into a mobile app. Simply paste a URL. Jev controls your Mac to rebuild the original website as a native mobile app, then submits it to the app stores for you. We've been using this a ton for iOS apps
Key points
Jev for Google Maps: A new tool, Jev, was introduced for turning local websites into mobile apps.
Mobile App Creation: Jev controls the user's Mac to rebuild the original website as a native mobile app.
App Store Submission: Jev submits the mobile app to the app stores.
Sources
OCR Model Comparison - WeVisDoc and Jina-OCR-V1
2 new OCR models landed on @huggingface today - tencent/WeVisDoc (2B and 4B), Apache 2.0 - jinaai/jina-ocr-v1, non-commercial license Which one should you pick? Based on the OmniDocBench v1.6 benchmark on Papers with Code, WeVisDoc-4B leads with an overall score of 95.38,
Key points
WeVisDoc and Jina-OCR-V1: Two new OCR models were introduced on Hugging Face, WeVisDoc and Jina-OCR-V1.
Benchmark Comparison: WeVisDoc-4B led the OmniDocBench v1.6 benchmark with an overall score of 95.38.
Model Selection: The choice between the two models depends on specific requirements.