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When Belinda and Jake Hare founded Launchpeer a few years ago, they weren’t sure if they could make it. Charleston’s tech scene was still emerging and finding new business was an uphill battle. Growth wasn’t happening and revenue was so low that they drained their savings accounts, maxed out credit cards, and even missed mortgage payments. It’s a story that might sound familiar to most entrepreneurs, but one that’s rarely shared.

“The first year building Launchpeer was extremely difficult.” Jake said. “At one point, we were planning for the worst and even started fixing up a small camper that we could move ourselves and our two small children into if needed. We were all in, with no safety net whatsoever.”

After making several strategic changes and tweaking their business model, things started to turn around. The team grew from four to 22 employees in just nine months, working alongside more than 200 startups in the past two years. Better yet, the Hares didn’t have to move their family into a camper.  

After their entrepreneurial rollercoaster ride, Jake and Belinda knew they wanted to do something to help early-stage entrepreneurs avoid those same pitfalls.

“We learned a lot during that time,” Belinda said, “but it would have been nice to have some support.”

Three years ago, Charleston, South Carolina was still getting its footing as a tech hub. Now, the coastal city ranks 11th in the U.S. for high tech GDP growth and 4th for its entrepreneurial ecosystem, according to Inc. It’s home to major technology companies like Blackbaud, Benefitfocus, and Snagajob, as well as an increasing number of coworking spaces and early-stage startups.

Read our coverage from DIG SOUTH at TechCo

But there’s certainly room for improvement.

“Startups in Charleston and around the Southeast don’t have the same resources as our counterparts in New York and San Francisco, especially when it comes to funding,” Belinda said.

“The local community is thriving, and thanks to our smaller scale, it’s easier for entrepreneurs to tap into all the available resources in a very short amount of time,” adds Jake. “But if we want the Charleston tech scene to continue to grow, we have to do more to prop up real, viable, revenue-generating startups so investors in larger metros will start to take notice.”

So the duo is rolling up their sleeves to make it happen.

This summer, Jake and Belinda started Launchpeer Labs, a combination of part investment fund, accelerator, and startup studio geared towards idea-stage companies who haven’t yet built a product, created a team, or secured funding to bring their idea to life.

“Launchpeer Labs is our way of propping up new startups, giving them the resources they need early so they can get to revenue, get follow-on investment, and then begin to draw larger investors to the Charleston tech scene,” Jake said.

The hybrid startup program will provide new companies with a $50,000 investment and access to a cofounding team to build their MVP and MDP.  Launchpeer team members who work with Labs participants will each get vested in the equity from the Labs startups, ensuring their dedication to the long-term success of Labs portfolio companies. In exchange for seed funding and talent, Launchpeer Labs will take 30 percent equity and will require the startups, or “Founders-in-Residence,” to relocate to Charleston, SC for at least one year.

The Labs startups will work alongside Launchpeer to go from zero to fully validated, revenue generating, and seed-funded within 4 to 6 months.

“We’re providing a resource that doesn’t readily exist in the Southeast,” Jake said. “It’s one we would’ve loved to have when we started our company, and we hope it will fuel new business growth, increase job creation, and bring the investment attention our startup community needs.”

As part of this bigger mission, Jake and Belinda partnered with VentureSouth, one of the nation’s largest angel investment organizations, to help the Labs startups secure follow-on funding of $100-500K. The VentureSouth network invested $4.5 million in 15 Southeastern companies in 2024, and they’ll offer additional funds to Labs companies who meet their criteria after the program.

“The ultimate goal of this program is to continue growing Charleston as a thriving tech hub,” Belinda said. “Until now, idea-stage entrepreneurs haven’t had this level of targeted support or direct connection to investors. We’re solving that problem, all in an effort to strengthen our region’s startup ecosystem.”

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How Is Digitalization Helping Cash Management?

The Financial Sector has to be meticulous in its cash management as there are a daily inflow and outflow of cash in large volumes. Organizing the flow of cash is essential to have liquidity for business operations and grow better, especially when the world is becoming much smaller. As an important financial activity, cash management is now assuming a new form to meet the requirements of the modern world. This digitalization of cash management is required to store and transfer cash in the form of ‘e-cash’. A digital ecosystem allows for ease of connectivity and communication of important information. A bank can benefit significantly by making the shift from in-house employees to hiring a cash management service provider. This provider can optimize your cash distribution network, provide

Digitalization and Cash Management Automation

Traditional cash management is proving to be no longer viable. The digitalization of cash management helps in automation. As numerous, monotonous transactions are constantly taking place, digital cash management can make this entire process faster and efficient. Errors by employees in the course of their employment is avoided to a considerable extent. Therefore, the institution or business can eliminate the possibility of human error. With a variety of tools and smart functionalities, the whole cash management process is enlivened by technology.  

Customer Service

With modern-day cash management services, there is an increase in customer satisfaction. There is an active engagement with the customer. Customers of today, millennials, in particular, are very tech-savvy and expect the banking services to be in alignment with and support their fast-paced living. Customers expect quick, timely responses. Digital money helps in making very quick, long-distance transactions. Customers can be served to their maximum satisfaction through digital cash management as it uses databases. Using these services is a great way to retain customers, encourage customer loyalty and increase the customer base.  

Preventing Fraud

There is a real-time record for every transaction that takes place. The digital cash management system is empowered with analytics and monitoring capacities to check for discrepancies, fraud, and illegal activities. It can keep a check on the behavioral activity and detect any suspicious deviation from the norm. With the rise in theft and loss, it is essential to optimize banks and businesses’ cash management system. With secured gateways, there is a greater sense of trust that can prevail with these systems. Integration of cash management solutions with financial institutions is an absolute necessity keeping in mind all the numerous cyber threats, cyber-attacks and the possibility of other illegal crimes that can threaten a financial institution’s service and reputation. With a modern cash management platform system, a user-friendly interface paves the way for a better overall customer experience.  

Reduction of costs

A good digital cash management system can help avoid all the unnecessary, time-consuming infrastructural needs and the burden of hiring employees and having ongoing obligations and formalities as an employer. Digitalization of cash management has proven to be very cost-effective in this regard. However, the existing employees themselves will find that much of their redundant, monotonous and repetitious work is eliminated because of the automation that a digital cash management system offers. And so, they have more time on their hands to meet the important needs and for the business’s core functions. With the reduction of operation costs and other organizational costs, a business can have more room for investment. Having all the business processes automated and inviting new technology such as cloud-based banking is an excellent way to reduce the costs that come with traditional cash management. A business can expect more profits this way.  

Financial Planning

Opting for digitalized cash management services has the benefit of giving you a very clear-cut, accurate picture of the cash flowing in and out of your business. This allows the finance department in your business in making better, healthy plans for investment, growth, development and expansion of the business. Digitalization of cash management services has, therefore, resulted in better forecasting ability. The digital software and products available can show you where your business stands when it comes to balances, income, expenses and other important information. It will provide you with the most accurate, best financial reports regularly.

Avoiding downtime

A financial institution or a business can experience cash shortages and downtime. Digital cash management systems can reduce the possibility of these unfortunate occurrences by using accurate predictions and performing diagnostic functions. Businesses will not have to rely on a technician to come to the site for regular maintenance and to fix these issues. With remote monitoring and 24×7 superior service, digital cash management services stand unparalleled. They can even solve these problems in the system even before they occur.  

Digital Services Are Customizable

A good cash management service provider offers you a wide range of products and services, from a-la-carte services to package services to customizable services. Incorporating these tailor-made-services into your business structure can optimize all your cash management processes.  

Streamlining of Cash Management Processes

The digitalization of cash management solutions has proven to be more effective in cash-handling processes than hiring and training employees to perform these functions. These cash solutions provide troubleshooting and perform other diagnostic functions. There is undoubtedly more transparency as there is quick access to reports that effectively increase the scale of operations and business performance.  

In Conclusion

Due to their smart functionality and high utility, Digital Cash Management Solutions has led to increased liquidity and cash management. With a sound cash management policy, a business can strategize better and make informed decisions.  It helps a business safely collect, organize and distribute the cash smoothly. Many banks, because of their diversified and complex functions, now choose to outsource many of their services.

Agribusiness Is Being Disrupted By 8 Blockchain Startups

Check out this article agribusiness is being disrupted by 8 blockchain startups for more information

A remarkable 47.8% compound annual growth rate (CAGR) is predicted to drive the market for blockchain technologies in the agriculture sector from US$41.2 million in 2023 to approximately US$430 million in 2023.

To increase food safety, blockchain agriculture makes it possible to trace information across the food supply chain. Traceability is created by the ability of blockchain to store and manage data, and it is utilized to ease the creation and deployment of innovations for intelligent farming and indexing. Agriculture-based insurance.

By reducing fraud risk, speeding up transactions, assisting farmers with crop control and analysis, and a host of other benefits, the Blockchain is already transforming the business world. The innovations in the sector are being redefined by these 8 blockchain startups.


A blockchain firm committed to empowering distributed farming exchanges and handling them without the utilization of go-betweens.


A commodity management system that is both blockchain-based and integrated for the global grains industry. The platform helps with the processing of intricate agricultural transactions by using smart contracts.


a project that uses social entrepreneurship to help farmers in the UK find where their food comes from, get easier financing, and store transaction data.


A focal community for leasing and cultivating miniature fields anyplace in the world, without the requirement for delegates, intricacy, or the above of a huge company.


Through the decentralized insurance applications of a blockchain startup, farmers can obtain crop insurance.


The company creates the Blockchain of Food by utilizing high-quality food data to establish a transparent digital food supply chain and track the food’s journey.


Identification tools are utilized throughout the supply chain to track animals, transporters, and shipments of fresh food.


Utilizing satellites to automatically trigger payouts and monitor rainfall, crop insurance can guard against yield loss.

How is Blockchain Changing the Agricultural Sector?

A team of innovators conducted in-depth interviews with over 150 agricultural businesses to investigate the potential applications of Blockchain in the agricultural sector.

Food Supply Chain Optimization:

To maintain customer confidence and loyalty, it is essential to provide information about the sources of food products. Using Blockchain, any local fruit or vegetable grown on a neighboring farm can be bought with confidence.

In traditional supply chains, food retailers lack an effective method for confirming that all products were grown by a specific supplier’s specifications. Because of this, food product origins are being tracked using Blockchain by retailers like Walmart, Unilever, and Carrefour.

In addition, tracing the origins of food takes significantly less time. Take Walmart as an illustration: it took nearly a week to locate where their mangoes came from. The Blockchain reduces this time to just two seconds. If a product does not meet the requirements of a retailer, reducing the amount of time it takes to track its source is critical because it enables retailers to isolate the product more quickly, lowering the risk of human injury.

Important Acts:

Blockchain has a unique chance to level the playing field for small-scale farmers and crop growers, particularly in low-income areas, by streamlining transaction procedures. Food waste is estimated to amount to $940 billion each year worldwide. This is because farmers and growers in less developed nations are unable to sell all of their produce. After all, they do not always have access to large marketplaces.

By providing small players with access to their proprietary blockchain-based platform for exchanging agricultural products and establishing trust among market participants, the blockchain company AgUnity is addressing this issue. Individual market participants can collaborate with their products by forming small cooperatives. One more benefit of Blockchain for farming makers is the possibility to fix evaluating all the more proficiently and actually. They can adjust their output in response to customer demand as a result of this.

Crop Insurance:

Savvy contracts in horticulture have a one-of-a-kind application in that they help ranchers in guaranteeing their yields and documenting claims with protection firms. In most cases, the procedure is extremely time-consuming and time-consuming for both the farmer and the insurance company.

It is challenging to accurately quantify the precise damages caused by unpredictable weather events. This makes the way for misrepresentation and transforms the cycle into a huge mess. Personalized smart blockchain contracts make the process simpler for farmers and insurers by allowing the damage claim to be triggered by weather conditions that meet specific criteria.


Facebook Is Helping Advertisers Reach Previously Unreachable People, On Any Device

Facebook reports that roughly 7 out of every 10 people in the world use devices less sophisticated than a smartphone to access the Internet, like a feature phone. Many of these people reside in high-growth countries like India, Brazil, Indonesia, Mexico, South Africa and Nigeria.

Since then, we’ve improved ad delivery by optimizing for low-bandwidth connections and offered enhanced features that give brands more storytelling options. Advertisers can reach millions for people — some for the very first time — on any device and in any country.

“Missed Call” Ad Units

Facebook has been using local insights to find new solutions. For example, in India there is a “missed call” behavior that acts as a workaround for expensive voice calls.

Think of it like how pagers used to work. People dial a number and hang up before before the call connects, that way they’re not charged for voice minutes. The purpose of this is to send a signal such as “I’m outside,” or “Call me back.”

Facebook is testing an ad unit in India that builds on this behavior:

Facebook reports that they have seen positive results in early tests, and plans to scale this product in the coming months with additional partners and markets.

New Ad Targeting Options

Geo-targeting: Advertisers in high-growth countries can now target people by state or even multiple states in India without having to list multiple cities. Facebook adds that their teams are currently working on additional geo-targeting enhancements in Nigeria, Turkey, South Africa, India, Indonesia and across Latin America.

Facebook points out that they will continue to rethink how they develop and implement products and services in high-growth countries: “Businesses in high-growth countries need customized solutions to connect with people.”

Startups Need App Development Management Tips

A mobile app is essential if you want to run a business that produces greater ROI in a specific industry sector. There are a few things you need to consider when developing mobile apps for startups.

This article will focus on factors that make it possible to complete a successful startup app development project. There are currently more than a 5.2million mobile apps available in the app store, but only two percent are actually productive. The rest, or 98 percent of them, are not doing things right.

What is App Development?

App development refers to the process and method of creating software for small wireless devices like smartphones and other handheld gadgets.

A gaming app, for example, could be developed to use the iPhone’s screen, while a mobile health app, for maximum use of a smartwatch temperature sensor, could be created.

Startup App Development Management Tips Things to Consider When Choosing a Mobile Application Development Company

A certain amount of knowledge is required to develop a mobile app. Learn about the past experience of the top mobile application development company and how many projects they have completed. To get an idea of the utility of mobile apps, take a look at their previous mobile app development projects.

To Develop an Application, Select Advanced Features and the Appropriate Platform

Once you have a clear understanding of the preferences of your customers, you can start to choose the features and platform that you want for your app. The platform runs on will affect the design and appearance of your application. Consider the platform that is used to run the application, its operation, and any unique features that it requires.

A key component to providing a great experience is choosing the right features for the program. This includes excellent content as well as a user interface (UI). It would be quickly removed from the storage if it did not contain certain essential elements that would make the program useful for the client.

Considering the Business Environment is a Must

Before you start a new venture, it is important to identify the business’s environment. The most efficient method to analyze your company’s environment is the SWOT analysis. This technique can help you identify and evaluate the potential strengths, weaknesses, opportunities, or threats to your company’s concept.

You must also constantly evaluate your own shortcomings in order to identify and fix them so that you can make the best progress possible in these areas. You should always be looking for new opportunities in the market before you enter it.

You may be exposed to risks that go beyond those of your competitors, such as a lack of public interest and a lack of uniqueness in the services or products offered by the firm.

Also read:

Best Video Editing Tips for Beginners in 2023

Gaining a Better Understanding of Your Competitors

You should be aware of a few key points when you plan your business and bring it to market, especially through an app. First, you need to know that both the App Store (and Google Play Store) are overpopulated with apps from different market segments.

Development Across Multiple Platforms

Apart from the fact that your app’s development, administration, and essential features are all crucial to its success, the platform where it runs is also important. While it’s beneficial to concentrate on one platform and work as efficiently as possible, it is also important to consider other platforms. Before publishing your software to the App Store, make sure it is available on other major platforms like the Google Play Store and Windows.


To avoid confusing your target audience, you should focus on one main feature when developing an app. Use the best ideas from your brainstorming sessions to create your presentation. Your software should be able to assist your clients seamlessly and without any glitches.

Is This Google’s Helpful Content Algorithm?

Google published a groundbreaking research paper about identifying page quality with AI. The details of the algorithm seem remarkably similar to what the helpful content algorithm is known to do.

Google Doesn’t Identify Algorithm Technologies

Nobody outside of Google can say with certainty that this research paper is the basis of the helpful content signal.

Google generally does not identify the underlying technology of its various algorithms such as the Penguin, Panda or SpamBrain algorithms.

So one can’t say with certainty that this algorithm is the helpful content algorithm, one can only speculate and offer an opinion about it.

But it’s worth a look because the similarities are eye opening.

The Helpful Content Signal 1. It Improves a Classifier

Google has provided a number of clues about the helpful content signal but there is still a lot of speculation about what it really is.

The first clues were in a December 6, 2023 tweet announcing the first helpful content update.

The tweet said:

“It improves our classifier & works across content globally in all languages.”

A classifier, in machine learning, is something that categorizes data (is it this or is it that?).

2. It’s Not a Manual or Spam Action

The Helpful Content algorithm, according to Google’s explainer (What creators should know about Google’s August 2023 helpful content update), is not a spam action or a manual action.

“This classifier process is entirely automated, using a machine-learning model.

It is not a manual action nor a spam action.”

3. It’s a Ranking Related Signal

The helpful content update explainer says that the helpful content algorithm is a signal used to rank content.

“…it’s just a new signal and one of many signals Google evaluates to rank content.”

4. It Checks if Content is By People

The interesting thing is that the helpful content signal (apparently) checks if the content was created by people.

Google’s blog post on the Helpful Content Update (More content by people, for people in Search) stated that it’s a signal to identify content created by people and for people.

Danny Sullivan of Google wrote:

“…we’re rolling out a series of improvements to Search to make it easier for people to find helpful content made by, and for, people.

…We look forward to building on this work to make it even easier to find original content by and for real people in the months ahead.”

The concept of content being “by people” is repeated three times in the announcement, apparently indicating that it’s a quality of the helpful content signal.

And if it’s not written “by people” then it’s machine-generated, which is an important consideration because the algorithm discussed here is related to the detection of machine-generated content.

5. Is the Helpful Content Signal Multiple Things?

Lastly, Google’s blog announcement seems to indicate that the Helpful Content Update isn’t just one thing, like a single algorithm.

Danny Sullivan writes that it’s a “series of improvements” which, if I’m not reading too much into it, means that it’s not just one algorithm or system but several that together accomplish the task of weeding out unhelpful content.

This is what he wrote:

“…we’re rolling out a series of improvements to Search to make it easier for people to find helpful content made by, and for, people.”

Text Generation Models Can Predict Page Quality

What this research paper discovers is that large language models (LLM) like GPT-2 can accurately identify low quality content.

They used classifiers that were trained to identify machine-generated text and discovered that those same classifiers were able to identify low quality text, even though they were not trained to do that.

Large language models can learn how to do new things that they were not trained to do.

A Stanford University article about GPT-3 discusses how it independently learned the ability to translate text from English to French, simply because it was given more data to learn from, something that didn’t occur with GPT-2, which was trained on less data.

The article notes how adding more data causes new behaviors to emerge, a result of what’s called unsupervised training.

Unsupervised training is when a machine learns how to do something that it was not trained to do.

That word “emerge” is important because it refers to when the machine learns to do something that it wasn’t trained to do.

The Stanford University article on GPT-3 explains:

“Workshop participants said they were surprised that such behavior emerges from simple scaling of data and computational resources and expressed curiosity about what further capabilities would emerge from further scale.”

A new ability emerging is exactly what the research paper describes.  They discovered that a machine-generated text detector could also predict low quality content.

The researchers write:

“Our work is twofold: firstly we demonstrate via human evaluation that classifiers trained to discriminate between human and machine-generated text emerge as unsupervised predictors of ‘page quality’, able to detect low quality content without any training.

This enables fast bootstrapping of quality indicators in a low-resource setting.

Secondly, curious to understand the prevalence and nature of low quality pages in the wild, we conduct extensive qualitative and quantitative analysis over 500 million web articles, making this the largest-scale study ever conducted on the topic.”

The takeaway here is that they used a text generation model trained to spot machine-generated content and discovered that a new behavior emerged, the ability to identify low quality pages.

OpenAI GPT-2 Detector

The researchers tested two systems to see how well they worked for detecting low quality content.

One of the systems used RoBERTa, which is a pretraining method that is an improved version of BERT.

These are the two systems tested:

OpenAI’s RoBERTa-based GPT-2 detector

Looks for the “statistical signature” of machine-generated content. Uses BERT and GPT-2.

They discovered that OpenAI’s GPT-2 detector was superior at detecting low quality content.

The description of the test results closely mirror what we know about the helpful content signal.

AI Detects All Forms of Language Spam

The research paper states that there are many signals of quality but that this approach only focuses on linguistic or language quality.

For the purposes of this algorithm research paper, the phrases “page quality” and “language quality” mean the same thing.

The breakthrough in this research is that they successfully used the OpenAI GPT-2 detector’s prediction of whether something is machine-generated or not as a score for language quality.

They write:

“…documents with high P(machine-written) score tend to have low language quality.

…Machine authorship detection can thus be a powerful proxy for quality assessment.

It requires no labeled examples – only a corpus of text to train on in a self-discriminating fashion.

This is particularly valuable in applications where labeled data is scarce or where the distribution is too complex to sample well.

For example, it is challenging to curate a labeled dataset representative of all forms of low quality web content.”

What that means is that this system does not have to be trained to detect specific kinds of low quality content.

It learns to find all of the variations of low quality by itself.

This is a powerful approach to identifying pages that are not high quality.

Results Mirror Helpful Content Update

They tested this system on half a billion webpages, analyzing the pages using different attributes such as document length, age of the content and the topic.

The age of the content isn’t about marking new content as low quality.

They simply analyzed web content by time and discovered that there was a huge jump in low quality pages beginning in 2023, coinciding with the growing popularity of the use of machine-generated content.

Analysis by topic revealed that certain topic areas tended to have higher quality pages, like the legal and government topics.

Interestingly is that they discovered a huge amount of low quality pages in the education space, which they said corresponded with sites that offered essays to students.

Google’s blog post written by Danny Sullivan shares:

“…our testing has found it will especially improve results related to online education…”

Three Language Quality Scores

Google’s Quality Raters Guidelines (PDF) uses four quality scores, low, medium, high and very high.

The researchers used three quality scores for testing of the new system, plus one more named undefined.

Documents rated as undefined were those that couldn’t be assessed, for whatever reason, and were removed.

The scores are rated 0, 1, and 2, with two being the highest score.

These are the descriptions of the Language Quality (LQ) Scores:

Text is incomprehensible or logically inconsistent.

Text is comprehensible but poorly written (frequent grammatical / syntactical errors).

Text is comprehensible and reasonably well-written (infrequent grammatical / syntactical errors).

Here is the Quality Raters Guidelines definitions of low quality:

Lowest Quality:

“MC is created without adequate effort, originality, talent, or skill necessary to achieve the purpose of the page in a satisfying way.

…little attention to important aspects such as clarity or organization.

monetization rather than creating original or effortful content to help users.

Filler” content may also be added, especially at the top of the page, forcing users to scroll down to reach the MC.

…The writing of this article is unprofessional, including many grammar and punctuation errors.”

The quality raters guidelines have a more detailed description of low quality than the algorithm.

What’s interesting is how the algorithm relies on grammatical and syntactical errors.

Syntax is a reference to the order of words.

Words in the wrong order sound incorrect, similar to how the Yoda character in Star Wars speaks (“Impossible to see the future is”).

Does the Helpful Content algorithm rely on grammar and syntax signals? If this is the algorithm then maybe that may play a role (but not the only role).

But I would like to think that the algorithm was improved with some of what’s in the quality raters guidelines between the publication of the research in 2023 and the rollout of the helpful content signal in 2023.

The Algorithm is “Powerful”

It’s a good practice to read what the conclusions are to get an idea if the algorithm is good enough to use in the search results.

Many research papers end by saying that more research has to be done or conclude that the improvements are marginal.

The most interesting papers are those that claim new state of the art results.

The researchers remark that this algorithm is powerful and outperforms the baselines.

What makes this a good candidate for a helpful content type signal is that it is a low resource algorithm that is web-scale.

In the conclusion they reaffirm the positive results:

“This paper posits that detectors trained to discriminate human vs. machine-written text are effective predictors of webpages’ language quality, outperforming a baseline supervised spam classifier.”

The conclusion of the research paper was positive about the breakthrough and expressed hope that the research will be used by others.

There is no mention of further research being necessary.

This research paper describes a breakthrough in the detection of low quality webpages.

The conclusion indicates that, in my opinion, there is a likelihood that it could make it into Google’s algorithm.

Because it’s described as a “web-scale” algorithm that can be deployed in a “low-resource setting” means that this is the kind of algorithm that could go live and run on a continual basis, just like the helpful content signal is said to do.

We don’t know if this is related to the helpful content update but it’s a certainly a breakthrough in the science of detecting low quality content.

Citations Google Research Page:

Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study

Download the Google Research Paper

Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study (PDF)

Featured image by Shutterstock/Asier Romero

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