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šŸ¤– Meta Executives Donā€™t See Super Intelligence Happening

PLUS: Google DeepMindā€™s AI Agents Learn From Humans

Welcome back AI enthusiasts!

In todayā€™s AI Report:

  • šŸ“ŠMeta Executives Donā€™t See Super Intelligence Happening

  • šŸ§ Google DeepMindā€™s AI Agents Learn From Humans

  • šŸ› 5 Trending Tools

  • šŸ’°Venture Capital Updates

  • šŸ’¼Whoā€™s Hiring?

Read Time: 3 minutes

šŸ—žRECENT NEWS

META

šŸ“ŠMeta Executives Donā€™t See Super Intelligence Happening

Image Source: CMAP/DATAAI Data Science Summer School

Metaā€™s chief scientist and deep learning pioneer, Yann LeCun, believes current AI systems are decades away from displaying alert emotions beyond generating text outputs in creative ways.

Key Details:
  • His opinion contrasts with Nvidia CEO Jensen Huang, who recently stated, ā€œAI will be fairly competitive with humans in less than five years.ā€

  • LeCun explained that Huang has much to gain from the AI craze: ā€œThere is an AI war, and heā€™s supplying the weapons. If you think AGI is in, the more GPUs you have to buy.ā€

  • The technology industryā€™s focus on language models and text data isnā€™t enough to create advanced human-like systems. Training these systems is slow and expensive. Once trained, the model is essentially frozen in time.

Why Itā€™s Important:
  • Nvidia has an economic incentive to hype generative AI research because its pricey Graphics Processing Units (GPUs) are the standard tool for training language models. For example, Meta required 16,000 Nvidia A100 GPUs to train its Llama AI software.

  • To reach super intelligence, companies need real-time training with massive computing power and constant data sets that mimic the human brain.

GOOGLE DEEPMIND

šŸ§ Google DeepMindā€™s AI Agents Learn From Humans

Image Source: Jung Yeon-Je/AFP/Getty Images

Google DeepMind recently developed AI agents that learn real-time tasks from a human instructor.

Key Details:
  • The agents acquire knowledge from human demonstrations in a rich 3D environment by observing movements and reproducing behaviors.

  • The agent-based system is powered by a neural network with weights trained using deep reinforcement learning.

  • This imitation-focused AI training removes the need for large datasets by combining memory, attention mechanisms, and automatic curriculum learning to achieve desired outputs.

Why Itā€™s Important:
  • DeepMindā€™s research could enhance the training of robotic systems, like lifting and placing boxes. It could also transform customer service systems by equipping them with interactive learning abilities to provide adaptive support.

  • This new training method could eliminate privacy concerns and monetary constraints for storing large datasets to fuel AI models.

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šŸ’°VENTURE CAPITAL UPDATES

  • AssemblyAI lands $50M to build and serve AI speech models.

  • Kognitos raises $20M to help businesses automate back-off processes.

  • Syrup raises $17.5M to expand its AI-powered inventory forecasting platform.

šŸ’¼WHOā€™S HIRING?

  • Amazon (Seattle, WA): Business Analyst Intern, Summer 2024

  • Lucid (Raleigh, NC): Customer Operations Intern, Summer 2024

  • Humane (San Francisco, CA): Software Engineering Intern, Summer 2024

  • Cohere (San Francisco, CA): Sales Manager

  • Anthropic (San Francisco, CA): Senior Contracts Manager

šŸ¤–PROMPT OF THE DAY

SALES

šŸ“†Seasonal Sales

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Region = [Insert Here]

šŸ“’FINAL NOTE

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