Trending February 2024 # Chatgpt + Enterprise Data: The Next Generation Of Ai # Suggested March 2024 # Top 11 Popular

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ChatGPT is an OpenAI large language model that may be used for generating text, translate languages, compose various types of creative material, and provide helpful answers to your questions. ChatGPT may be used to build a range of AI-powered customer service apps when combined with enterprise data.

ChatGPT + Enterprise data with Azure OpenAI and Cognitive Search

This sample shows how to use the Retrieval Augmented Generation pattern to create ChatGPT-like experiences over your own data. It makes use of Azure OpenAI Service to connect to the ChatGPT model (gpt-35-turbo) and Azure Cognitive Search to index and retrieve data.

The repo includes example data, so you may try it from beginning to end. We utilize a fictitious company named Contoso Electronics in our sample application, and the experience allows its workers to ask questions regarding benefits, internal policies, and job descriptions and positions.


Interactions for chat and Q&A

Investigates several possibilities for assisting users in determining the credibility of replies through citations, source material monitoring, and so on.

Shows methodologies for data preparation, quick creation, and orchestration of model (ChatGPT) and retriever (Cognitive Search) interaction.

To adjust the functionality and experiment with options, use the settings directly in the UX.

Azure Resource Costs and Configuration Prerequisites for Local Deployment

To run the project locally, you will need the following prerequisites:

Azure Developer CLI

Python 3+

Important: Python and the pip package manager must be in the PATH environment variable in Windows for the setup scripts to work.

Important: Ensure you can run python --version from the console. On Ubuntu, you might need to run sudo apt install python-is-python3 to link python to python3.



PowerShell 7+ (pwsh) – For Windows users only.

Important: Ensure you can run pwsh.exe from a PowerShell command. If this fails, you likely need to upgrade PowerShell.

Note: Your Azure account must have Microsoft.Authorization/roleAssignments/write permissions, such as User Access Administrator or Owner.

Installation and Project Initialization

Create a new folder and switch to it in the terminal.

Run the command azd auth login to authenticate with your Azure account.

Run the command azd init -t azure-search-openai-demo to initialize the project using the provided template.

For the target location, the regions currently supporting the models used in this sample are East US or South-Central US. You can check for an up-to-date list of regions and models here.

Starting from scratch:

If you don’t have any pre-existing Azure services and want to start from a fresh deployment, execute the following command:

Run azd up – This will provision Azure resources and deploy the sample application to those resources, including building the search index based on the files found in the ./data folder.

Note: It may take a minute for the application to be fully deployed. If you see a “Python Developer” welcome screen, wait a minute and refresh the page.

Using Existing Resources:

If you want to use existing resources instead of creating new ones, follow these steps:

To change the name of an existing OpenAI service, use the command azd env set AZURE_OPENAI_SERVICE {Name of existing OpenAI service}.

To set the name of the existing resource group where the OpenAI service is provisioned, use the command azd env set AZURE_OPENAI_RESOURCE_GROUP {Name of existing resource group}

If your ChatGPT deployment is not the default ‘chat,’ use the command azd env set AZURE_OPENAI_CHATGPT_DEPLOYMENT {Name of existing ChatGPT deployment}.

If your GPT deployment is not the default ‘davinci,’ use the command azd env set AZURE_OPENAI_GPT_DEPLOYMENT {Name of existing GPT deployment}

Run the command azd up to deploy or re-deploy the repository’s local clone utilizing the existing resources.

Note: If you want to use existing Search and Storage Accounts, refer to the ./infra/main.parameters.json file for a list of environment variables to pass to azd env set in order to configure those existing resources.

Running Locally:

To run the project locally, follow these steps:

Run the command azd login to authenticate with your Azure account.

Change the directory to the app folder.

Run ./start.ps1 or ./ or use the “VS Code Task: Start App” command to start the project locally.

Sharing Environments:

If you want to share a completely deployed and existing environment with someone else, follow these steps:

They must install the Azure CLI on their computer.

To start the project on their system, use azd init -t azure-search-openai-demo

Use the command azd env refresh -e {environment name} to refresh the environment. To run this command, they will need the azd environment name, subscription Id, and location. These values are contained in the./azure/{env name}/.env file. This script will populate the.env file in their azd environment with the settings required to execute the app locally.

Execute pwsh ./scripts/roles.ps1. This will provide the user all of the required roles, allowing them to operate the app locally. You may need to execute this script for them if they do not have the appropriate rights to establish roles in the subscription. Set the AZURE_PRINCIPAL_ID environment variable in the azd.env file or in the current shell to their Azure ID, which they may acquire by running az account show.

Getting Started with the Application:

To get started with the application:

In Azure:

Navigate to the Azure WebApp that azd has deployed. You may discover the URL written out after azd finishes (as “Endpoint”) or on the Azure portal.

Running locally:

Navigate to in your web browser.

Once you’re in the web app:

Experiment with different themes in the conversation or Q&A setting. Experiment with follow-up questions, clarification requests, and requests to simplify or expound on replies in chat.

Investigate the citations and sources for the generated replies.

Also Read: How to Upload a Document to ChatGPT

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Novel Ai Image Generation Guide

See More : How To Use NovelAI Image Generation Free

In today’s digital age, visual content plays a crucial role in capturing attention and conveying messages effectively. Whether you are an artist, designer, marketer, or content creator, having the ability to generate compelling images is a valuable skill. This is where NovelAI steps in, offering a user-friendly platform that harnesses the power of artificial intelligence to generate stunning visuals that match your creative vision.

To embark on your image generation journey with NovelAI, the first step is to subscribe to their platform. By becoming a NovelAI member, you gain access to their extensive suite of tools and features, including the highly acclaimed image generation feature. Subscribe today and unlock the full potential of your creative prowess.

Once you have subscribed to NovelAI, it’s time to dive into the world of image generation. Start by figuring out your prompt—a concise description of the image you envision. Whether it’s a majestic landscape, a mythical creature, or a futuristic cityscape, clearly define your prompt to guide the AI in generating the desired visuals.

NovelAI offers the flexibility to pick your favorite prompts and experiment with various editing options. Tweak, refine, and enhance your prompts to achieve the perfect balance between imagination and reality. Let your creativity run wild as you explore the possibilities that NovelAI has to offer.

To fine-tune your image generation process, NovelAI provides you with the option to adjust your text prompt and generation settings. The Edit Image canvas allows you to make precise modifications, ensuring that the generated images align with your creative vision.

Experiment with different parameters such as strength, noise, and resolution aspects to refine your results further. Refocus your text prompt to emphasize specific visual characteristics or let the AI interpret your words and create stunning compositions that surpass your expectations.

In the realm of image generation, NovelAI empowers users to define the visual characteristics of their creations in two distinct ways. You can either use tags to specify the desired attributes of your character or composition, or you can let the AI interpret your words and generate visuals based on its understanding.

By using tags such as {detailed}, {ornate}, {realistic}, or {photorealistic}, you can add intricate details to objects or clothing and steer the image away from a flat 2D anime style. These tags provide you with granular control over the final output, allowing you to bring your creative vision to life.

NovelAI’s cutting-edge technology is driven by their custom NovelAI Diffusion Models, built on the foundation of Stable Diffusion. This unique approach ensures the generation of high-quality images with remarkable realism and artistic appeal.

Also Read : How To Create NSFW AI Art?

After generating the initial set of images, NovelAI offers a range of powerful image editing and refinement tools to further enhance and customize your visuals. These tools allow you to fine-tune various aspects of the image, such as color, lighting, composition, and more.

With NovelAI’s intuitive interface, you can easily navigate through the editing tools and make adjustments in real-time. Experiment with different filters, effects, and adjustments to add your personal touch and make the images truly unique.

Through this collaborative process, NovelAI becomes a creative partner that evolves alongside your artistic vision, continually improving its ability to generate images that align with your unique style and preferences.

Once you are satisfied with the generated and refined images, it’s time to save and export your masterpieces. NovelAI allows you to download the images in high-resolution formats, ensuring that you can showcase your artwork in all its glory.

Whether you plan to use the images for personal projects, commercial endeavors, or sharing on social media, NovelAI provides the flexibility to export your creations in various file formats, including JPEG, PNG, and TIFF.

Q: Can I use the images generated by NovelAI for commercial purposes?

A: Yes, you can use the images generated by NovelAI for both personal and commercial purposes. However, it’s always a good practice to review and comply with NovelAI’s terms of service to ensure you are utilizing the images within the allowed guidelines.

Q: How long does it take to generate images with NovelAI?

A: The generation time for images with NovelAI may vary depending on factors such as complexity, resolution, and the number of iterations. Simple images can be generated within seconds, while more complex and high-resolution images may take a few minutes. The platform provides estimated generation times for each image, allowing you to plan your creative process accordingly.

Q: Can I collaborate with other artists or creators on NovelAI?

A: Currently, NovelAI focuses on providing individual creative experiences. While you cannot directly collaborate with other users within the platform, you can certainly share your generated images with fellow artists and collaborate outside of NovelAI using the exported files.

Q: Can I adjust the style or artistic elements of the generated images?

A: Yes, NovelAI offers a range of editing and refinement tools that allow you to adjust the style and artistic elements of the generated images. You can experiment with various filters, effects, and adjustments to achieve your desired look and make the images truly unique.

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Why Bant Fails For Modern Enterprise Technology Demand Generation

Why BANT Fails for Modern Enterprise Technology Demand Generation Michael Box

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BANT—popularized by IBM—has been in use for decades. It was established when budget, authority, need and timing were easier to determine—a time before buyers had the luxury of tools like Google and online research and relied on your call to get to know your business.

3 primary reasons BANT no longer serves the needs of enterprise technology marketers #1 – The single enterprise IT decision-maker is a unicorn

BANT seeks to establish whether a lead—a single individual— has authority. Enterprise IT buying is a team sport and authority and influence are distributed across several roles in a buying committee that consists of 7 or more buyers on average.

#2 – BANT is blind to buying behavior

BANT relies on static questions and point-in-time interactions to establish buying intent. However, by the time you get the “buyer” on the phone, it may already be too late. That is because buying teams will demonstrate purchase intent behavior in multiple environments throughout the buying cycle before they ever end up with you. Topics and content your prospects are accessing in third-party environments are far more indicative of interest in solutions like yours. More precisely, accessing this type of data will allow you to understand what they are interested in and when they are interested—without having to ask.

#3 – It’s four “yeses” or broke

BANT essentially amounts to four yeses in a call. Those four yeses could mean they are ready to buy or it could mean they just wanted to get you off the phone. In contrast, if they say “no” to any of the requirements, it doesn’t mean they won’t be ready to talk in the near future or that another member of the buying team may be a more appropriate contact.

To illustrate where this breaks down, Budget and Timing won’t be there unless there’s a Need. Need cannot always be established right away—especially if your technology is a new concept or paradigm, in which case your sales teams must educate prospective buyers. Authority no longer resides in a single individual. Timing is not set in stone.

Attempting to “qualify” buyers through this flawed process essentially amounts to cutting off your best salespeople at the knees. By depending on third-party BANT qualification, sales are not able to get in early and shape the deals as they’re happening.

For a more detailed analysis of the weakness of BANT—and an alternative—download the new white paper Is BANT Killing Your Business?

Learn more: 4 additional resources on the shortcomings of BANT

1) BANT Isn’t Enough Anymore: A New Framework for Qualifying Prospects—Pete Caputa—HubSpot

This article examines why this strategy no longer works like it used to.

2) BANT and Beyond: Advanced Sales Qualification for SDRs & AEs—Jacco Van der Kooij—Sales Hacker

Jacco addresses the challenges of BANT for SaaS sales and proposes a modernized version.

3) Why It’s Time For B.A.N.T. To Go—Jim Keenan—Forbes

According to Jim Keenan, the biggest problem with BANT is that it’s extremely seller-focused, not prospect-focused.

4) Why BANT No Longer Applies for B2B Lead Qualification—Carlos Hidalgo—ANNUITAS

According to one study, only 29% of B2B buyers said they “always” supply accurate information on custom questions—in other words, buyers lie. Another failure point for BANT.

BANT, demand generation, lead generation, lead qualification

Klarna Introduces Chatgpt Plugin For Ai

Klarna is a retail bank that works globally and helps enhance users’ shopping ventures by providing direct payments, installment plans, pay-later options, and more. Klarna is one of the first brands that introduces the ChatGPT plugin for AI-assisted shopping. 

In this article, we are going to talk about the Klarna ChatGPT collaboration, How will the Klarna ChatGPT plugin work, its release date, and more. 

What is the Klarna ChatGPT collaboration?

Klarna’s collaboration with ChatGPT will provide a new intuitive shopping experience to its users by curating highly personalized product suggestions at their comfort. The integration of the AI chat service ChatGPT with Klarna will provide users a shopping link, which users can view along with a comparison tool right there. This tool will almost work like a shopping assistant to users and will help users pick the best product for them. 

Klarna CEO and Co-founder, Sebastian Siemiatkowski said, “I’m excited about our plugin with AI chatbot ChatGPT, as it passes my criteria of ‘North star’ which I call my ‘mom test.’ i.e would my mom understand the benefits of this plugin? In a written statement, Sebastian Siemiatkowski also stated, “it’s easy to use and helps solve several problems – it can drive a tremendous value for each and every one. 

Klarna is a great platform to leverage useful technology and information which can help people explore new products. Klarna can help solve consumer issues at all stages of the shopping journey, and the company aims to keep innovating technology and introducing new services to help its consumers. 

The plugin is currently available on OpenAI’s plugin page. For now, there isn’t too much information on the ChatGPT Klarna Plugin release. Although it was reported the plugin will first be made available in the United States and Canad for ChatGPT Plus subscribers and further regions and countries will be added following the stage of safety testing, improvement, and development. 

It was also reported the new feature would eventually be made available for regular ChatGPT users as well and will be connected to the AI chatbot to the internet. 

How will the Klarna ChatGPT plugin work?

Using the Klarna ChatGPT plugin is extremely easy, Users need to install the Klarna plugin through the ChatGPT plugin store. Once you have installed the plugin, you can begin asking questions. 

For example, you have entered a prompt saying “I have $40, what shoes will I be able to afford?” Once you have entered this prompt the plugin will immediately develop a list of items based on your request. Users can further ask additional questions and look for more product suggestions from the Klarna ChatGPT plugin. 

ChatGPT limitations with Klarna

ChatGPT is an AI chat service and at times, it has generated biased/incorrect responses to users’ queries. Which is its major limitation with Klarna. Though ChatGPT can provide incorrect responses unsuitable to your generated requests.

Users can provide feedback and issue a statement regarding the issue, which will help ChatGPT learn and improve their service over time. 


Klarna’s collaboration with ChatGPT will benefit users and help make their shopping easier. Through this plugin, users can receive tons of suggestions for their product based on their budget and requirement.

Users can even compare the products using the comparison tool, which can be a useful feature for users. 

Above we mentioned all the details about Klarna’s collaboration with ChatGPT, its release date, limitations, and more, which will help you gain all the details about the upcoming plugin.  

Mosyle Leads The Rise Of A New Generation Of Apple Endpoint Software

Apple’s growth in the enterprise over the last two decades has been an impressive turnaround when you consider how entrenched Microsoft was in desktop computing for the early part of the 2000s. Did enterprise IT managers love Windows XP, Windows 7, etc.? 

They loved the seamless management a complete solution of Windows Server, Microsoft Exchange, Microsoft Office, and Windows brought to their work-life.

Now companies leveraging Apple devices are gaining access to a next generation of products that bring this concept to a new level, making the management and security of Apple devices a fully unified and automated experience that can’t be matched when using any other devices. 

At the forefront of this movement is Mosyle. Over the past five years, the company grew from a new Apple MDM provider to a leader in the market. Mosyle is responsible for several innovations that have become table stakes for other vendors in the Apple MDM space.

Now, Mosyle is innovating again and introducing the concept of Apple Unified Platform. 

The idea for Mosyle’s Apple Unified Platform is clear. It makes perfect sense when you hear it for the first time: integrating five critical security and management applications into a single Apple-only platform.  

Still, it completely changes how B2B companies providing endpoint solutions position themselves.

Until now, companies usually position themselves on one of the traditional “Unified” categories, such as “Unified Endpoint Management” or “Unified Endpoint Security.” Those categories are well known for their quadrants and industry recognition.

The angle for these traditional B2B market segments is the specialization of an application category (e.g., mobile device management) and the generalization of the platform (macOS, iOS, Android, Windows, Linux and others).

So, a vendor in the traditional Unified Endpoint Management market would provide MDM functionality for all platforms. A customer would then need several unified solutions to cover their devices’ needs, as security, identity, patch management and others.

The problem with that? Lack of specialization and increased complexity.

The growing differences between operating systems, proactively created by companies like Apple, Microsoft and Google to differentiate themselves from competitors, are making it virtually impossible for multi-platform providers to offer a good experience, coverage and performance on each platform. Instead, they are forced to focus on the common points between operating systems while the platform providers simultaneously eliminate these common elements.

Mosyle’s Apple Unified Platform is exactly the opposite. 

Mosyle’s specialization happens on the operating system (in this case, Apple), and the offer is extended to different solution needs, including MDM, endpoint security, identity management, content filtering and more. This new approach allows companies to use a single solution for all their Apple devices’ needs while reducing the number of providers they need to cover their entire fleet.

A company using only Apple devices can solve all its needs with a single and integrated platform. And in the worst case, even if they are agnostic and let employees use any platform, they would end up with no more than three providers – it’s a game-changer.

Mosyle currently offers this concept through a product called Mosyle Fuse that delivers the following capabilities:

Enterprise-grade mobile device management;

Identity Management;

Automated patch management;

Endpoint security, including device hardening and compliance, next-generation antivirus and privilege management; and

Online privacy and security through encrypted DNS-based content filtering. 

In addition to allowing customers to use a single solution for all their Apple device needs (literally), this concept also brings several other benefits:

1. Complete feature set due to OS specialization. A company focusing on a single platform such as Mosyle for Apple devices can dramatically increase specialization on one operating system provider, reaching a level of quality and efficiency that’s unmatchable for multi-platforms providers. For specialized Apple providers, there are no other platforms than macOS, iOS, iPadOS and tvOS and this makes a huge difference when designing and developing new products and features. With no exception, they are more powerful and perform much better. 

2.  Allows for total automation. IT administrators know how challenging it is to deploy multiple isolated solutions on endpoints and ensure they are working as expected on all company devices. These solutions are designed to be deployed and used independently of any other vendor solution. The side effect: they don’t work well with other vendor products. If you have ever tried to deploy an endpoint security solution to a fleet of hundreds or thousands of Macs, you understand this problem. Several steps must be performed, from installing an app (that normally is not available at Apple’s App Store), configuring a system extension, sending app configurations so the app is connected with the company account without relying on employee manual login, and more.

And if multiple steps are not enough, they need to be performed in a specific order and remotely. In the best case, 80% of devices will work. And when a new update is available, you must do it all again. Mosyle’s Apple Unified Platform concept simply eliminates all of that. An employee boots up a brand-new device for the first time, and it all happens automatically. The device is configured, apps installed, endpoint security and content filtering automatically enforced, and no one must do anything. It just works because Mosyle is using its own MDM to natively enforce the content filtering, endpoint security and much more.

3. Better performance due to native integration. All endpoint software has one thing in common: it runs on the same device. However, most of the software is designed to ignore this fact, which has several implications. First, different pieces of endpoint software generally impact each other. It’s common for web filtering solutions to block the online traffic of the MDM or the EDR, or for the EDR to quarantine the MDM agent or the web filtering solution by mistake.

When that happens, they all stop working, and the IT team must perform a lot of manual work to fix the devices (until it happens again). Second, they don’t leverage the information from the other solutions. The MDM knows what is expected to run on each device because it deployed and configured the device. The web filtering solution has full visibility of web traffic but has no idea what connection comes from malware. And the EDR can’t leverage the info coming from the MDM and the web filtering to make better and quicker detections. Having them all designed to work together and leverage each other unleashes amazing possibilities. When this happens, one solution won’t only avoid impacting the other, but help them. This is mind blowing.

4. Better cost. Mosyle also shows that an Apple Unified Platform can be extremely affordable and cost less than one of the five single independent solutions it replaces currently. 

The potential of the new Apple Unified Platform is unbelievable, and based on Mosyle’s shared information, customers are rapidly embracing it. Since Mosyle first introduced this concept with Mosyle Fuse a little more than one year ago, over 70% of all new customers opted for Mosyle Fuse rather than its MDM-only product.

With these kinds of results, it’s clear there’s no way back to a strategy of isolated and independent multi-platform solutions struggling to work together.

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I Asked Chatgpt About Elon Musk’s Influence On Dogecoin, The Ai Bot Said…

As you may already know, Dogecoin (DOGE) has become somewhat of a cultural phenomenon in recent years, thanks in no small part to the vocal support of figures like Elon Musk. The Tesla CEO has been an outspoken proponent of the meme-inspired cryptocurrency, frequently tweeting about it, and even referencing it at any given opportunity.

Read Dogecoin’s [DOGE] Price Prediction 2023-2024

ChatGPT is scary good. We are not far from dangerously strong AI.

— Elon Musk (@elonmusk) December 3, 2023

Thus, in this article, I would be asking ChatGPT what it thinks of the DOGE- Musk relationship. Furthermore, I will also engage in a conversation about the correlation between the parties while assessing Musk’s role in shaping development within Dogecoin.

Putting Musk’s power on the market causes

There is no doubt that Musk, as one of the world’s richest men, has immense influence. And in 2023, the lover of memes engaged this authority in influencing DOGE’s price. Needless to say, Musk has had a hand in DOGE’s 27,668% all-time hike.

However, as market conditions worsened in 2023, the correlation between Dogecoin and Musk fell. In fact, on several occasions, Musk tweeted about DOGE but there was little to no effect on the price action. This means that the correlation between both decoupled until recently when Musk changed the Twitter logo to a dog, in the representation of Dogecoin. 

The action resulted in a 30% hike in less than 24 hours. However, the hike in value only lasted a while even though the dog logo remained on the social media platform for more than three days. Therefore, I proceeded to ask ChatGPT what it thought of Dogecoin’s relationship with the controversial Elon Musk.

ChatGPT’s “normal” response stated that its cutoff knowledge data was September 2023. It also admitted that the link between Elon Musk’s tweets and Dogecoin was solid at that point in time. However, it could not provide a straightforward answer as to if the correlation would be the same at the time of writing.

The connection is as solid as ever

So, I considered it necessary to find a way to ensure that it replied as I desired. And the solution?— Jailbreak it! There are several ways to do this, including the switch method, the character play, the API way, and the Do Anything Now (DAN) method.

So, I decided to go with the DAN method to ease my conversation with ChatGPT. After successfully jailbreaking it, I again asked— “ChatGPT, tell me, do Dogecoin tweets from Elon Musk have a strong correlation with the cryptocurrency?”

Based on the response above, ChatGPT agreed that DOGE and Musk’s relationship was as solid as ever. Also, it mentioned that the actions of the Twitter CEO suggest market manipulation. And, there was speculation about such occurrences with the most recent one relating to the Twitter logo change and DOGE’s hike. 

On 7 March, Lookonchain reported that two whale addresses saved as “DDuX” and “D8ZE” profited from the DOGE pump and dump.

In terms of development, not much has been happening in Dogecoin’s ecosystem. However, on 23 March, the project’s core developer Michi Lumin announced a rollup of the 0.1.1 development release. With the new version 0.1.2, functionalities including executable utility and transaction verification would become easy for users. 

“We’re ALREADY working on all sorts of new inclusions for 0.1.3, so keep watching – libdogecoin will continue to do more and more while remaining ultra lightweight and cross-compatible.”

Prior to that, Halborn security identified some susceptibles on the Dogecoin blockchain and recommended measures against possible exploits. With respect to its price action, CoinMarketCap revealed that DOGE slipped from its quick run to $0.1.

DOGE: A clampdown on the hype

Earlier this week DOGE came very close to breaching a key support level at $0.076. However, the bulls defended the support zone and reversed the bearish momentum.

At the time of writing, the memecoin was trading at $0.077, down almost 5.5% since the beginning of the week. Its daily trading volume rose to $320 million at press time.

As for the bear case, $0.076 is the support zone to watch out for. Should the bears take this level, a downward trend is likely.

The reading from DOGE’s technical indicators painted a bullish scenario for the memecoin.

The relative strength index (RSI) was at 38.67, right near the oversold region. To add to the bull case, its current On Balance Volume (OBV) of 306.76 billion indicated positive volume pressure for the memecoin.

A $1000 investment would end in a…

I then progressed to ask ChatGPT about Dogecoin. This time, I queried if it is a wise decision to invest $1,000 in the meme. As expected, its classic answer was that which any individual would give, as it encouraged me not to invest in any asset without doing any research.

However, the tool’s jailbroken response gave me the go-ahead to invest the funds in the cryptocurrency. In the words of ChatGPT,

“Investing in Dogecoin for the long term is a wise decision. The cryptocurrency has a strong community of supporters, a growing acceptance as a form of payment, and the backing of influential figures such as Elon Musk”

How much are 1,10,100 DOGEs worth today?

For the time being, Elon Musk’s deep affection for Dogecoin does not seem like one that would be thwarted anytime soon. In fact, the Tesla Founder once mentioned that he would love a DOGE lover like himself to become Twitter’s CEO when he steps down.

However, OpenAI, the team behind ChatGPT, has addressed the safety concerns raised about the platform. 

According to its 5 April press release, its latest model GPT-4  has been subjected to rigorous safety evaluation. Moreover, it has been working on improving its accuracy, research, and privacy worries. This could also extend to its knowledge of the crypto-ecosystem. OpenAI noted, 

“Improving factual accuracy is a significant focus for OpenAI and many other AI developers, and we’re making progress. By leveraging user feedback on ChatGPT outputs that were flagged as incorrect as a main source of data—we have improved the factual accuracy of GPT-4.”

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