At the end of 2022, the world witnessed the advent of ChatGPT, which triggered widespread discussion and attention, marking an important milestone in artificial intelligence (AI) technology.
In 2024, Sora has become the new focus. Both technologies originate from OpenAI, a pioneering research institution in the United States.
Their sophistication has reached a level where it is difficult to distinguish reality from virtuality.
The achievement of 2023 is that AI has learned to communicate verbally with humans, and this year, it has gone one step further and learned to understand images captured by human vision.
Some experts even predict that we may only be 2-3 years away from realizing artificial general intelligence (AGI), which means that we are experiencing the wave of the fourth industrial revolution.
AI power supply potential crisis
The rapid development of artificial intelligence technology has attracted public attention to the energy companies that power it. “The future of artificial intelligence lies in energy” has become a consensus in the industry.
The latest warning comes from Musk
At the “Bosch Connected World 2024” conference held on February 29, 2024, Elon Musk accepted a remote interview with Bosch CEO Stefan Hartung and Chairman Marcus Hein and published Thoughts on Artificial Intelligence.
Musk said that while the chip shortage may be over, the rapid expansion of artificial intelligence and electric vehicles will cause the world to face a tight supply of electricity and transformers next year.
This issue deserves attention. It is not the first time Musk has tried to draw industry attention to the power shortage crisis.
The relationship between the development of AI and energy
Since 2023, Musk has warned of the coming power shortage on various occasions.
At the X AI company conference on July 14, 2023, Musk predicted that there would be situations ranging from silicon shortages to voltage shortages to power shortages in the next two years.
He pointed out that the effective calculation of the amount per unit of energy will become the most critical indicator.
At the end of July, Musk once again emphasized at the Innovation Summit hosted by PG&E that the United States will face a severe power shortage within two years.
U.S. electricity consumption will triple by 2045, which if not handled properly will hinder opportunities for AI and electric vehicles.
He urged power generators to increase their sense of urgency and warned that faster action must be taken.
Coincidentally, OpenAI CEO Sam Altman publicly expressed concerns about the energy crisis that the AI industry may face in the future.
He warned at the World Economic Forum’s annual meeting in Davos, Switzerland, that future generative artificial intelligence systems will consume more electricity than currently expected, and existing energy systems may not be able to afford it.
NVIDIA founder Jensen Huang also pointed out that artificial intelligence is not only about increasing computing power but also involving energy solutions such as photovoltaics and energy storage.
He reminded people that if we only focus on improving computing power and ignore the energy required, we may exceed the carrying capacity of the earth.
AI’s electricity demand appears bottomless. Zhou Hongyi, founder of 360 Group, has also repeatedly emphasized that energy is a key factor limiting AI development.
The trend of energy layout
While some artificial intelligence companies are still worried about how to obtain more advanced GPUs to increase computing power, top AI companies have begun to consider how to solve potential power shortages.
According to experts from the University of Pennsylvania, computers accounted for less than 2% of global electricity consumption in 2018, but now this figure has risen to 10%.
It is expected that by 2030, this proportion will reach 20%.
To train models, artificial intelligence companies need to process massive amounts of data and conduct continuous training.
Current data shows that ChatGPT alone consumes 300,000 households’ power consumption.
All of these trends point to a consensus: as artificial intelligence reaches its ultimate stage, achieving energy independence will be key.
Therefore, for those companies that hope to occupy a favorable position in future technological competition, it has become crucial to make arrangements in the energy field in advance.
PVMars has customers all over the world. For example, hotels in Saipan have used solar systems and saved 80% of their monthly energy bills.
At the same time, the power supply pressure of the local public utility grid is reduced, and plans are made in advance to prepare for the future trend of large-scale power shortages and gradually achieve self-sufficiency in power.
AI and the future of solar energy storage
Energy storage technology plays a vital role in the new energy industry chain.
Due to the intermittency and instability of photovoltaic and wind power generation, energy storage systems have become the key to balancing supply and demand and improving energy efficiency.
To realize this vision, many technical and market challenges need to be overcome.
For example, the power generation efficiency and cost issues of photovoltaic technology.
Energy storage density and cycle life issues of energy storage technology. As well as intelligent management and dispatching issues of power networks.
However, with the continuous advancement of technology and continuous policy support, these problems are expected to be gradually solved.
We should also know that technology development is a long-term and complex process that requires joint efforts and continuous investment from all parties.
Only when governments, enterprises, scientific research institutions, and all sectors of society work together to jointly promote the integrated development of AI, photovoltaics, energy storage, and other technologies.
Only then can AI technology’s huge value to human society be truly realized.
Against this backdrop, the deep integration of artificial intelligence with photovoltaic and energy storage technologies heralds a new chapter in technological development.
This kind of cross-field cooperation and innovation will not only promote innovation in the energy field but also provide a stronger foundation for artificial intelligence development.
