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Top 10 Trends for Data in 2024

Tom Tunguz

LLMs Transform the Stack : Large language models transform data in many ways. If you’re curious about the evolution of the LLM stack or the requirements to build a product with LLMs, please see Theory’s series on the topic here called From Model to Machine.

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How Generative AI Will Turn Traditional SaaS Models On Their Head with AWS VP of Generative Builders Adam Seligman

SaaStr

Within the next 12 months, Adam Seligman, VP of Generative Builders at AWS, believes there will be an inversion of SaaS. Adam came up with the wildest idea he could think of for an app and used Anthropc, a large language model company, to help develop the idea. Foundation models will do that. What does that mean?

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The Battle for AI Gravity

Tom Tunguz

Then we began to add routers, mixtures of experts, & small language models. Now we’re realizing the LLM architecture isn’t the best at planning work : reinforcement learning is better & must be integrated. AWS & others have stopped charging to move data. Both have decreased switching costs.

AI 307
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How Shopify Implements AI Across Sales and Product with Mike Tamir, Head of AI at Shopify, and Rudina Seseri, Managing Partner at Glasswing Ventures

SaaStr

Culture Structure You want a culture of checking results and having metrics to evaluate those results from the LLM or a more traditional model. Historically, Cloud platforms like AWS and Azure help with the sporadic needs of renting a GPU for a few hours for training vs. long-term use, which would cost thousands of dollars.

AI Search 287
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Payment and Checkout Scalability for D2C Gaming Partners

FastSpring

FastSpring continuously monitors transaction flow via machine learning models that are under the oversight of an enterprise-grade team of infrastructure and payments experts. Moreover, we have an enterprise-grade engineering team that has built and maintains a scalable and resilient cloud-native stack using AWS.

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Cloud Data Lakes - The Future of Large Scale Data Analysis

Tom Tunguz

This modern architecture for data analysis, operational metrics, and machine learning enables companies to process data in new ways. Various roles in your organization, like data scientists, data engineers, application developers, and business analysts, can access data with their choice of analytic tools and frameworks.

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From $1M to $3B ARR: Databricks CRO Ron Gabrisko on Scaling a Revenue Rocket Ship

SaaStr

For context,Ron has an MBA and a master’s in engineering from Stanford. Pricing: Keep It Simple (At First) Databricks started with a simple, consumption-based pricing model. Because thats how their customerswho were used to AWS, Azure, and GCP pricingexpected to buy. You gotta know the product cold.)

Scale 176