Practical AI

Practical AI

Practical AI LLC

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Episode (200)

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131
AI trends: a Latent Space crossover

AI trends: a Latent Space crossover

Jun 14, 2023

Daniel had the chance to sit down with @swyx and Alessio from the Latent Space pod in SF to talk about current AI trends and to highlight some key learnings from past episodes. The discussion covers o...

132
Accidentally building SOTA AI

Accidentally building SOTA AI

Jun 06, 2023

Lately.AI has been working for years on content generation systems that capture your unique “voice” and are tailored to your unique audience. At first, they didn’t know that they were going to build a...

133
Controlled and compliant AI applications

Controlled and compliant AI applications

May 31, 2023

You can’t build robust systems with inconsistent, unstructured text output from LLMs. Moreover, LLM integrations scare corporate lawyers, finance departments, and security professionals due to halluci...

134
Data augmentation with LlamaIndex

Data augmentation with LlamaIndex

May 23, 2023

Large Language Models (LLMs) continue to amaze us with their capabilities. However, the utilization of LLMs in production AI applications requires the integration of private data. Join us as we have a...

135
Creating instruction tuned models

Creating instruction tuned models

May 16, 2023

At the recent ODSC East conference, Daniel got a chance to sit down with Erin Mikail Staples to discuss the process of gathering human feedback and creating an instruction tuned Large Language Models ...

136
The last mile of AI app development

The last mile of AI app development

May 11, 2023

There are a ton of problems around building LLM apps in production and the last mile of that problem. Travis Fischer, builder of open AI projects like @ChatGPTBot, joins us to talk through these probl...

137
Large models on CPUs

Large models on CPUs

May 02, 2023

Model sizes are crazy these days with billions and billions of parameters. As Mark Kurtz explains in this episode, this makes inference slow and expensive despite the fact that up to 90%+ of the param...

138
Causal inference

Causal inference

Apr 25, 2023

With all the LLM hype, it’s worth remembering that enterprise stakeholders want answers to “why” questions. Enter causal inference. Paul Hünermund has been doing research and writing on this topic for...

139
Capabilities of LLMs 🤯

Capabilities of LLMs 🤯

Apr 19, 2023

Large Language Model (LLM) capabilities have reached new heights and are nothing short of mind-blowing! However, with so many advancements happening at once, it can be overwhelming to keep up with all...

140
Computer scientists as rogue art historians

Computer scientists as rogue art historians

Apr 12, 2023

What can art historians and computer scientists learn from one another? Actually, a lot! Amanda Wasielewski joins us to talk about how she discovered that computer scientists working on computer visio...

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