Censius

AI Observability for Enterprises - Helping ML & DS teams to continuously monitor, explain, and improve machine learning models (including Large Language Models)

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The soaring costs of fine-tuning LLMs: As models grow bigger, fine-tuning gets costlier. How does this impact innovation and accessibility for AI teams?

Join us at the AI Townhall and learn strategies to keep model performance in check.

Save your spot: https://t.co/E4nZFeGnHH

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We are stoked to be a part of the Data Science Festival, Oktoberfest 2023!🚀

Join us for a talk with our Co-founder, Devanshi Vyas, where she shares tactics for risk minimization of LLMs in production. Save your spot by entering the ticket ballot at:👉https://t.co/2qnLsqQxjK

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⏳The countdown is on. 'The AI Townhall' Webinar goes LIVE in 1 hour!🚀

Join us for an insightful conversation with AI experts on Generative AI risks, and strategies to fine-tune LLMs in a dynamic data-led world.

👉Save your spot now: https://t.co/QUMwSBP6KP

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Data Council Talks 2023 Austin is officially a wrap!✨

Big thanks to the @DataCouncilAI team for putting together an amazing networking event!

Here's a quick recap of our favorite moments featuring our Founder, @ayushpatelxyz 👉

#datacouncil23 #mlops #event

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It's officially ONE WEEK until we go LIVE at @DataCouncilAI Talks 2023!

Will we see you in person at Austin?

👥 3-days
✨ 75+ speakers
🌎 800 attendees

When: March 28th - 30th, 2023
Time: 8 am - 5 pm (each day)

Don't miss out! Save your spot 👉 https://t.co/x8YquqONM2

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Click the link to read our blog and take the first step towards simplifying your feature management workflow and improving the accuracy of your machine learning models.

👉 https://t.co/OblEreO1o0

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As the number of features increases in an ML Model, managing them becomes a daunting task. That's where Feature Stores come in! ⚙️

Censius's latest blog delves into the technical details of three popular feature stores - Feast, Tecton, and Hopsworks. 👇

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Last week, @ayushpatelxyz gave a talk on 'The Subtle Art of Fixing Silently Failing ML Models' at @datasciencefest, where he discussed strategies to diagnose & fix the root causes of ML model failures.

Watch the on-demand session now. 👇
https://t.co/WfTtMdnVCX

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Join a session to discuss the US AI Bill of Rights and find out how to overcome unwanted inequities and harmful biases to achieve Responsible AI. 📢

Date: March 28-30, 2023
Location: Austin, TX
Speaker: @ayushpatelxyz

Grab your tickets here! 👉 https://t.co/x8YquqPlBA

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Are you playing catch-up with the latest AI laws and regulations? 🤔

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How can you achieve responsible AI?

1️⃣ Perform risk assessment and review AI systems for potential biases and inaccuracies.

2️⃣ Leverage Monitoring, Explainability & Fairness tools to ensure algorithmic discrimination-free systems.

3️⃣ Implement robust security measures.

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To explore this topic further, visit this link 👉

https://t.co/SAmR763ogc

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Capital One and Harvard Business Review Analytic Services collaboratively researched the vast and complex landscape of how organizations effectively use ML at scale.

The key highlights of this research are...👇🧵

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3️⃣ ML is not simply a process of data scientists writing deeply technical code. Scaling ML is a highly systematic process based on standards, frameworks, and organizational collaboration.