Image by Hotpot.ai
Author: Jill Maschio, PhD
Frankenstein, a fiction novel written and published by Shelley in 1818, is about a science student who creates a monster creature out of human corpus. Advance to today and peek into the labs of today, and it might seem similar to Frankenstein’s lab. Scientists have created mini-brains (Govindan et al., 2021) that are human iPSC-derived Neural Stem Cells (Jordan et al., 2024). Finalspark, a Swiss company, uses their lab to run biocomputing where mini-brains are a means of electricity to run AI and computers. This may be the next revolution in providing energy for AI and computers.
Image by Hotpot.aineurons growing in brain nursery
The Energy Dilemma
AI has an energy consumption dilemma in that it requires high energy to program and run it, which may have a significant impact on the environment. Not only do AI data centers consume lots of electricity, but also add to the carbon footprint with greenhouse gas emissions and require fresh water and e-waste. A research firm, Garter Inc, predicts that as the use of AI grows rapidly, the need for cloud data centers grows. The growth may lead to AI consuming more energy than the human workforce, which would significantly impact the goal of climate change by reducing human carbon footprint. ChatGPT uses more energy than an Internet search engine. Each message you send ChatGPT produces approximately 4.32 grams of CO2. Training ChatGPT might use as much water as manufacturing a vehicle (Wong, 2024). Wong reported one estimate was that with the current use of ChatGPT of 30,000 GPUs, that is equivalent to emitting 43,200 kg CO2 daily.
Innovation for AI Sustainability
We need more solutions for energy consumption to sustain AI. A mini-brain has neuron differentiation by week 6, displays network activity in the 8th week, and synchronized neuronal activity by week 12 – a fully functional brain with inhibitory neurons, excitatory neurons, oligodendrocytes, astrocytes, and dendrites. The mini-brains are 0.0217 inches in size, which makes mass production attainable Govindan et al., (2021). The human brain generates about 12-25 watts of electrical power. FinalSpark states that its revolutionary biocomputing may provide a solution: “Biocomputing is one billion times more energy efficient than computing hardware”. Although biocomputing seems unreal and although it is still in its infancy, it may be a solution to the energy consumption issue.
References
Jordan, F., Kutter, M., Comby, J-M, Borzzi, F., & Kurtys, E. (2024). Open and remotely accessible Neuroplatform for research in wetware computing. Frontiers in Artificial Intelligence. 7. doi: 10.3389/frai.2024.1376042
Gartner. (2022). Gartner top 10 strategic predications for 2023 and beyond. https://www.gartner.com/en/articles/gartner-top-10-strategic-predictions-for-2023-and-beyond
Govindan, S., Batti, L., Osterop, S. F., Stoppini, L., & Roux, A. (2020). Mass generation, neuron labeling, and 3D imaging of minibrains. Frontiers. 8. doi.org/10.3389/fbioe.2020.582650
Wong, V. (2024, May 3). Gen AI’s environmental ledger: A closer look at the carbon footprint of ChatGPT. Picktochart.com
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One Reply to “Will AI be Sustainable?: Innovation is Needed to Reduce its Carbon Footprint”
I had heard about the energy requirements in vague terms. This article helped me understand the energy needed to conduct basic AI operations. I had never heard of the brain being used for electricity other than the movie the Matrix. Funny coincidence. Thank you for the informative article.
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I had heard about the energy requirements in vague terms. This article helped me understand the energy needed to conduct basic AI operations. I had never heard of the brain being used for electricity other than the movie the Matrix. Funny coincidence. Thank you for the informative article.