Embedded AI: The Questions Every CEO is Asking
As AI continues to revolutionize industries, CEOs are discussing how to integrate this new superpower.
On the a16z Podcast, we talk with Hex, Sourcegraph, and Cresta - three companies at the forefront of integrating AI into their existing products. From navigating data privacy concerns to optimizing accuracy and managing costs, these companies are navigating the complexities of this new superpower.
Topics Covered:
00:00 - Introduction
01:29 - How AI can enhance customer service
07:50 - Using AI to shape data and analytics
08:56 - Solving the challenges on contextual understanding
11:27 - Giving AI the right information and context
13:31 - Tools that help build language Models (LLMs)
16:25 - Constructing prompts
19:08 - How do you differentiate?
21:09 - The value of proprietary datasets
22:22 - Customization as a moat
23:44 - Increasing compilation rates
26:49 - Where is the moat?
29:49 - Privacy challenges
34:01- Cost and pricing of models
39:35 - What does the contact center look like in 2028?
Resources:
* Find Zayd Enam on Twitter: https://twitter.com/zaydenam
* Find Barry McCardel on Twitter https://twitter.com/barrald
* Find Beyang Liu on Twitter: https://twitter.com/beyang
* Learn more about Cresta: https://cresta.com
* Learn more about Hex: https://hex.tech
* Learn more about Sourcegraph: https://sourcegraph.com/
Stay Updated:
Find a16z on Twitter: https://twitter.com/a16z
Find a16z on LinkedIn: https://www.linkedin.com/company/a16z
Subscribe on your favorite podcast app: https://a16z.simplecast.com/
Follow our host: https://twitter.com/stephsmithio
Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. For more details please see a16z.com/disclosures.
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Chapters (14)
Introduction
1:29
How AI can enhance customer service
7:50
Using AI to shape data and analytics
8:56
Solving the challenges on contextual understanding
11:27
Giving AI the right information and context
13:31
Tools that help build language Models (LLMs)
16:25
Constructing prompts
19:08
How do you differentiate?
21:09
The value of proprietary datasets
22:22
Customization as a moat
23:44
Increasing compilation rates
26:49
Where is the moat?
29:49
Privacy challenges
39:35
What does the contact center look like in 2028?
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