Wallaroo.AI

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Wallaroo.AI

Wallaroo.AI

@Wallarooai

Easy Production AI at Scale: Any Model, Any Hardware, Anywhere.

Brooklyn, NY Katılım Aralık 2015
111 Takip Edilen752 Takipçiler
Wallaroo.AI
Wallaroo.AI@Wallarooai·
Statistics reveal that a whopping 90% of AI projects fall short of their ROI targets, with over half never even making it to production. But why is this the case & more importantly, what can be done to reverse this trend? Learn more: buff.ly/3Tpwt3x #AI #AImodels #ROI
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Wallaroo.AI@Wallarooai·
Calling all @ShopTalk attendees! Join us at Booth #154 for an exclusive meet & greet on Monday, 3/18 @ 5 PM. Don't miss the chance to connect with the @WallarooAI team & discover how we're simplifying the deployment, monitoring, & scaling of Production AI/ML. #ShopTalk2024
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Wallaroo.AI@Wallarooai·
In this short video, we show how to quickly test the performance of a new model against one in production using the Shadow Deploy method & then easily Hot Swap the better performing model into production! Watch here: buff.ly/49JSjWj #ShadowDeploy #ModelHotSwap
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Wallaroo.AI
Wallaroo.AI@Wallarooai·
If you missed our MS Reactor livestream on 'Getting Your AI Models To The Production Start Line' you can catch up with the video below 👇 Watch here: buff.ly/49IN619 Thanks again to Aishwarya Srinivasan and Ankush Garg for a great tech talk! #ai #mlops #azureml
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Wallaroo.AI@Wallarooai·
Are you looking for a comprehensive & flexible solution to deploy, serve, observe, & optimize your computer vision models? Try @WallarooAI, the ultimate platform for computer vision AI at scale. Request a consultation: buff.ly/49B5M2y #ComputerVision #AI
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Wallaroo.AI@Wallarooai·
There's still time to register for our Microsoft Reactor Livestream event tomorrow 2/28 @ 1pm ET! We will have 2 speakers Aishwarya Srinivasan & Ankush Garg covering how to easily & quickly Get Your AI Models To The Production Start Line. Register here: buff.ly/3wA2z4T
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Wallaroo.AI@Wallarooai·
In this video we show an end to end production model lifecycle using a house price regression model. The #ModelLifecycle will go through deploy, serve, screening for anomalies & data drift, comparing champion & challenger models. Watch here: buff.ly/3wlJCmc
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