#ChatGPT App Development Company

[smtlabsio]

If you are looking to elevate user engagement with cutting-edge ChatGPT applications! SMT Labs, the best ChatGPT Application Development Company, brings expertise and creativity to transform your ideas into conversational masterpieces. We're the premier ChatGPT Application Development Company at SMT Labs, dedicated to crafting conversational masterpieces that captivate and engage your audience. We combine cutting-edge technology with uncontrolled creativity to bring your ideas to life, altering how users interact with your brand.

[cryptocurrencydevelop]

Elevating Communication: The Art of Developing ChatGPT Applications

ChatGPT - An Overview

ChatGPT, short for Chat Generative Pre-Trained Transformer, was built by a popular AI research company called Open AI. This technology, functioning as an AI chatbot, has the capability to comprehend natural human language and formulate appropriate responses. In simple terms, you can pose a question to ChatGPT and it will provide you with an answer. It doesn't just answer questions, you can also ask it to help plan a fun day in a tourist city, write a computer code, or solve mathematical equations. The tool will likely provide you with the information you're looking for.

Business Benefits Of Launching ChatGPT Like Application:

Innovative Collaboration: It fosters collaborative efforts within teams by assisting in brainstorming sessions, idea generation, and facilitating communication, enhancing overall productivity.

Data Insights: The platform can generate valuable insights by analyzing user interactions, helping businesses understand customer preferences, pain points, and trends for informed decision-making.

Time and Cost Savings: Automation of tasks through a ChatGPT-like platform reduces the time spent on routine queries, allowing businesses to allocate resources more efficiently and potentially lowering operational costs.

Efficient Customer Support: Businesses can use the platform to streamline customer support processes, addressing queries and issues effectively, resulting in improved service efficiency.

Enhanced Customer Engagement: A platform like ChatGPT improves customer interactions by providing intelligent and prompt responses, leading to increased satisfaction and engagement.

Extensive Money Making Options: Launching a ChatGPT-like platform helps in generating huge revenue through various monetization strategies.

These wide range of benefits has attracted numerous entrepreneurs looking to launch an AI tool similar to ChatGPT. If you are one among them, then hire an expert team of AI developers to launch your own chatbot like ChatGPT.

ChatGPT Application Development

For businesses and individuals seeking skilled ChatGPT developers, Developcoins is the ideal choice. As a prominent AI development company, we can assist you in creating an exceptional AI Chatbot system that surpasses your expectations. Committed to excellence, we bring innovation, reliability, and personalized solutions to our AI-based chatbot development services. To know more in detail about the perks of our ChatGPT Application Development, connect with our experts now.

[app-development-stuff]

ChatGPT App Development Company

[jcmarchi]

Maciej Saganowski, Director of AI Products, Appfire – Interview Series

New Post has been published on https://thedigitalinsider.com/maciej-saganowski-director-of-ai-products-appfire-interview-series/

Maciej Saganowski, Director of AI Products, Appfire – Interview Series

Maciej Saganowski is the Director of AI Products at Appfire.

Appfire is a leading provider of enterprise software solutions designed to enhance collaboration, streamline workflows, and improve productivity across teams. Specializing in tools that integrate with platforms like Atlassian, Salesforce, and Microsoft, Appfire offers a robust suite of apps tailored for project management, automation, reporting, and IT service management. With a global presence and a commitment to innovation, the company has become a trusted partner for organizations seeking to optimize their software ecosystems, serving a wide range of industries and empowering teams to achieve their goals efficiently.

Appfire is known for providing enterprise collaboration solutions, can you introduce us to Appfire’s approach to developing AI-driven products?

Over the past year, the market has been flooded with AI-powered solutions as companies pivot to stay relevant and competitive. While some of these products have met expectations, there remains an opportunity for vendors to truly address real customer needs with impactful solutions.

At Appfire, we are focused on staying at the forefront of AI innovation, enabling us to anticipate and exceed the evolving needs of enterprise collaboration. We approach AI integration with the aim of delivering real value rather than merely claiming “AI-readiness” only for the sake of differentiation. Our approach to developing AI-driven products centers on creating seamless, impactful experiences for our customers.

We want AI to blend into the user experience, enhancing it without overshadowing it or, worse, creating an extra burden by requiring users to learn entirely new features.

“Time to Value” is one of the most critical objectives for our AI-powered features. This principle focuses on how quickly a user—especially a new user—can start benefiting from our products.

For example, with Canned Responses, a support agent responding to a customer won’t need to sift through the entire email thread; the AI will be able to suggest the most appropriate response template, saving time and improving accuracy.

Appfire has partnered with Atlassian to launch WorkFlow Pro as a Rovo agent. What makes this AI-powered product stand out in a market filled with similar products?

This category of products is relatively uncommon. We are one of the first companies to ship a Jira-class software automation configuration assistant—and this is only the beginning.

WorkFlow Pro is an AI-powered automation assistant for Jira that is transforming how teams set up and manage their automation workflows. Powered by Atlassian’s Rovo AI, it assists users in configuring new automations or troubleshooting existing ones.

Historically, Jira automation products have been complex and required a specific level of expertise. WorkFlow Pro demystifies these configurations and enables new or less-experienced Jira admins to accomplish their tasks without spending time on product documentation, forums, or risking costly mistakes.

A new Jira admin can simply ask the agent how to perform a task, and based on the automation app installed (JMWE, JSU, or Power Scripts), the agent provides a step-by-step guide to achieving the desired outcome. It’s like having a Michelin-star chef in your kitchen, ready to answer any question with precise instructions.

At Appfire, we are committed to simplifying the lives of our customers. In the next version of WorkFlow Pro, users will be able to request new automations in plain English by simply typing the desired outcome, without the need to navigate the configurator UI or know any scripting language. Returning to our chef analogy, the next version will allow the user not only to ask the chef how to cook a dish but to prepare it on their behalf, freeing them up to focus on more important tasks.

How do you involve user feedback when iterating on AI products like WorkFlow Pro? What role does customer input play in shaping the development of these tools?

At Appfire, we stay very close to our users. Not only do our designers and product managers engage regularly with them, but we also have a dedicated user research group that undertakes broader research initiatives, informing our vision and product roadmaps.

We analyze both quantitative data and user stories focused on challenges, asking ourselves, “Can AI help in this moment?” If we understand the user’s problem well enough and believe AI can provide a solution, our team begins experimenting with the technology to address the issue. Each feature’s journey begins not with the technology but from the user’s pain point.

For instance, we learned from our users that new admins face a significant barrier when creating complex automations. Many lack the experience or time to study documentation and master intricate scripting mechanisms. WorkFlow Pro was developed to ease this pain point, helping users more easily learn and configure Jira.

Beyond WorkFlow Pro, Appfire plans to develop additional AI-driven applications. How will these new products transform the way users set goals, track work, and harness data more effectively?

AI will have a profound impact on what future knowledge workers can accomplish and how they interact with software. Organizations will evolve, becoming flatter, more nimble, and more efficient. Projects will require fewer people to coordinate and deliver. While this sounds like a bold prediction, it’s already taking shape through three key AI-powered advancements:

Offloading technically complex or mundane tasks to AI

Interacting with software using natural language

Agentic workflows

We’re already seeing AI reduce the burden of mundane tasks and ease new users into these products. For instance, AI assistants can take meeting notes or list action items. To illustrate this on the Appfire example, when a manager creates a new Key Result within their OKR framework, the AI will suggest the Key Result wording based on industry best practices and the company’s unique context, easing the mental load on users as they learn to define effective OKRs.

Natural language interfaces represent a major paradigm shift in how we design and use software. The evolution of software over the past 50 years has created virtually limitless capabilities for knowledge workers, yet this interconnected power has brought significant complexity.

Until recently, there wasn’t an easy way to navigate this complexity. Now, AI and natural language interfaces are making it manageable and accessible. For example, one of Appfire’s most popular app categories is Document Management. Many Fortune 500 companies require document workflows for compliance or regulatory review. Soon, creating these workflows could be as simple as speaking to the system. A manager might say, “For a policy to be approved and distributed to all employees, it first needs to be reviewed and approved by the senior leadership team.” AI would understand this instruction and create the workflow. If any details are missing, the AI would prompt for clarification and offer tips for smoother flows.

Additionally, “agentic workflows” are the next frontier of the AI revolution, and we’re embracing this at Appfire with our agent WorkFlow Pro. In the future, AI agents will act more like human collaborators, capable of tackling complex tasks such as conducting research, gathering information from multiple sources, and coordinating with other agents and people to deliver a proposal within hours or days. This agent-run approach will go beyond simple interactions like those with ChatGPT; agents will become proactive, perhaps suggesting a draft presentation deck before you even realize you need one. And voice interactions with agents will become more common, allowing users to work while on the go.

In summary, where we’re heading with AI in knowledge work is akin to how we now operate vehicles: we know where we want to go but typically don’t need to understand the intricacies of combustion engines or fine-tune the car ourselves.

You’re also enhancing existing Appfire products using AI. Can you give us examples of how AI has supercharged current Appfire apps, boosting their functionality and user experience?

Each of our apps is unique, solving distinct user challenges and designed for various user roles. As a result, the use of AI in these apps is tailored to enhance specific functions and improve the user experience in meaningful ways.

In Canned Responses, AI accelerates customer communication by helping users quickly formulate responses based on the content of a request and existing templates. This AI feature not only saves time but also enhances the quality of customer interactions.

In OKR for Jira, for example, AI could assist users who are new to the OKR (Objective and Key Results) framework. By simplifying and clarifying this often complex methodology, AI could provide guidance in formulating effective Key Results aligned with specific objectives, making the OKR process more approachable.

Finally, WorkFlow Pro represents an innovative way to interact with our documentation and exemplifies our commitment to agentic workflows and natural language automation requests. This AI-driven approach reduces the barrier to entry for new Jira admins and streamlines workflows for experienced admins alike.

Shared AI services, such as the summarization feature, are being developed across multiple Appfire apps. How do you envision these services impacting user productivity across your platform?

At Appfire, we have a broad portfolio of apps across multiple marketplaces, including Atlassian, Microsoft, monday.com, and Salesforce.

With such a large suite of apps and diverse use cases for AI, we took a step back to design and build a shared internal AI service that could be leveraged across multiple apps.

We developed a platform AI service that allows product teams across our apps to connect to multiple LLMs. Now that the service is live, we’ll continue expanding it with features like locally run models and pre-packaged prompts.

With the rapid evolution of AI technologies, how do you ensure that Appfire’s approach to AI development continues to meet changing customer needs and market demands?

At Appfire, a product manager’s top priority is bridging the gap between technical feasibility and solving meaningful customer problems. As AI capabilities advance rapidly, we stay up to date with market trends and actively monitor the industry for best practices. On the customer side, we continually engage with our users to understand their challenges, not only within our apps but also in the underlying platforms they use.

When we identify an overlap between technical feasibility and a meaningful customer need, we focus on delivering a secure and robust AI feature. Before launching, we experiment and test these solutions with users to ensure they genuinely address their pain points.

Appfire operates in a highly competitive AI-driven SaaS landscape. What steps are you taking to ensure your AI innovations remain unique and continue to drive value for users?

Appfire’s approach to AI focuses on purpose. We’re not integrating AI just to check a box; our goal is for AI to work so naturally within our products that it becomes almost invisible to the user. We want AI to address real challenges our customers face—whether it’s simplifying workflows in Jira, managing complex document processes, or streamlining strategic planning. Ideally, using AI should feel as intuitive as picking up a pen.

Many SaaS products have traditionally required specialized expertise to unlock their full potential. Our vision for AI is to reduce the learning curve and make our apps more accessible. With the launch of our first Rovo agent, WorkFlow Pro, we’re taking an important step in this journey. Ultimately, we aim to ensure AI within our apps enables users to achieve value more quickly.

Looking ahead, what trends in AI development do you think will have the greatest impact on the SaaS industry in the coming years?

Two major AI trends that will shape the SaaS industry in the coming years are the rise of AI-powered agents and increasing concerns about security and privacy.

Some argue that agent technology has yet to live up to its hype and remains relatively immature. To these skeptics, I’d say that we often overestimate what technology will achieve in 1–2 years but vastly underestimate what it will accomplish over a decade. While current agent use cases are indeed limited, we are witnessing massive investments in agentic workflows throughout the software value chain. Foundational models from companies like OpenAI and Anthropic, along with platforms Appfire currently operates or plans to operate on, are making extensive investments in agent technology. OpenAI, for instance, is working on “System 2” agents capable of reasoning, while Anthropic has launched models capable of using regular apps and websites, emulating human actions. Atlassian has introduced Rovo, and Salesforce has launched Agentforce. Each week brings new announcements in agentic progress, and, at Appfire, we’re excited about these developments and look forward to integrating them into our apps.

At the same time, as AI capabilities expand, so do the risks associated with data security and privacy. Enterprises must ensure that any AI integration respects and protects both their assets and those of their customers, from sensitive data to broader security measures. Balancing innovation with robust security practices will be essential to unlocking AI’s full value in SaaS and enabling responsible, secure advancements.

Thank you for the great interview, readers who wish to learn more should visit Appfire. 

[atcuality1]

Advanced WordPress Security Services for Peace of Mind

A secure website is essential for any business, whether you’re running an e-commerce platform or a blog. At Atcuality, we provide advanced WordPress security services tailored to your specific needs. Our solutions include malware removal, vulnerability scanning, and backups to safeguard your data. We also offer 24/7 monitoring to ensure immediate response to any security breaches. With a focus on providing end-to-end protection, we help businesses maintain credibility and uptime. Partner with us and experience unmatched security for your WordPress site, ensuring that you stay one step ahead of cyber threats.

[oliviaemiley444]

Fintech Fun: Exploring the Cool Benefits of Fintech and Chatbots

Introduction:

Hey there little buddies! Today, we're going on a super cool adventure to explore something called "Fintech." It's like a special kind of magic that helps us with money, and guess what? Chatbots are our new superhero friends in this fintech world! Let's find out what fintech is, how chatbots help, and why it's all so awesome.

 What is Fintech? 

Fintech is like having a superhero friend for your money. It stands for "financial technology," and it's all about using smart computer tricks to make handling money way more fun and easy. Imagine your piggy bank getting a digital upgrade – that's fintech in action!

The Cool Benefits of Fintech 

1. Digital Piggy Banks:

With fintech, your piggy bank goes digital! It's like having a secret treasure chest inside your tablet or phone. You can see your money growing and even set goals for special treats or toys.

2. Quick Money Moves:

Fintech, along with chatbots, helps you buy things super fast. It's like using a magic spell to get your favorite toys in a blink! No more waiting – just a tap on the screen, and it's yours.

3. Saving Adventures:

Saving money becomes an exciting quest with fintech apps and chatbots. Picture it as a cool game where you collect coins and unlock rewards. Saving for that awesome toy becomes a fun adventure!

4. Learning with Games:

Guess what? Fintech and chatbots aren't just for grown-ups. There are games that teach you about money and how to be a money master. It's like playing your favorite video game while becoming a money superhero!

 Fintech Explorers Club

You can be part of the Fintech Explorers Club! It's like a club where we learn about the future of money together. Imagine being in a secret group where you're the expert in cool fintech and chatbot stuff!

Conclusion 

So, little buddies, fintech is like having a magical friend for your money. Digital piggy banks, quick money moves, saving adventures – fintech and chatbots make handling money a big, awesome adventure! Join the Fintech Explorers Club, and let's explore the future of money and chatbots together!

[appsdevelopmentservice]

Find out how much it costs to build a chatbot app like ChatGPT. From ChatGPT API license costing to ongoing maintenance costs. Catch it now!

[perfectiongeeks]

How ChatGPT and Bard are Helping Websites and Apps

Google Search has been the dominant search engine on the Internet for a long time. ChatGPT was the first possible rival to Google Search last year. It is an innovative chatbot developed by OpenAI that aims to revolutionize the technology industry. OpenAI's ChatGPT quickly gained more than a million users in a week after its release. This caused alarm at Google, even though ChatGPT has room to grow. Google's business intelligence services introduced Google Bard in 2023 as a response. Businesses that offer process outsourcing are constantly looking for new ways to grow and improve their businesses. AI and machine-learning technology can now help companies streamline their processes and increase their revenue. Many people believe that these new inventions will soon replace us and threaten our jobs. Here, we'll learn about these AI tools and how they could help your business.

Visit us:

[ibrinfotech]

IBR Infotech is a leading chat app development company that provides chat app development solutions that meet your business needs. Contact us today.

[dreamschat-dreamguystech]

Introducing a New Era of Streamlined Communications Beyond Simple Conversations in "Dreamschat 2023"

Dreamschat is a Real-time chat application that utilizes advanced language models like ChatGPT to enable users to have conversations with unprecedented depth and detail.

The concept behind Dreamschat is simple yet powerful.

In this article, we are going to look at how Dreamschat is transforming team communication software and redefining how we communicate.

Whether the user wants to talk about career goals, personal aspirations, or creative ideas, Dreamschat can help explore thoughts and gain new insights. 

Dreamschat is a powerful communication platform that goes beyond small talk. It enables users to delve into deeper topics and ideas, explore complex issues, and have meaningful discussions. This is particularly valuable for individuals or groups looking to solve challenging problems or gain new insights.

One of the key advantages of Dreamschat is that it fosters conversations that are focused on specific topics or areas of interest. This enables users to engage in discussions that are relevant to them and can lead to greater understanding and collaboration.

Dreamschat is also designed to be a safe and inclusive space where users can express themselves freely without fear of judgment or harassment. It includes features such as moderation tools and privacy settings that enable users to control who can see their conversations.

Dreamschat with ChatGPT

The success of Dreamschat lies in its ability to use natural language processing (NLP) and machine learning (ML) techniques to understand and respond to human language.

ChatGPT, the language model powering Dreamschat, has been trained on vast amounts of text data and has learned to generate text that sounds like it was written by a human. This makes conversations with Dreamschat feel natural and engaging, even though the user is talking to a machine.

Generative Pre-trained Transformer, or GPT, is a kind of language model that creates text that resembles human speech via unsupervised learning. The model is pre-trained on a large corpus of text data and then fine-tuned for specific tasks such as language translation, text summarization, or in the case of Dreamschat, conversational AI. 

One of the benefits of using GPT in Dreamschat is its ability to generate coherent and engaging responses. Unlike rule-based chatbots that rely on predefined scripts, GPT can generate responses that are contextually relevant and conversational in nature.

Another benefit of using GPT in Dreamschat is its ability to learn from ongoing conversation. As users continue to talk to Dreamschat, GPT can adapt and improve its responses based on the user's input. This helps to create a more personalized experience for the user and makes the conversation more meaningful and insightful.

Team Communication Software

Dreamschat has the potential to revolutionize team communication software by facilitating deep and meaningful conversations among team members. This open and supportive environment can foster a collaborative and innovative team culture, empower every team member to contribute their ideas and insights, and promote continuous learning and improvement.

To Conclude

Overall, Dreamschat is a unique chat application that offers a new and innovative way to communicate. The integration of GPT in Dreamschat is a powerful example of how advanced language models can be used to create engaging and meaningful conversational AI. By leveraging GPT's ability to generate natural language responses and learn from ongoing conversations, Dreamschat is changing the way we communicate in 2023.

Looking for fresh, creative approaches to enhance internal communication in your business? Try Dreamschat, a cutting-edge chat programme that can help your team work more efficiently towards common objectives by encouraging innovation and creativity.

Try Dreamschat today and revolutionize the way you communicate in 2023! Contact : email: business@dreamguystech.com, phone : 91 99425 76886.

[smtlabsio]

SMT Labs is a leading app development company that develops chatbots using ChatGPT technology. Our team of professional developers can create custom chatbots for any business or industry. Our chatbots are designed to be engaging, informative, and helpful, and they can be used to improve customer service, provide product information, and generate leads. If you want to hire the Best ChatGpt App Development Company to automate your customer service, improve your marketing, or increase your sales, then SMT Labs can help you develop a chatbot that meets your needs.

[xicomtechnologiesllc]

ChatGPT: The Future of Mobile App Development

Mobile apps have become an integral part of our daily lives. From shopping and social media to productivity and entertainment, there’s an app for almost everything. As the demand for mobile apps continues to grow, so does the need for innovative and efficient app development solutions. This is where ChatGPT comes in – the future of mobile app development. What is ChatGPT? ChatGPT is a language…

[jcmarchi]

AI and The Coming Implosion of Media

New Post has been published on https://thedigitalinsider.com/ai-and-the-coming-implosion-of-media/

AI and The Coming Implosion of Media

It is popular among journalists these days to warn that AI might have catastrophic effects on humanity. These concerns are overblown with regards to humanity as a whole. But they are actually quite prescient with regards to journalists themselves.

To understand why, let’s take a closer look at the sub-disciplines that we collectively call AI. AI is the widest umbrella term, but we can generally break it down into rule-based systems and machine-learning systems. Machine-learning systems can be broken down by their application (video, images, natural language, etc). Among these, we’ve seen the greatest recent strides made in natural language processing. Specifically, we’ve seen the invention of the transformer model in 2017, followed by rapid growth in the size of transformers. Once the model exceeds 7 billion parameters, it is generally referred to as a large language model (LLM).

The core “skill” (if you might call it that) of an LLM is its ability to predict the most likely next word in an incomplete block of text. We can use this predictive mechanism to generate large blocks of text from scratch, by asking the LLM to predict one word at a time.

If you train the LLM on large datasets with variable quality, this predictive mechanism will often produce bad writing. This is the case with ChatGPT today. This is why, whenever I broach the topic with journalists, I encounter skepticism – journalists see how badly ChatGPT writes, and they assume AI poses no threat to them because it’s inept.

But ChatGPT is not the only LLM out there. If an LLM is trained on a carefully-selected dataset of text written by the best journalists – and no one else – then it will develop the ability to write like the best journalists.

Unlike journalists, however, this LLM will require no salary.

Writing vs. Knowing What to Write

Before we proceed, we need to distinguish between the mechanics of writing and the creativity required to know what is worth writing about. AI can’t interview whistleblowers or to badger a politician long-enough for the politician to accidentally tell the truth.

AI cannot gather information. But it can describe information gathered by humans in an eloquent way. This is a skill that journalists and writers used to have a monopoly over. They no longer do.

Given the current rate of progress, within a year, AI could write better than 99% of journalists and professional writers. It will do so for free, on demand, and with infinite throughput.

The Economics of Zero-Cost Writing

Anyone who has a list of facts to convey will be able to turn these facts into a well-written article. Anyone who finds an article on any subject will be able to produce another article, covering the same subject. This derivative article will be just as good as the first one, and won’t plagiarize it or violate its copyrights..

The marginal cost of written content will become zero.

Currently, the economics of written media are based on human labor. Well-written content is scarce, so it has value. Entire industries were built to capture this value.

When AI can produce high-quality content for free, the financial foundation of these industries will collapse.

The Abolition of Publications

Consider traditional publications. For decades, companies like The New York Times have employed skilled writers to produce a limited number of articles each day (typically around 300). This model is inherently constrained by the number of writers and the costs involved.

In a world where AI can generate an unlimited number of articles at no cost, why limit production to a fixed number? Why not create personalized content for every reader, tailored to their interests and generated on demand?

In this new paradigm, the traditional model of periodic issues and fixed article counts becomes obsolete. Publications can shift to a model where content is continuously created and personalized, catering to the specific needs of individual readers. One reader might need a single article each day. Another might need 5000.

Publications whose primary product is packing 300 articles into a single daily issue will go extinct.

Search Engines Becoming Answer Engines

Search engines act as distributors, connecting users to pre-existing content. To achieve this, they perform four steps.

First, they index vast amounts of pre-written content. Second, they receive a query from the user. Third, they search the pre-written content to find items that are relevant to the user’s query. And fourth, they rank the retrieved content and present a sorted list of results to the user.

So far so good. But if content can be created on demand, for free, then why would search engines return pre-existing content to the user? They could simply generate the answer instead. The user would certainly be happier with a single answer to her query, instead of a long list of results whose quality may vary.

Now let’s consider the logical next step. If search engines no longer lead users to any content written by others, what would happen to the “content” economy?

Most content on the internet was written to be monetized. People write articles, rank on Google, receive traffic, and turn it into income (using ads, affiliate links, or direct sales of products or services).

What will happen to this ecosystem when the traffic disappears?

Social Media: The Next Domino

Social media platforms were initially designed to facilitate interaction between users. I am old enough to remember the days when people logged into Facebook to write on a friend’s wall, poke, or throw a virtual sheep at someone.

Today’s social media is different. The most common number of followers users have on Instagram is zero. The second most common number of followers is one. The vast majority of views, shares, comments and followers is amassed by a small number of professional creators. Most users post nothing and are followed by no one.

Simply put – most users visit social media to find content they might enjoy. Social media companies act as distributors, just like search engines. The main difference between Facebook and Google is that Google uses a query to select content, whereas Facebook selects content without one.

If this is the case, then the next step becomes obvious. Why would social media promote user-generated content, when they can generate AI-based content on demand? Text-only at first, perhaps, but eventually images and videos too.

And once social media no longer leads users to content made by creators, what will happen to the “creator economy”?

The Star Trek Replicator Analogy

We are entering a new paradigm where AI functions as a Star Trek replicator for content.

In Star Trek, there is no need for farmers who grow food, stores who sell food, chefs who cook food or waiters who serve food. The replicator can create any food you like, on demand, by directly transforming raw materials into the final product.

Likewise, I see no place in our future for any company who creates written content, distributes written content, mixes written content in some special way, or serves pre-existing written content to the user. The only valuable functions will be obtaining raw materials and transforming them into the final product on demand.

We still need ways to create information that did not exist before and gather information that was not publicly available before. Everything else will be achieved by AI engines that convert the available information into personalized content.

Implications for Content Creators and Distributors

Traders often talk about “positive exposure” and “negative exposure”. The easiest way to understand these concepts is to ask yourself – if this thing goes up, will I benefit or suffer?

AI is going up. And it is going up especially fast in areas like natural language and other human-generated content. The question every professional needs to ask themselves is – do I have positive or negative exposure to AI right now?

If you are a content creator – let’s say a news publication – and your cost structure is non-zero, then you are likely in trouble. You will soon be competing with content creators whose cost is zero, and that is not a competition you can win. In all likelihood, you have exactly 3 choices: exit the market; reduce your costs to zero (by becoming an AI company); or go bankrupt.

If you are on the distribution side of things, you probably have more time before the full effects reach your bottom line. Network effects will help you stave off the disruption for a few years. But eventually, things that must happen, do happen. Search engines replaced web directories. Feeds replaced a large part of the function search engines served before. And soon, on-demand content creation will replace both.

The Role of Government and Regulation

As someone who was born in the Soviet Union, I am not a big fan of government regulating speech. The moral hazards are usually higher than any temporary benefit such regulation might bring.

Nevertheless, I think that governments might have an important role to play in determining how this unfolds.

We have good and bad examples of government regulations and the effects they’ve had on industry. The “26 words that created the internet” grew a nascent industry to trillions of dollars in value. The regulation of ISPs in the 90s, however, brought down the number of ISPs in the US from over 3000 to 6, and resulted in a situation where US consumers have the worst bandwidth access in the developed world.

When asked for my recommendations, I usually point out three ways in which government regulation can help, rather than hinder, the development of this new ecosystem:

1. Mandate interoperability, and make it easier for consumers to switch providers.

Capitalism works like natural selection – companies that do  things better or more efficiently will grow faster than companies who don’t. “Lock in” mechanisms that make it harder to switch, like the inability to export one’s data out of a service and port it to a competitor, slow down this evolution and result in lower growth.

If governments can mandate interoperability throughout the tech industry, we will see more good features and good behaviors rewarded. We will create incentive for companies to innovate in things people want, rather than innovating in ways to squeeze more out of a captive audience.

2. Enforce antitrust by focusing on monopoly abuses, rather than monopoly risks.

We all know that when two companies merge, the resulting entity might become large and have outsized power relative to its customers. But the existence of outsized power does not always lead to bad service or predatory pricing.

Meanwhile, companies who already have outsized power are often engaging in anti-competitive behaviors right before our eyes. And yet the FTC focuses on blocking mergers and acquisitions.

If governments focus on banning and strict enforcement of anti-competitive practices like dumping and bundling, especially with regards to tech products that are used by the majority of the population, the entire system will become unclogged.

Some specific examples might help illustrate this point.

Providing a browser, which is a very complex piece of software that costs billions to develop, for free – is a clear case of dumping. New browser companies like Cliq or Brave find it hard to innovate in this space because their much larger competitors give this expensive product away for free. The result is that all browsers look the same these days, and there’s been no significant innovation in this space since 2016.

Providing a corporate messaging app as a part of a document editing suite that every business must buy – is a clear case of bundling. Even a very successful startup like Slack was essentially forced to sell itself to a larger company, just to be able to compete as a paid product in a space where their main competitor is bundled with something their customer must have anyway.

As AI develops into a new ecosystem that becomes larger than the internet, we’re bound to see even greater abuses in this nascent space – unless governments step in and ensure that dumping and bundling do not pay.

3. Consider ways to subsidize or protect original content creation.

Government funds basic research and science through grants and other subsidies. It also protects new ideas that people discover in their research through patents. The reason these two mechanisms are necessary is that copying an idea that works is much cheaper than coming up with a new idea that works. Without intervention, this might lead to a tragedy of the commons where everyone copies from their neighbor and no one creates anything new.

In journalism, and content creation in general, these mechanisms were unnecessary because copying without violating copyrights was a difficult process. But with the advent of AI, this is no longer true. As the price of paraphrasing others’ writing approaches zero, we will need mechanisms to incentivize something other than paraphrasing – and the best answers might look a lot like the ones we have in basic research today.

Making the Best of this Challenge

The transformation brought about by AI is one of the greatest challenges facing humanity today. Journalists and other content creators will be affected first. Distributors of content will follow soon thereafter. We will eventually enter a completely new paradigm, which I referred to as the “Star Trek Replicator” model for content creation and distribution.

We have an opportunity here to build something much better than what exists today. Just as the invention of the printing press led to the Enlightenment, the invention of AI could lead to a second Enlightenment. But unfortunately, not all the possible futures are benign.

It’s up to us to nudge this evolution in the right direction.

[hiehq]

How ChatGPT can be leveraged in social media apps?

Go for ChatGPT integration to embrace the power of AI with Hie HQ

Know How- https://hiehq.com/blog/chatgpt-and-social-media-apps-harnessing-the-ai-power-of-language-generation/