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Mastering Growth in the AI Era: How to Stand Out, Acquire Customers, and Raise VC Dollars with B Capital, Zetta, and Glasswing

SaaStr

Large enterprises have an immediate need for governance solutions to handle AI at scale. This represents an under-recognized opportunity for B2B AI startups focusing on compliance, risk management, and administrative controls.

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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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Meet the Rockstars of Risk: Essential insights for software companies navigating payments, compliance, and security

Payrix

At Payrix from Worldpay, we have an internal team of risk management experts dedicated to helping software companies, like yours, manage payment processing, fraud prevention, and compliance. Mike’s key takeaway: Data modeling has become a cornerstone of effective risk management. Explore risk and compliance advice for platforms.

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Clouded Judgement 1.24.25 - The Year of Enterprise AI

Clouded Judgement

In AI terminology, “generalizing” refers to a model’s ability to apply learned knowledge to new tasks or unseen data. However the pace of innovation in large language models is extraordinary. Early research, including projects like R1 from DeepSeek, has shown promising results in this area.

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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. AI operations, including compliance, security, and governance. AI ethics, including privacy, bias and fairness, and explainability.

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Which AI Model Should You Pick for Your Startup?

Tom Tunguz

A product manager today faces a key architectural question with AI : to use a small language model or a large language model? the company would prefer to rely on external experts to drive innovation within the models. the company would prefer to rely on external experts to drive innovation within the models.

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How Enterprise Companies are Buying AI (or Not) with ContextualAI, Anthropic, Glean, and Unusual Ventures

SaaStr

Benjamin Mann, co-founder of Anthropic added: “ For example, one large bank that we were talking to came to us and said, ‘we’ve talked to everybody in our company, and we have 500 different use cases that we want to apply large language models to.’ Compliance matters. Security matters.

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