#How to make money with ChatGPT in 2023 ( 20+ ways)

[ashimkumar]

ChatGPT for Internet Marketers (PLR) Review 2023

ChatGPT for Internet Marketers PLR OTO – Make More Money With AI is WONDERFUL. We’ve created a masterclass teaching internet marketers how to use ChatGPT to increase their productivity and make more money online. You can download that course from this page today. AND. Better yet… we’re including full Private Label Rights, so you can also SELL this course as your own product and keep all the profits. 

ChatGPT for Internet Marketers PLR OTO – Make More Money With AI. In a nutshell, ChatGPT is the Hottest Topic on the Entire Internet Right Now… Here’s Your Chance to Cash In by Selling This ChatGPT Course as Your Own Product. We’ve created a masterclass teaching internet marketers how to use ChatGPT to increase their productivity and make more money online. You can download that course from this page today. AND. Better yet… we’re including full Private Label Rights, so you can also SELL this course as your own product and keep all the profits.

With hundreds of millions of people looking for this information right NOW, this is the perfect way for you to cash in on this trend ; Here’s what you’ll be getting… 20 Step by step tutorial videos showing how to use ChatGPT in your business, 20 Audio files from those videos, 20 text transcripts, Graphics for this package, and more. Yes, we’re even including a copy of this very sales page, so you can sell this package with Private Label Rights, just like we’re doing. Some of the things you can do with this package include.

Here’s what you’ll be getting…

20 Step by step tutorial videos showing how to use ChatGPT in your business.

20 Audio files from those videos.

20 text transcripts.

Graphics for this package.

Promo tools. (Emails, banners, basic sales page)

A lead magnet (report) with a squeeze page and download page.

A copy of this sales page, plus a download page!

For More Details Information:

[digitalnomadhub]

Errr Negative Thoughts

Kahit na I practice gratitude, hindi ko pa rin maiwasan maoverpower ng negative thoughts. I was triggered by someone na may utang sakin and naisip ko ang money ko ngayon na nabawasan pa savings ko. Hindi ko mabalik yung balance ng bank ko.

Tapos yung 200K na nagastos ko sa shopping as of August. Haha Hays. Mas madali ako nakamove on sa utang ng parents ko kahit mas malaki pa kasi I have no control over that pero iniisip ko ngayon na sana di ko nagastos or bat ba ko napabili ng mga ganito. Kung sana tinipid ko na lang o ininvest sa ibang bagay. Hindi ko tuloy nasimulan yung work ko kakaisip kung paano ko mabubuo yung balance ko. Goal ko pa naman makaipon ng 500K to 1M.

May travel pa ko sa Japan and Baguio. Pero last naman na this year.

How can I learn from my 2024 experience?

Una, thankful ako sa 2023 and sa salary increase dahil malaki ang naipon ko at ito ang nagsave sakin kahit na nagoverspend talaga ko this year, hindi ako naging broke. Nabawasan lang savings at hindi napaayos yung house huhu. Para tuloy wala akong effort itaas ang finances ko this year or magimprove man lang pero siguro this lesson will grow my money exponentially next year. Manifesting!

Second, over time, at least this August, hindi December haha. I am beginning to understand what decisions led me to this place so I can avoid going back here. Hindi na ulit magooverspend or magja-Japan every quarter or mapo FOMO.

Third, mas naging maayos ang spreadsheet ko at nanotice ko din yung signs na kakabahan na talaga ko kasi hindi na ko advance magbayad at nagaabang na ng sweldo. Kaya nagiging emotional ngayon na dati naman, wala kong pake. Ngayon, sakto lang sa bills yung income na dumarating. Mapifree up naman yung bills after 2 months kaya looking forward ako na mabalik din ang ipon.

Lastly, I am accepting na din na hindi na mababalik yun and I can only do something now kesa magcontemplate sa past. I want to make better actions moving forward. 20s pa naman ako. Laban lang.

So according to chatgpt, here are the things I will do from now on.

Reframe Negative Thoughts: When you find yourself dwelling on negative thoughts, try to reframe them in a more positive light. Ask yourself "How else could I look at this situation?"

Limit Negative Input: Be mindful of the media, news, and people you surround yourself with. Try to limit exposure to overly negative content and people.

Celebrate Small Wins: Don't just focus on big achievements. Recognize and celebrate the small positive things that happen each day.

Use Positive Affirmations: Repeat positive statements to yourself, such as "I am capable" or "Good things are coming my way." This can help shift your mindset.

Practice Mindfulness: Being present in the moment can help you appreciate the positive aspects of your current situation, rather than dwelling on the past or worrying about the future.

Seek out Positivity: Surround yourself with uplifting books, podcasts, and people who inspire you and make you feel good.

The key is to make a conscious effort to shift your focus and train your brain to notice the good things in your life, even when it's easier to dwell on the negative. With consistent practice, you can rewire your brain to have a more positive outlook.

Sana makatulong ito paunti-unti para hindi na rin ako masyadong affected. After all, I can't do something about it (for now). Thankful pa rin sa lahat ng nangyari sa kabila ng lahat.

[review-with-metul]

Opal Review – Full OTO Details + Bonuses + Demo

Introduction: Opal Review 2023

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About Vendor | Opal Review What Is The Opal App?

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Read Also AI Audio Avatar Review Opal Review | Does It Worth Buying?

This will work because it’s personally proven and tested by us personally to produce results. Secondly we’ve made it as easy as possible to get results, just set & forget.

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[mrkhan75090]

Opal Review — Full OTO Details + Bonus Information

Opal Review – Product Overview

Vendor: Billy Darr

Product: Opal

Launch Date: December 20, 2023

Launch Time: 11:00 AM EST

Front-End Price: $17

Refund: YES, 30 Days Money-Back Guarantee

Opal Review – Product Creator

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Opal Review – What is Opal?

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Features

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Frequently Asked Questions On Opal

 Why Will This Work For Me?

This will work because it’s personally proven and tested by us personally to produce results. Secondly we’ve made it as easy as possible to get results, just set & forget… 

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Well what you generally see on the market for sale right now is reliant upon beat up old models that frankly speaking are not very effective anymore, Opal is in demand and hot right now…

 Is There A Money Back Guarantee?

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[jcmarchi]

Generative AI from an enterprise architecture strategy perspective

New Post has been published on https://thedigitalinsider.com/generative-ai-from-an-enterprise-architecture-strategy-perspective/

Generative AI from an enterprise architecture strategy perspective

Eyal Lantzman, Global Head of Architecture, AI/ML at JPMorgan, gave this presentation at the London Generative AI Summit in November 2023.

I’ve been at JPMorgan for five years, mostly doing AI, ML, and architecture. My background is in cloud infrastructure, engineering, and platform SaaS. I normally support AI/ML development, tooling processes, and use cases.

Some interesting observations have come about from machine learning and deep learning. Foundation models and large language models are providing different new opportunities and ways for regulated enterprises to rethink how they enable those things.

So, let’s get into it.

How is machine learning done? 

You have a data set and you traditionally have CPUs, although you can use GPUs as well. You run through a process and you end up with a model. You end up with something where you can pass relatively simple inputs like a row in a database or a set of features, and you get relatively simple outputs back. 

We evolved roughly 20 years ago towards deep learning and have been on that journey since. You pass more data, you use GPUs, and there are some different technology changes. But what it allows you to do is pass complex inputs rather than simple ones. 

Essentially, the deep learning models have some feature engineering components built in. Instead of sending the samples and petals and length and width for the Iris model and figuring out how to extract that from an image, you just send an image and it extracts those out automatically. 

Governance and compliance in generative AI models

Foundation models are quite interesting because first of all, you effectively have two layers, where there’s a provider of that foundation model that uses a very large data set, and you can add as many variants as you want there. They’re GPU-based and there’s quite a bit of complexity, time, and money, but the outcome is that you can pass in complex inputs and get complex outputs. 

So that’s one difference. The other is that quite a lot of them are multimodal, which means you can reuse them across different use cases, in addition to being able to take what you get out of the box for some of them and retrain or fine-tune them with a smaller data set. Again, you run additional training cycles and then get the fine-tuned models out. 

Now, the interesting observation is that the first layer on top is where you get the foundation model. You might have heard statements like, “Our data scientist team likes to fine-tune models.” Yes, but that initial layer makes it available already for engineers to use GenAI, and that’s the shift that’s upon us. 

It essentially moves from processes, tools, and things associated with the model development lifecycle to software because the model is an API. 

But how do you govern that? 

Different regulated enterprises have their own processes to govern models versus software. How do you do that with this paradigm? 

That’s where things need to start shifting within the enterprise. That understanding needs to feed into the control assurance functions and control procedures, depending on what your organization calls those things. 

This is in addition to the fact that most vendors today will have some GenAI in them. That essentially introduces another risk. If a regulatory company deals with a third-party vendor and that vendor happens to start using ChatGPT or LLM, if the firm wasn’t aware of that, it might not be part of their compliance profile so they need to uplift their third-party oversight processes. 

They also need to be able to work contractually with those vendors to make sure that if they’re using a large language model or more general AI, they mustn’t use the firm’s data.

AWS and all the hyperscalers have those opt-out options, and this is one of those things that large enterprises check first. However, being able to think through those and introducing them into the standard procurement processes or engineering processes will become more tricky because everyone needs to understand what AI is and how it impacts the overall lifecycle of software in general. 

Balancing fine-tuning and control in AI models

In an enterprise setting, to be able to use an OpenAI type of model, you need to make sure it’s protected. And, if you plan to send data to that model, you need to make sure that data is governed because you can have different regulations about where the data can be processed, and stored, and where it comes from that you might not be aware of. 

Some countries have restrictions about where you can process the data, so if you happen to provision your LLM endpoint in US-1 or US central, you possibly can’t even use it. 

So, being aware of those kinds of circumstances can require some sort of business logic.

Even if you do fine-tuning, you need some instructions to articulate the model to aim towards a certain goal. Or even if you fine-tune the hell out of it, you still need some kind of guardrails to evaluate the sensible outcomes. 

There’s some kind of orchestration around the model itself, but the interesting point here is that this model isn’t the actual deployment, it’s a component. And that’s how thinking about it will help with some of the problems raised in how you deal with vendor-increasing prices. 

What’s a component? It’s exactly like any software component. It’s a dependency you need to track from a performance perspective, cost perspective, API perspective, etc. It’s the same as you do with any dependency. It’s a component of your system. If you don’t like it, figure out how to replace it.

Now I’ll talk a bit about architecture.

Challenges and strategies for cross-cloud integration

What are those design principles? This is after analyzing different vendors, and this is my view of the world. 

Treating them as a SaaS provider and as a SaaS pattern increases the control over how we deal with that because you essentially componentize it. If you have an interface, you can track it as any type of dependency from performance cost, but also from an integration with your system. 

So if you’re running on AWS and you’re calling Azure OpenAPI endpoints, you’ll probably be paying for networking across cloud cost and you’ll have latency to pay for, so you need to take all of those things into account. 

So, having that as an endpoint brings those dimensions front and center into that engineering world where engineering can help the rest of the data science teams.

We touched on content moderation, how it’s required, and how different vendors implement it, but it’s not consistent. They probably deal with content moderation from an ethical perspective, which might be different from an enterprise ethical perspective, which has specific language and nuances that the enterprise tries to protect. 

So how do you do that? 

That’s been another consideration where I think what the vendors are doing is great, but there are multiple layers of defense. There’s defense in depth, and you need ways to deal with some of that risk 

To be able to effectively evaluate your total cost of ownership or the value proposition of a specific model, you need to be able to evaluate those different models. This is where if you’re working in a modern development environment, you might be working on AWS or Azure, but when you’re evaluating the model, you might be triggering a model in GCP. 

Being able to have those cross-cloud considerations that start getting into the network and authentication, authorization, and all those things can become extremely important to design for and articulate in the overall architecture and strategy when dealing with those models. 

Historically, there were different attempts to wrap stuff up. As cloud providers, service providers, and users of those technologies, we don’t like that because you lose the value of the ecosystem and the SDKs that those provide. 

To be able to solve those problems whilst using the native APIs, the native SDK is essential because everything runs extremely fast when it comes to AI and there’s a tonne of innovation, and as soon as you start wrapping stuff then, you’re already out in terms of dealing with that problem and it’s already pointless.

How do we think about security and governance in depth?  

If we start from the center, you have a model provider, and this is where the provider can be an open source one where you go through due diligence to get it into the company and do the scanning or adverse testing. It could be one that you develop, or it could be a third-party vendor such as Anthropic.

They do have some responsibility for encryption and transit, but you need to make sure that that provider is part of your process of getting into the firm. You can articulate that that provider’s dealing with generative AI, that provider will potentially be sent classified data, that provider needs to make sure that they’re not misusing that data for training, etc. 

You also have the orchestrator that you need to develop, where you need to think about how to prevent prompt injection in the same way that other applications deal with SQL injection and cross-site scripting. 

So, how do you prevent that? 

Those are the challenges you need to consider and solve. 

As you go to your endpoints, it’s about how you do content moderation of the overall request and response and then also deal with multi-stage, trying to jailbreak it through multiple attempts. This involves identifying the client, identifying who’s authenticated, articulating cross-sessions or maybe multiple sessions, and then being able to address the latency requirements. 

You don’t want to kill the model’s performance by doing that, so you might have an asynchronous process that goes and analyzes the risk associated with a particular request, and then it kills it for the next time around. 

Being able to understand the impact of the controls on your specific use case in terms of latency, performance, and cost is extremely important, and it’s part of your ROI. But it’s a general problem that requires thinking about how to solve it. 

You’re in the process of getting a model or building a model and creating the orchestrated testing as an endpoint and developer experience lifecycle loops, etc. 

But your model development cycle might have the same kind of complexity when it comes to data because if you’re in an enterprise that got to the level of maturity that they can train with real data, rather than a locked up, synthesized database, you can articulate the business need and you have approval taxes, classified data for model training, and for the appropriate people to see it.

This is where your actual environment has quite a lot of controls associated with dealing with that data. It needs to implement different data-specific compliance. 

So, when you train a model, you need to train this particular region, whether it’s Indonesia or Luxembourg, or somewhere else. 

Being able to kind of think about all those different dimensions is extremely important. 

As you go through whatever the process is to deploy the application to production, again, you have the same data-specific requirements. There might be more because you’re talking about production applications. It’s about impacting the business rather than just processing data, so it might be even worse. 

Then, it goes to the standard engineering, integration, testing, load testing, and chaos testing, because it’s your dependency. It’s another dependency of the application that you need to deal with. 

And if it doesn’t scale well because there’s not enough computing in your central for open AI, then this is one of your decision points when you need to think about how this would work in the real world. How would that work when I need that capacity? Being able to have that process go through all of those layers as fast as possible is extremely important. 

Threats are an ongoing area of analysis. There’s a recent example from a couple of weeks ago from apps about LLM-specific threats. You’ll see similar threats to any kind of application such as excessive agency or or denial of service. You also have ML-related risks like data poisoning and prompt object injection which are more specific to large language models.

This is one way you can communicate with your controller assurance or cyber group about those different risks, how you mitigate them, and compartmentalize all the different pieces. Whether this is a third party or something you developed, being able to articulate the associated risk will allow you to deal with that more maturely. 

Navigating identity and access management

Going towards development, instead of talking about risk, I’m going to talk about how I compartmentalize, how to create the required components, how to think about all those things, and how to design those systems. It’s essentially a recipe book. 

Now, the starting assumption is that as someone who’s coming from a regulated environment, you need some kind of well-defined workspace that provides security. 

The starting point for your training is to figure out your identity and access management. Who’s approved to access it? What environment? What data? Where’s the region? 

Once you’ve got in, what are your cloud-native environment and credentials?  What do they have access to? Is it access to all the resources? Specific resources within the region or across regions? It’s about being able to articulate all of those things.

When you’re doing your interactive environment, you’ll be interacting with the repository, but you also may end up using a foundation model or RAG resource to pull into your context or be able to train jobs based on whatever the model is. 

If all of them are on the same cloud provider, it’s simple. You have one or more SDLC pipelines and you go and deploy that. You can go through an SDLC process to certify and do your risk assessment, etc. But what happens if you have all of those spread across different clouds?

Essentially, you need additional pieces to ensure that you’re not connecting from a PCI environment to a non-PCI environment. 

Having an identity broker that can have additional conditions about access that can enforce those controls is extremely important. This is because given the complexity in the regulatory space, there are more and more controls and it becomes more and more complex, so pushing a lot of those controls into systems that can reason about them and enforce that is extremely important. 

This is where you start thinking about LLM and GenAI from a use case perspective to just an enterprise architecture pattern. You’re essentially saying, “How do we deal with that once and for all?” 

Well, we identify this component that deals with identity-related problems, we articulate the different data access patterns, we identify different environments, we catalog them, and we tag them. And based on the control requirements, this is how you start dealing with those problems. 

And then from that perspective, you end up with fully automated controls that you can employ, whether it’s AWS Jupyter or your VS code running in Azure to talk to Bedrock or Azure OpenAI endpoint. They’re very much the same from an architecture perspective. 

Innovative approaches to content moderation

Now, I mentioned a bit about the content moderation piece, and this is where I suggested that the vendors might have things, but: 

They’re not really consistent. 

They don’t necessarily understand the enterprise language. 

What is PI within a specific enterprise? Maybe it’s some specific kind of user ID that identifies the user, but it’s a letter and a number that LLM might never know about. But you should be careful about exposing it to others, etc. 

Being able to have that level of control is important because it’s always about control when it comes to risk.

When it comes to supporting more than one provider, this is essentially where we need to standardize a lot of those things and essentially be able to say, “This provider, based on our assessment of that provider can deal with data up to x, y, and z, and in regions one to five because they don’t support deployment in Indonesia or Luxembourg.” 

Being able to articulate that part of your onboarding process of that provider is extremely important because you don’t need to think about it for every use case, it’s just part of your metamodel or the information model associated with your assets within the enterprise. 

That content moderation layer can be another type of AI. It can be as simple as a kill switch that’s based on regular expression, but the opportunity is there to make something learn and adjust over time. But from a pure cyber perspective, it’s a kill switch that you need to think about, how you kill something in a point solution based on the specific type of prompt. 

For those familiar with AWS, there’s an AWS Gateway Load Bouncer. It’s extremely useful when we’re coming to those patterns because it allows you to have the controls as a sidecar rather than part of your application, so the data scientist or the application team can focus on your orchestrator. 

You can have another team that can specialize in security that creates that other container effectively and deploys and manages that as a separate lifecycle. This is also good from a biased perspective because you could have one team that’s focused on making or breaking the model, versus the application team that tries to create or extract the value out of it.

From a production perspective, this is very similar because in the previous step, you created a whole bunch of code, and the whole purpose of that code was becoming that container, one or more depending on how you think about that. 

That’s where I suggest that content moderation is yet another type of kind of container that sits outside of the application and allows you to have that separate control over the type of content moderation. Maybe it’s something that forces a request-response, maybe it’s more asynchronous and kicks it off based on the session. 

You can have multiple profiles of those content moderation systems and apply them based on the specific risk and associated model. 

Identity broker is the same pattern. This is extremely important because if you’re developing and testing in such environments, you want your code to be very similar to how it progresses. 

In the way you got your credentials, you probably want some configuration in which you can point to a similar setup in your production environment to inject those tokens into your workload. 

This is where you probably don’t have your fine-tuning in production, but you still have data access that you need to support. 

So, having different types of identities that are associated with your flow and being able to interact, whether it’s the same cloud or multi-cloud, depending on your business use case, ROI, latency, etc., will be extremely important. 

But this allows you to have that framework of thinking, Is this box a different identity boundary? Yes or no? If it’s a no, then it’s simple. It’s an IM policy in AWS as an example, versus a different cloud, how do you federate access to it? How do you rotate credential secrets?

Conclusion

To summarise, you have two types of flows. In standard ML, you have the MDLC flow where you go and train a model and containerize it. 

In GenAI, you have the MDLC only when you fine-tune. If you didn’t fine-tune, you run through pure SDLC flow. It’s a container that you just containerized that you test and do all those different steps. 

You don’t have the actual data scientists necessarily involved in that process. That’s the opportunity but also the change that you need to introduce to the enterprise thinking and the cyber maturity associated with that. 

Think through how engineers, who traditionally don’t really have access to production data, will be able to test those things in real life. Create all sorts of interesting discussions about the environments where you can do secure development with data versus standard developer environments with mock data or synthesized data.

[tomreview]

Prompt Engine Runs inside the ChatGPT Interface

cynty_1980_guarantee u5mdk_1016_icona1 The only ChatGPT Extension you will ever need czmje_999_icona2 Get 100X better results from ChatGPT a3ntm_1009_icona3 20+ Profitable Prompt Categories q4ndy_932_icona4 10000+ Income Generating Prompts y5otq_94 People wondered, "Can it get any easier?" when ChatGPT was released. Working with ChatGPT has become much simpler thanks to Karthik and his team, and the results are 100 times better. The app's ability to function within ChatGPT's user interface and provide a variety of revenue-generating Prompts is one of my favorite features. With ChatGPT and Prompt Engine Pro, you can easily begin your journey, even if you are a novice. Not to mention how simple it is to record videos using the built-in Teleprompter. Ben Murray u2mdi_962_e2mtq962abhi Abhi Dwivedi If you're looking for ways to make money, ChatGPT could be a lifesaver. But where do you begin? How can you get the most out of ChatGPT? With Prompt Engine Pro, Karthik has solved that problem for you. He has covered everything, from affiliate marketing to becoming an online coach, and the ChatGPT interface will load ready-to-use, customizable prompts for you. The best part is that the app lets you use a Teleprompter to record videos!

Hey there! My name is Karthik Ramani, and I'm on a mission to help you generate a steady stream of income by channeling the power of AI. y5njy_1980_line1 Unless you've been living under a rock, you already know that ChatGPT is the latest trend on the internet.

Within five days of its launch, it had 1 million users, and it now has over 100 million. It took entertainment platform Netflix 3.5 years to reach the one million mark, while social media giant Facebook took almost 10 months.

It is evident that ChatGPT has gained more support more quickly.

The technology is simply amazing; it is free; it is fairly adaptable; and it is accessible to almost anyone. q4njk_1467_karthik There are always new technologies, and not everyone who uses them succeeds, right?

Stay with me if you want to profit from this new technology. Break free from the 9-to-5 grind and ignite your path to massive success in 2023 and beyond. Cash in on the $250 billion worth Creator Economy! My mission is to help you use ChatGPT to its fullest potential and open up income opportunities for you.

We have woken up to layoffs happening in big companies to small organizations and it is happening every single day. Thousands of people are dreading a layoff email from their company. k0nji_1008_graphic1 i5otq_1911_graphic2 y3mtk_1980_proof1 Do you know what is growing consistently in spite of the recession scenario that we are facing right now? As much as I want to say that 2023 has been great, unfortunately it has

What is a Creator Economy? It is expanding and is currently worth a staggering $250 billion. By 2027, the Creator Economy is expected to double in size.

cynjg_1580_line2 In the age of social media, people use their skills to build an audience and expand their businesses or assist other brands and businesses.

In this economy, a lot of people with different skills create content in a variety of formats and take advantage of the opportunity to make a decent income online!

gzmzu_300_arrow2 Tori Dunlap, a money and career expert, made $4 million in 2022 as a Creator gzmzu_300_arrow2 But it's not true that you need to have a big following to earn on these platforms. gzmzu_300_arrow2 Jay Clouse made $338 thousand in 2022 with just 3000 subscribers and he is educating fellow content creators through his videos, podcast, and Newsletter gzmzu_300

u2njq_300_arrow3 and g2ode_1895_graphic7 were all modest beginnings that developed into their current status.

You can use ChatGPT like everyone else and get regular results. Option #1 Use Customizable Prompts like this one along with refinement options. And get results like this that are more relevant to your product or service. yynje_1518_graphic12 Do you want to go for the one that will actually get you results?

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Prompt Engine Pro is an agency app that will help you profit using ChatGPT and get 100x better results. m4mji_1447_graphic13 Is this just another Prompt tool where you get a bunch of prompts??? When Chat GPT exploded on the Internet, we knew that this is not a fad and that this AI is here to stay. We used it every day and quickly realized the gaps in the AI and started working on how one can overcome them.

m4mdg_1654_graphic14 No, although we do offer "Done-For-You" prompts, Prompt Engine Pro is more than just prompts. It was developed with the sole purpose of generating pure profits for you!

Let us explain how Prompt Engine Pro will give anyone an unfair advantage. With Prompt Engine Pro by your side, we will demonstrate multiple ways to profit using ChatGPT and Prompt Engine Pro with the click of a few buttons.

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i3mjc_1080_a0mza1080sb Saurabh Bhatnagar At first, I was hesitant when Karthik told me that he was working on AI and ChatGPT projects because I was aware that a lot of apps were coming out in this area. I was wondering what might have changed. But it completely blew my mind when Karthik showed me what he had built. I believe that this app will have a significant impact on my mentees, as I have assisted thousands of people in starting their online journeys. With Pre Done Prompts and the power of AI, it will assist them in automating a lot of work and completing tasks. It won't matter if you don't have a particular set of skills anymore. With Karthik's DFY Prompts and AI, you can get professional-level results. It will accelerate your success. Ideal in any event, for Beginners who are attempting to get everything rolling.

With ChatGPT and Prompt Engine Pro, how does one actually make money?

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Based on our research, we created categories, subcategories, prompts, and all possible refinement options for you to get the best results. At the outset, ChatGPT gives you content, and we found ways for you to use it to make money. We have created thousands of tried-and-true DFY prompts in a variety of fields, including affiliate marketing, copywriting, online coaching, Facebook marketing, YouTube marketing, e-commerce, social media, SEO, customer support, online funnels, and

y2nji_1980_graphic17 Want to sell other people's products and become an affiliate marketer?

With Done-For-You Prompts designed to help you achieve the best results as an Affiliate Marketer, you can write product reviews, email sequences, blogs, Facebook posts, ad copy, and much more by selecting the appropriate category.

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Ideas for YouTube Video Scripts for Thumbnails Interested in becoming a Digital Coach?

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The Course Outline, Video Script, and Lesson Are You Interested in Marketing?

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Landing Page for Sales Email Opt-Ins Do you want to work for yourself?

Utilizing Done-For-You Prompts, select any Upwork task and immediately complete it. With Done-For-You Prompts, you can complete tasks like video scripting, content writing, email copy, funnel building, ad copywriting, and many more and generate content with just a few clicks.

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With Prompt Engine Pro by your side, you can accomplish anything, from gaining followers on Instagram and Twitter to entertaining viewers on TikTok. You can do everything with ChatGPT powered by Prompt Engine Pro, including creating full-length Video Scripts and allowing you to record them. Tik Tok Video Ideas Tik Tok Video Scripts Want to become a blogger?

With ready-to-use prompts, you can quickly create blogs, articles, and content in any niche and reap the benefits of blogging.

Articles Keyword List for Articles Interested in Authorship?

You can use PromptEngine pro to help you write ebooks, fiction, or any other kind of book, and then sell those books to make money.

Write a book readers love There are many more ways to make money with ChatGPT, and we've covered all of them with a lot of very useful prompts in different categories.

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mxoty_1980_line5 q5odq_1465_cross Other Extensions and Prompt Packs Only work with ChatGPT and not within Copy, Paste, and Customize Prompts Manually Most of the time, you get a zip file or excel sheet of prompts that you have to manually search through to find the prompt that works best. Chat History cannot be stored because there is no backend. It is also not possible to quickly create notes from the chat response.

Only one language for prompts, no ability to create client accounts, no agency rights, and no way to record videos. It helps you with your work but does not actually do your work.

Covers multiple categories, works as an overlay on ChatGPT, and you don't have to copy and paste prompts. Require monthly or annual fees. Easily create Notes from the Chat Responses Organize work for multiple clients under different workspaces Multiple Refinement options to get better results from ChatGPT Prompts in 5 popular Language Create client Accounts with included Agency Rights Lets you record videos with AI-generated content using in-built Teleprompter Focuses on making you more profits and covers all income-generating categories and assists you with your actual work. Comes in a customizable Fill-in-the-blanks format Easy to locate Promp

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gxnte_1052_vivek1 Vivek Gour If you're looking for ways to make money, ChatGPT could be a lifesaver. But where do you begin? How can you get the most out of ChatGPT? With Prompt Engine Pro, Karthik has solved that problem for you. He has covered everything, from affiliate marketing to becoming an online coach, and the ChatGPT interface will load ready-to-use, customizable prompts for you. The best part is that the app lets you use a Teleprompter to record videos!

The ONLY Chat GPT Extension One Needs Save all ChatGPT responses and see whenever you want Easily create Notes with Chat Response Organize all your work in workspaces and keep all your client's work separately Done-For-You Prompts in various categories Prompts in 5 popular Languages Multiple refinement options to make Chat GPT’s response better 100s of ways to start making profits with ChatGPT Record videos with in-built teleprompter perfect for content creation Increases productivity Removes

k2mzy_961_iconf: Digital marketers; m3mzi_905_iconf: coaches; cwnjy_822_iconf: writers; cyotm_939_iconf: social media managers; kwmzy_879_iconf: freelancers; e0njy_917_iconf: content creators; y3odi_956_iconf: copywriters; k Even if you do not fall into any of the categories listed above, you are still able to begin your online journey with Prompt Engine Pro because the app was designed with beginners in mind.

cynty_1980_guarantee Get instant access to Prompt Engine Pro for just $97 per month with no monthly fees and a $32 one-time payment. Here's a look at all the cool features in this must-have app: 10000+ Done-For-You Prompts Hand-crafted, tried, and proven to work customizable prompts

We cover everything from e-commerce to SEO, as well as email marketing and affiliate marketing, in our iymzk_800_one prompts. Get your Done-For-You Prompts completed in a matter of minutes by selecting any category that generates income.

i3mdy_800_0220 Subcategories to get content that is laser-focused 100 subcategories to help you get prompts for your work that are laser-focused

e3njq_800_03Subcategories Fill in the Blanks Format for Prompts To create prompts that will produce exceptional results, select a prompt that best suits your requirements and fill in the blanks with information about your product or service.

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Pick Prompts In 5 Famous Dialects

Try not to need to pick your prompts in English? We've got your back. Prompts are available in Italian, German, Spanish, and French. You can select a language, and the Prompt Engine Pro section of the page will load in that language. You can easily select the prompts from this location. czodm_1280_image20230619T160513286Z Refinement Options The ability to filter the results by length (for example, 100, 200, or 300 words) and type (for example, letter, email, story, etc.). yzmju_800_05 Workspace to Store Your Conversations Organize all of your work for different clients in workspaces. ezmtu_800_06workspace Save History You can add as much text as you want. Give the Workbook a name, edit the text, move it around, and save it in your workspace by clicking on it.

q3mzk_1027_history Quick Access to Popular and Trending Categories Quickly access prompts in popular and trending categories without having to look in the main directory of prompts.

[yourfinanceacc]

Make Money Fast and Easy with ChatGPT - Earn $20 Every 5 Minutes for Free! | Your Finance

Are you tired of the daily grind and looking for ways to make some extra money? Look no further than ChatGPT, the free money-earning AI bot that lets you earn $20 every 5 minutes! With ChatGPT, you can earn money on your own schedule, from the comfort of your own home. Our revolutionary AI bot is easy to use and requires no special skills or experience. Simply chat with ChatGPT, and start earning money right away! Whether you're looking to earn extra cash on the side, or looking for a full-time gig, ChatGPT is the perfect solution. And the best part? ChatGPT is completely free to use. There are no hidden fees, no up-front costs, and no catch. Just sign up, start chatting, and watch the money roll in. So why wait? Sign up for ChatGPT today and start earning money in no time! 🔔Subscribe to the channel for tips & strategies for managing money & achieving financial independence: https://www.youtube.com/@your_finance_account/ ✅ Stay Connected with Us. 👉Twitter: https://mobile.twitter.com/your_finance_?t=rr4nnhz-e3j1KAtHHwWc-w&s=09 ✅ For Business Inquiries: channelyourfinance@gmail.com ============================= ✅ Recommended Playlists 👉 Motivational Videos https://www.youtube.com/watch?v=RcFJAHHVBMw&list=PLYxqx3-R5Rlg6uJu6hzoH1RmzhFl1lRJB 👉Videos about finance https://www.youtube.com/watch?v=NfDTd6CpFyk&list=PLYxqx3-R5Rlh2BGPUCJoij3xX1MiSxRNJ ✅ Other Videos You Might Be Interested In Watching: 👉Expert tips for saving a massive down payment and Achieving Your homeownership dreams https://www.youtube.com/watch?v=D_Xjr5q6M_0 👉How to become a Billionaire like Jeff Bezos in 2023 https://www.youtube.com/watch?v=0495kUXBGkE 👉BEST WARREN BUFFET SPEECH THAT WILL CHANGE YOUR FUTURE IN 2023 https://www.youtube.com/watch?v=aSsFFed9tdo 👉Unlock the Secrets to Billionaire Success: 6 Expert Tips to Achieve Billionaire Status! https://www.youtube.com/watch?v=c5iRreERdHE 👉The ultimate top 10 money-earning apps without investment in 2023 https://www.youtube.com/watch?v=mi0qULllG8A ============================= ✅ About Your Finance. Welcome to Your Finance channel, where we empower you to achieve financial freedom. Our mission is to bridge the gap in financial education and equip you with the knowledge and tools needed to take control of your finances. From saving and investing strategies to budgeting and debt management, our team of experts will guide you every step of the way. Join us on this journey to financial stability and independence. Subscribe now and hit the notification bell to stay updated on all things finance. Your financial success starts here! For Collaboration and Business inquiries, please use the contact information below: 📩 Email: channelyourfinance@gmail.com 🔔 Subscribe to the channel for tips & strategies for managing money & achieving financial independence: https://www.youtube.com/@your_finance_account/ ================================= #budgetingtips #personalfinance #moneymanagement #financialplanning #savingsplan #financialfreedom #chatgpt #howto #makemoneyonline Disclaimer: We do not accept any liability for any loss or damage incurred from you acting or not acting as a result of watching any of my publications. You acknowledge that you use the information I provide at your own risk. Do your own research. Copyright Notice: This video and my YouTube channel contain dialog, music, and images that are the property of Your Finance. You are authorized to share the video link and channel and embed this video in your website or others as long as a link back to my Youtube Channel is provided. © Your Finance https://ifttt.com/images/no_image_card.png https://www.youtube.com/watch?v=XTOs5oCtnGk