The idea of using modern tech to transform the multi-trillion dollar healthcare industry has been around for a long time.
In 1996, legendary Silicon Valley entrepreneur Jim Clark launched his third startup, Healtheon, which was focused on what he called the “Magic Diamond”. The diamond represented the $1.5 healthcare market in the U.S. and its shape came from the doctors, providers, payers, and consumers slotted into the four outer points.
In the middle of the diamond, Clark had placed his new company Healtheon, which he expected to profit immensely from connecting the healthcare world together with the internet.
Before Its Time?
Healtheon had a successful IPO in the middle of the Dotcom bubble, but it never was able to truly achieve its bold and original vision. As signals mounted that Dotcom stocks would implode, the fledgling company merged with WebMD in 1999.
Despite the fate of Healtheon, the dream of tech invading the healthcare market lives on – and today, big tech companies like Amazon, IBM, Alphabet, and Apple all have plans to enter the sector in a big way.
Today’s infographic from Koeppel Direct shows how this is all playing out, as well as the specific initiatives that big technology companies are using to gain a foothold in a market that’s ripe for change.
The story is no longer about the startups coming in to “disrupt” healthcare – unfortunately, the industry seems to have too much red tape, regulation, and bureaucracy for this to be possible in the conventional way. Instead, it’s the big companies like Amazon, Apple, IBM, and Alphabet that are eyeing to invade the space.
And for technology companies focused on big data, the healthcare market is a compelling opportunity.
Healthcare Market Potential
By the numbers, here is a snapshot of the healthcare market, and why big tech wants in:
- Global healthcare spending is expected to reach $8.7 trillion by 2020
- In the U.S., there will be 98.2 million people aged 65+ years by 2060
- Diabetes will affect 642 million people globally by 2040
- 70% of healthcare firms are investing in consumer-facing tech, like apps, remote monitoring, and virtual care
- Wearable tech could drop hospital costs by 16% over the course of five years
- Remote patient monitoring tech could save the healthcare system $200 billion over the next 25 years
- Over 80% of consumers say that wearable tech has the potential to make healthcare more convenient
- 88% of physicians want patients to monitor health parameters at home
Scientific advancements and technology have already been responsible for saving billions of lives through history, and now it’s time to see if big tech can step up to the plate using AI, augmented reality, big data, and other technologies to do more of the same – especially if it helps move these companies closer to the center of the “diamond”.
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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