Artificial intelligence (AI) writing assistants have made it possible to create content fast and with ease. These tools can generate content that matches the input given by the user in a few seconds. That is why some professionals use it to improve writing efficiency and productivity.
The accessibility and capabilities of AI generator paper tools are expected to further improve as hardware advances continue to accelerate. Students can also take advantage of this technology and experiment with their content creation process by selecting an AI essays writer from several options, such as Bard, ChatGPT, and Rytr, says Angelina Grin, a creative writer at Studybay. They can try an AI bot or an AI essay generator in writing essays or other types of content.
Stylus AI is another excellent example of an AI writer. You can not only expect high-quality results from this AI essay maker, but you may also learn how to improve your own writing style using this tool.
What Are AI Writing Tools?
Writing tools are among the commonly used applications powered by artificial technology. Examples are ChatGPT, Jasper, and Google Bard. There are also AI tools, like AI generator paper, designed for creating specific content types.
By now, a digital nomad likely has stumbled upon AI-generated content or used the tool. AI writing tools can write a wide range of materials, from essays to social media posts and email messages. It can generate content in a matter of seconds. The speed makes it a valuable tool for individuals and companies seeking to create content quickly.
AI Hardware: What to Know
AI writing apps are powerful tools, but they won’t run without hardware. AI hardware refers to specialized computer hardware capable of performing AI-related tasks efficiently. It includes integrated circuits and specific chips that can support the execution of complex programs for deep learning models.
The kind of hardware you use in running an AI platform will affect the speed of AI model training.
Specialized Processors Tailored to the Needs of AI Workloads
Once upon a digital age, the CPU or central processing unit was the core of computing. These chips can handle various tasks, from crunching spreadsheet numbers to running video games. But although the CPU can crunch numbers at astonishing speed, it isn’t ideal for AI. AI demands a completely different kind of computational muscle.
Then, the graphics processing unit (GPU) came. It was originally conceived to cater to the demands of video games, but its architecture was well-suited for deep learning tasks. It’s now one of the most common hardware used for processing, particularly machine learning tasks.
And as the demand for AI technology grew, so did the need for more specialized hardware. It led to the development of chips designed from the ground up for AI tasks. An example of these AI chips is Google’s tensor processing units (TPUs). TPUs can work faster and use fewer resources than GPUs.
There are also neural processing units (NPUs), which are designed to accelerate AI computation. It offers speed and efficiency gains in areas like natural language processing and image recognition.
Ideal Memory and Storage for Running AI Models Quickly and Efficiently
AI models can be a data-hungry beast, so they need robust storage and memory that can meet the processor’s demands. A large rapid access memory (RAM) is necessary to train AI quickly and seamlessly.
Regarding storage, the traditional hard disk drives (HDDs) may not be sufficient. AI models typically require fast read-write speeds to run smoothly and efficiently. For this reason, solid-state drives (SSDs) have become the preferred storage in AI hardware setups.
Using AI Writing Tools: Are Specialized Hardware Necessary?
If you’re a professional or student who wants to get help from AI writing tools in creating your assignment, email, and other types of content, you don’t have to worry about hardware. Most AI writing tools are accessible on nearly all kinds of gadgets and devices, no matter the hardware specifications. Most of them only require a stable internet connection.
However, the case will be different if you plan to run an AI or machine learning (ML). The hardware must be powerful enough to handle complex computations. You will need a high-end processor, a dedicated graphics card, and a large amount of RAM. It’s also better to have a device with a long battery life and portable if you’re working on the go.
AI Hardware Accessibility Issue
The AI hardware landscape is constantly evolving, and we are looking at many promising technologies right now. Here are some of them:
- Quantum computing hardware. Quantum computers are much faster than traditional computers. They can also enable AI models to be trained with a high volume of data in a shorter time. Additionally, they can open up possibilities for breakthroughs and developments in the market.
- ASICs. Application-specific integrated circuits are specifically designed for speech recognition and image processing. Its efficiency and task performance can far surpass CPUs and GPUs.
- FPGA. Field programmable gate arrays are specialized chips that can be programmed and customized to meet the specific needs of the AI ecosystem. Its inherent flexibility allows for a broad array of applications in the field of AI.
Innovations in processors, accelerators, and chips can unlock more potential for human-like learning. But this high-performance AI hardware does not come cheap. The AI hardware cost can be a barrier for researchers, start-ups, and institutions in regions with limited resources.
Experts are fully aware of the accessibility and cost issues. Therefore, to make AI available to a wide range of organizations and people, there’s a movement called AI democratization. And one of the three keys to this democratization is accessible, ubiquitous hardware.
Some leading companies are already part of the movement. One of them is Intel, which works hard to ensure that AI benefits are available to all. They address the accessibility issue by incorporating AI accelerators directly into their AI hardware, like some of their processors.
Use AI Writing Tools With Caution
While the advances in AI hardware will make AI writing more accessible, users should not completely rely on this technology. AI writing still has a long way to go. Right now, these tools still have their limitations.
One of the biggest problems with AI writing tools is accuracy. They can confidently present inaccurate information as a fact. But that’s just the way they work for now. AI writing tools scan pre-existing content and utilize it as a reference to make new content. Nevertheless, poor accuracy is a serious concern, especially if you’re writing academic papers.
Most AI writing tools, particularly those available for free, also rarely have unique insights. As a result, the content becomes boring and hard to read. Audiences with attention disorders and other disabilities that affect reading may find reading an AI-generated text frustrating.
Sources:
Ali, W. (2023, June 5). The 5 most promising AI hardware Technologies. MUO. https://www.makeuseof.com/most-promising-ai-hardware-technology/
Is A.I.-Generated Content Bad for Accessibility? (2023, May 25). Bureau of Internet Accessibility. https://www.boia.org/blog/is-a.i.-generated-content-bad-for-accessibility
How AI is accessible to all, regardless of technical background. (2023, August 23). Washington Post. https://www.washingtonpost.com/creativegroup/intel/how-ai-is-accessible-to-all-regardless-of-technical-background/
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