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Infographic: Generative AI Explained by AI

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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.

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Can Data Centers Be Sources of Sustainable Heat?

Data centers produce a staggering amount of heat, but what if instead of treating it as waste, we could harness it instead?

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Diagram showing how waste heat from data centers could be recaptured and recycled to provide sustainable heat in residential and commercial settings.

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The following content is sponsored by HIVE Digital

Can Data Centers Be Sources of Sustainable Heat?

Data centers support the modern technologies on which we rely, but also generate incredible amounts of heat as waste. 

And since computers tend to be very sensitive to heat, operators go to great lengths (and expense) to get rid of it, even relocating to countries with lower year-round average temperatures. But what if instead of letting all that heat disappear into thin air, we could harness it instead?

In this visualization, we’ve teamed up with HIVE Digital to see how data centers are evolving to recapture and recycle that energy.

How Much Heat Does a Data Center Produce?

To get an idea how much heat we’re talking about, let’s imagine a mid-sized cryptocurrency operation with 1,000 of the most energy-efficient mining rigs on the market today, the Antminer S21 Hydro. One of these rigs needs 5,360 watts of power, which over a year adds up to 47 MWh.

Multiply that by 1,000 and you end up with over 160 billion BTU, which is enough energy to heat over 4,600 U.S. homes for a year, or if it happens to be Oscar season, enough heat to pop 463,803 metric tons of popcorn. Less if you want melted butter on it. 

How Waste Heat Recycling Works?

At a high level, waste heat is recaptured and transferred via heat exchangers to district heating networks, for example, where it can be used to provide sustainable heat. Cool air is then returned to the data center and the cycle begins again.

Liquid cooling is by far the most efficient means of recapturing and transporting heat, since water can hold roughly four times as much heat as air.

Data centers around the world are already recycling their waste heat to farm trout in Norway, heat research facilities in the U.S., and to heat swimming pools in France.

A Greener Future for Data Centers?

Waste heat recycling has so far been voluntary, led by operators looking to put their operations on a more sustainable footing, but new regulations could change that. 

Amsterdam and Haarlemmermeer in the Netherlands require all new data centers to explore recycling their waste heat. In Norway, they require it for all new data centers above 2 MW, while Denmark has taken a carrot approach, and developed tax cuts and financial incentives. And in late 2023, the EU Energy Efficiency Directive came into force, which will require data centers to recycle waste heat, or show that recovery is technically or economically infeasible. 

With Europe leading the way, could North America be very far behind?

HIVE Digital Provides Sustainable Heat

HIVE Digital is already recycling waste heat from its data center operations in Canada and Sweden. 

Their 30 MW data center in Lachute, Québec, is heating a 200,000 sq. ft. factory, while their 32 MW data center in Boden, Sweden, is heating a 90,000 sq. ft. greenhouse, helping to provide sustainably grown local produce, just one degree short of the Arctic Circle.

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Learn how HIVE Digital is helping to meet the demands of emerging technologies like AI, sustainably.

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