But while these articles read naturally and appear human-written to real readers, there has been worry about AI detection, penalties and even general content rejection.   

So, we took action and today, we are excited to announce a new feature that makes Article Forge content pass any AI content detector.

How Does Article Forge Pass AI Content detection?

All you need to do is activate the “Avoid AI Detection” toggle and Article Forge content will pass every single AI detection tool at the same rate as human content. In other words, your content will be indistinguishable from human content!

What AI Detectors Does Article Forge Pass?

All of them. This feature makes Article Forge content appear human-written to all machines, even future tools. 

But we’ll let the data speak for itself. We ran a case study to test which popular AI writers pass and fail the most popular AI content detection tools.

You can read the results of the AI content detection case study here.

Will Article Forge Content Pass AI Detectors Every Time?

When this feature is enabled, Article Forge content will pass AI detectors at the same rate as human content. However, AI content detectors are not fully reliable. For instance, OpenAi’s blog post announcing their AI detector states multiple limitations and Originality.ai warns of false positives:

Any tool that would classify Article Forge content as AI generated, would also incorrectly classify human content as AI generated at about the same rate.

What Does This Mean for Content Producers?

Article Forge uses AI to write useful SEO articles. 

This update builds on that foundation of good content to give content producers confidence that Article Forge content appears human-written to actual readers and AI detection tools.  

The post Article Forge Update: Pass AI Content Detection appeared first on Article Forge Blog.

Here’s what is new:

Core AI Update: Our Biggest AI Quality Improvement to Date

We know this is a big claim, and we did release an update just two months ago… but progress does not happen in a straight line.

Generative AI is moving at breakneck speeds and our latest breakthroughs make Article Forge content: 

• More fluent
• More accurate
• More diversely structured (nested sections, lists, more sentence and paragraph variation)
• Less repetitive

Complete Control Over What Article Forge Writes

You can now instruct Article Forge on exactly what you want it to write about.

Instead of just asking Article Forge to write about the keyword “FTX scandal”, you can now tell Article Forge to:

You can write whatever you want in these instructions – so your articles come out exactly how you want them.

With instructions, you can create even more diverse, detailed, and high quality content with Article Forge. Check out this best practices post for tips and examples!

Write Articles That Are Unlimited Words

You can now write infinitely long articles directly in the Article Forge editor.

Once you create your article, you can have Article Forge extend it indefinitely, writing as many headers, subheaders, and sections as you want.

Using this, we have created articles that are 20,000+ words!

What’s Next?

The combination of these three updates makes it even easier to create truly useful articles with minimal time and effort. 

But, we’re not stopping here, our team of machine learning engineers and linguists are still hard at work. And, in the next few weeks and months, we will be releasing even more core AI improvements and features to make sure you can easily get even higher quality, useful content from Article Forge. 

So if you are not already using Article Forge to revolutionize your content creation process, there is no better time to start than today!

Happy forging!

The post Article Forge 4.5: Major Quality Improvements, More Control Over Articles, Infinitely Long Articles appeared first on Article Forge Blog.

This recognition is based on the responses of real uses for each of the content creation related questions featured in the G2 review form.

Article Forge achieved the High Performer award on the G2 Winter report by receiving positive reviews from verified users compared to similar products in the content creation category.

“Rankings on G2 reports are based on data provided to us by real software buyers,” said Sara Rossio, Chief Product Officer at G2. “Potential buyers know they can trust these insights when researching and selecting software because they’re rooted in vetted, verified, and authentic reviews.”

A few highlights from what customers are saying about Article Forge:

Learn more about what real users have to say about Article Forge on G2!

About G2

G2 is the world’s largest and most trusted software marketplace. More than 80 million people annually — including employees at all of the Fortune 500 — use G2 to make smarter software decisions based on authentic peer reviews. Thousands of software and services companies of all sizes partner with G2 to build their reputation, manage their software spend, and grow their business – including Salesforce, HubSpot, Zoom, and Adobe.

The post Article Forge Named a High Performer by Real Users in the G2 Winter Report appeared first on Article Forge Blog.

Since being released in 2020, GPT-3 has become synonymous with artificial intelligence and text generation. Countless research papers have been released analyzing its capabilities, ranging from its ability to problem solve, answer questions, tell jokes, and more. GPT-3 has been featured in every major news organization under the sun, and it seems a startup built around GPT-3 emerges every other day.

For the customers of these startups, using GPT-3 to write text has become almost synonymous with using AI to write text.

Ultimately, OpenAI, the creators of GPT-3, have created the best marketed AI model¹ of all time.

But the stratospheric rise of GPT-3 has stifled better approaches. Two years might not seem like a long time, but in the fast moving field of artificial intelligence, that might as well be a decade.

While AI researchers continue to devise even more impressive ways of writing content, end users of AI powered tools are stuck using outdated technology.

Where is GPT-3 Strong?

Now with that being said, GPT-3 does have several strengths – the biggest one being its flexibility. GPT-3 was trained on a large portion of the internet, and the internet is very diverse. People write all sorts of things: Pop culture stories, persuasive ad copy, educational material on preparing for the MCAT, trivia about US history, philosophical discussions on artificial intelligence, and everything in between.

By training on all of this data, and due to its very large size, GPT-3 has learned to do many of these tasks without requiring extra engineering, research, or training. This makes GPT-3 a great swiss army knife for prototyping new ideas – especially if you lack expensive GPU resources or machine learning research expertise.

Some different applications for this could include “taking a positive review and making it into a negative one,” “write marketing copy about a product with these five features,” or “take all of this data and turn it into a two sentence summary.” A single model that can do all that with no coding required is quite powerful!

Another great advantage of large language models like GPT-3 is that they have memorized a lot of information. If you ask GPT-3, “How many inches are in a meter?” it will correctly answer “39.37”.

When combining these two features together, you have something that can, with almost no engineering effort required, write generally decent content that is mostly accurate.

The Downsides of Being “Mostly Accurate”

I said above that GPT-3 was trained on the internet, and while reading the internet, it memorized quite a lot of the information it read. This is very useful in some cases, but this can also be quite disastrous in others.

If you ask GPT-3 who the current president of the United States is, you will receive back “Donald Trump” – who has not been the president since 2021.

The problem is that GPT-3 was trained once and memorized everything during that training. However, since then, the world has changed, and GPT-3’s knowledge has grown stale and out of date.

There are other situations where GPT-3 is just flat out wrong. When asked what month Volodymyr Zelenskyy (the current president of Ukraine) was born, GPT-3 confidently and incorrectly declares December. He was actually born in January.²

Why is this? Zelenskyy was not commonly talked about when GPT-3 was first trained, meaning that GPT-3 never assigned any importance to “memorizing” anything about him. Now he is important, but GPT-3 never got the memo.

This can reflect itself very dangerously when you have GPT-3 actually write text:

GPT-3 writes text very confidently and is often accurate, but it also is often disastrously inaccurate.

The Downsides of Being Closed Source

Despite the name OpenAI, GPT-3 is one of the few models where the weights and code are completely closed. Except for Microsoft, who is a part owner of OpenAI, nobody else is allowed to modify or study the internals of GPT-3, making it impossible to apply new research techniques.

For many people, this is not a big deal. They are not engineers or researchers. They simply want an easy-to-use API that mostly works, around which they can quickly build a product to sell. (This has led to a flurry of undifferentiated products that are largely clones of each other, all with the same problems and limitations.)

However, to researchers trying to improve the field, this opaqueness is a stop sign that prevents further iteration and improvement. This is in stark contrast to Google and Facebook, who release their work publicly to try to further AI research.

If you are looking for an example of open source versus closed source, look no further than image generation. OpenAi released Dall-E 2 earlier this year. But within months, it was completely overshadowed by Stability.ai, which released a similar model called Stable Diffusion, but open source. Immediately researchers got to work improving and iterating on it, leaving Dall-E 2 in the dust only months after it was released.

The same fate is happening with GPT-3. It is falling further and further behind in industry AI benchmarks³, and its closed-ness prevents the real tweaking that is required to help it catch up.

And for people looking to use AI to create content, there is no way to truly tailor it to writing large amounts of high quality, accurate text. There is a way (by paying OpenAI) to lightly tune the model, but no way to do the level of changes required to turn it from a novelty to something great.

Is There a Better Alternative?

Outside of GPT-3, research into AI content generation has been moving at a brisk pace. Researchers have found various major inefficiencies in how GPT-3 was trained and have managed to create even better language models at smaller sizes.

But, one of the most important evolutions has flown largely under the radar: a language model capable of doing its own research.

The truly great researchers are in the know. Adept.ai, founded by Google researchers who were responsible for inventing transformers (which GPT-3 is a type of), just released a new prototype that is able to use Wikipedia to fully research and answer any question.

LaMDA, the chatbot built by Google that is so good, one of its creators was convinced it was conscious, does its own research in the background to help better answer chat queries.

Our product, Article Forge, uses AI to create high quality, accurate, and helpful long-form articles in a single click – it is an end to end article writer rather than a writing assistant. We are doing the same thing as Adept.ai and LaMDA, but specifically for article creation – and to that end, we have built our own knowledge search engine.

First, An Important Note About Google

A lot of this pioneering work is being done by Google researchers. This should not be surprising – Google is itself a search engine. Their entire business revolves around accurately answering questions from users using the internet.

When you search “who won the last football game” or “Volodymyr Zelenskyy birthdate,” Google needs to give you an accurate and up to date answer. Google can’t return that Donald Trump is the current US president.

So you can expect when Google returns search results, it is using facts and information it has gathered from all across the internet to verify whether something is accurate and helpful.

(By the way, this is a topic we have discussed at great length with real AI researchers working at Google!)

So if you are generating SEO content with an AI tool that doesn’t research, not only will your users realize the information is inaccurate, but Google will as well. And if you are generating content and don’t care about SEO – well you probably still want your content to be accurate… right?

What Is a Knowledge Search Engine?

You are probably already familiar with a normal search engine – you enter a query and get back results. Our knowledge search engine is also like that but built specifically for machines.

Instead of taking search queries a user would write, this search engine takes queries that a machine would write. Our AI is able to give this search engine its entire thoughts about what it is writing, how it is planning on writing it, all of the topics it wants to cover, and the search engine will give back results that are geared entirely towards helping it write that content.

The results this search engine returns are also different. Instead of returning websites, it returns key pieces of knowledge in a way easily digestible by machines.

This search engine is almost like if you could hook Google directly up to your brain, where it can read your mind and then upload the facts and knowledge that answer your question directly back into your brain.

This Makes Content More Accurate But Also More Insightful

It is not hard to understand why AI (and Article Forge specifically) would benefit from a search engine built directly for it.

Unlike GPT-3, this allows Article Forge to write with reference material to ensure that what it says is accurate and up to date. It also can judge the quality of the reference to make sure it isn’t writing fake news. When it writes something inaccurate, we can trace back the bad information it was given, so it doesn’t repeat the same mistake.

But also, there is another big advantage. GPT-3 is a very large language model with a very large “brain,” but a huge portion of that “brainpower” is devoted to memorizing things. Since GPT-3 doesn’t do outside research, it needs to rely on its own memory – which we showed above is prone to mistakes.

Since our AI is not burdened with this requirement, it is instead able to use its brainpower to work on drawing insights from the data it is given. It can take the portion of its “brain” devoted to memory and instead use it towards “intelligence”.

It is very similar to if you were studying for an exam. If it were a closed book exam (you couldn’t use any reference material), you would have to spend all of your time memorizing that reference material. If it was an open book exam (you could use whatever reference material you wanted), you could instead use that time to come up with more insightful and useful ways to use that information.

All of these factors combine together in a way that makes Article Forge content more accurate and more useful than content written by GPT-3, or any of the writing assistants powered by it.

We Control Our Destiny

Of course, I’m not going to promise that at the writing of this blog post, the content Article Forge writes is 100% perfect 100% of the time (they are really good though!). You will almost certainly want to proofread the content yourself – but then again, you’d probably do the same thing no matter how you were getting your content.

But what I can promise is that since we have built these models ourselves, we are in control of our own destiny. We aren’t reliant on another company for models, and we aren’t even reliant on investors. Despite taking no outside funding, we have still grown to be 20 people strong.

Even more importantly, where most companies that use GPT-3 are largely staffed by marketing people, 70% of the company (14 of us at the time of writing) are Machine Learning Engineers or Linguists working directly on improving the quality of our AI.

So we are in control of our research roadmap and can tailor it specifically to solving our users’ problems – writing a high quality and factually accurate long-form article in a single click.

And the rate of AI research, both internally and externally, is moving at a breathtaking pace. As these incredible advancements continue, Article Forge will be the first tool to deliver them to end users – no need to wait on a 3rd party to update their API!

So no matter what your opinion is of AI generated content right now, pay close attention to this field. What seems impossible and out of reach now will become commonplace and easy in the blink of an eye.

Footnotes:

The post Why We Don’t Use GPT-3 appeared first on Article Forge Blog.

Here’s what is new:

Huge Update to Article Flow and Cohesion 

We take customer feedback very seriously and we’ve heard people say many variations of:

• Your articles are sometimes disjointed
• There needs to be better flow between paragraphs
• Paragraphs can get repetitive

And our customers are right, long (especially 1,500+ word) articles need to be well organized and flow naturally – you can’t just have a wall of repetitive, disjointed, and unfocused text!

With this update, Article Forge 4.0 writes more coherently, giving you a true article rather than a collection of semi-related paragraphs.

The Ability to Exclude Topics

Another piece of feedback we have heard more recently is that customers want more control over what Article Forge writes about. When you are writing about a product or service, you want your brand mentioned and not your competitors!

Or maybe you generated an article and Article Forge wrote about something that missed the mark a little bit.

With this update, you can now tell Article Forge what topics or talking points to avoid, making Article Forge the only tool that gives you this level of control.

Learn more about how Excluding topics can give you higher quality, more focused articles

Support for Additional User Seats for Employees, Contractors, or Virtual Assistants

We know many times you aren’t the only person trying to create articles to fill out your content pipeline and sharing accounts is cumbersome and risky.

Now, Article Forge supports adding multiple user accounts to your subscription. And, you can control what level of access each user has, so you can produce content at scale without worrying about logistics.

What Comes Next?

While these new features will help you create more useful, cohesive and focused content. We are nowhere close to finished developing Article Forge. 

In fact, we are already working on prototypes for our next major updates. Our team of engineers and linguists are working on projects that will not only improve the core AI, but will make Article Forge even more flexible and will give you even more control over how your articles turn out. 

So if you’re not already using Article Forge to boost your content production, there is no better time to start!

The post Announcing Article Forge 4.0: Improved Article Flow and Cohesion, More Control appeared first on Article Forge Blog.

Article Forge Grades It’s Content as It Writes

When humans write content, we very rarely write the entire piece in one go. Instead, we usually write something, revise it, then write something else until we have fully refined our text. This helps us make sure we are writing the highest quality content we can.

The same is now true Article Forge. For this update, we trained a model to grade the quality of the content Article Forge writes. This model evaluates each sentence Article Forge writes on:

• Accuracy
• Relevancy
• Sentence structure and flow

Using this information, Article Forge creates a final grade for each sentence. 

This model was trained to grade content by learning from thousands of hours of intense work from our team of linguists. And this “grader” model shows superhuman (better than human) performance at determining the overall quality of an article.

Article Forge Writes Eight Drafts for Each Sentence

Of course grading a bad sentence and improving a bad sentence are not the same thing.

So, for each sentence Article Forge would normally write, it now writes eight versions, and our content grader picks the best one. By doing this for each sentence, Article Forge is able to consistently write higher quality articles, all without any human involvement!

This Improves Article Quality By 57.34%

To test the impact of this new grader, and this new update, we created thousands of articles – half without this new content grader (old Article Forge), and half with this new content grader (this new Article Forge update).

We then created a double blind test where real humans were given an article about the same keyword written by both, and the humans were asked which of the two articles was higher quality.

The results of this experiment shows that this new update led to a 57.34% increase (p=0.0000000000) in article preference.

What Does This Mean For You?

Article Forge now goes beyond simply writing a first draft. Using our content grader, Article Forge makes sure it is writing the highest quality sentence possible at each step, leading to an overall much higher quality and more polished article.

Instead of spending significant time writing manually or $1000s buying content from freelancers, Article Forge handles the entire writing process for you and delivers complete, high-quality articles with the click of a button.

While you just have to enter a keyword, Article Forge will:

• Research your topic (learn more)
• Plan out all the points it will cover throughout your article – including section headings (learn more)
• Write multiple versions of each sentence and only use the highest quality content
• Deliver a full, high quality piece of content

There is simply no faster or cheaper way to produce high quality content.

Where We Are Heading

Although our content grader consistently picks the best sentences, it is still limited by the eight options it is given. 

Moving forward, we will be using this grader to train our article writing model. Like how a teacher may train a student, our grader will continually train Article Forge to write higher quality content.

In addition to this, we have several other major updates planned in the next couple of weeks and months.These updates will include: new content types, new functionality, and other major quality updates. 

So make sure to be on the lookout for the latest news and updates from Article Forge!

Until then, happy forging!

The post Article Forge Update: 57.34% Better Articles with our new Quality Grader appeared first on Article Forge Blog.

Along with these major quality improvements, Article Forge is now the only AI writer that can create 1,500+ word articles with section headings… all completely automatically.

Check out this video to watch Article Forge generate a 1,500+ word article in a single click. 

How we got here

Last November we launched Article Forge 3.0, which introduced a real-time research component that led to more accurate and relevant articles.

In short, that update gave Article Forge the ability to research each keyword in real-time to understand what type of content is ranking and what information is relevant to readers and Google. 

This was a huge step forward in Article Forge’s ability to write accurate, up-to-date, and relevant information about any topic.

And once that research component was introduced, we redesigned the rest of the article creation process to boost quality in the following ways:    

More organization

With this update, Article Forge now uses its research to create an entire outline for each article before writing, spanning from section topics all the way down to the talking points for each paragraph. As a result, each paragraph has a focused and unique point that will provide value to your readers.

Article Forge’s new planning step approaches article writing in the same way that many humans do, just in a fraction of the time. 

Planning out each article before writing it also lends itself naturally to including section headings for each subtopic covered, resulting in much longer, more structured, and higher quality articles overall.

More topic control

Article Forge’s research and planning components allow it to write about relevant subtopics automatically. But, because Article Forge writes a completely unique article every time, your keyword could lead to many very different articles. And in some cases, you might have a more specific goal for your article where you might want to control the direction your article takes. 

So, with this update, we added the ability for you to enter your own section headings to tell Article Forge exactly what to write about at each point in your article. 

Taking the example above, Article Forge now allows you to specify the different sections within the automatically generated outline it creates for each article. 

Learn more about how Article Forge can write 1,500+ word articles automatically and how you can enter your own section headings for more control over your articles. 

Less repetition     

Because Article Forge now plans out full outlines before writing, it knows to focus on multiple different topics throughout each article. This results in much less repetitive articles because once Article Forge has covered a topic, it moves on to the next topic in its outline. 

Beyond this, when writing, Article Forge now knows when it has written about something already and has been taught specifically not to repeat itself. 

Not only do these updates decrease repetition, they increase the variety of relevant information included in each article. This leads to more comprehensive and diverse articles of all lengths. 

More accurate

Most popular text generation models are only able to write from their internal memory. This causes huge accuracy issues because: 

1. Information is constantly evolving and each model was trained at one static time in the past. So, the models will be unaware of any new or updated information that developed after that point in time.
2. No model is big enough to know everything from memory. So at some point, they have to start making things up to fill the gaps in their knowledge. 

Adding a research component was a huge step forward for generating accurate content. 

But with this update, Article Forge now also fact checks every single sentence it writes, and if it writes a sentence that it finds to be inaccurate, it will delete it and write a new one. This built in verification step makes your content more accurate and up to date.

Where we are heading

Planning out each article before writing is a major step up in quality. But more importantly, it opens up multiple new avenues for us to continue to make major quality improvements in the following months. 

Whether you want to produce high quality content with as little input as possible or you want to automate content generation with more control, this update will help you revolutionize the way you get high quality, long form content.

In the next few months and beyond, we will continue to push the quality of automatically generated content to new heights. So make sure to be on the lookout for the latest news and updates from Article Forge!

The post Article Forge Update: Increased Accuracy, Organization, and Length appeared first on Article Forge Blog.

Recently, forward strides in AI content generation have begun to offer a third, more efficient option. And here at Article Forge, we are investing heavily in creating a true AI writer.

Over the last year, we doubled the size of our AI team and focused all our efforts on creating articles that not only flow naturally but are relevant, accurate, and useful.

And today, we are excited to announce Article Forge 3.0!

In this article:

I will briefly cover the current state of natural language generation and why this update puts Article Forge in a league of its own.

Then, more importantly, I will go over what Article Forge 3.0 means for your content pipeline, show you an example, and highlight where we plan to go from here.

A brief background on the current state of AI text generation

In the last few years, the buzz around AI content generation has skyrocketed. This is largely thanks to groundbreaking advancements in deep learning language models from tech leaders like Google, OpenAi, Facebook, and others. Most significantly, these models have been trained on massive amounts of information (billions of data points) to understand and write text the same way a human does.

These breakthroughs have led to the increased popularity of AI generated content. However, even the leading models are plagued with one significant problem: accuracy.

Writing from memory != accuracy

Without going into the technical details, modern language generation models write using their internal (also known as parametric) knowledge (memory). This knowledge is gathered when the models are trained on large amounts of content. However, given the nearly infinite (and constantly growing) amount of information that exists, it is impossible for a model to “know” everything, let alone restate its “memorized facts” properly. Therefore, these models are forced to make probabilistic predictions based on the information they do have. 

These models can usually write plausible, naturally readable articles about general or simple topics because their memory likely includes that information. However, when the topics become more complicated, specific, or timely, the models struggle because they don’t have enough internal knowledge to write a natural or accurate article. Specifically, when these models don’t have enough internal knowledge, they are forced to just repeat the same information or worse, make things up.

One of the major goals of Article Forge 3.0 was to address this inability for models to adhere to a set of facts. More broadly, Article Forge 3.0 aimed to introduce the ability for our deep learning models to research any topic in real-time as they write. 

Introducing Article Forge 3.0

Over the last few updates, we have built our own deep learning models and trained them to write naturally readable articles from scratch, just like the popular models referenced above. 

However, with Article Forge 3.0, we took an important step further. We also built our own research (retrieval) models and algorithms to provide Article Forge with relevant factual information as reference material while it is writing. With these improvements, Article Forge writes articles that are unique, high quality, and factually accurate!

What this means for your content creation pipeline

Article Forge 3.0 can write accurate and relevant content about more topics than ever before

By adding real-time research components, Article Forge can produce articles that not only read naturally, but include accurate and relevant information. This also allows Article Forge to write higher quality content about current events and more nuanced and complicated topics than ever before.

I don’t think I need to explain why it is more important than ever to have accurate and relevant content in your pipeline, especially about new and breaking topics.

Article Forge 3.0 content is SEO optimized

You can’t talk about SEO content and not discuss Google. For years, Google has been using deep learning models to provide more relevant search results for any given query. Most recently, Google introduced their MUM technology to help their existing Deep Rank algorithm better understand and judge content relevancy. 

This MUM technology is based on the same framework that Article Forge’s models use to decide what related information to include when writing about your main keywords. Because of this, Article Forge’s content is naturally designed to include content that Google and normal people find relevant, resulting in articles that rank and provide value to your readers.

In addition, as Google continues to roll out new deep learning updates to judge the quality and relevancy of content, it will become increasingly effective to use a tool that automatically optimizes for these algorithms.

Article Forge 3.0 creates long-form content from a single input

One of Article Forge’s most significant differentiators is its simple, one-step process to create long-form content. Instead of walking through the entire writing process step by step with other AI tools, all you have to do is enter your keyword(s) and Article Forge will research and write an entire, SEO optimized article for you from scratch. 

With the increase in quality from the 3.0 update, the articles could be good enough to use as is. But even if you want to use Article Forge content as a first draft, you will be saving significantly more time and effort than using an AI writing assistant.

One of the biggest impacts of this streamlined process is how easy it becomes to scale your content strategy. Whether you want to fully automate your content calendar or simply move content through your existing pipeline faster, Article Forge 3.0 is the most efficient option available. 

Article Forge 3.0 allows you to control the tone and style of content

Last but certainly not least, with Article Forge 3.0, you are able to influence the tone, style, and even sentiment of your article by changing the way you phrase the main keyword. 

For example, The articles below are both about an unreleased video game called “Starfield“. 

The first article was generated from the simple keyword “Starfield”. Because the main keyword lacks any indication of intent or tone, the article is generally neutral but still contains accurate and useful information. 

The second article, however, was generated from the keyword “Why the new Starfield game will be incredible”. In this article, you can see that Article Forge took a completely different tone in describing the game while still providing accurate and useful information.

By simply changing the way the main keywords are phrased, you can control the intent of your articles. This allows for far more range in the content supplied by Article Forge and caters to wider writing styles than any previous version.

Where Article Forge is heading

As exciting as this update is for us at Article Forge, it is only the tip of the iceberg of what is coming soon!
In the next few months, we will be:

• Rolling out multiple quality improvement updates (both silently and publicly)
• Expanding support for more input types, and allowing more control over article outputs including:
  • Longer articles
  • Subheaders and overall article structure
  • More control over style and tone

Overall, we understand that everyone has different expectations when it comes to quality. Article Forge 3.0 is a huge step forward in AI generated article quality, but it is just the beginning. With each update, the quality, usefulness, and power of our content increases. No matter how high your content standards are, I am confident that now or in the future, our updates will surprise you and exceed your expectations. 

If you made it here, thank you for your time! As always, I (and the whole team at Article Forge) would love to hear any questions or feedback you have, just shoot us a message at support at articleforge.com

The post Article Forge 3.0: A Major Breakthrough in Accurate AI Content Generation appeared first on Article Forge Blog.