The first price point for usable solar technology that I can find is from the year 1956. At that time, the cost of just one watt of solar photovoltaic capacity was $1,865 (adjusted for inflation and in 2019 prices).10 One watt isn’t much. Today, one single solar panel of the type homeowners put on their roofs produces around 320 watts of power.11 This means that at the price of 1956, one of today’s solar modules would cost $596,800.12
Our World In Data explaining why renewable energy prices have dropped dramatically, showing how solar and wind technologies have become cheaper than fossil fuels within just 15 years.
Comprehensive Coverage
139 Skills - Extensive coverage across all major scientific domains
28+ Databases - Direct access to OpenAlex, PubMed, bioRxiv, ChEMBL, UniProt, COSMIC, and more
55+ Python Packages - RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioServices, PennyLane, Qiskit, and others
GitHub repository with 139 scientific skills for Claude, enabling complex multi-step research workflows across biology, chemistry, medicine, and other scientific domains
The trouble with these calculations is that they mire us in epistemically tricky terrain. I’m bothered by how quickly the discussions of AI become utopian or apocalyptic.
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It also forces thinking to be obsessively short term. People start losing interest in problems of the next five or ten years, because superintelligence will have already changed everything. The big political and technological questions we need to discuss are only those that matter to the speed of AI development. Furthermore, we must sprint towards a post-superintelligence world even though we have no real idea what it will bring.
I started my tools.simonwillison.net site last year as a single location for my growing collection of vibe-coded / AI-assisted HTML+JavaScript tools ... The new browse all by month page shows I built 110 of these in 2025!
Simon Willison's Annual review blog post examining major trends and developments in large language models (LLMs) during 2025.
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