In the modern world, Artificial Intelligence, or “AI”, is used in an exponentially increasing number of applications, the purpose of which is to make many of the repetitive, mundane decisions for us. However, AI often struggles with tasks that traditionally rely to some extent on human creativity. One of those tasks is producing written documents – books, articles etc, but several software providers offer exactly that service. My interest piqued, I signed up for a trial of https://ai-writer.com and asked its AI: “can AI write like a human?”
What it produced (provided below) was surprisingly well-written, with clear indications that the AI understood the task that I had presented to it and could fairly easily pass for a piece of work written by a human. Where it falls short, I think, is that the article lacks a coherent structure that you would expect to find in a human-written piece – a clear “flow” to the article. Even with this criticism in mind however, the article produced by the AI represents the rapid development of AI capabilities seen in recent years, and development which we can expect to witness continue into the future.
AI uses technology called deep learning and natural language processing to harness millions of existing patterns from which AI databases can be drawn. Deep learning is an artificial intelligence that tries to mimic the way the human brain functions and how data patterns are handled. This is achieved by processing data patterns, while natural language processing attempts to analyze and generate language as humans actually use it.
The aim is to create a sound from an artificial piece of content. In this process, the computer learns to read and understand human language. Other implementations of AI generation from natural language allow the organization and processing of large, artificial data sets.
Organisations that implement solutions to generate natural language can create thousands of new narratives in a fraction of the time it takes a person to write one. Nowadays, computers can write novels like Jack Kerouac-inspired narrative road-trip poetry, and natural language generation has been used in award-winning novels. If one works with complete confidence that machines can write with the same creativity and innovation as humans, this development suggests that human creative endeavors enable high-quality writing without glitches.
Computer scientists are writing next generation of automated content using the latest artificial intelligence (AI) on typewriters using the latest technology. It’s hard to ignore the hype around AI-based text generation in content marketing, where a great number of tools for everyday tasks are already in use. For journalists, this is the next step, and we look forward to seeing which of the best tools for writing articles, blogs and relevant words (ahem, training authors) will be abolished.
A consistent brand voice is one of the most valuable features you can have when there are multiple contributors to your content stack. It is not the magic ointment that your company has a writing problem, but a useful tool that integrates into professional structures for generating content.
Earlier this year, it was revealed that a new AI-based speech generation software, GPT-3, has attracted a lot of attention due to its ability to generate scriptures like a human. With Quillbot, a paraphrasing tool with great integrations helping you to rewrite and improve sentences and paragraphs, this article uses a state-of-the-art AI-based word selection for short, concise content that conveys a message. This article is based on an advanced AI-based platform that generates unique and high quality articles in just a few seconds.
This breathless reporting reveals the natural collusion between people’s heads, appearance, language, and ability to think. As indicated above, it is widely believed that Artificial General Intelligence (AGI) is capable of understanding and performing tasks better than humans. The question arises with the publication of the Open AIs GPT-3 text generator, whose output is unrecognizable from human writing.
The biggest breakthrough in AI writing comes from the Open AI Generative Pre-trained Transformer (GPT) model. GPT is a bilingual algorithm used by machine learning to write text.
GPT-3, the largest artificial voice model, has been trained on an estimated 4.5 terabytes of text and runs on 1.75 billion parameters. It’s more like autocompleted generated code than writing stories like humans, but it still makes mistakes like humans. Human oversight of GPT in production applications is why it has the potential to raise concerns.
Although AI software is capable of producing technically correct text for humans, it still lags behind us humans in terms of common sense. It is becoming increasingly difficult for people to see the difference between an article written by people and an article written by a machine.
A team of computer scientists from the University of Southern California (USC) in the United States and the University of Washington (Allen Institute for Artificial Intelligence) has developed a new test to analyze the verbal thinking abilities of machine learning systems. Faced with a list of simple nouns and verbs, the model processes natural language and commissions a series of sentences to describe a common scenario.
It all started with GPT, or GPT-2, an AI speech generation model that can generate human-sounding language on a scale. When it was first released in 2019, GPT wowed the world with its ability to create long-term content in a variety of styles for the enormous amount of content available on the Internet. Last month, software developer Kevin Lacker conducted the “GPT-3” test with the latest version of the artificial intelligence-based voice system developed by San Francisco-based software company OpenAI LP.
Porr explains that language generation programs often use formulaic typefaces, such as sports coverage, because these typefaces report numbers that don’t require much analysis.
For lack of creativity, AI can only cope with writing content if it relies on data provided by humans. The wrong kind of randomly generated articles could lead to lost readers. That does not appear to be a real threat to the journalism foundation, which Porr says could be disbanded by understaffed editorial offices.
The complexity of human thoughts and emotions in human content far exceeds what an AI can select the right words to click with other humans. AI authors can filter content from a database to mimic intelligence, but they cannot create human emotional ties. Content can help customers build relationships, but AI writing cannot compete with a real person’s brand in terms of feelings, experience, understanding and goals.
In theory, it can predict the next word based on what has already been written. Companies like Tesla are trying to build AI systems that can do this and focus on human drivers to scale back their efforts to build autonomous cars that will transform society and save millions of lives – which is their most fundamental goal.
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