The human mind has inspired computing since its origins. But it wasn’t until the 1990s, and really the 2010s, that neural networks became powerful enough to process increasing amounts of data using increasingly powerful machines.
The rise of graphics cards, primarily developed for gaming, coincidently allowed the flourishing of machine learning, since GPUs can easily calculate matrix multiplications. Progress has been made on AI specific chips, moving beyond GPUs to neuromorphic chips.
Google has been working on Tensor Processing Units (TPUs) internally since 2015 and externally since 2018. If that wasn’t enough, Google announced in 2020 that they could use deep reinforcement learning to improve on chip design itself. In 2021, Tesla announced the D1 Dojo Chip, a card designed for self driving by neural network.
All this progress is leading some to wonder if neuromorphic chips will allow Moore’s Law to continue well into the 21st century. For more info about neuromorphic engineering and spintronic synapses, we recommend Ayon Datta’s article on the topic, Brain-inspired computing
All the while progress has been made on many technological fronts including FemTech, a term coined in 2013 to describe companies focused on addressing women’s biological needs. In 2019, VC backing for FemTech startups was only ~$600 million, compared to the ~$500 billion in annual medical care for women, indicating a huge potential for growth.
If you are a tech founder or entrepreneur, you may be interested to check out DDI Founder’s Network
, where entrepreneurs, mentors, and investors(fund managers) turn intellectual sparks into tangible processes and results. If you have an idea that needs access to funding, we would like to have a chat with you. If you have a proven record of growing a business and are ready for your next series, the DDI Founder’s Network might just be the place for you.
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