Technology
Infographic: Generative AI Explained by AI
Generative AI Explained by AI
After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.
We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.
Everything in the infographic above – from illustrations and icons to the text descriptions—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.
Without further ado, generative AI as explained by generative AI.
Generative AI: An Introduction
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.
Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.
Generative AI has a wide range of applications, including:
- Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
- Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
- Audio: Generative AI can generate new music tracks, sound effects, and even voice acting
Disrupting Industries
People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.
Generative AI has the potential to disrupt several industries, including:
- Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
- Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
- Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences
Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.
In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.
How This Article Was Created
This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.
In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.
Technology
Visualizing AI Patents by Country
See which countries have been granted the most AI patents each year, from 2012 to 2022.
Visualizing AI Patents 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.
This infographic shows the number of AI-related patents granted each year from 2010 to 2022 (latest data available). These figures come from the Center for Security and Emerging Technology (CSET), accessed via Stanford University’s 2024 AI Index Report.
From this data, we can see that China first overtook the U.S. in 2013. Since then, the country has seen enormous growth in the number of AI patents granted each year.
Year | China | EU and UK | U.S. | RoW | Global Total |
---|---|---|---|---|---|
2010 | 307 | 137 | 984 | 571 | 1,999 |
2011 | 516 | 129 | 980 | 581 | 2,206 |
2012 | 926 | 112 | 950 | 660 | 2,648 |
2013 | 1,035 | 91 | 970 | 627 | 2,723 |
2014 | 1,278 | 97 | 1,078 | 667 | 3,120 |
2015 | 1,721 | 110 | 1,135 | 539 | 3,505 |
2016 | 1,621 | 128 | 1,298 | 714 | 3,761 |
2017 | 2,428 | 144 | 1,489 | 1,075 | 5,136 |
2018 | 4,741 | 155 | 1,674 | 1,574 | 8,144 |
2019 | 9,530 | 322 | 3,211 | 2,720 | 15,783 |
2020 | 13,071 | 406 | 5,441 | 4,455 | 23,373 |
2021 | 21,907 | 623 | 8,219 | 7,519 | 38,268 |
2022 | 35,315 | 1,173 | 12,077 | 13,699 | 62,264 |
In 2022, China was granted more patents than every other country combined.
While this suggests that the country is very active in researching the field of artificial intelligence, it doesn’t necessarily mean that China is the farthest in terms of capability.
Key Facts About AI Patents
According to CSET, AI patents relate to mathematical relationships and algorithms, which are considered abstract ideas under patent law. They can also have different meaning, depending on where they are filed.
In the U.S., AI patenting is concentrated amongst large companies including IBM, Microsoft, and Google. On the other hand, AI patenting in China is more distributed across government organizations, universities, and tech firms (e.g. Tencent).
In terms of focus area, China’s patents are typically related to computer vision, a field of AI that enables computers and systems to interpret visual data and inputs. Meanwhile America’s efforts are more evenly distributed across research fields.
Learn More About AI From Visual Capitalist
If you want to see more data visualizations on artificial intelligence, check out this graphic that shows which job departments will be impacted by AI the most.
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