The Future of AI: Leaders from TikTok, Google & More Weigh In (FII Panel) | EP #127
The podcast discusses the importance of quantitative AI and generative data for various industries, and predicts the arrival of AGI within 5-8 years. The podcast discusses the dual nature of AI, emphasizing its potential for both financial gain and social good, while highlighting the transformative impact of AI on health, education, and business. The discussion covers the vast AI market, challenges in hardware infrastructure, the fast-growing foundation models market, and the race for new applications in AI. The podcast discusses the role of AI in content moderation, its importance for economic growth, integration into the physical world, and the challenges of building AI factories, with Nvidia emphasizing its accelerated computing platform.
Quantitative AI, based on equations and data, is discussed as a complementary tool to large language models (LLMs) for applications like biofarma and material science.
Generative data, generated from equations rather than internet data, is highlighted as crucial for applications in finance, material science, and energy.
The panel discusses the path to AGI, with predictions that within 5-8 years, AI systems will be able to write their own code and become 80-90% as capable as human experts in various fields.
AI's impact on industries like biopharma, chemicals, and energy is discussed, with examples of how AI can transform the bottom of the refinery stack and accelerate biomarket development.
“within 6 to 8 years from now so 2030 right after that maybe 2032 under current growth rate it will be possible to have a single system that is 80 or 90% of the ability of a of the expert in every field”
Your call:
openPeter Diamandis: AI will transform businesses and industries over the next five years, creating a generational opportunity for innovation and change.
“do you imagine is it the rest of this decade um well I think one of the PE things that people Miss is NVIDIA is not just about the GPU we are about an accelerated Computing platform”
Your call:
Numbers that matter
40 millionRevenue growth of a Dev Tool company in 3 months.
5-8 yearsTimeframe for AI systems to become 80-90% as capable as human experts in various fields.
$100 millionModels that cost less than $100 million to train are probably not that dangerous, while those that cost more than $100 million are more dangerous.
10 yearsIn 10 years, there will be a need for more hardware infrastructure like chips and data centers.
100 foldThe price of a token has fallen 100 fold in the last two years.
3 monthsA Dev Tool company has grown from 0 to 40 million in Revenue in 3 months.
two yearsThe time since chat GPT and generative AI became impressive.