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AI Canon

Andreessen Horowitz

It’s difficult for AI experts to keep up with everything new being published, and even harder for beginners to know where to start. So, in this post, we’re … The post AI Canon appeared first on Andreessen Horowitz. Source: Midjourney Research in artificial intelligence is increasing at an exponential rate.

AI 145
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Usage as the Moat in AI

Tom Tunguz

As generative AI captivates Startupland, startups will do what they have always done: integrate new technology to build transformative businesses. Incumbents have seized the moment with Microsoft, Adobe, & others integrating generative AI into their products quickest. What are these moats? More users means a better product.

AI 279
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Microsoft's Billion Dollar AI Business

Tom Tunguz

But the story in this quarter’s reports is AI. Another example of AI favoring incumbents : Epic, a large health records company worth about $10-12b with about 30% market share in the US, has implemented some OpenAI features. The total customer count for Azure’s OpenAI has grown dramatically.

AI 183
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Why Every Startup Needs an AI Strategy

Tom Tunguz

Every company will be an AI company. Every startup needs an AI strategy - not just for fundraising or press appeal. User expectations have changed. When one email composer window autocompletes sentences, every email product will need to follow. These new user interfaces will change software.

AI 204
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Humility in AI: Building Trustworthy and Ethical AI Systems

AI is becoming ubiquitous. The number of critical touch points is growing exponentially with the adoption of AI. But with the incredible pace of the modern world, AI systems continually face new data patterns, which make it challenging to return reliable predictions. Brought to you by Data Robot.

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Seeking a Distribution Advantage with AI

Tom Tunguz

What is the distribution advantage AI confers to startups? AI enables ABM-at-scale. The first time a user visits a site AI asks “What do you want to accomplish today?” The teams who unlock novel distribution advantages first will have a tremendous competitive advantage in the AI wave.

AI 152
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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 has no plan/interest to staff a team to manage AI infrastructure or develop deep machine learning experience / expertise in-house. The pace of innovation in the field clouds the answer.

AI 161
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AI in Manufacturing

In our AI in Manufacturing eBook, you can learn how to solve your most urgent manufacturing and business needs with an enterprise AI platform. Get this eBook to learn about: Achieving ROI with AI and delivering valuable results with urgency. How AI modernizes demand forecasting, supply chain, and predictive maintenance.

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Democratizing AI for All: Transforming Your Operating Model to Support AI Adoption

Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. But in order to reap the rewards that AI offers, it is essential that businesses first address how their organizations are set up, from their people to their processes. Building trust in AI.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data. Are you ready to deliver fair, unbiased, and trustworthy AI?

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How to Choose an AI Vendor

You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. But rapid change, vendor churn, hype and jargon make it increasingly difficult to choose an AI vendor. The five key things to consider when looking for an AI vendor.

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Build Trustworthy AI With MLOps

For businesses that are AI-driven, this trust hinges on the confidence that their AI solution can help them make their most critical decisions. 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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10 Keys to AI Success in 2021

Capitalizing on the incredible potential of AI means having a coherent AI strategy that you can operationalize within your existing processes. Download this eBook to learn about: Achieving ROI with AI and delivering valuable results with urgency. AI storytelling in communicating value to your organization.

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology. Download the report to gain insights including: How to watch for bias in AI.

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The Forrester Wave™: AI/ML Platforms: Vendor Strategy, Market Presence, and Capabilities Overview

As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams. The Forrester Wave™ evaluates Leaders, Strong Performers, Contenders, and Challengers.