Outsourcing Layer 2: From Asia to AI
The manufacturing shift of the 1970s was transformative. From the precision-driven workshops in Japan to the effervescent factories of Taiwan, transitioning through the vibrant ports of Hong Kong, the expansive terrains of China, and presently, the dynamic hubs in Vietnam — outsourcing redefined cost efficiency in manufacturing. Today, the world stands at the cusp of another outsourcing upheaval. It’s no longer just about geography; it’s digital, it’s instantaneous, and its driving force? Artificial Intelligence (AI).
AI’s Deflationary Impact on SaaS
Drawing parallels from the past, just as outsourcing molded manufacturing, AI is reshaping the SaaS landscape. Historically, companies that run on SaaS have been laden with overheads: human management, software asset management, periodic upgrades, and maintenance. But AI-driven platforms are rapidly eradicating these operational expenditures. While the initial capital investment remains significant, the subsequent costs are spiraling down to near nothingness.
Picture this: SaaS platforms that self-update not in weeks or days, but in real-time, all powered by AI. The age-old norm of manual intervention for updates, maintenance, and troubleshooting is fast becoming archaic. The result? Cutting-edge, nearly instantaneous solutions that set a new gold standard in software efficiency.
For corporations, this evolution is a paradigm shift. AI-empowered SaaS solutions can be utilized at nearly zero costs, rendering expensive subscriptions and update fees obsolete. The landscape is reminiscent of an endless, free gateway to bleeding-edge technology.
But AI’s influence doesn’t stop at optimization. Take a case of cybersecurity where AI systems can self-evolve through relentless iterations, achieving hacking proficiencies that far exceed human capabilities. If such AI were to be open-sourced, the implications for security systems designed by humans could be monumental.
Physical Goods Face Persistent Inflation
While AI drives efficiency improvements in the digital realm, the physical world operates on a different timeline. While the digital realm undergoes a rapid transformation driven by AI, the tangible world lingers in its immutable rhythm, resisting dramatic change. Here’s why:
Firstly, the tangible world is intertwined with intricate biological, geological, and physical processes. Consider the time it takes for crops to grow: regardless of how sophisticated AI systems become in predicting the best planting times, optimizing irrigation, or identifying potential diseases, the wheat still requires its season to mature, and the grapevine its cycles to yield fruit.
Similarly, the human body, a masterpiece of nature, follows its own pace. We might employ AI to predict injuries or illnesses with unprecedented accuracy, but the time it takes for a wound to heal or for a broken bone to mend remains relatively constant.
And in the realm of livestock? Whether it’s the incubation period for chickens or the biological clock governing when cows produce milk, these processes are, by large, fixed in their timelines. Even with AI-enhanced feed optimization, a cow can’t digest food and convert it to proteins, like meat and milk, any faster than nature allows.
Processes like irrigation, pivotal for agriculture, can be enhanced using AI to predict weather patterns and allocate water resources more effectively, but the fundamental principles of redirecting and using water remain untouched.
Outsourcing Layer 2
Outsourcing has evolved from a geographic shift towards Asia to a digital transformation steered by AI. This metamorphosis, reminiscent of the ’70s manufacturing wave, has ushered in AI-optimized SaaS platforms with unprecedented operational efficiency. Corporations will enjoy almost free, cutting-edge technology, while AI’s prowess could revolutionize cybersecurity. However, the physical world, including agriculture and human physiology, still adheres to nature’s timeline despite AI’s enhancements. Intriguingly, as AI reduces digital costs, the value of tangible goods and manual tasks becomes pronounced. Thus, professions tied to the physical world gain prominence in our AI-integrated future, suggesting a horizon rich in opportunities and challenges.
No bubble. Nothing to see here.
What do you see?
CoreWeave:
Is backed by $NVDA.
Buys $2.3 billion worth of NVIDIA chips.
This purchase is financed by a $2.3 billion line of credit (LOC) from Blackrock.
The NVIDIA chips are used as collateral for this loan.
Blackrock:
Owns 182 million shares of NVIDIA.
Is a significant investor in the $2.3 billion line of credit provided to CoreWeave.
NVIDIA:
Has a "data center beat" worth $2.3 billion.
Its stock price increased by 11% in after-hours trading (AH) but then dropped during regular trading hours (RTH).
Re-publish my June 28's article about a hypothetical merger between Nvidia and Snowflake and its impact on Databricks.
