Most Overhyped Sectors in Tech
What founders think about emerging technologies
The Chart of the Week is a weekly Visual Capitalist feature on Fridays.
Founders are at the very ground level, and their pursuits have a ripple effect on the entire startup ecosystem.
As a result, how entrepreneurs think about different subsectors within tech is of utmost importance. Not only do their perceptions influence what projects they themselves choose to build, but how founders allocate their time and energy may also be a useful gauge of where future economic potential lies.
Today’s chart focuses on what entrepreneurs think of specific technologies, using data from a survey of 869 entrepreneurs that was done by First Round Capital.
Seeing Through the Hype
In the survey, entrepreneurs were asked to give their opinions on 14 different technologies, on whether they were overhyped or underhyped. Entrepreneurs could also answer “neutral” to any of the questions.
Here are the three technologies that were considered the most overhyped:
1. VR/AR: 65% Overhyped
VR has been the “next big thing” for many years, with still a minimal consumer footprint. It’s not surprising that entrepreneurs see this sector as overhyped. For companies like Facebook and Magic Leap to reverse the perception of VR/AR, they’ll need to get consumers adopting these technologies at a faster rate.
2. Wearables: 64% Overhyped
When Google Glass first came out in 2013, hype about a future filled with wearables seemed inevitable. Now it’s almost five years later, and wearables haven’t delivered on the scale that many entrepreneurs thought was possible.
3. Chatbots: 61% Overhyped
Will chatbots really change customer service, health, and other industries? Most entrepreneurs seem to be a little skeptical about their potential impact.
Diamonds in the Rough?
Entrepreneurs also thought some sectors deserve more attention – and this is where there may be some potential opportunities for investors or new founders.
1. Agtech: 57% Underhyped
Farming is not flashy, but entrepreneurs recognize agtech as something that city slickers should pay more attention to. New tech is making agriculture more sustainable and urban, while increasing crop yields.
We covered some of these interesting next generation food systems in a previous infographic post.
2. Life Sciences: 55% Underhyped
Advances in areas such as longevity, genomics, and biotechnology are unnerving to some people, but life sciences seems to be at a tipping point. Founders see this as an area that deserves more attention from the media and investors.
3. Security: 51% Underhyped
Last year, $450 billion was spent on cybersecurity – and this number is growing fast as the IoT becomes even more prevalent. Stopping hackers is not flashy, but it is vital to the global economy and many dollars will be spent on it in the coming years.
Infographic: Generative AI Explained by AI
What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.
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
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.
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