Tag

machine-learning.

73 writings found

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Spotify's AI Playlist Generator Now Handles Podcasts, and It's Actually Useful

Spotify extends Prompted Playlists to podcasts. I tested the AI-powered discovery tool and found it surprisingly competent at solving podcast overload.

Meta's KernelEvolve: When AI Writes Its Own Performance Code

Meta's KernelEvolve system uses AI agents to automatically optimize low-level hardware kernels, achieving 60% performance gains in hours instead of weeks.

Meta's Adaptive Ranking Model: The Real Cost of Serving Trillion-Parameter Ads

Meta scaled ads recommendations to LLM complexity while keeping latency under a second. Here's why their inference trilemma solution matters beyond advertising.

Why Your AI Benchmark Is Probably Wrong: The N,K Trade-off

Google Research reveals why using 3-5 human raters per item isn't enough for reproducible AI evaluation. The depth vs breadth problem explained.

Meta's AI is Reshoring American Concrete, One Mix at a Time

How Bayesian optimization is helping U.S. concrete producers ditch imported cement and redesign mixes in days instead of months.

Suno v5.5: AI Music Generation Gets Personal with Voice Cloning and Custom Training

Suno's v5.5 update brings voice cloning, custom model training, and personalization. A look at what this means for creators and the music industry.

How Facebook Built Friend Bubbles: A Deep Dive into Social ML Architecture

Meta's friend bubbles system combines closeness prediction models, ranking optimization, and performance engineering to surface friend-driven content at scale.

GitHub's New Data Policy: Your Code Becomes Training Data

GitHub will train AI models on Copilot Free, Pro, and Pro+ user data starting April 24. Here's what developers need to know about this industry shift.

Facebook's Friend Bubbles: When Social Graphs Meet Recommendation Systems

Meta's friend bubbles on Reels reveal how social signals and ML models can coexist in video recommendations without destroying performance.

Facebook's Friend Bubbles: A Masterclass in Social Graph ML

How Meta blends closeness prediction models, multi-task ranking, and prefetch optimization to surface friend-driven content at scale on Reels

The Eugenic Roots of AI: Why Your Model Keeps Being Racist

Generative AI's bias problem isn't a bug to be fixed. It's baked into the statistical foundations borrowed from Victorian-era race science.

Anthropic vs Pentagon: What the Technical Evidence Actually Shows

Anthropic's court filings reveal technical misunderstandings in the Pentagon's national security case. What this means for AI companies working with government.

Facebook's Friend Bubbles: When Social Graphs Meet Video Recommendations

Meta's approach to blending relationship closeness with content relevance reveals hard truths about building social features at scale.

Patreon's Jack Conte Just Called Out AI's Fair Use Hypocrisy

Why Patreon's CEO thinks AI companies' fair use argument crumbles when you look at their Disney and Warner Music deals

Google's Flash Flood AI: Training on News Reports to Predict Urban Disasters

Google Research uses Gemini to extract flood data from news articles, creating an AI model that predicts flash floods 24 hours early across the Global South

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