Explosive Growth in Resources
We’re witnessing a 10,000-fold increase in computer resources dedicated to AI this decade. This isn’t just growth; it’s a revolution.
It’s Happened Before
Per Moore’s Law, processing power doubles every two years. Nvidia CEO Jensen Huang has claimed Nvidia’s GPUs had boosted AI processing performance by a factor of no less than one million in the last 10 years. Huang has predicted another million x increase in compute.
Trillions of Tokens
Modern AI models are being trained on a staggering trillion tokens. To put that in perspective, the entire Library of Congress is around 20TB of text, or 3.6 trillion tokens. For reference, GPT-4 is thought to have 1.75 trillion parameters.
Every Word Ever Written
The ambition doesn’t stop at the Library of Congress. The next training model may have the capacity to encompass effectively every word ever penned in human history.
Monster Data Sets
The term ‘big data’ feels antiquated when we talk about these monster data sets AI is now grappling with.
Multimodal Learning
It’s not just about text. The future AI will be multi-modal, processing images, sounds, and more, both for input and output.
Personal AI
You’ll be able to chat and call your personal AI, which could even be a clone of a person, like yourself.
Multimodel
AI systems will also be multi-model, bringing together a mixture of models depending on the expertise and information needed.
Foundational Giants
The AI models of tomorrow are vast. They’re not just big; they’re colossal foundation models that redefine scale.
A Book’s Worth of Context
Imagine an AI that uses 100k tokens, akin to an entire book, just to provide context for answering a single question. You don’t have to imagine this; Anthropic’s Claude.ai can already do this.
Context is King
This extensive context isn’t just for show. It’s crucial in helping AI avoid ‘hallucinations’ or erroneous outputs.
The AI Revolution is Just Getting Started
The future of AI isn’t just about bigger data or more processing power. It’s about redefining the very fabric of knowledge, understanding, and context. As we stand on the precipice of this new era, one thing is clear: the AI revolution is just getting started.
Emerging Opportunities
AI is on the cusp of explosive growth that will reshape how we live and work. Students at the AI for Impact course at MIT are identifying massive opportunities for AI to transform major industries.
Bold and Focused
The ideas emerging from the course have the potential to be tomorrow’s breakthrough unicorns. But they are grounded in solving real human needs first, technology second. Students pitched startups in agtech, edtech, waste, and elderly care. Speakers stressed the importance of being bold, but focused, given the timing of the market.
Real-World Impact
The key is matching these powerful technologies with real market demand. MIT’s AI Venture Studio focuses on real-world impact and encourages students to deeply understand their customers, map the ecosystem, and articulate how AI can enable a step-change in value.
Decentralized AI
“Although AI effort seemed to be trapped in the hands of large centralized companies, the future is in millions of mini-models that will engage with each other and usher the field of Decentralized AI”, said Ramesh Raskar, MIT Professor.
This was from a conversation with Ramesh Raskar, MIT professor & Dave Blundin, MIT ‘88 and members of the class.
