These 8 Pivots by Startups Changed the World
How do successful companies get built? Is there a predetermined formula or ideal circumstances to get off on the right foot as an entrepreneur?
When it comes to the technology world, the truth is that the most successful companies come in all shapes and sizes. Once in a while, strategy and its execution go as planned – but more often than not, a company must change its entire basis to get its best shot at winning.
In the startup world, this is called a “pivot”. It’s a risky change of direction that could end up as a game-changing success or a resolute failure. Circumstances can change fast to prompt such a desperation move. With technological progress growing at an exponential rate, in many tech-focused businesses such pivots can even be the norm.
There are many reasons a company may shake up its strategy. Maybe the customer response isn’t what was expected, or perhaps intuition suggests that a product could be used another way with a few modifications. Sometimes a mentor or friend may have a different vision on how something can be used, and other times a competitor can apply pressure to an early-stage startup by offering a similar or better product.
I know something about pivots myself, as this website (Visual Capitalist) is the result of a few of them. We first started as a marketing consultancy, and then we gambled at the idea of using infographics to supplement the press releases of microcap public companies. Neither of those really were effective, but we still loved the idea of explaining the business and investment world with rich visuals – and eventually Visual Capitalist was born.
Similarly, many other companies that we cherish would not exist without these types of strategic pivots. Twitter, Paypal, Nintendo, and many others were born under completely different circumstances than we know them today. Nintendo built vacuum cleaners and made instant rice until they thought the video game industry could be an interesting market. Nokia, which in the late 2000s was one of the biggest mobile phone makers by market share, used to have a Finnish paper mill and manufacture rubber goods in its early stages.
Today’s infographic looks at eight of the startup pivots that have changed the world.
Original graphic by: WhoisHostingThis?
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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