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5 Interesting Learnings from Palantir at $2.7 Billion in ARR

SaaStr

Artificial Intelligence Platform (AIP) is a Year Old But Fueling $159m in Q2 Bookings Alone To some Cloud and SaaS leaders, AI is a table-stakes addition. This potential for a decade of growth at scale here helps justify the high revenue multiple Palantir trades at. #4. Pretty impressive. #2. Grow AND be more efficient?

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Building Resolution Bot: How to apply machine learning in product development

Intercom, Inc.

We are at the start of a revolution in customer communication, powered by machine learning and artificial intelligence. So, modern machine learning opens up vast possibilities – but how do you harness this technology to make an actual customer-facing product? The cupcake approach to building bots.

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How to Successfully Bring AI Products to Market at Scale with GitHub’s CRO

SaaStr

At this year’s SaaStr AI Summit, GitHub CRO Elizabeth Pemmerl shared how to bring AI products to market at scale successfully. With 90% of the Fortune 100 on GitHub and 40% of its $2B revenue coming from AI products, these real-world examples will also help you launch an AI-powered product at scale. The next horizon is scaling.

Scale 264
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The new dawn of Machine Learning

Intercom, Inc.

GPT-3 can create human-like text on demand, and DALL-E, a machine learning model that generates images from text prompts, has exploded in popularity on social media, answering the world’s most pressing questions such as, “what would Darth Vader look like ice fishing?” Today, we have an interesting topic to discuss.

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How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale.

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Cutting Through the Noise of Gen AI with CEOs of Writer, Orby and Limitless + NEA

SaaStr

May Habib from Writer heads a full-stack generative AI company that combines large language models with microservices to build custom AI applications, agents, and workflows for enterprise clients. Writer is at the forefront of creating flexible, tailored AI solutions that integrate seamlessly into existing business processes.

AI Search 244
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How AI Infrastructure Will Power the Future with Oracle and Bain Capital Ventures

SaaStr

Today, it’s all about having enough raw physical power to power artificial intelligence. So you can do the math on how serious that is that we’ll be scaling up now to gigawatt data centers. Previously, we had enough data centers to power a lot of CPU computing needs. Head of the Global VC Practice at Oracle, J.D.

AI 264
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Build Trustworthy AI With MLOps

In our eBook, Building Trustworthy AI with MLOps, we look at how machine learning operations (MLOps) helps companies deliver machine learning applications in production at scale.

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Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

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MLOps 101: The Foundation for Your AI Strategy

Many organizations are dipping their toes into machine learning and artificial intelligence (AI). And for those who are already underway, scaling their results across their organizations is completely uncharted waters. Download this comprehensive guide to learn: What is MLOps?

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Building User-Centric and Responsible Generative AI Products

Speaker: Shyvee Shi - Product Lead and Learning Instructor at LinkedIn

In the rapidly evolving landscape of artificial intelligence, Generative AI products stand at the cutting edge. This presentation unveils a comprehensive 7-step framework designed to navigate the complexities of developing, launching, and scaling Generative AI products.