Artificial Intelligence

AI investments soared in 2021, but big problems remain

Commentary: For all the cash and expertise being thrown at AI, we nonetheless haven’t solved a few of its most elementary shortcomings.

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Image: iStock/Jolygon

The synthetic intelligence wealthy undoubtedly acquired richer in 2021, based on the 2022 Stanford AI Index report. Private enterprise funding in AI exploded to $93.5 billion in 2021, greater than doubling the 2020 tally. Even as funding ranges have ballooned, the variety of corporations getting that cash has gone down. In 2019, enterprise capitalists funded 1,051 AI corporations. In 2020, that quantity dropped to 762, then plunged once more to 746 in 2021, whilst the scale of funding rounds skyrocketed for the fortunate few: In 2020 there have been simply 4 funding rounds that exceeded $500 million, but in 2021, that quantity climbed to fifteen.

SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium) 

All of which can point out that the stakes for AI hold rising. If solely lets say the identical for the outcomes.

The AI gold rush

By a variety of measures, curiosity in AI is off the charts. Take analysis and growth, for instance. According to the report, the variety of AI patents filed in 2021 was 30X greater than in 2015, representing a 76.9% compound annual progress price. Those patents, in flip, are serving to to gas a frenzy in enterprise funding of startups, as talked about above. While such funding is widespread, the very best focus of funding is in the U.S. At $52.9 billion in 2021 funding, the US funds AI at greater than thrice the speed of the following nation (China, $17.2 billion) and over 10 occasions third place (United Kingdom, $4.6 billion).

Image: Stanford Institute for Human-Centered Artificial Intelligence (HAI) AI Index.
Image: Stanford Institute for Human-Centered Artificial Intelligence (HAI) AI Index.

Given how a lot cash is pouring into AI, it’s not stunning that corporations are feverishly in search of AI expertise. According to the report, the share of job postings that point out a necessity for AI abilities was up throughout the globe, with probably the most demand for machine studying abilities (0.6% of all job postings), adopted by synthetic intelligence (0.33%), neural networks (0.16%) and pure language processing (0.13%). What are the most well liked sectors for AI? In the U.S., the primary business for AI jobs is Information. Last place? Waste administration.

Image: Stanford Institute for Human-Centered Artificial Intelligence (HAI) AI Index.

At the identical time, extra folks than ever earlier than are getting levels in associated fields to organize themselves for these jobs:

Image: Stanford Institute for Human-Centered Artificial Intelligence (HAI) AI Index.

In sum, there’s extra expertise chasing extra jobs in corporations getting extra money. Yet AI actuality can’t fairly sustain.

For instance, in the realm of deep studying, AI skilled Gary Marcus instructed that DL is “at its best when all we need are rough-ready results, where stakes are low and perfect results optional.” That’s helpful, but it’s not robots reasoning with normal intelligence like we generally think about AI ought to be delivering by now.

Ask the IEEE technical crowd, they usually marvel if AI is “reaching its limits.” Then there’s the heightened concern that for all its promise, we nonetheless haven’t tackled probably the most fundamental questions on AI and built-in bias.

Small marvel, then, that on Gartner’s 2021 Hype Cycle for AI, most AI-related disciples are barreling up the Peak of Inflated Expectations, getting ready themselves for a stoop into the Trough of Disillusionment. Just a small handful of issues—like Autonomous Vehicles—are readying to depart the Trough and, in the case of autonomous autos, it’s unclear that so-called self-driving vehicles are anyplace close to true self-driving. (As analyst Benedict Evans has written, “[V]ersion nine of ‘Full Self-Driving’ is shipping soon (in beta) and yet will not in fact be full self-driving, or anything close to it.”

No, this doesn’t imply there’s no substance underlying the AI euphoria. Investors are betting big on tomorrow’s potential, not right this moment’s actuality. That’s advantageous. But let’s not get forward of ourselves. As David Meyers has mentioned, “Too many businesses now are pitching AI almost as though it’s batteries included [which may] potentially lead to over-investment in things that over-promise. Then when they under-deliver, it has a deflationary effect on people’s attitudes toward the space.” We shouldn’t dim our hopes in AI, but ought to mood near-term expectations.

Disclosure: I work for MongoDB, but the views expressed herein are mine alone.

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