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Join Malcolm Gladwell, author and host of Revisionist History, for Smart Talks with IBM as he speaks with visionaries who are creatively applying technology in business to drive change and transform their industries. This season, Smart Talks with IBM is hitting the road. We’re stepping outside the studio to explore how IBM clients are using artificial intelligence to transform the way they do business. It’s a fresh look behind the curtain of technology, where big ideas meet cutting-edge solu ...
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Uber is paying its drivers as little as $1 to train LLMs. 😯
Smart business move or eery sign of what's to come?
On this Hot Take Tuesday episode, we uncover the trend of dirt cheap data labeling, why it's a good thing and a bad thing, and how this is actually a sign of what's next.
Uber paying drivers $1 to train AI models? A sign of what’s next -- An Everyday AI chat with Jordan Wilson
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Topics Covered in This Episode:
- Uber Digital Task Program Overview
- Uber Paying Drivers $1 for AI Training
- AI Data Labeling and Microtask Economics
- Impact on Gig Worker Job Security
- Human Data Training for AI Model Quality
- AI Model Collapse and Internet Data Exhaustion
- Future of Nine-to-Five Work and AI
- Enterprise Strategies for First-Party Data Collection
- Universities and AI Company Partnerships Prediction
Timestamps:
00:00 Uber Drivers Training AI Models
05:03 Uber Drivers Completing Digital Tasks
07:11 AI Workforce Shift
12:17 Changing Future of 9-to-5
14:13 AI's Mixed Impact on Jobs
18:39 AI Competition and Data Scraping
22:37 AI Content Crisis Explained
26:02 Model Collapse and AI Plateau
28:24 Reddit: AI's Human Data Source
33:39 AI, Data, and Future Blueprint
Keywords:
Uber digital task program, Uber paying drivers to train AI, AI model training, $1 micro tasks, Large Language Models, AI data labeling, crowdsourcing human data, gig workers, AI gig economy, job automation, job replacement by AI, AI impact on workforce, autonomous vehicles, computer vision, Waymo, driverless cars, AI-powered ride sharing, AI data collection, first party data, AI data scarcity, synthetic data, AI regurgitation, model collapse, reinforcement learning with human feedback, incremental AI model improvements, knowledge cutoff, AI-generated content, dead Internet theory, bot traffic, Imperva bad bot report, Reddit data deals, Quora, AI partnerships, Fortune 1,000 companies, enterprise AI adoption, fine-tuning teams, domain specific models
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