The yr 2020 might have been one in every of turmoil and uncertainty throughout the globe, however synthetic intelligence remained on a gentle course of development and additional exploration — maybe due to the Covid-19 disaster. Healthcare was an enormous space for AI funding, and considerations about variety and ethics grew — however little motion has been taken. Most surprisingly of all, whereas AI job development accelerated internationally, it flattened within the US.
These are among the many key metrics of AI tracked within the newest launch of the AI Index, an annual knowledge replace from Stanford College’s Human-Centered Artificial Intelligence Institute. The index tracks AI development throughout a spread of metrics, from diploma applications to trade adoption.
Listed below are some key measures extracted from the 222-page index:
AI investments rising: The report cites a McKinsey survey that exhibits the Covid-19 disaster had no impact on their funding in AI, whereas 27% really reported rising their funding. Lower than a fourth of companies decreased their funding in AI.
AI jobs develop worldwide, flatten within the US: One other key metric is the quantity of AI-related jobs opening up. Surprisingly, the US recorded a lower in its share of AI job postings from 2019 to 2020-the first drop in six years. The entire variety of AI jobs posted within the US additionally decreased by 8.2% from 2019 to 2020, from 325,724 in 2019 to 300,999 jobs in 2020. This can be attributable to the mature market within the US, the report’s authors surmise. Globally, nevertheless, demand for AI expertise is on the rise, and has grown considerably within the final seven years. On common, the share of AI job postings amongst all job postings in 2020 is greater than 5 instances bigger than in 2013. In 2020, industries targeted on data (2.8%); skilled, scientific, and technical providers (2.5%); and agriculture, forestry, fishing, and looking (2.1%) had the best share of AI job postings amongst all job postings within the US.
AI funding in healthcare elevated considerably: The product class of “medication, most cancers, molecular, drug discovery” obtained the best quantity of personal AI funding in 2020, with greater than $13.8 billion, 4.5 instances greater than 2019, the report states. “The panorama of the healthcare and biology industries has advanced considerably with the adoption of machine studying,” the report’s authors state. “DeepMind’s AlphaFold utilized deep studying approach to make a big breakthrough within the decades-long biology problem of protein folding. Scientists use ML fashions to study representations of chemical molecules for simpler chemical synthesis planning. PostEra, an AI startup used ML-based methods to speed up COVID-related drug discovery through the pandemic.”
Generative every little thing: “AI methods can now compose textual content, audio, and pictures to a sufficiently excessive customary that people have a tough time telling the distinction between artificial and non-synthetic outputs for some constrained purposes of the expertise. That guarantees to generate an amazing vary of downstream purposes of AI for each socially helpful and less-useful functions.”
AI has a variety and ethics problem: In 2019, 45% new U.S. resident AI PhD graduates had been white — by comparability, 2.4% had been African American and three.2% had been Hispanic, the report states. Plus, “regardless of rising calls to handle moral considerations related to utilizing AI, efforts to handle these considerations within the trade are restricted. For instance, points comparable to fairness and equity in AI proceed to obtain comparatively little consideration from firms. Furthermore, fewer firms in 2020 view private or particular person privateness dangers as related, in contrast with in 2019, and there was no change within the proportion of respondents whose firms are taking steps to mitigate these specific dangers.”
Laptop imaginative and prescient has turn out to be industrialized: “Corporations are investing more and more massive quantities of computational assets to coach pc imaginative and prescient methods at a quicker fee than ever earlier than. In the meantime, applied sciences to be used in deployed systems-like object-detection frameworks for evaluation of nonetheless frames from videos-are maturing quickly, indicating additional AI deployment.”
AI convention attendance up, just about: An essential metric of AI adoption is convention attendance. “That is means up. If something, Covid-19 might have led to the next variety of individuals collaborating in AI analysis conferences, because the pandemic pressured conferences to shift to digital codecs, which in flip led to vital spikes in attendance,” the survey’s authors contend.
Increasingly more data and analysis is obtainable: The variety of AI journal publications grew by 34.5% from 2019 to 2020 — a a lot greater proportion development than from 2018 to 2019 (19.6%), the report’s authors state. “In simply the final six years, the variety of AI-related publications on arXiv grew by greater than six-fold, from 5,478 in 2015 to 34,736 in 2020. AI publications represented 3.8% of all peer-reviewed scientific publications worldwide in 2019, up from 1.3% in 2011.”