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Shaped now integrates with Hugging Face! 🎉 Use state-of-the-art NLP & CV models to encode text/images into embeddings for semantic search & ranking. More info here 👇 docs.shaped.ai/docs/model_cre…

Imagine a compass that misguides you—Netflix and Cornell researchers found cosine similarity, a key metric in ML, can yield arbitrary results due to embedding rescaling. Full article here: shaped.ai/blog/cosine-si… Nathan Kallus

What if AI not only matched jobs but explained decisions to all? Transparent, fair, and collaborative systems like OKRA redefine recruitment. Our latest article unpacks "Explainable Multi-Stakeholder Job Recommender Systems" by Roan Schellingerhout. shaped.ai/blog/decoding-…

Are traditional recommender systems outdated? EmbSum leverages LLM-driven summarization to precompute rich user & content embeddings, outperforming UNBERT & MINER with fewer parameters. Handles 7,400+ tokens for deep personalization. 🤔👇 🔗 shaped.ai/blog/embsum-ll…

Can data splitting impact recommender performance? This study shows that different splitting strategies can drastically alter model rankings, challenging claims of state-of-the-art performance. Learn more: shaped.ai/blog/data-spli…

Still using notebooks & spreadsheets for analytics? A fragmented stack slows ML teams down. Shaped Analytics unifies data, experiments & business impact—so you can iterate faster & optimize with confidence. Learn more: shaped.ai/analytics

MaskNet, introduced in 2021, boosts CTR prediction by using instance-guided multiplicative interactions. Its MaskBlock architecture still outperforms DeepFM and xDeepFM, improving AUC by up to 5.23%. Full article: shaped.ai/blog/masknet-c…

In our latest write up Bailu Ding & Jiaqi Zhai introduce MoL, a retrieval model that learns similarity functions beyond dot products. It combines multiple embeddings for better accuracy in recommendations and QA while staying efficient. shaped.ai/blog/beyond-do…

🚀 Introducing Shaped Value Modeling – full control over ranking optimization. Blend engagement, revenue, retention & more with a dynamic, interpretable framework. More here: shaped.ai/value-modelling

Meta's Jagged Flash Attention improves recommendation systems with up to 9x speedup and 22x memory reduction, outperforming dense flash attention by 3x and 53% in efficiency. Full write up here: shaped.ai/blog/jagged-fl…

Still using Algolia for search and recommendations? You're paying the price in relevance and flexibility. Shaped is AI-native, unified, and built for real-time personalization. We did a full breakdown—here’s why it matters: shaped.ai/blog/evaluatin…

Everyone wants a killer “For You” feed. But building one? It’s ML, data engineering, infra, A/B testing hell. We break down what it really takes — and how platforms like Shaped make it 10x easier. 👇 shaped.ai/blog/how-to-bu…

Static recs miss what users want now. Sequential models fix that — modeling when users act, not just what they like. From N-Grams → Transformers → Generative Recs, here’s how modern systems capture real-time intent 👇 shaped.ai/blog/beyond-st…

Criteo is still the benchmark for real-world ads + recsys: 📊 Sparse + dense features 🧠 Billions of rows ⚙️ Infra stress test Why it still matters in 2025 👇 shaped.ai/blog/criteo-da…

Two-Tower models are the backbone of real-time recommendations at scale. 🎯 Separate user/item towers ⚡ Fast ANN search for retrieval 🏗️ Key to multi-stage recsys pipelines Why they work—and where they fall short 👇 📖 shaped.ai/blog/the-two-t…

The Shaped team had a blast at Netflix's RecSys Workshop 🎬 Top takeaways: 🧱 FMs are becoming infra ⚙️ Fewer models, more multitask 🧩 Domain grounding > raw LLMs 🔄 Meta-optimization is here ⚡ Efficiency still matters Full recap 👇 shaped.ai/blog/key-insig…

Snowplow captures rich, event-level user data. Shaped turns it into real-time personalization. 🚀 Session-aware feeds 🔍 Behaviorally boosted search 🤖 No custom ML infra Here’s how to connect them via Kinesis 👇 shaped.ai/blog/unlock-gr…

Building “People to Follow” shouldn’t take a whole ML team. Shaped’s similar_users API lets you power smart user-to-user recs in one call 🤝 📌 No complex infra 🧠 Learns from behavior + profiles ⚡ Real-time, relevant, ready to ship Full post 👇 shaped.ai/blog/connect-y…

Can LLMs choose their own collaborative examples? AdaptRec says yes - letting the model iteratively refine which user histories to learn from. 🧠 LLM-in-the-loop 📈 +18% HR@1 gains Full breakdown 👉 shaped.ai/blog/bringing-…