AI the emerging technology that's impacting every sphere of industry and human life and creating a new standard for the way we do our tasks and more!

AI the emerging technology that's impacting every sphere of industry and human life and creating a new standard for the way we do our tasks and more! Great Furure awaits

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Explore the Benefits of Leveraging Artificial Intelligence Development

How Artificial Intelligence (AI) Helps Content Creation?

Benefits of using AI in content marketing. How AI can help you boost strategy with simple AI content creation.

Do you want to improve your content marketing strategy? Learn how AI content creation can assist you in this mission.

Content marketing is the most effective marketing strategy. And there is always a competition to write better

content, be more creative, and be more engaging. But in this new digital era, artificial intelligence can be used in content creation. As you know, AI evolved into more than simply a futuristic technology. There’s a high possibility you’re already experimenting with AI, no matter what field you work in. Let’s face it, AI is everywhere, whether it’s deploying chatbots to collect data about your users’ most urgent concerns or assessing content results with AI platforms.

However, in the content marketing world, AI content creation is increasing daily. AI content creation can assist you in determining what type of content to offer your readers. So, let’s dig deeper, and see what AI can offer.

What Artificial Intelligence Is In The Content World?

AI is a broad word that encompasses a wide range of technology. Some of these, such as computer vision, machine learning, speech recognition, and natural language generation, may be familiar to you.

But AI content creation is more related to machine learning and natural language generation. Natural language processing is an AI-powered technology that allows you to “read” human words. In other words, AI can speak or write because it is capable of analyzing and producing human language to some extent. And the most interesting part is that they teach themselves to improve based on users’ inputs. So, you must provide research on the user’s input and then teach AI to associate with them. Or, if you might need some additional help, you can use TrustMyPaper services, and they will help you with the research.

4 Benefits Of Using AI Content Creation

AI content creation is a way of writing human language that is written by a sophisticated, intelligent machine. When it writes, it also learns a little more about how to improve and adapts accordingly. It’s not ideal every time, however, things quickly improve. AI content creation can help you boost your content marketing strategy. All you need to have your content piece ready and run it by AI. In fact, the writing services of SupremeDissertations can help you with content creation on a professional level. Anyway, let’s see what AI content creation do for your business;

1.??It Helps You With Personalized Customer Interactions

Mass messaging initiatives are no longer effective. You can’t send a mass email to tens of thousands of individuals and expect them to buy something. Consumers don’t interact with brands because of irrelevant content. They will, without a doubt, lose interest if they do not locate content that is relevant to them. So, here is when AI content creation comes to help you. It will aid in the customization of your content marketing initiatives and provide you with greater control. Which isn’t possible with manual labor

2.??It Helps You Find The Right Audience

Marketers can use AI content creation to forecast what content will be relevant to the correct audience. AI is being used by 61% of firms with innovation goals to uncover critical possibilities in data. These market opportunities are likely to be missed if this technology is not available. It assists advertisers in unlocking the full potential of viewer data and customizing and automating customer satisfaction. You may examine an infinite quantity of data, such as age, income levels, age, region, personal hobbies, the phone used, online social media time, and so on. And use all of it in your content creation because you will know who you speak to.

3.??It Helps You With Marketing Campaigns

With the proper application of AI, content marketers may significantly improve their marketing strategies and approaches. It is because they adapt the unique experience based on what they know about their clientele. According to 79% of content marketers, AI content creation has made their jobs easier and more efficient. AI is already being used by 51% of marketing executives in their content strategy.

4.??It Helps You Save Time

Sadly, AI was created to partially or entirely replace human labor. However, in the content world, using AI content creation increases content production, and it helps you have time for difficult tasks that AI can’t yet do.

Improve Your Content Strategy With AI Content Creation

AI may not be the solution to all of a company’s content generation issues. On the other hand, the correct technology will allow you to develop a better-informed plan for communicating with your audience. AI content creation empowers you to sift through massive amounts of data and extract important insights that deepen your relationship with your customers. You’ll be ready to accommodate an understanding of technology customers looking for more engaging and relevant content experiences if you have AI and chatbots at your disposal.

The Bottom Line

To summarize, the marketing sector is beginning to be revolutionized by artificial intelligence. It will undoubtedly continue to affect content marketing at a much faster rate than any of us can fathom, revolutionize jobs, and open up a slew of new opportunities for firms that can master AI content creation.

It’s never been easy to create engaging and educative content no matter if it was text, voice, videos, or photos. But, AI content creation is becoming a powerful force in the realm of content marketing. AI-enabled content is a game-changer for your company. AI can help you make sense of a growing amount of information, increase the content creation workflow, and give personalized content to your users.

For a long time, marketers have prioritized creating content that is based on the interests of each client. However, with AI content creation you can personalize the content for the target audience, and aim for the stars.

Developing Artificial Intelligence for Agriculture

Artificial intelligence has the potential to unlock new opportunities for agriculture. But in order for this technology to be effective, the model needs to be trained to accurately identify what it’s seeing. So for companies like TerraClear, an agtech company whose first product is a robotic rock picking arm, they picked a needed use case to invest in developing their artificial intelligence model.

Thompson… “At a very basic level, we're saying, okay, what is the widest use case where people need to have in our case, you know, a map of, of rocks but it could be weeds or it could be really anything else.”

That’s TerraClear president Trevor Thompson.

Thompson… “And so let's get that one right first. And then let's sort of see, can we have a, transfer learning or other technical approaches that allow us to then add different field conditions that maybe have a little bit of a smaller market.”

Thompson says for artificial intelligence to really take off in ag, there needs to be a shared database that companies can access to train their models more quickly.

Thompson… “I think this is the challenge for solutions that are using AI in many cases is it is a tremendous amount of data, and we've got narrow windows. You know, so if you're looking at a specific weed that only really happens in a very kind of tight window. So data sharing or some sort of marketplace where we can kind of exchange, but we have to figure that out or else a lot of these solutions are going to take years because you're just really limited.”

Developing technologies that actually work in the field is no easy task.

Nvidia promises easier enterprise AI

The Lead

[1] Nvidia launches AI Enterprise in general availability

[2] How AI will reshape software development

[3] The do’s and don’ts of machine learning research

The Follow

[1] Nvidia today announced the general availability of AI Enterprise, a software suite of tools and frameworks that enable companies running VMware vSphere to virtualize AI workloads on Nvidia-certified servers. Systems from Atea, Carahsoft, Computacenter, Insight Enterprises, SoftServe, Dell Technologies, and SVA System are now available, featuring a range of Nvidia GPUs including the A100, A30, A40, A10, and T4.

Companies are increasingly embracing AI during the pandemic as they discover the benefits of automation and big data analytics. According to 451 Research, 95% of businesses indicate that they consider AI to be “important to their digital transformation efforts.” AI Enterprise enables organizations that use VMware vSphere to run traditional enterprise applications while using the same tools they use to manage large-scale datacenters and hybrid clouds. VSphere, VMware’s cloud computing virtualization platform, includes a configuration manager as well as an app discovery dashboard and the ability to move more than one virtual machine at a time from one host server to another.

“The first wave of AI has been powered by specialized infrastructure that focused adoption to industry pioneers,” Manuvir Das, head of enterprise computing at Nvidia, said in a press release. “Today is the beginning of a new chapter in the age of AI, as Nvidia software brings its transformative power within reach for enterprises around the world that run their workloads on VMware with mainstream data center servers.” >> Read more here.?

[2] It appears the first realm to face a new AI-driven operating paradigm is the one that created AI in the first place: software development.

According to IDC, the worldwide AI market is expected to top $341.8 billion in 2021 and then blow past $500 billion by 2024 for an annual growth rate of 18.8%. It should be noted, however, that 88% of this market will be in the form of software, about half from applications. So how will this change the software market??

For one thing, it will alter the way code is written, updated, and released. With AI empowered to make changes to itself, the focus of highly trained, highly paid software engineers will shift from the dull drudgery of writing and rewriting minute functions to more creative, strategic-level operations that produce greater value and drive core business operations. At the same time, DevOps will become increasingly automated and responsive to users with the power to define their objectives and have AI convert them into code. This could alter the way software is bought and sold, with individual users getting the updates they need from AI, rather than having to shell out more dollars for a generic new release from the developer. And as AI continues to evolve and acquires the ability to learn on its own and infer from context, we can expect to see broader democratization of software development to the point that virtually anyone can create new programs – no experience necessary. >> Read more here.

[3] Machine learning is becoming an important tool in many industries and fields of science. But machine learning research and product development present several challenges that, if not addressed, can steer your project in the wrong direction. In a recent paper, Michael Lones, associate professor in the School of Mathematical and Computer Sciences at Heriot-Watt University, provides a list of dos and don’ts for machine learning research.

When it comes to the data, for example, Lones says do pay extra attention, and “do not assume that, because a data set has been used by a number of papers, it is of good quality.“ “No amount of computation power and advanced technology can help you if your data doesn’t come from a reliable source and hasn’t been gathered in a reliable manner. And you should also use your own due diligence to check the provenance and quality of your data,” he writes.?

Other do’s include knowing your final goal and its requirements, knowing what to measure and report, and knowing your models (as well as those of others). You should always have a roster of candidate algorithms to evaluate, and the first thing you should check is whether your model matches your problem type. You should also look to avoid excessive complexity. All together, this only scratches the surface on the tips Lones includes in his paper, "How to avoid machine learning pitfalls: a guide for academic researchers.”

The Funding Breakdown

Urbint nabs $60M – As the U.S. prepares to spend hundreds of billions of dollars repairing national infrastructure, AI is being heralded as a solution to long standing challenges. In addition to Urbint, who says its software can make predictions about construction, maintenance, and field operations failures up to a week in advance, Alphabet’s “moonshot” X lab and startups like Myst and Autogrid are also working on similar technologies.?

Ramp raises $300M – In addition to the raise, Ramp, which offers a corporate card focused on cost savings, today said it acquired Buyer, a “negotiation-as-a-service platform” that aims to help enterprise customers save on purchases like annual software contracts.

Hunters secures $30M – Ofer Schreiber, partner at YL Ventures, which co-led the company’s seed round, said this additional investment is an affirmation of faith in the extended detection and response (XDR) category. Indeed, competition among providers of XDR platforms seeking to replace legacy security information event management (SIEM) platforms is intensifying.

Moesif raises $12M – The API analytics startup aims to create an open API platform for developers to create custom reporting and workflows in pursuit of better product experiences. APIs can be a massive revenue driver; as of 2015, Expedia generated 90% of its revenue through APIs, for example. And with the success of “API-first” companies like Stripe and Twilio, which are now valued at $95 billion and $65 billion, respectively, companies are investing in new API-first strategies at a record pace.

AI in the Cloud Contact Centre

Artificial Intelligence (AI)

Artificial Intelligence & Machine Learning are arguably the most transformative technologies available to mankind today.

AI is impacting every area of service delivery, and customer service is no exception. Call centre work is sometimes repetitive, but there’s often no one-size-fits-all template for responding to customer queries and complaints. This means it can be a perfect use case for machine learning and automation. However, it’s vital that the use of AI and automation is done in a way that doesn’t deprive your customers of human contact at the time they need it most!

Customers calling into call centres have high expectations of the experience they will receive, and a low threshold for disappointment. For example, in the telco sector, research shows that 70% of customers place experience among the three most important factors when making buying decisions. In fact, 43% say that one poor customer relationship experience is enough to make them cut ties with a brand.

Automation can certainly help companies reduce cost when it comes to dealing with customer enquiries. But is that really helpful, if it’s also going to drive away customers? Today, though, thanks to advances in AI, companies are finding ways to automate call centre processes that not only avoid a negative customer experience, but also deliver an improved experience.

This is a huge driver behind the adoption of AI in call centres right now, in a world where enterprises in general are moving away from the idea that advanced technology exists merely to reduce costs, but instead is a driver of growth and new business opportunities.

Call Routing

Even with advanced natural language based processing (NLP) systems, call centres will, for some time yet, have to deal with questions that are too sophisticated for automated information systems. But NLP systems can certainly help direct callers to the right human that can answer the question.

Everyone who has contacted a contact centre will know that it can be infuriating to get put through to the wrong person, and then have to re-join a queue to be put through to someone else. If automated routing systems can reduce the instance of this happening by more accurately predicting the reason for a person’s call, they can certainly improve customer experience.

Early attempts at automating call routing often provided a poor experience, forcing humans to wait through lengthy menus before choosing the option they wanted, or offering poorly implemented, non-AI voice recognition. NLP can help companies tackle this problem today with voice recognition that is accurate and gets better as it learns from interacting with more and more customers. It can even predict which callers are best suited to which agents, based on personality traits or the agents’ success at solving similar problems in the past.

Jonathan Rosenberg, CTO and head of AI at intelligent cloud contact centre provider Five9, told me, “AI has immense business value in the contact centre, an area where every minute matters – for the customer, for service agents, and for the organization. It is also an area that is dominated by people doing very repetitive tasks, and the combination of those two factors is a recipe for AI-powered transformation.”

AI also augments the abilities of human call handlers to provide guidance for questions they face on the fly.

Augmented Workforces

There’s a lot of talk about whether widespread automation will lead to large-scale human redundancy and unemployment. But today, at least, the focus within forward-thinking organisations is very much on using automation to enhance employees’ abilities to do their jobs, rather than replacing them.

Genefa Murphy, chief marketing officer at Five9, says, “Organizations are increasingly seeing the potential of AI and automation to work alongside their contact centre agents, rather than as a means of replacing them to cut costs.

“It has become clear that the future of customer care is an “and,” not an “or,” strategy and will be powered by human agents and a digital workforce. With a digital workforce, AI is persistent. It’s used before, during, and after the customer interaction.”

In this respect, AI can act as a second pair of ears for the customer service agent – listening in on the communication and automatically suggesting solutions to the agent as to how the customer’s?issue might best be resolved. When this is done in a way that reduces the?need for the caller to wait while the agent manually consults a database of potential remedies to find the correct solution, this can also improve customer experience.