Custom API examples by Hume - saves months of research

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Custom model API allows for training and using models for various use cases such as tracking depression symptoms from video diaries, customer support analysis, educational applications, and predicting customer satisfaction. It automates the process of training models and provides access to model embeddings, resulting in higher accuracies in predicting outcomes. Additionally, it enables training models on gold standard data, which may be limited, and comparing the performance of different models to achieve high accuracy.

In this episode, Nathan sits down with Alan Cowen, CEO and Chief Scientist at Hume AI, an emotional intelligence startup working on creating emotionally aware AI. If you need an ecommerce platform, check out our sponsor Shopify: https://shopify.com/cognitive for a $1/month trial period.

We're hiring across the board at Turpentine and for Erik's personal team on other projects he's incubating. He's hiring a Chief of Staff, EA, Head of Special Projects, Investment Associate, and more. For a list of JDs, check out: eriktorenberg.com.

SPONSORS:

Shopify is the global commerce platform that helps you sell at every stage of your business. Shopify powers 10% of ALL eCommerce in the US. And Shopify's the global force behind Allbirds, Rothy's, and Brooklinen, and 1,000,000s of other entrepreneurs across 175 countries.From their all-in-one e-commerce platform, to their in-person POS system – wherever and whatever you're selling, Shopify's got you covered. With free Shopify Magic, sell more with less effort by whipping up captivating content that converts – from blog posts to product descriptions using AI. Sign up for $1/month trial period: https://shopify.com/cognitive

Omneky is an omnichannel creative generation platform that lets you launch hundreds of thousands of ad iterations that actually work customized across all platforms, with a click of a button. Omneky combines generative AI and real-time advertising data. Mention "Cog Rev" for 10% off.

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@labenz (Nathan)

@AlanCowen (Alan)

@eriktorenberg (Erik)

@CogRev_Podcast

LINKS:

Hume: https://hume.ai/

TIMESTAMPS:

(00:00) - Episode Preview

(00:04:52) - How do you define happiness? How can AI make people happy?

(00:08:40) - The striking experience of trying the Hume demo

(00:09:16) - Building multimodal models using facial expressions, vocal signals, speech patterns

(00:12:27) - How Hume’s models have an advantage of LLMs when it comes to interpreting emotions

(00:13:23) - Assembling diverse datasets of emotional judgments via surveys

(00:15:27) - Sponsors: Shopify

(00:22:00) - Across populations, what is common or different in people’s judgement of facial expressions

(00:26:00) - Interrater reliability for training data

(00:30:48) - Sponsors: Omneky

(00:33:20) - The unique labelling of “awe” across different cultures

(00:36:23) - Customizing models for cultural emotional expression norms

(00:41:13) - How they determined the set of emotions recognized by the model

(00:42:50) - Schadenfreude as a unique example of semantic space research

(00:49:00) - Custom models

(00:52:42) - Using Hume in B2B contexts

(00:59:49) - The cost comparison of having a human analyze emotions vs AI

This show is produced by Turpentine: a network of podcasts, newsletters, and more, covering technology, business, and culture — all from the perspective of industry insiders and experts. We’re launching new shows every week, and we’re looking for industry-leading sponsors — if you think that might be you and your company, email us at erik@turpentine.co.