ML infrastructure investments

Two thousand and twenty was the year in which the promise of artificial intelligence became more tangible. We are probably entering the phase in which the early majority is starting to adopt machine learning infrastructure. Breakthroughs such as GPT-3 (an autoregressive language model that uses deep learning to produce human-like text) and AlphaFold 2 (code that predicts the 3D structure of a protein based on its genetic sequence) are hints of what lays ahead the coming decades.

Tim Davidson, founder and CEO of Aiconic and one of our advisors in the field of artificial intelligence, concluded his year-end note by saying “In the unique world of machine learning, it was a year of meaningful breakthroughs. While uncertainty looms over 2021, we see enough evidence to support a bullish view on everything that is cloud + machine learning (ML). The expanding ML-as-a-Service industry and ever declining costs of research are likely to empower a new generation of ML products and companies. Lower failure costs combined with increased competition will accelerate the startup iteration cycle, providing investors with faster outcomes. Finally, corporations and governments will drastically increase their venture investment targets in an attempt to stay relevant in a rapidly digitalizing and automating economic environment.”

We are excited about emerging machine learning infrastructure companies that are able to deliver the end solutions that the market is now ready for to start implementing.