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Here’s everything you need to know 👇 I developed a machine learning model with @Eight Sleep and we just released it today 1️⃣ What data was it built on? This model was built on the largest raw biosignal dataset ever used to train an AI, from any device, including every wearable on the market. 2.04 million hours 136,575 participants 498k sessions 122 million segments 2️⃣ What can it predict? It can predict your biological age (the age your body acts like) within 3.3 years. It also predicts heart
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Here’s everything you need to know 👇 I developed a machine learning model with @Eight Sleep and we just released it today 1️⃣ What data was it built on? This model was built on the largest raw biosignal dataset ever used to train an AI, from any device, including every wearable on the market. 2.04 million hours 136,575 participants 498k sessions 122 million segments 2️⃣ What can it predict? It can predict your biological age (the age your body acts like) within 3.3 years. It also predicts heart
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Cloudflare's Monetization Gateway went live July 1, 2026. Snowflake, Datamatics, and Monte Carlo are all calling 2026 the year clean data becomes the actual bottleneck for AI agents, not the models themselves. Poor data quality is already costing companies 15 to 25% of annual revenue. That part isn't one guy's theory. That's the consensus. The
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Cloudflare's Monetization Gateway went live July 1, 2026. Snowflake, Datamatics, and Monte Carlo are all calling 2026 the year clean data becomes the actual bottleneck for AI agents, not the models themselves. Poor data quality is already costing companies 15 to 25% of annual revenue. That part isn't one guy's theory. That's the consensus. The
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Someone asked me if AI is killing data science. The answer depends on where you sit. Senior data scientists are still in high demand. It’s junior hiring where things get tricky. A lot of the work junior data scientists used to cut their teeth on, like dashboards, SQL queries, and simple ML models, is exactly what AI handles well. Give it clear instructions and it rarely makes syntax mistakes. Where AI still falls short is the open ended, vague business questions. It doesn’t understand the busine
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🔥 Hoy toca armar polémica en Data. Pusimos frente a frente algunas de las herramientas más usadas del mundo tech y solo una regla: elegir una en cada duelo. 👀 Power BI vs Looker Studio Python vs R SQL Server vs Oracle Excel vs Google Sheets Después de varias eliminaciones, la final quedó así: 🐍 Python vs SQL Server 🗄️ No hacen lo mismo, pero si solo pudieras quedarte con una para tu stack… ¿cuál sobrevive? Te leo 👇 #Data #Python #SQLServer #PowerBI #SmartData #Tecnología #IA #IngenieriaDeDa
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