AI will transform automation, productivity, and growth. Big ambitions are hard to achieve. Goldman Sachs expects tech to spend $1 trillion on AI in five years. Efficiency gains, not breakthroughs, were obtained. AI’s future is uncertain as NVIDIA’s stock price falls. Experts concur with this caution. MIT’s Daron Acemoglu opposes AI’s lofty aspirations. Under 5% of labor functions will be automated by AI in the next decade.
He believes AI will gradually increase productivity and GDP without economic damage. Not the revolutionary transformation envisaged. Joseph Briggs of Goldman Sachs is more upbeat. He thinks AI will automate 25% of tasks, boosting productivity. His hope stems from cheaper AI automation. However, significant initial costs and technical challenges temper this outlook.
Combining AI and cryptocurrencies is hard. AI’s massive processing power and chip supply may limit crypto-based AI applications.
Cryptographic algorithms in AI-driven crypto solutions demand a lot of processing power, compounding these issues. The growing power demands of AI data centers strain our aging power systems, making energy-intensive crypto mining harder. Former Microsoft VP of Energy Brian Janous warns that our infrastructure may not be ready for this demand, hindering AI and AI-enhanced crypto growth.
AI and Crypto Integration: Emerging Synergies and Investments
MIT senior researcher Daron Acemoglu and Goldman Sachs Head of Global Equity Research Jim Covello have examined AI’s economic impact. Acemoglu expects AI to boost GDP by 1% and productivity by 0.5% in the next decade. In contrast to Goldman Sachs’ 9% productivity growth and 6.1% GDP forecast.
Acemoglu doubts generative AI since it automates tasks, not disrupts industries. AI may boost data analysis but won’t endanger manufacturing and transportation. He estimates AI may cost-effectively automate 4.6% of tasks in the next decade, boosting total factor productivity by 0.66% and GDP by 0.9%.
Covello shares Acemoglu’s pessimism, but differently. He predicts $1 trillion in AI infrastructure spending in the next few years. Covello wonders if AI can address critical, complicated problems affordably. AI’s high cost and unclear ROI contrast with the internet’s inexpensive cost.
AI and crypto are exciting and promising despite these concerns. AI crypto tokens have risen to $30 billion as of July 23, 2024. AI’s financial and healthcare implications attract interest.
Fetch.ai, SingularityNET, and Ocean Protocol are making ASI coins. A decentralized AI platform for AGI and ASI is their goal. AGI can accomplish any human job, but ASI exceeds them.
However, reaching ASI is challenging. Large computing power and chip supply restrictions may hinder AI-driven crypto apps. Energy-intensive AI data centers and coin mining strain electrical systems.
Recent discoveries show how AI and crypto are interwoven and may become more so. Bitcoin miners use AI after losing earnings following halving. After the April 2024 halving event lowered mining rewards from 6.25 Bitcoin to 3.125, Lancium and Crusoe Energy Systems invested in AI data centers. To fulfill AI’s expanding needs and abandon Bitcoin mining, they invested billions in a Texas data center. Both bitcoin mining and AI infrastructure are similar. Each requires large data centers, energy, and cooling.
Bitcoin miners can reuse infrastructure as AI computes more. Core Scientific and Hut 8 are long-term AI investors. Balance hope with realism to solve it. Both technologies have great potential but face financial, technological, and infrastructure obstacles. Time opens up unlimited possibilities. Both industries may merge or undergo a major revamp. However, the tech era has taken over the world, and future years and decades will bring surprising advances.
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