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AI’s Material ‘Breakthroughs’ are Still Useless
- Orbital Materials is creating new materials to decarbonise Amazon's data centres using their proprietary AI platform.
- Orbital claims using AI has improved the speed of material discover 10 times faster than traditional methods.
- Meta recently released a colossal dataset called Open Materials 2024, containing over 118 million examples of material simulations and structures.
- The numbers speak for themselves. The next time it seems exciting when AI has discovered new materials, it’s time to give ourselves a reality check.
- When Google Deepmind made the announcement last year, the company did not take long for contradictory results to come into the picture.
- Moreover, newly discovered materials need to go through a lot of testing, and the world has seen quite a few tragedies when they’re put out in the real world.
- From analysing the materials’ failure modes in controlled conditions to setting up an industrial-scale factory, following regulations, and justifying the choices to investors and customers, one is surely set to turn into Sisyphus.
- Deep learning has amplified materials research and discovery for a few years now. However, if there’s one way AI can save humanity, it lies in not just discovering new materials, but also finding ways to synthesise and manufacture them in commercial capabilities.
- Google DeepMind released research titled ‘Scaling deep learning for material discovery’ discovering 380,000 materials, but many materials discovered weren’t truly novel.
- Orbital plans to test carbon removal technologies by the end of 2025.
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