Search results for: “AI”
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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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AI: industrial applications by company?
This data-file tabulates industrial companies deploying AI, based on their patent filings. 200 leading industrial companies have filed 40,000 AI/ML-related patents in 2022-24, with 65% now developing their own AIs in house. Examples are summarized. We will continue adding to and expanding this data-file over time.
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AI and sensors: case studies and examples?
The global sensor market is worth $230bn pa and likely accelerates due to the rise of AI. This data file has compiled 15-20 examples of AI systems integrating sensor data, as patented by industrial companies in 2024, to estimate what types of sensors, will be used in which contexts, and whether AI demand will surprise…
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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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Energy intensity of AI: chomping at the bit?
Rising energy demands of AI are now the biggest uncertainty in all of global energy. To understand why, this 17-page note is an overview of AI computing from first principles, across transistors, DRAM, GPUs and deep learning. GPU efficiency will inevitably increase, but compute increases faster. AI most likely uses 300-2,500 TWH in 2030, with…
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AI and Power Grid Bottlenecks: TSE Presentation, June-2024
Energy transition is entering a new era of power grid bottlenecks linked to the rise of AI, rising volatility, and materials high-grading. These themes are kingmakers for gas, midstream, marketing, efficiency, metals and advanced materials. What matters most for AI is rapidly-available, scalable baseload, which could be decarbonized in the future,at low cost. Hence data-centers…
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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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Energy and AI: the power and the glory?
The power demands of AI will contribute to the largest growth of new generation capacity in history. This 18-page note evaluates the power implications of AI data-centers. Reliability is crucial. Gas demand grows. Annual sales of CCGTs and back-up gensets in the US both rise by 2.5x? This is our most detailed AI report to…
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Energy transition in 1H24: 101 companies and the rise of AI?
This 13-page note summarizes the key conclusions across all of our research from 1H24, concisely, for busy decison-makers. We highlight 101 companies, which have come up in our recent work, to enable the rise of AI, and debottleneck its electricity supplies, out of 1,500 companies that have now crossed our screens overall.
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CO2 offsets: Pachama’s AI platform?
Pachama is a nature-based technology company, which has raised $79M, to create a portal where buyers can choose “from rigorously vetted forest restoration and conservation projects”, which in turn are tracked using proprietary AI. This data-file evaluates Pachama’s portfolio and our own experiences, using our usual framework for assessing nature-based CO2 removals.
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