Announcing the release of Spice.ai v0.6.1-alpha
Thursday, April 21, 2022 in Blog
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Announcing the release of Spice.ai v0.6.1-alpha! 🌶 Building upon the Apache Arrow support in v0.6-alpha, Spice.ai now includes new Apache Arrow data processor and Apache Arrow Flight data connector components! Together, these create a …
Announcing the release of Spice.ai v0.6-alpha
Tuesday, February 08, 2022 in Blog
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Announcing the release of Spice.ai v0.6-alpha! 🏹 Spice.ai now scales to datasets 10-100 larger enabling new classes of uses cases and applications! 🚀 We’ve completely rebuilt Spice.ai’s data processing and transport upon Apache Arrow, a …
Adding Soft Actor-Critic
Wednesday, January 12, 2022 in Blog
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Last month in the v0.5-alpha version, a new learning algorithm was added to Spice.ai: Soft Actor-Critic. This is a very popular algorithm in the Reinforcement Learning field. Let’s see what it is and why this is an interesting addition. The …
What Data Informs AI-driven Decision Making?
Tuesday, January 04, 2022 in Blog
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AI unlocks a new generation of intelligent applications that learn and adapt from data. These applications use machine learning (ML) to out-perform traditionally developed software. However, the data engineering required to leverage ML is a …
A New Class of Applications That Learn and Adapt
Thursday, December 30, 2021 in Blog
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A new class of applications that learn and adapt is becoming possible through machine learning (ML). These applications learn from data and make decisions to achieve the application’s goals. In the post Making apps that learn and adapt, Luke …
Announcing the release of Spice.ai v0.5.1-alpha
Tuesday, December 28, 2021 in Blog
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Announcing the release of Spice.ai v0.5.1-alpha! 📈 This minor release builds upon v0.5-alpha adding the ability to start training from the dashboard plus support for monitoring training runs with TensorBoard. Highlights in v0.5.1-alpha Start training …
Understanding Q-learning: How a Reward Is All You Need
Wednesday, December 15, 2021 in Blog
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There are two general ways to train an AI to match a given expectation: we can either give it the expected outputs (commonly named labels) for differents inputs; we call this supervised learning. Or we can provide a reward for each output as a score: …
Announcing the release of Spice.ai v0.5-alpha
Monday, December 06, 2021 in Blog
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We are excited to announce the release of Spice.ai v0.5-alpha! 🥇 Highlights include a new learning algorithm called “Soft Actor-Critic” (SAC), fixes to the behavior of spice upgrade, and a more consistent authoring experience for reward …
AI needs AI-ready data
Sunday, December 05, 2021 in Blog
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A significant challenge when developing an app powered by AI is providing the machine learning (ML) engine with data in a format that it can use to learn. To do that, you need to normalize the numerical data, one-hot encode categorical data, and …
Spicepods: From Zero To Hero
Thursday, December 02, 2021 in Blog
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In my previous post, Teaching Apps how to Learn with Spicepods, I introduced Spicepods as packages of configuration that describe an application’s data-driven goals and how it should learn from data. To leverage Spice.ai in your application, …