# Future AI hardware advances could drive materials science R&D

**URL:** <https://community.materialssquare.com/t/future-ai-hardware-advances-could-drive-materials-science-r-d/278>\
**Category:** News\
**Created:** [May 27, 2024, 11:31am UTC](https://community.materialssquare.com/t/future-ai-hardware-advances-could-drive-materials-science-r-d/278 "2024-05-27T11:31:13Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![gabriele1](https://yyz1.discourse-cdn.com/flex003/user_avatar/community.materialssquare.com/gabriele1/32/20_2.png) [@gabriele1](https://community.materialssquare.com/u/gabriele1)\
**Post date:** [May 27, 2024, 11:31am UTC](https://community.materialssquare.com/t/future-ai-hardware-advances-could-drive-materials-science-r-d/278/1 "2024-05-27T11:31:13Z")

</div>

Pradyumna Gupta, founder of Infinita Lab, discusses the limitations of current AI hardware, emphasizing the “memory wall” as a major bottleneck. Despite advances in logic chips, memory technology lags behind. Gupta highlights the potential of AI in materials science for designing experiments and analyzing data. Infinita Lab addresses the challenge of accessing advanced testing equipment by partnering with numerous labs across the U.S., democratizing material testing services for startups and engineers.

For more details, read the full article here:

> **[Future AI hardware advances could drive materials science R&D](https://www.rdworldonline.com/infinita-lab-founder-on-ai-hardware-limitations-and-the-future-of-material-science/)**
>
> AI's potential in materials science is limited by hardware bottlenecks and access to testing, says Infinita Lab's founder.