Introduction
AI, or Generative AI, is a bit of a buzzword at the moment, with people talking extensively about the incredible power of artificial intelligence.
But what everyone’s talking about at the moment is not true artificial intelligence, but rather a sort of advanced predictive text based on learning common word patterns and replicating them.
There is nothing truly intelligent about so-called generative AI: it can’t create new things and can only repurpose words and phrases previously written by others. There are significant ethical issues with a lot of uses of AI at the moment, but there are also some very good use cases for generative tools like Auto Blogging.
Let’s take a look at these AI tools and how they work.
The Basics of Generative AI
Generative AI is a sort of so-called artificial intelligence system that can generate a variety of material, such as text, pictures, audio, and synthetic data. The recent hype surrounding generative AI has been fueled by the ease of use of new user interfaces for quickly producing high-quality text, drawings, and movies.
It should be mentioned that the technology is not actually new. Chatbots first used generative AI back in the 1960s; but only since 2014 with the invention of GANs (generative adversarial networks – an algorithmic machine learning program) could GANs produce lifelike photos, videos and audio of real people.
On the one hand, this newly improved system has created prospects such as improved movie dubbing and rich instructional information.
It also raised worries about deepfakes, which are digitally falsified photos or movies, as well as detrimental cybersecurity assaults on enterprises, such as fraudulent demands that genuinely resemble an employee’s supervisor.
Despite these advances, we are still in the early stages of applying generative AI to produce understandable text and lifelike-styled pictures. Early implementations had accuracy and bias difficulties, as well as being prone to hallucinations and spewing forth strange replies.
Nonetheless, development thus far suggests that the inherent potential of this form of AI might radically alter industry. In the future, this technology might aid in the creation of code, the development of goods, the redesign of corporate processes, and the transformation of supply networks.
The Shortcomings of Generative AI
While generative AI systems are great for creating things at high speed, they need very careful oversight. A large language model does not have any critical reasoning ability, so it cannot distinguish between facts and popular misconceptions.
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As such, any output produced by these tools needs to be carefully manually fact-checked, as it will make confident claims of authority that are not necessarily accurate. To prevent disinformation and outright lies, AI text needs to be checked over and properly referenced.
That does not mean that it is all bad! With appropriate fact-checking and manual oversight, AI-generated text can be very useful, particularly in the SEO industry.
However, it is important to be aware of how to make it useful rather than blindly accepting the initial output without any critical evaluation. Remember, this is not true artificial intelligence: it is a language tool, not an actual brain with critical reasoning!
