The State of AI in 2022
Summary from The report by AI investors Nathan Benaich and Ian Hogarth.
Artificial intelligence is complex and many sided. I could spend a lifetime blogging about it and barely scratch the surface. While I am naturally skeptical of reports by consulting firms or Venture Capitalists (no matter how versed in A.I), it’s always worth a look and a quick glance to see what they are saying.
I don’t always know what to make of these summaries, but there are some important conclusions, graphs, tidbits and insights of A.I.’s global nature and its commercial politics between public, private, national and industry groups. It’s surprisingly difficult to be objective about it all.
While AI’s growing impact on society and the economy is now evident, their report highlights that research into AI safety and the impact of AI still lags behind its rapid commercial, civil, and military deployment.
I was interested to read Troy Angrignon’s favorite parts here. Different analysts have different perspectives on what we might consider the highlights of the State of A.I. in 2022. People tend to hype different aspects, while journalists are also looking to be read with sometimes suspect clickbait headlines. A lot of the report reads like praises for Google’s research.
There are however some important trends that some might have considered unexpected in 2022. If you think about it, small, previously unknown labs like Stability.ai and Midjourney have developed text-to-image models of similar capability to those released by OpenAI and Google earlier in the year, and made them available to the public via API access and open sourcing.
Meanwhile, AI continues to advance scientific research.
Nathan Benaich’s own key takeaways are not those I would have chosen, but still let’s try to unpack their report:
We hope the report has something for everyone- from AI research to politics. Here are five key findings:
1) AI is stepping up in more concrete ways: AI is increasingly being applied to mission critical infrastructure like national electric grids and automated supermarket warehousing calculations during pandemics.
2) AI-first approaches have taken biology by storm: AI has enabled faster simulations of humans’ cellular machinery (proteins and RNA) which has the potential to transform drug discovery and healthcare.
3) Transformers have emerged as a general purpose architecture for machine learning: beating the state of the art in many domains including NLP, computer vision, and even protein structure prediction.
VENTURE CAPITAL HYPE CONTINUES
4) Investors have taken notice: We have seen record funding this year into AI startups, and two first ever IPOs for AI-first drug discovery companies, as well as blockbuster IPOs for data infrastructure and cybersecurity companies that help enterprises retool for the AI-first era.
CHINA TOP IN RESEARCH AND PAPERS
5) China's ascension in research quality is notable: China’s universities have rocketed from publishing no AI research in 1980 to the largest volume of quality AI research today.
Read the State of AI Report
It’s also a bit fun that they attempt to make predictions and take a tally over their previous predictions. The report is 114 Google slides, so it’s not exactly exhaustive. They try to take the following into account as dimensions:
There was not much chatter on Hacker News or Reddit about the 2022 edition of this report. This is the 5th edition of the State of AI report, in 2022.
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