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🚀 Video Editing - Outfit Change Transitions

👁️0reads (human + AI)🤖0AI ingestions

🚀 Video Editing - Outfit Change Transitions

This article explains how to easily create outfit change transitions in videos using Filmora's Smart Cutout feature. The process requires minimal effort and eliminates the need for green screens.

Key Points:

• Seamless outfit changes without green screen

• Simplified editing workflow

• Faster and more enjoyable editing experience

🔗 Resources:

Filmora Editor ↗ - Video editing software

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🤖 LLM Evaluation - Introduction to PGRM

This article discusses the limitations of using Large Language Models (LLMs) as evaluators for generative models and introduces PGRM as an alternative. LLM evaluators are slow, expensive, nondeterministic, and lack calibration.

Key Points:

• LLM judges are slow and expensive

• LLM evaluation is nondeterministic

• PGRM offers a more reliable alternative

🔗 Resources:

Databricks ↗ - Data and AI platform

Jeff Frankle ↗ - AI researcher

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💡 AI Agent Building - Free Training Program

This article announces a free training program to certify individuals as AI Agent Builders. The program addresses the current skills gap in AI agent development.

Key Points:

• Free training for AI agent building

• Addresses high demand for AI agent builders

• Includes prizes

🔗 Resources:

Lindy ↗ - AI training

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✨ AI Innovation - Women in AI Panel

This article announces a panel discussion featuring women leaders in AI innovation. The event will take place on August 15th at 3:00 PM PDT in Palo Alto, CA.

Key Points:

• Panel discussion featuring women leaders in AI

• August 15th, 3:00 PM PDT

• Location: JPMC Tech Center, Palo Alto, CA

🔗 Resources:

ApertureData ↗ - AI company


🤖 Data Quality Control - Autoraters

This article describes a new approach to scaling quality control for complex data using autoraters powered by multi-agent model debate. The approach is designed to handle data that challenges even advanced LLMs.

Key Points:

• Novel approach to data quality control

• Uses multi-agent model debate

• Addresses challenges of scaling data quality

🔗 Resources:

Scale AI ↗ - Data solutions

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💡 Human-AI Collaboration - Delphi

This article highlights the importance of human connection, curation, and trust in the age of abundant AI and introduces Delphi as a platform designed to amplify uniquely human qualities.

Key Points:

• Human connection is key in the AI era

• Delphi amplifies uniquely human qualities

• Focus on curation and trust

🔗 Resources:

Delphi ↗ - Human-centric AI platform

Jess Kah ↗ - AI thought leader

Darla Adje ↗ - AI thought leader

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🤖 GPT-OSS-120B API Benchmarks

This article presents benchmarks comparing the accuracy of providers offering APIs for the GPT-OSS-120B model. The benchmarks use GPQA Diamond, AIME25, and IFBench.

Key Points:

• Benchmarks compare accuracy of GPT-OSS-120B APIs

• Uses GPQA Diamond, AIME25, and IFBench

• Reports median and percentile scores

🔗 Resources:

Artificial Analysis ↗ - AI benchmarking

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🤖 Agent Leaderboard - New Models

This article announces the addition of several new models to the Agent Leaderboard, highlighting the performance of glm-4.5-Air.

Key Points:

• Expanded Agent Leaderboard

• glm-4.5-Air shows strong performance

• High tool selection quality

🔗 Resources:

Run Galileo ↗ - Agent evaluation platform

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🤖 AI Progress - Gemini and Genie Models

This article discusses the need for both advanced AI models and better benchmarks to evaluate progress towards artificial general intelligence. It highlights a conversation between Demis Hassabis and Logan Kilpatrick about Google's Genie 3 and Gemini 2.5 world models.

Key Points:

• Need for advanced AI models and better benchmarks

• Discussion on Google's Genie 3 and Gemini 2.5

• Focus on evaluating progress towards AGI

🔗 Resources:

Google AI ↗ - AI research

Demis Hassabis ↗ - Google DeepMind CEO

Logan Kilpatrick ↗ - Google AI

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🤖 Vision-Language Models - LFM2-VL

This article introduces LFM2-VL, an efficient liquid vision-language model. It highlights the model's speed, accuracy, and support for large images.

Key Points:

• Efficient vision-language model

• Competitive accuracy and speed

• Supports large images via smart patching

🔗 Resources:

Hugging Face ↗ - Model hosting platform

Liquid AI ↗ - AI company

Ramin Mehran ↗ - AI researcher

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Drix10
Written by Drix10

Co founder @ PartPilot | 1 x Acquired Founder | Canopy @ f.inc | Cybersec @ DSU | 2x International Hackathon 🏆. Read more on drix10.com.