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- 🤖 Meta Executives Don’t See Super Intelligence Happening
🤖 Meta Executives Don’t See Super Intelligence Happening
PLUS: Google DeepMind’s AI Agents Learn From Humans
James Roesser
December 05, 2023
Welcome back AI enthusiasts!
In today’s AI Report:
📊Meta Executives Don’t See Super Intelligence Happening
🧠Google DeepMind’s AI Agents Learn From Humans
🛠5 Trending Tools
💰Venture Capital Updates
💼Who’s Hiring?
Read Time: 3 minutes
🗞RECENT NEWS
META
📊Meta Executives Don’t See Super Intelligence Happening
Image Source: CMAP/DATAAI Data Science Summer School
Meta’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, “AI will be fairly competitive with humans in less than five years.”
LeCun explained that Huang has much to gain from the AI craze: “There is an AI war, and he’s supplying the weapons. If you think AGI is in, the more GPUs you have to buy.”
The technology industry’s focus on language models and text data isn’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 It’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
🧠Google DeepMind’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 It’s Important:
DeepMind’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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💰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.
💼WHO’S HIRING?
🤖PROMPT OF THE DAY
SALES
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