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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. Even fully staffed, teams required years to develop models with reasonably accurate performance. Today, it’s a matter of days or weeks.

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Context.ai - Unlocking Insight into LLM-Based Applications

Tom Tunguz

Large-language models have transformed how millions interact with products : from customer support to code generation to legal document analysis. These new engagement models invite users through a meaningfully different product journey. How should a product manager gauge the customer experience?

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Building Resolution Bot: How to apply machine learning in product development

Intercom, Inc.

We are at the start of a revolution in customer communication, powered by machine learning and artificial intelligence. Our Custom Bots and Resolution Bot already work for thousands of businesses every day. These bots help businesses deliver both radical efficiencies and better, faster support experiences.

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Generative AI – The End of Empty Textboxes

TechEmpower SaaS

On a different project, we’d just used a Large Language Model (LLM) - in this case OpenAI’s GPT - to provide users with pre-filled text boxes, with content based on choices they’d previously made. This gives Mark more control over the process, without requiring him to write much, and gives the LLM more to work with.

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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?” Today, we have an interesting topic to discuss.

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5 Things That Are Actually Working and 5 Things That Aren’t in B2B SaaS AI with Ironclad’s CEO and a16z

SaaStr

Ironclad CEO and co-founder Jason Boehmig joined Seema Amble, Partner at Andreessen Horowitz at SaaStr Annual to share their observations on what’s currently working and what’s not quite there yet for Artificial Intelligence (AI) in SaaS. What’s Currently Working in AI for SaaS 1.

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How Much of Customer Support Will AI Replace? Gartner Says 80%

SaaStr

And in many cases, also seen the number of human customer success reps already reduced by -20% to -30%. Can AI replace almost everything a human does today in customer support? I don’t know but perhaps what’s just as important is what customers are expecting, thinking, and buying based on. But 80% by 2029?