83 min listen
Synthetic Data with Alex Watson, Founder of Gretel AI
From"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis
Synthetic Data with Alex Watson, Founder of Gretel AI
From"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis
ratings:
Length:
83 minutes
Released:
Nov 14, 2023
Format:
Podcast episode
Description
In this episode, Nathan interviews Alex Watson, founder and CPO of Gretel AI, about the company's work in synthetic data. They discuss why we need synthetic data, Gretel’s new pre trained tabular LLM that creates synthetic data on a zero shot basis, privacy techniques to prevent LLM memorization, and more. If you need an ecommerce platform, check out our sponsor Shopify: https://shopify.com/cognitive for a $1/month trial period.
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
ORACLE:
With the onset of AI, it’s time to upgrade to the next generation of the cloud: Oracle Cloud Infrastructure. OCI is a single platform for your infrastructure, database, application development, and AI needs. Train ML models on the cloud’s highest performing NVIDIA GPU clusters.
Do more and spend less like Uber, 8x8, and Databricks Mosaic, take a FREE test drive of OCI at oracle.com/cognitive
NETSUITE:
NetSuite has 25 years of providing financial software for all your business needs. More than 36,000 businesses have already upgraded to NetSuite by Oracle, gaining visibility and control over their financials, inventory, HR, eCommerce, and more. If you're looking for an ERP platform ✅ head to NetSuite: http://netsuite.com/cognitive and download your own customized KPI checklist.
OMNEKY:
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.
X/SOCIAL:
@labenz (Nathan)
@AlexWatson405 (Alex)
@Gretel_AI
@CogRev_Podcast
TIMESTAMPS:
(00:00:00) - Intro
(00:03:02) - Origins of the company name Gretel AI and initial vision around enabling data sharing while protecting privacy
(00:05:16) - Alex's background in data privacy and compliance from his previous startup Harvest AI, acquired by AWS
(00:06:37) - Early experimentation with language models in 2020
(00:07:24) - Using synthetic data to create additional examples and improve detection of rare disease
(00:12:50) - Why use synthetic data?
(00:17:02) - Sponsors: Shopify | Omneky
(00:19:00) - Training models to recreate real-world data distributions and using validators to detect unrealistic outputs
(00:21:30) - Generating tabular data row-by-row
(00:24:40) - Pre-training the Gretel tabular LLM on diverse internet data sets
(00:30:40) - Sponsors: Oracle | Netsuite
(00:34:00) - Using an agent planning architecture
(00:37:40) - Having the agent determine when to use code vs the LLM for different parts of the data
(00:39:41) - Example use case of adapting models with synthetic data samples for long-tail cases
(00:43:00) - Using reinforcement learning to intentionally generate more diverse and representative synthetic data
(00:48:20) - The importance of alignment checks and controls while still providing model openness and flexibility
(00:51:16) - The potential of efficient, lightweight models compared to massive LLMs like GPT-4
(00:56:00) - Analogizing model specialization to specialized parts of the brain
(01:06:04) - Using differential privacy techniques to prevent memorization and exposure of private data
(01:14:37) - Adding noise during training to blur memorization
(01:18:42) - Optimism that synthetic data quality issues reflect details not fully understood yet vs inherent problems
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
ORACLE:
With the onset of AI, it’s time to upgrade to the next generation of the cloud: Oracle Cloud Infrastructure. OCI is a single platform for your infrastructure, database, application development, and AI needs. Train ML models on the cloud’s highest performing NVIDIA GPU clusters.
Do more and spend less like Uber, 8x8, and Databricks Mosaic, take a FREE test drive of OCI at oracle.com/cognitive
NETSUITE:
NetSuite has 25 years of providing financial software for all your business needs. More than 36,000 businesses have already upgraded to NetSuite by Oracle, gaining visibility and control over their financials, inventory, HR, eCommerce, and more. If you're looking for an ERP platform ✅ head to NetSuite: http://netsuite.com/cognitive and download your own customized KPI checklist.
OMNEKY:
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.
X/SOCIAL:
@labenz (Nathan)
@AlexWatson405 (Alex)
@Gretel_AI
@CogRev_Podcast
TIMESTAMPS:
(00:00:00) - Intro
(00:03:02) - Origins of the company name Gretel AI and initial vision around enabling data sharing while protecting privacy
(00:05:16) - Alex's background in data privacy and compliance from his previous startup Harvest AI, acquired by AWS
(00:06:37) - Early experimentation with language models in 2020
(00:07:24) - Using synthetic data to create additional examples and improve detection of rare disease
(00:12:50) - Why use synthetic data?
(00:17:02) - Sponsors: Shopify | Omneky
(00:19:00) - Training models to recreate real-world data distributions and using validators to detect unrealistic outputs
(00:21:30) - Generating tabular data row-by-row
(00:24:40) - Pre-training the Gretel tabular LLM on diverse internet data sets
(00:30:40) - Sponsors: Oracle | Netsuite
(00:34:00) - Using an agent planning architecture
(00:37:40) - Having the agent determine when to use code vs the LLM for different parts of the data
(00:39:41) - Example use case of adapting models with synthetic data samples for long-tail cases
(00:43:00) - Using reinforcement learning to intentionally generate more diverse and representative synthetic data
(00:48:20) - The importance of alignment checks and controls while still providing model openness and flexibility
(00:51:16) - The potential of efficient, lightweight models compared to massive LLMs like GPT-4
(00:56:00) - Analogizing model specialization to specialized parts of the brain
(01:06:04) - Using differential privacy techniques to prevent memorization and exposure of private data
(01:14:37) - Adding noise during training to blur memorization
(01:18:42) - Optimism that synthetic data quality issues reflect details not fully understood yet vs inherent problems
Released:
Nov 14, 2023
Format:
Podcast episode
Titles in the series (100)
E6: The Computer Vision Revolution with Junnan Li and Dongxu Li of BLIP and BLIP2: As recently as January 2021, the challenge of "interpreting what is going on in a photograph" was considered "nowhere near solved." Today's guests Junnan Li and Dongxu Li changed that with their publication and open-sourcing of BLIP, which delivered state-of-the-art performance on image captioning and other vision-language tasks. BLIP became the #18 most-cited AI paper of 2022, and now Junnan and Dongxu are back with BLIP-2, this time showing how small models can harness the power of existing foundation models to do multi-modal tasks. We talked to Junnan and Dongxu about their research and how they see the trend toward connector models shaping the future. We talked to Junnan and Dongxu about their research and how they see the trend toward connector models shaping the future. by "The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis