article thumbnail

The AI API : The Twilio Moment for Machine Learning

Tom Tunguz

Training, deploying, & optimizing machine learning models has historically required teams of dedicated researchers, production engineers, data collection & labeling teams. AI deployment is sufficiently straightforward that a majority of teams won’t hire new experts to build them & will staff 1-2 people to launch them.

article thumbnail

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?” It’s all about artificial intelligence and machine learning.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Machine learning isn?t as hard as it looks

Intercom, Inc.

It’s easy to believe that machine learning is hard. After all, you’re teaching machines that work in ones and zeros to reach their own conclusions about the world. Indeed, the majority of literature on machine learning is riddled with complex notation, formulae and superfluous language. Wikipedia (e.g.

article thumbnail

Usage as the Moat in AI

Tom Tunguz

Models require millions of dollars & technical expertise to deploy: document chunking, vectorization, prompt-tuning or plugins for better accuracy & breadth. Machine learning systems, like any complex program, benefit from more use. At the moment, capital & technical expertise create competitive advantage.

article thumbnail

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.

article thumbnail

OneStream: Benchmarking the S1 Data

Clouded Judgement

A S-1 is a document companies file with the SEC in preparation for listing their shares on an exchange like the NYSE or NASDAQ. The document contains a plethora of information on the company including a general overview, up to date financials, risk factors to the business, cap table highlights and much more.

article thumbnail

Data Product Teams : Best Practices for a Modern Data Team

Tom Tunguz

DPRDs, or Data Product Requirements Documents, contain the key information about a data product: what it will provide, how it will produce value, how the data will be governed including data quality alerting. Unlike code, data is stochastic or unpredictable.

Data 266