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AI vs. Humans: Which Performs Certain Skills Better?



AI vs. Humans: Which Performs Certain Skills Better?

AI vs. Humans: Which Performs Certain Skills Better?

With ChatGPT’s explosive rise, AI has been making its presence felt for the masses, especially in traditional bastions of human capabilities—reading comprehension, speech recognition and image identification.

In fact, in the chart above it’s clear that AI has surpassed human performance in quite a few areas, and looks set to overtake humans elsewhere.

How Performance Gets Tested

Using data from Contextual AI, we visualize how quickly AI models have started to beat database benchmarks, as well as whether or not they’ve yet reached human levels of skill.

Each database is devised around a certain skill, like handwriting recognition, language understanding, or reading comprehension, while each percentage score contrasts with the following benchmarks:

  • 0% or “maximally performing baseline”
    This is equal to the best-known performance by AI at the time of dataset creation.
  • 100%
    This mark is equal to human performance on the dataset.

By creating a scale between these two points, the progress of AI models on each dataset could be tracked. Each point on a line signifies a best result and as the line trends upwards, AI models get closer and closer to matching human performance.

Below is a table of when AI started matching human performance across all eight skills:

SkillMatched Human
Database Used
Handwriting Recognition2018MNIST
Speech Recognition2017Switchboard
Image Recognition2015ImageNet
Reading Comprehension2018SQuAD 1.1, 2.0
Common Sense
Grade School MathN/AGSK8k
Code GenerationN/AHumanEval

A key observation from the chart is how much progress has been made since 2010. In fact many of these databases—like SQuAD, GLUE, and HellaSwag—didn’t exist before 2015.

In response to benchmarks being rendered obsolete, some of the newer databases are constantly being updated with new and relevant data points. This is why AI models technically haven’t matched human performance in some areas (grade school math and code generation) yet—though they are well on their way.

What’s Led to AI Outperforming Humans?

But what has led to such speedy growth in AI’s abilities in the last few years?

Thanks to revolutions in computing power, data availability, and better algorithms, AI models are faster, have bigger datasets to learn from, and are optimized for efficiency compared to even a decade ago.

This is why headlines routinely talk about AI language models matching or beating human performance on standardized tests. In fact, a key problem for AI developers is that their models keep beating benchmark databases devised to test them, but still somehow fail real world tests.

Since further computing and algorithmic gains are expected in the next few years, this rapid progress is likely to continue. However, the next potential bottleneck to AI’s progress might not be AI itself, but a lack of data for models to train on.

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Mapped: The Number of AI Startups By Country

Over the past decade, thousands of AI startups have been funded worldwide. See which countries are leading the charge in this map graphic.



Mapped: The Number of AI Startups By Country

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Amidst the recent expansion of artificial intelligence (AI), we’ve visualized data from Quid (accessed via Stanford’s 2024 AI Index Report) to highlight the top 15 countries which have seen the most AI startup activity over the past decade.

The figures in this graphic represent the number of newly funded AI startups within that country, in the time period of 2013 to 2023. Only companies that received over $1.5 million in private investment were considered.



Data and Highlights

The following table lists all of the numbers featured in the above graphic.

RankGeographic areaNumber of newly funded
AI startups (2013-2023)
1🇺🇸 United States5,509
2🇨🇳 China1,446
3🇬🇧 United Kingdom727
4🇮🇱 Israel442
5🇨🇦 Canada397
6🇫🇷 France391
7🇮🇳 India338
8🇯🇵 Japan333
9🇩🇪 Germany319
10🇸🇬 Singapore193
11🇰🇷 South Korea189
12🇦🇺 Australia147
13🇨🇭 Switzerland123
14🇸🇪 Sweden94
15🇪🇸 Spain94

From this data, we can see that the U.S., China, and UK have established themselves as major hotbeds for AI innovation.

In terms of funding, the U.S. is massively ahead, with private AI investment totaling $335 billion between 2013 to 2023. AI startups in China raised $104 billion over the same timeframe, while those in the UK raised $22 billion.

Further analysis reveals that the U.S. is widening this gap even more. In 2023, for example, private investment in the U.S. grew by 22% from 2022 levels. Meanwhile, investment fell in China (-44%) and the UK (-14.1%) over the same time span.



Where is All This Money Flowing To?

Quid also breaks down total private AI investment by focus area, providing insight into which sectors are receiving the most funding.

Focus AreaGlobal Investment in 2023
(USD billions)
🤖 AI infrastructure, research,
and governance
🗣️ Natural language
📊 Data management$5.5
⚕️ Healthcare$4.2
🚗 Autonomous vehicles$2.7
💰 Fintech$2.1
⚛️ Quantum computing$2.0
🔌 Semiconductor$1.7
⚡ Energy, oil, and gas$1.5
🎨 Creative content$1.3
📚 Education$1.2
📈 Marketing$1.1
🛸 Drones$1.0
🔒 Cybersecurity$0.9
🏭 Manufacturing$0.9
🛒 Retail$0.7
🕶️ AR/VR$0.7
🛡️ Insurtech$0.6
🎬 Entertainment$0.5
💼 VC$0.5
🌾 Agritech$0.5
⚖️ Legal tech$0.4
👤 Facial recognition$0.3
🌐 Geospatial$0.2
💪 Fitness and wellness$0.2

Attracting the most money is AI infrastructure, research, and governance, which refers to startups that are building AI applications (like OpenAI’s ChatGPT).

The second biggest focus area is natural language processing (NLP), which is a type of AI that enables computers to understand and interpret human language. This technology has numerous use cases for businesses, particularly in financial services, where NLP can power customer support chatbots and automated wealth advisors.

With $8 billion invested into NLP-focused startups during 2023, investors appear keenly aware of this technology’s transformative potential.

Learn More About AI From Visual Capitalist

If you enjoyed this graphic, be sure to check out Visualizing AI Patents by Country.


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