Google Helpful Content Update Can Demote & Now Promote Content

The other day we reported how Google will be releasing an update to the helpful content system that can identify "hidden gems" deep within the web and promote that in the Google Search results. As Glenn Gabe points out, that means that the helpful content system can now not only demote unhelpful content but now also promote, at the same time, "hidden gems" within the content.

Glenn Gabe asked Danny Sullivan, Google's Search Liaison, "With this update to the helpful content system, will the system soon be tackling multiple tasks (demote + promote)? I know in the past you said it could be expanded, so I wanted to make sure I understood this correctly."

Danny Sullivan responded on Twitter saying, "The helpful content system will be working to identify and show more 'hidden gems' on Search, along with still working to ensure unhelpful content is not performing well."

So in short, the Google helpful content update will soon be able to not just identify unhelpful content and demote that content but also be able to identify helpful content deep inside the web and promote it.

Here are those tweets:

Here is how Glenn summed up Danny Sullivan's response:

If you read the official Google helpful content page closely, you will see it is more about a negative aspect. "The helpful content system aims to better reward content where visitors feel they've had a satisfying experience, while content that doesn't meet a visitor's expectations won't perform as well," it says.

"The system automatically identifies content that seems to have little value, low-added value or is otherwise not particularly helpful to people," see, more negative focused. It goes on and on with the negative sentiment, "Any content—not just unhelpful content—on sites determined to have relatively high amounts of unhelpful content overall is less likely to perform well in Search, assuming there is other content elsewhere from the web that's better to display. For this reason, removing unhelpful content could help the rankings of your other content."

Expect this Google document to be updated when the new "hidden gem" Google helpful content system update rolls out.

Forum discussion at Twitter.

Generative AI In Devops Market Predicted To Garner USD 22,100 Mn By 2032, At CAGR 38.20% | Report By Marketresearch.Biz

Generative AI is a type of machine learning that uses previously learned examples to create new information, such as text, code, or graphics. DevOps, on the other hand, is a methodology that emphasizes collaboration & communication with IT experts & software developers in order to provide software quickly and reliably. Together, DevOps and generative AI can automate some tasks in the software development process, boosting output and effectiveness. Due to the increased popularity of cloud computing and the expanding desire for automation in the software development process, it is projected that the market for generative AI in DevOps will grow dramatically.

Get additional highlights on major revenue-generating segments, Request a Generative AI in DevOps Market sample report at

Key Takeaway

Factors affecting the growth of generative ai in the devops industry ?

There are several factors that can affect the growth of generative AI in DevOps industry, including:

To understand how our report can bring a difference to your business strategy, Inquire about a brochure at

Top Trends in Generative AI in DevOps Market

A growing emphasis on tools that can offer insights into how generative AI models are making decisions and producing content is a result of how transparent and explainable generative AI solutions are becoming. Another development is the application of generative AI to cybersecurity, which enables real-time detection and reaction to cyber threats.

Also, there is a slew of brand-new AI platforms and tools that are entering the market. It ranges from open-source software frameworks to cloud-based platforms. These tools make it easier and more efficient for enterprises to create and implement generative AI solutions. Overall, the generative AI in DevOps market is expanding rapidly and innovating, and new trends and advancements are always appearing. In the upcoming years, it is anticipated that the market will continue to expand and change as more firms use cloud computing, DevOps practices, and cutting-edge technologies like generative AI.

Market Growth

The growth of generative AI in DevOps market can be attributed to several factors, including the increasing adoption of cloud computing, the growing need for automation, advancements in AI and machine learning, and increased adoption of DevOps methodologies. Moreover, the COVID-19 pandemic has also accelerated the adoption of digital transformation initiatives, including the adoption of cloud computing & DevOps methodologies, which has further fueled the growth of generative AI in DevOps market.

We can anticipate continued growth and development in this fascinating subject as more companies come to understand the advantages of generative AI solutions in the DevOps market. The availability of trained labour, however, as well as security and privacy issues, may have an impact on the market's expansion.

Regional Analysis

Due to the widespread use of cloud computing and DevOps practices in the region, North America is home to the greatest generative AI in DevOps market. The market share of North America is about 40%. Major businesses like IBM, Microsoft, and Google are all present in this sector which is helping it to expand.

Additionally, Europe is a sizable generative AI in DevOps market, with Germany, UK, and France setting the bar high. The market in Europe is expanding because of the increasing demand for automation in software development and rising cloud computing use.

The APAC market has substantial growth in the upcoming years in the countries such as Japan, China, and India, because of the growing adoption of cloud computing and DevOps approach. Also, this region is home to a significant number of start-ups that make investments in generative AI solutions.

The generative AI in DevOps market is also anticipated to expand in Latin America, the Middle East, and Africa because of the rising popularity of cloud computing and the rising demand for software development automation.

Have Queries? Speak to an expert, or To Download/Request a Sample, click here .

Scope of the Report

Market Drivers

One of the main drivers is the increasing popularity of cloud computing. It gives businesses access to powerful computer resources whenever they need them. It also increases the scalability and flexibility of the software development process. The need for automation & efficiency in software development is growing as more businesses migrate to the cloud, also generative AI is viewed as a critical tool for attaining these objectives.

The rising demand for DevOps approaches, which emphasize cooperation and communication between software developers and IT experts, is another motivating reason. DevOps is gaining popularity as a means of accelerating the software development lifecycle and enhancing software product quality. In the DevOps process, processes like code generation and testing may be automated with the use of generative AI, making it a useful tool for DevOps teams.

Market Restraints

The possibility of bias in generative AI models is potential restraint. When generative AI models are trained on biased datasets, the resulting models run the risk of amplifying and perpetuating the bias. This might raise moral and legal concerns and limit the applicability of generative AI solutions in some fields.

Market Opportunities

Integration with other emerging technology: Generative AI can be integrated with other technologies such as IoT (Internet of Things), blockchain, and edge computing to create new applications and uses cases. This integration can help businesses achieve greater efficiency, productivity, and cost savings.

Expansion to new industries: The DevOps market for generative AI has already gained traction across industries like IT and telecom, BFSI, and healthcare. There are many industries that can benefit by adopting generative AI solutions. These include manufacturing, retail, and transportation. Demand for generative AI is expected to rise as businesses in different industries adopt digital-transformation initiatives.

Adoption of hybrid clouds: The adoption of hybrid cloud models that combine public and private cloud architecture is expected to open up new opportunities for generative AI. Hybrid cloud models allow businesses to have more flexibility and control over IT infrastructure while also taking advantage of the scalability, cost-savings, and benefits provided by public cloud providers.

Grow your profit margin with MarketResearch.Biz - Purchase This Premium Report at

Report Segmentation

Component Insight

Software platforms and solutions that use generative AI to automate various processes in the software development process are included in the solutions sector. Tools for code development, test data generation, and model training are just a few examples of these solutions. The market for generative AI in DevOps is anticipated to be dominated by the solutions sector, thanks to the growing popularity of cloud computing and DevOps practices. The consulting, integration, and support services pertaining to generative AI products in the DevOps industry are included in the services sector. Providing clients with guidance on the optimal methods for adopting generative AI solutions, integrating generative AI solutions with current processes, and providing ongoing support and maintenance for generative AI solutions are a few examples of the services that may fall under this category.

Deployment Mode Insight

Microsoft Azure, Google Cloud, or AWS are some third-party providers whose cloud infrastructure is maintained by third parties and is known as "cloud-based deployment." Due to it enabling companies to scale their operations effectively and fast without the need for sizable upfront expenditures in IT infrastructure, cloud-based deployment is growing in popularity in the DevOps industry. On-premise deployment means software installation on the firm's own servers. These servers are controlled and maintained by the IT department. Larger businesses that demand tighter control over their software and data frequently employ on-premise implementation.

Application Insight

The applications of generative AI in the DevOps market include testing, deployment, monitoring, maintenance, and other applications. Generative AI is used to produce test data and automate the testing process in software development when testing apps. Because of this, software testing can be done more rapidly and efficiently, which improves both quality and efficiency. Generative AI is used in monitoring apps to track software systems and spot potential problems or anomalies in real-time. This enhances system efficiency and reduces downtime. Generative AI is used in maintenance applications to automate maintenance chores like system updates, patching, and bug patches. This lowers maintenance expenses and increases system reliability.

For more insights on the historical and Forecast market data from 2016 to 2032 - download a sample report @

Market Segmentation

Based on Component

Based on Deployment Mode

Based on Application

Key Regions

Competitive Landscape

Key participants in the generative AI in DevOps market have been identified based on market share, including IBM, Microsoft, Google, AWS, Intel, Infosys, HCL Technologies, Wipro, Happiest Minds, and Cognizant. To fulfill the rising need for automation and efficiency in software development, these businesses are making research and development investments in the creation of new generative AI solutions and platforms.

Some of the major players include:

Recent Development

Related Reports

About Us:MarketResearch.biz (Powered by Prudour Pvt. Ltd.) delivers customized research solutions by actuating its broad spectrum of research methodologies, databases, and resources, and this is further strengthened by our global experience in syndicated and customized industry projects. Our tailor-made research services include quick market scans, country reports, in-depth market analysis, competition monitoring, consumer research and satisfaction studies, supplier research, growth planning, and quite a lot more.

Follow Us on LinkedIn:Follow Us on Facebook:Follow Us on Twitter:

MENAFN08062023004107003653ID1106410564

Google & Other Tech Giants Not Liable For Terrorist Content

The Supreme Court decided today that tech companies aren’t liable for terrorist content posted on their platforms.

The lawsuit, initiated by the family of a victim of a 2017 ISIS attack, argued that Twitter, Facebook, and Google should be held accountable for allowing the terrorist organization to utilize their platforms in its terrorism efforts.

However, the court unanimously decided that the lawsuit couldn’t proceed.

Justice Clarence Thomas, writing for the unanimous court in Twitter v. Taamneh, clarified that social media platforms aren’t guilty, even if nefarious actors use such platforms for illegal and sometimes terrible ends.

The argument brought forth by the victim’s family, that tech companies should be held liable for the alleged failure to stop ISIS from using these platforms, lacked the necessary link between the tech companies and the terrorist attack to establish liability.

Justice Ketanji Brown Jackson, in a brief concurring opinion, underscored that the court’s opinion was narrow in significant respects. She suggested that other cases with different allegations and records could lead to different conclusions.

Following the Twitter ruling, the Supreme Court addressed the case of Gonzalez v. Google, a lawsuit filed by the family of Nohemi Gonzalez, a 23-year-old American woman killed in the 2015 ISIS attack on a Parisian cafe.

The Gonzalez family argued that Google, through its ownership of YouTube, aided ISIS’s recruitment by allowing the terrorist group to post videos on YouTube that incited violence and sought to recruit potential ISIS members.

The family also claimed that Google’s algorithms recommended ISIS videos to users.

The U.S. Court of Appeals for the 9th Circuit previously held that Section 230 of the Communications Decency Act of 1996, which shields tech companies from liability for user-published content, protected such recommendations.

However, in light of the Twitter decision, the Supreme Court vacated this judgment and remanded the case for reconsideration.

The court refrained from deciding on the scope of Section 230, suggesting that this issue is best left to Congress or a future case.

Certain members of Congress feel strongly about reforming Section 230, believing it offers tech giants too much protection.

The office of Senator Mark Warner, a vocal critic and advocate for reforms to Section 230, provided a statement to Search Engine Journal regarding the decision in the Gonzalez v. Google case.

He characterizes Section 230 as old and outdated, arguing it’s a “Get Out of Jail Free Card” for large companies.

“For years now, I have been saying that Congress needs to take action to address the sweeping protection that Section 230 gives technology companies. This antiquated statute has outlived its usefulness and provided the largest platform companies with a “Get Out of Jail Free Card,” as their sites are used by scam artists, harassers, and violent extremists.”

Senator Warner, however, makes it clear that he doesn’t view reforming Section 230 as opening the floodgates for massive liability claims against platform companies.

“Reforming Section 230 doesn’t mean that platforms will automatically be subject to massive liability claims; victims will still have to prove their case in court.”

These cases collectively highlight the ongoing debate surrounding the responsibility of tech companies in moderating user-generated content and the extent to which they can be held liable for harmful content shared on their platforms.

The Supreme Court’s decisions indicate that, at least for now, a direct connection between the actions of tech companies and specific acts of terrorism is necessary to establish legal liability.

Nonetheless, the court’s comments suggest that different circumstances could result in different outcomes.

Sources: SCOTUS

Featured image generated by the author using Midjourney.