Digital
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AI energy: industrial demand and the Jevons effect?
Increasingly efficient AI should unlock ever more widespread and more sophisticated uses of AI. This is shown by reviewing 40,000 patents from 200 industrial companies. This 15-page report summarizes notable companies, patent filings, and updates our 2030 forecasts for AI energy.
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Cool concept: absorption chillers, data-centers, fuel cells?!
Absorption chillers perform the thermodynamic alchemy of converting waste heat into coolness. Interestingly, their use with solid oxide fuel cells may have some of the lowest costs and CO2 for powering and cooling AI data-centers. This 14-page report explores the opportunity, costs and challenges.
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Kraken Technologies: smart grid breakthrough?
Kraken Technologies is an operating system, harnessing big data across the power value chain, from asset optimization, to grid balancing, to utility customer services. We reviewed ten patents, which all harness big data, of which 65% optimize aspects of the grid, and 40% are using AI. This supports the deployment of distributed energy, renewables and…
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Groq: AI inference breakthrough?
Groq has developed LPUs for AI inference, which are up to 10x faster and 80-90% more energy efficient than today’s GPUs. This 8-page Groq technology review assesses its patent moat, LPU costs, implications for our AI energy models, and whether Groq could ever dethrone NVIDIA’s GPUs?
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Moving targets: molecules, electrons or bits ?!
New AI data-centers are facing bottlenecked power grids. Hence this 15-page note compares the costs of constructing new power lines, gas pipelines or fiber optic links for GW-scale computing. The latter is best. Latency is a non-issue. Thus AI reshapes the future of US shale, midstream and fiber-optics?
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Fiber optic data transmission costs?
The costs of fiber optic data transmission run at $0.25/TB per 1,000km in order to earn a 10% IRR on constructing a link with $120 per meter capex costs. Capex is 85% of the total cost. This data fiber breaks down the costs of fiber optic data transmission from first principles, across capex, utilization, electricity…
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Internet energy consumption: data, models, forecasts?
This data-file forecasts the energy consumption of the internet, rising from 800 TWH in 2022 to 2,000 TWH in 2030 and 3,750 TWH by 2050. The main driver is the energy consumption of AI, plus blockchains, rising traffic, and offset by rising efficiency. Input assumptions to the model can be flexed. Underlying data are from…
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Omniscience: how will AI reshape the energy transition?
AI will be a game-changer for global energy efficiency, saving 10x more energy than it consumes directly, closing ‘thermodynamic gaps’ where 80-90% of all primary energy is wasted today. Leading corporations will harness AI to lower costs and accelerate decarbonization. This 19-page note explores opportunities.
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What is the energy consumption of the internet?
Powering the internet consumed 800 TWH of electricity in 2022, as 5bn users generated 4.7 Zettabytes of traffic. Our guess is that the internet’s energy demands double by 2030, including due to AI (e.g., ChatGPT), adding 1% upside to global energy and 2.5% to global electricity demand. This 13-page note aims to break down the…
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Energy intensity of fiber optic cables?
What is the energy intensity of fiber optic cables? Our best estimate is that moving each GB of internet traffic through the fixed network requires 40Wh/GB of energy, across 20 hops, spanning 800km and requiring an average of 0.05 Wh/GB/km. Generally, long-distance transmission is 1-2 orders of magnitude more energy efficient than short-distance.
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