A 4-Year-Old Child Has Seen 50x More Information Than the Biggest LLMs! : Chris
by: Chris
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“A 4-year-old child has seen 50x more information than the biggest LLMs that we have.” — Yann LeCun (Professor at NYU) source
Feel free to listen to the interview with top-notch AI experts including Yann LeCun here:
What are some implications from this that help us to be positioned on the right side of change? Let’s explore three simple investment ideas next (no financial advice)! 
1. The Exponential Growth of AI Training
The future of AI training is poised for a significant expansion, potentially increasing by two or even three orders of magnitude.
If kids have 50x more training data than current AI models, we’ll scale AI training by 50x at least! More likely, we’ll outpace the training data by a 40-year old professor that’s 10×50 = 500x the current size of AI training.
500x!!!
Computing infrastructure is minuscule today in comparison to what it will be when we’ll reach AGI.
This immense growth signals a prosperous future for companies specializing in AI training services. Giants like Google (GOOGL), Microsoft (MSFT), and Amazon (AMZN) are already key players in this space, providing essential AI training services.
Moreover, NVIDIA (NVDA) plays a crucial role by supplying the necessary AI training infrastructure.
Despite current market perceptions that these companies might be overvalued and the trend of AI training a passing fad, this prediction suggests we are only at the beginning of a massive surge in AI training demand.
The reality is that these companies are well-positioned to capitalize on this burgeoning market, making them potentially sound investments for the future.
2. The Importance of Data and Data Sources
In the realm of AI, the quality and scale of data are fundamental. Platforms like YouTube (owned by GOOGL) and Facebook/Instagram (META) stand out as examples of massive data sources, offering a wealth of information for AI algorithms.
Additionally, Tesla (TSLA) is a noteworthy example, possessing an extensive collection of unique proprietary data gathered from its fleet of Full Self-Driving (FSD) capable cars.
This data is invaluable for the development and refinement of AI in autonomous vehicle technology. Investing in companies that have access to such large-scale, high-quality data repositories could be a strategic move, as they have the raw materials necessary for significant advancements in AI.
3. The Rise of Next-Generation Large Language Models (LLMs)
Large Language Models (LLMs) have already made impressive strides, but the future promises even more groundbreaking advancements.
Companies like OpenAI, backed by Microsoft (MSFT), and Anthropic are at the forefront of this innovation, showing no signs of convergence in the scaling laws of AI.
This indicates a long runway for exponential improvement, positioning these firms as leaders in a high-growth industry reminiscent of the early days of the internet.
However, it’s also possible that the most influential companies in this space may not have even emerged yet. Keeping an eye on new entrants and current leaders in the LLM domain is crucial for investors seeking to capitalize on this wave of technological advancement.
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4. Integrating Human Experience into AI Training
The next frontier in AI development involves integrating real-world human experiences into AI training. One approach to achieving this is through the use of humanoid robots that can simulate and learn from human-like experiences.
Tesla Bot Optimus: Is $5,000 per Share (TSLA) Realistic?
Tesla’s development of a humanoid robot exemplifies this trend. The potential for robotics to become a much larger industry is significant, especially if robots can be developed to understand and replicate human behaviors and interactions.
To reach human-level AGI, we’re likely to need to train and obtain data from the perspective of a human (sensing, seeing, touching, talking, feeling). Humanoid robots are the perfect carrier of sensors to obtain this data.
January 26, 2024 at 08:10PM
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