Verum Insights...
- Marcus Nikos
- Mar 9, 2025
- 3 min read

I lost the Most Beautiful person in my life so I saught out Beauty in Nature
“In the story of AI and humans, if we get the dance between artificial intelligence and human society right, it would unquestionably be the single greatest achievement in human history.”
“RENEWABLE ENERGY REVOLUTION: SOLAR + WIND + BATTERIES In addition to AI, we are on the cusp of another important technological revolution—renewable energy. Together, solar photovoltaic, wind power, and lithium-ion battery storage technologies will create the capability of replacing most if not all of our energy infrastructure with renewable clean energy. By 2041, much of the developed world and some developing countries will be primarily powered by solar and wind. The cost of solar energy dropped 82 percent from 2010 to 2020, while the cost of wind energy dropped 46 percent. Solar and onshore wind are now the cheapest sources of electricity. In addition, lithium-ion battery storage cost has dropped 87 percent from 2010 to 2020. It will drop further thanks to the massive production of batteries for electrical vehicles. This rapid drop in the price of battery storage will make it possible to store the solar/wind energy from sunny and windy days for future use. Think tank RethinkX estimates that with a $2 trillion investment through 2030, the cost of energy in the United States will drop to 3 cents per kilowatt-hour, less than one-quarter of today’s cost. By 2041, it should be even lower, as the prices of these three components continue to descend. What happens on days when a given area’s battery energy storage is full—will any generated energy left unused be wasted? RethinkX predicts that these circumstances will create a new class of energy called “super power” at essentially zero cost, usually during the sunniest or most windy days. With intelligent scheduling, this “super power” can be used for non-time-sensitive applications such as charging batteries of idle cars, water desalination and treatment, waste recycling, metal refining, carbon removal, blockchain consensus algorithms, AI drug discovery, and manufacturing activities whose costs are energy-driven. Such a system would not only dramatically decrease energy cost, but also power new applications and inventions that were previously too expensive to pursue. As the cost of energy plummets, the cost of water, materials, manufacturing, computation, and anything that has a major energy component will drop, too. The solar + wind + batteries approach to new energy will also be 100-percent clean energy. Switching to this form of energy can eliminate more than 50 percent of all greenhouse gas emissions, which is by far the largest culprit of climate change.”
Regardless of these theories, I believe it’s indisputable that computers simply “think” differently from our brains.”
“IT IS BETTER TO LIVE YOUR OWN DESTINY IMPERFECTLY THAN TO IMITATE SOMEBODY ELSE’S PERFECTLY.”
“So, will deep learning eventually become “artificial general intelligence” (AGI), matching human intelligence in every way? Will we encounter “singularity” (see chapter 10)? I don’t believe it will happen by 2041. There are many challenges that we have not made much progress on or even understood, such as how to model creativity, strategic thinking, reasoning, counter-factual thinking, emotions, and consciousness. These challenges are likely to require a dozen more breakthroughs like deep learning, but we’ve had only one great breakthrough in over sixty years, so I believe we are unlikely to see a dozen in twenty years. In addition, I would suggest that we stop using AGI as the ultimate test of AI. As I described in chapter 1, AI’s mind is different from the human mind. In twenty years, deep learning and its extensions will beat humans on an ever-increasing number of tasks, but there will still be many existing tasks that humans can handle much better than deep learning. There will even be some new tasks that showcase human superiority, especially if AI’s progress inspires us to improve and evolve. What’s important is that we develop useful applications suitable for AI and seek to find human-AI symbiosis, rather than obsess about whether or when deep-learning AI will become AGI. I consider the obsession with AGI to be a narcissistic human tendency to view ourselves as the gold standard.”


