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Arize AI

@arizeai

10 hours

Our AI agents bootcamp starts tomorrow! 🚀 Learn how to build sophisticated agents that can tackle real-world challenges in just six short sessions. On day 1, @JohnGilhuly and Dat Ngo will cover core concepts like components, execution branches, and routers. They'll also touch

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Arize AI

@arizeai

3 days

NYC: Build better AI with us on Sept 26. 🗽 Connect with AI practitioners, gain insights from teams that have successfully deployed LLMs, and stay at the forefront of LLM tooling. We teamed up with @pinecone and @guardrails_ai for an evening of insights, networking, and spicy

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Arize AI Retweeted

John Gilhuly

@JohnGilhuly

4 days

Excited to have contributed to this deep dive on creating and validating synthetic datasets for LLM evaluation. Synthetic data helps us test models, simulate app behavior, and create golden datasets for experimentation. Dive in if you're working with LLMs!

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Arize AI Retweeted

Towards Data Science

@TDataScience

6 days

If you've been hearing a lot of buzz around AI agents but are not sure what tools are available and which ones you should use, @aparnadhinak shares helpful insights based as a leader whose company recently implemented a complex agent-based system.

Navigating the New Types of LLM Agents and Architectures

The failure of ReAct agents gives way to a new generation of agents — and possibilities

towardsdatascience.com

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Arize AI Retweeted

Aparna Dhinakaran

@aparnadhinak

7 days

What does an AI agent look like today? 🤖 My newest post on @TDataScience dives into different modern agent architectures, the current benefits and problems each brings, and my own recommendations on addressing these issues. Agents have come a long way in the past year, from

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Arize AI

@arizeai

13 days

While static guards are great at filtering out predefined content like NSFW language, they can struggle when faced with sophisticated attacks. Here's how to implement 🏎️ dynamic guards 🏎️:

Advanced Guards: Moving To Dynamic Guardrails for LLM Applications

How to leverage dynamic LLM guardrails leveraging few-shot prompting and embedding-based guards that are adaptive with emerging threats

arize.com

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Arize AI Retweeted

arize-phoenix

@ArizePhoenix

15 days

🤖🤝 Imagine if you had a team of top-performers, each with their own specialty, that could work collaboratively to solve big problems, 24/7. @crewAIInc gives you just that. And now you can trace your CrewAI applications with Phoenix! Check out this walkthrough to see how you

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Arize AI

@arizeai

16 days

Very demure. AI developers don't need your code bloating their apps - we are always *mindful* with how we engineer our tools.

arize-phoenix

@ArizePhoenix

17 days

See how we can trace an AI application in 3 lines… very demure, very mindful 😌✨💅 Like what you see? Give us a star on Github ⭐

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Arize AI

@arizeai

18 days

Next week we’re talking to Kyle O'Brien, Applied Scientist at @Microsoft about his paper: Composable Interventions for Language Models. Join us live: This paper has important implications for how we can keep expensively trained models up-to-date over

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