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Microsoft Announced OpenAI’s GPT-4 Access to US Government Agencies

In a significant development, Microsoft has announced that it will provide government agencies in the U.S. with access to OpenAI’s artificial intelligence (AI) models, including the highly regarded GPT-4 and its predecessor. This move aims to empower government offices by harnessing the capabilities of AI and leveraging the benefits of Azure OpenAI services.

At the forefront of Microsoft new Bing search engine, OpenAI’s GPT-4 has proven to be a formidable force, capturing the attention of companies seeking to optimize their data utilization through AI-driven insights. With over 4,500 customers already benefiting from Azure OpenAI services since its launch in January, major corporations such as Mercedes, Volvo, Ikea, and Shell have embraced this technology to enhance employee productivity and data analysis.

While private companies have eagerly adopted AI to revolutionize their operations, government agencies have often lagged behind in adopting these transformative technologies. However, Microsoft’s latest offering breaks down those barriers, extending the opportunity for government offices to leverage powerful AI models effectively.

By integrating OpenAI’s AI models into their operations, government agencies can tap into the immense potential of AI, unlocking opportunities for improved decision-making, enhanced efficiency, and increased productivity. The availability of Azure OpenAI services to government entities signifies a pivotal step toward enabling data-driven insights and advanced analysis in the public sector.

Through this collaboration, government agencies will gain the means to harness the capabilities of OpenAI’s cutting-edge AI models, enabling them to derive valuable insights from vast amounts of data and make informed decisions. This technological leap promises to propel government operations into a new era of efficiency and effectiveness, ultimately benefiting the public at large.

With the convergence of Microsoft’s Azure OpenAI services and OpenAI’s powerful AI models, government agencies now have a transformative tool at their disposal. This development marks an important milestone in bridging the gap between private and public sectors in the adoption of AI, paving the way for innovation and progress in government operations.

What is Microsoft offering?

Microsoft will allow government agencies to access GPT-4, GPT-3, and Embeddings from OpenAI using the Azure OpenAI service. Embeddings measure the relatedness of text strings and are helpful in operations such as Search, Clustering, Anomaly Detection, and Classification, to name a few, as per OpenAI’s website.

These services are aimed at helping government agencies “improve efficiency, enhance productivity and unlock new insights from their data,” Microsoft wrote in a blog post. Users of this service can use REST API, Python SDK as well as the web-based interface in Azure AI Studio to adapt AI models to specific tasks.

Using the service is expected to help government agencies accelerate content generation, reduce the time and effort required for research and analysis, generate summaries of logs, and rapidly analyze long reports while also facilitating enhanced information discovery, a Microsoft blog post stated.

Users will also be able to build custom applications to query data models and generate code documentation, processes which have historically been very time-consuming.

Ensuring the security of government data

Since most government agencies tackle sensitive information that needs a high level of security, Microsoft will provide these services through Azure Government which uses stringent security and compliance standards.

Government agencies will use the AI services on the Azure Government network, which will pair directly with the commercial Azure network over Microsoft’s own backbone networks. Through this architecture, Microsoft guarantees that government applications and data environments remain on Azure Government.

Additionally, Microsoft encrypts all Azure traffic using AES-128 block cipher and ensures that the traffic remains within Microsoft’s networks and is never made part of the public internet. Microsoft has also clarified in the blog post that government data will not be used to learn about the data or to train or improve the AI models.

Specifically, Azure Government users will not have access to ChatGPT, the conversational chatbot commonly accessed by users on the internet, a Microsoft spokesperson confirmed to Bloomberg.

This should put to rest any concerns about government or individual data being accidentally released to the public due to some misgivings about the technology from a state or federal employee, unlike what happened at Samsung.

How Does OpenAI’s GPT-4 Differ from Its Predecessor, GPT-3.5?

OpenAI’s GPT-4: How it is different from its predecessor GPT-3.5, With ChatGPT’s ongoing success and popularity, OpenAI has now created GPT-4, the highly anticipated successor to GPT-3.5. GPT-4 is a large multimodal model capable of accepting text and image inputs and generating text outputs.

With its unmatched language-generating capabilities, GPT-3.5 has raised the bar for natural language processing (NLP). OpenAI’s GPT-4 is expected to push the boundaries of NLP even further and enable the development of more advanced and sophisticated language-based applications.

OpenAI’s technical report states that GPT-4 has demonstrated human-level proficiency in academic and professional environments, including achieving scores in the top 10% of test takers on the bar exam. While GPT-4 continues to utilize the Transformer architecture, it surpasses its predecessors by exhibiting enhanced capabilities in comprehending the subtleties of language, such as its context, mood, and significance.

One of the most impressive feats of GPT-4 is its ability to understand and follow user intent. This may have significant implications in many sectors, including finance, healthcare, education, etc. Additionally, its advanced NLP capabilities could lead to the development of more efficient and accurate virtual assistants, such as chatbots.

In this article, we will focus on understanding the main differences between GPT-4 and GPT-3.5 in terms of performance and training. We will also take a look at GPT-4’s release and which industries are most likely to benefit from it.

GPT 3.5: What are its capabilities?

In 2022, OpenAI released ChatGPT based on the GPT-3.5 series. This is a series of models that have been trained on a blend of text and code, with the data or information being used dating to before September 2021. 

GPT stands for generative pre-trained transformer and is a language model that uses neural networks to generate human-like text. The largest model in GPT-3.5 has 175 billion parameters (the training data used is referred to as the ‘parameters’) which give the model its high accuracy compared to its predecessors. ChatGPT is capable of language translation, writing various types of creative content, and answering user questions in an informative way.

OpenAI's GPT-4: How is it different from its predecessor GPT-3.5?
OpenAI’s ChatGPT is built on their GPT-3.5 seriesOpenAI/Wikimedia Commons 

The output from ChatGPT is of very high quality, often making it difficult to distinguish between human and machine-generated text. Among other things, ChatGPT has been used to generate news articles, write poems, and create chatbots that can hold conversations with humans. Since its launch, ChatGPT has surprised users with its powerful technology with a variety of applications in many fields.

A brief overview of GPT-4 and its capabilities

Similar to its predecessors, GPT-4 is a language model capable of generating human-like responses. The exact architecture of GPT-4 and the amount of training data used with the model have not been revealed by OpenAI. According to their report, GPT-4 can accept input in the form of images and text and provide responses accordingly. 

The main aim behind their development of this version was to improve previous GPT models’ responses in complex scenarios and fine-tune responses based on human feedback. This is considered a significant improvement, allowing the model to align more closely with human intent. 

The model was used in various professional, academic, and social scenarios to test its capabilities. They found that GPT-4 performed excellently — comparable to humans. In particular, the model scored in the top 10% of test takers for the Uniform Bar Examination and did well in other tests, such as the SAT. Scientists and developers from OpenAI believe that the excellent performance of the model is highly reliant on the pre-training process.

OpenAI's GPT-4: How is it different from its predecessor GPT-3.5?
GPT-4 performs as well as humans in exams and assessmentsKF/Wikimedia Commons 

Undeniably, GPT-4’s most exciting feature is its ability to accept input in the form of images or visuals. The input visuals can be in the form of documents with texts and photos, diagrams, or screenshots. Additionally, the model has also shown the ability to identify humor in visual inputs. This means that it can not only generate funny text but it can also recognize and explain jokes in images.

Also Read: Top 5 Ways GPT-4 Can Increase Workers Productivity

Performance comparison between GPT-3.5 and GPT-4

GPT-4 has shown improved performances in many different situations compared to GPT-3.5. According to early reports by users and comments by OpenAI’s co-founder, GPT-4 is better than GPT-3.5 at producing creative writing, and it is capable of generating poems and other creative text. Additionally, GPT-4 can correct itself when it makes a mistake and produce a perfect response, which is lacking in GPT-3.5.

Another area where GPT-4 outperforms GPT-3.5 and other state-of-the-art models is in exam-taking. GPT-4 is acing exams and tests, even the challenging ones like the bar exam. This is an exciting development and may be used as a teaching (or cheating) aid in schools.

GPT-4 is also showing promise in the area of massive multi-task language understanding (MMLU). This is a benchmark that measures the knowledge acquired by a model during pretraining. GPT-4 has demonstrated excellent performance in a total of 27 languages, including English.

OpenAI's GPT-4: How is it different from its predecessor GPT-3.5?
GPT-4 outperforms GPT-3.6 in exams and testsOpenAI (2023) 

GPT-4’s improved factual accuracy is a significant development. This means that users can be more confident that the information they receive from GPT-4 is accurate and up-to-date. This is especially important in areas such as learning, technology, writing, history, math, science, recommendation, code, and business.

GPT-4’s improved factual accuracy is likely due to several factors, including its larger dataset, its more sophisticated training methods, and its ability to learn from feedback. However, this cannot be said with certainty since the training methods have not been disclosed. However, it is likely that with continued development, GPT-4’s factual accuracy will improve even further.

OpenAI's GPT-4: How is it different from its predecessor GPT-3.5?
Performance of GPT-4 on MMLUOpenAI (2023) 

Potential applications of GPT-4

Due to its multimodal interface, GPT-4 has the potential to revolutionize many industries, including customer service, education, and entertainment. It can also improve existing technologies and research by improving chatbots and further advances in machine learning (ML) research. 

Customer service

GPT-4 can be used to automate customer service tasks, such as answering questions, resolving issues, and providing support. This would allow human customer support representatives to concentrate on more complicated problems that would require more time and effort.


The model can be used to create educational content, such as interactive lessons, practice exercises, and assessments. By allowing students to interact with the technology in real time, teachers can get real-time feedback on how well students are understanding the material.


It can also be used to create entertainment content, such as stories, poems, and music. For example, it can be used to generate realistic and nuanced dialogues for movies, TV shows, and video games. This can help to make these products more immersive and engaging for users, while also freeing up the creator’s time to focus on more technical aspects of their work.

OpenAI's GPT-4: How is it different from its predecessor GPT-3.5?
GPT-4’s recognition of humor in visual inputOpenAI (2023) 

Improving chatbots

GPT-4 can be used to improve existing chatbots by making them more human-like and engaging. Chatbots powered by GPT-4 can hold conversations that are more natural and nuanced, and they can provide more helpful and informative answers to questions.

Further advancements in machine learning research 

Finally, GPT-4 can be used to further machine learning (ML) research. By studying how GPT-4 can generate responses in different forms, researchers can develop new and innovative ML algorithms that can improve on the fallacies of existing models.

These are just a few examples of the potential applications of GPT-4. As GPT-4 continues to develop, we will likely see even more innovative and creative uses for this technology.

Limitations of GPT-4

Similar to other language models, GPT-4 also has certain limitations. Some of these limitations include bias, accuracy, and safety. Let’s take a look at each of them below.

Bias: Since GPT-4 is trained on a large dataset of text and code, the model will inherit any existing biases in the dataset. 

Accuracy: Just like its predecessors, GPT-4 is capable of making factual mistakes and providing inaccurate or misleading information. 

Safety: GPT-4-generated material has the potential to be harmful and degrading. As a result, when using the model, it is critical to be conscious of this danger. It is good to be aware of these limitations when using GPT-4, because it can help users to take appropriate actions to mitigate the risks and use GPT-4 to its full potential.

A Wharton Professor Gave AI Tools 30 Minutes To Work On A Business Project

Artificial intelligence is presenting new possibilities in terms of how to do work, and leaving many observers nervous about what will become of white-collar jobs.

Ethan Mollick, a management professor at the Wharton School of the University of Pennsylvania, has been closely following developments in generative A.I. tools, which can create essays, images, voices, code, and much else based on a user’s text prompts.

Ethan Mollick

He recently decided to see how much such tools could accomplish in only 30 minutes, and described the results this weekend on his blog One Useful Thing. The results were, he writes, “superhuman.”

In that short amount of time, he writes, the tools managed to do market research, create a positioning document, write an email campaign, create a website, create a logo and “hero shot” graphic, make a social media campaign for multiple platforms, and script and create a video.

The project involved marketing the launch of a new educational game, and he wanted A.I. tools to do all the work while he only gave directions. He chose a game he himself authored so that he could gauge the quality of work. The game, Wharton Interactive’s Saturn Parable, is designed to teach leadership and team skills on a fictional mission to Saturn.

First, Mollick turned to the version of Bing powered by GPT-4. Bing, of course, is Microsoft’s search engine—long a distant second to Google—while GPT-4 is the successor to ChatGPT, the A.I. chatbot from OpenAI that took the world by storm after its release in late November. Microsoft has invested billions in OpenAI.

Mollick instructed Bing to teach itself about the game and the business simulation market of which it’s a part. He then instructed it to “pretend you are a marketing genius” and produce a document that “outlines an email marketing campaign and a single web page to promote the game.”

In under three minutes it generated four emails totaling 1,757 words.

He then asked Bing to outline the web page, including text and graphics, and then used GPT-4 to build the site.

He asked MidJourney, a generative A.I. tool that produces images from text prompts, to produce the “hero image” (the large image visitors encounter first when visiting a website).

Next, he asked Bing to start the social media campaign, and it produced posts for five platforms, including Facebook and Twitter.

Then he asked Bing to write a script for a video, an A.I. tool called ElevenLabs to create a realistic voice, and another called D-id to turn it into a video.

At that point, Mollick ran out of time. But, he notes, if he’d had the plugins that OpenAI announced this week, his A.I. chatbot, connected to email automation software, could have actually run the email campaign for him.

According to OpenAI, plugins for Slack, Expedia, and Instacart are among the first to be created, with many more to come. The problem with A.I. chatbots, the company notes, is that “the only information they can learn from is their training data.” Plugins can be their “eyes and ears,” giving them access to more recent or specific data.

Mollick writes that he would have needed a team and “maybe days of work” to do all the work the A.I. tools did in 30 minutes.

Bill Gates wrote on his blog this week that ChatGPT and similar tools “will increasingly be like having a white-collar worker available to help you with various tasks.”

Actual white-collar workers might be forgiven for feeling some anxiety.

Top 5 Ways GPT-4 Can Increase Workers Productivity

The language model that powers chatGPT, GPT-4, has developed the latest version with considerable improvements over GPT 3 and GPT 3.5. Though, workers can use GPT-4 to enhance their productivity and quality of work.

The newest version of GPT is capable enough to accept inputs in both the forms of text and images. In contrast, GPT 3 and 3.5 could only take data in text.

ChatGPT is an innovative artificial intelligence technology created by OpenAI. The company aims to provide effective results in less period.

However, I can suggest some potential ways in which a language model like GPT-4 could increase workers’ productivity in the future based on the advancements made by previous models like GPT-3:

  1. Automating Repetitive Tasks: GPT-4 could be used to automate repetitive tasks such as data entry, email responses, and social media posts, freeing up workers’ time to focus on more complex tasks.
  2. Enhancing Communication: GPT-4 could help workers communicate more efficiently by providing real-time language translation and automatic summarization of long texts or meetings, making it easier to understand and respond to information.
  3. Improving Research: GPT-4 could assist workers in conducting research by providing accurate and relevant information from a vast range of sources, making it easier to find the data needed to complete tasks.
  4. Streamlining Workflows: GPT-4 could help workers streamline their workflows by providing suggestions on the best way to complete a task, identifying potential roadblocks, and offering solutions to overcome them.
  5. Personalizing Work: GPT-4 could help workers personalize their work by analyzing their work habits, preferences, and productivity patterns and offering customized recommendations on how to improve their workflow and increase productivity.

Apple’s Siri Might Soon Get Technology Similar to Chat-GPT

Apple’s Siri was introduced in 2011 with iPhone 4S. Since the launch of Siri, Apple has incorporated new features and surprised its customer base. Recently the news is that it will get a complete makeover, as the company is working on its natural language, which might give Siri ChatGPT-like abilities. 

Apple’s Siri Will Have ChatGPT-like Features

The rise in OpenAI’s ChatGPT is miles ahead of the competition, which has forced Google and Apple to reinvent their AI. This has encouraged Apple to try new ChatGPT-like features. The underutilized assistant, Siri, will get natural language generation capabilities, which will be a major turn-up for the company. The company has already incorporated a new feature in Apple TV – the streaming box. The new feature allows Siri to crack jokes and potentially set timers using AI features. 

However, the tvOS 16.4 beta upgrade is only available for developers. The general public will soon be able to avail of the feature and test it by signing up for Apple’s beta software program. However, in the coming days, Siri can be accessed with natural languages on several devices such as iPhones, iPads, and Macs. 

Google has also launched its “BARD” to compete against OpenAI’s ChatGPT – which has opened up to trusted testers before the company reveals it widely to the public. 

Recently, OpenAI has said that the launch of ChatGPT and GPT-4 is the start of an era of huge technological empowerment. It also set the stage for human-like technology to compete with Microsoft Corp. and Alphabet Inc’s Google. 

Unlike ChatGPT or GPT-4, Apple’s Siri will offer a more humane touch because of its speech feature. It is also said the capability will be limited only to Siri. However, there is no update on the feature launch as the concern grows over AI’s potential harm. Hopefully, we will hear the news soon and see the hype. 

10 Use Cases Of ChatGPT In Banking Sector

Here we are bringing the top 10 use cases of ChatGPT in the banking sector.

Client Assistance

ChatGPT facilitates the banking sector by providing support to their client care. It responds quickly and effectively to customer inquiries, complaints, and requests for information. In addition, the Banking sector feels blessed after having the capabilities of chatGPT.

Detection Of Fraud

ChatGPT is very helpful in detecting any kind of fraud. It analyzed a large amount of transaction data and identify suspicious patterns.

Hence, ChatGPT plays a vital role in assisting banks in safeguarding the financial assets of their customers and minimizing fraud losses. Technical departments at banks might set up alarms, therefore, security experts will be aware of dubious actions.

Credit Banking

The collection, evaluation, of data and the evaluation of risks, and the processing of loans are one of the most complex processes of bank operations.

However, Banks can easily cut down the efforts by using chatGPT’s Natural Language Processing (NLP) model. However, banks can also utilize their Machine Learning capabilities to make the loan origination process easier and quicker.

ChatGPT provides real-time guidance and assistance to customers who are willing to apply for loans.

Therefore, Banks can take advantage of chatGPT to gather information about their customers, evaluate their creditworthiness, and offer real-time feedback on loan applications.

Banks can utilize the application in many ways to lessen the likelihood of default and by analyzing huge data.

Financial Management

ChatGPT can assist banks in providing personalized wealth management services to their customers. ChatGPT helps in analyzing customer data and providing customized investment recommendations. The best part is, it takes the decision on an individual basis.


The banking sector heavily relies on consistency, and failing to do so can result in severe financial penalties and reputational damage.

Hence, by monitoring banking transactions and identifying potential violations of compliance, chatGPT can help banks in adhering the requirements of the regulatory bodies. The new innovation chatGPT can help banks in protecting their reputation and avoid costly penalties and fines.


Banks need to know your customer (KYC) and Anti Money Laundering (AML) process to cut down the risks of financial dangers and stay in compliance with the law.

Therefore, by evaluating a large amount of customer personal information and transaction history, chatGPT can help banks in automating these processes.

Moreover, it can easily identify suspicious transactions, and verify the identity of customers.

Planning Your Finances

Many clients depend on banks to give them leverage in monetary arranging administrations and this can be easily done by chatGPT. The new advanced technology helps in providing a proper financial plan for their future. This includes budgeting, retirement planning, and budgeting.

Onboarding New Customers

ChatGPT help banks to develop strong relationship with their customers. Building strong relationships is time-consuming and needs powerful strategies. By using chatGPT, banks can make the process smooth and easier.

Opening New Records

It can help banks accurately check customer data and identify problems that need to be done by verifying customer identities.

However, chatGPT can help banks identify and manage potential risks by analyzing massive amounts of data and locating potential risk factors.

In addition, banks can use chatGPT to monitor transactions, flag questionable ones, and identify potential fraud.

Additionally, by examining news and market data, the model can also assess potential economic risks that might have an impact on the bank’s operations.

By utilizing chatGPT’s machine learning capabilities, banks can gradually improve their risk management practices.

Banking Virtual Assistants

Banks can provide their customers with a 24/7 remote assistant to help them with dealing with their records, paying their bills, and competing transactions

Man Creates Remarkable 3D Game Using GPT-4

To create a basic Doom style game, the man asked users to simply ask GPT4 to create a game that resembles Doom

ChatGPT took the internet by storm upon its release last year. With the launch of GPT 4 a few days ago, AI experts are experimenting with the model and testing all the limits to which it can exceed.

While people had enough hopes for this new AI technology when it came to basic AI work, what no one expected from GPT 4 was to develop a full-fledged game. However, technology is the name for surpassing user expectations and that is exactly what has happened.

The Indian Express on Twitter spotted an AI enthusiast Jani Lopez who experimented with GPT4 and gave an in-depth breakdown to show how this latest technology could be used for game development purposes. In a twitter thread shared by the user, he demonstrated how to leverage the AI technology to produce basic video games similar to a well-known one like Doom, ways one should use the AI to generate the required codes, showed simple steps on how to increase the game’s prototype visual appeal and showed small glimpses of codes written entirely by the GPT4 itself.

Javi stated that while users can create some meaningful content, they should look at the AI realistically and keep their expectations in check before wanting the GPT version to pop out something never seen before.

In order to create a basic Doom style game, Jani said that users can simply ask GPT4 to create a game in resemblance to Doom. He further stated that while tis initial request might seem basic, users can improve the visual aesthetics and overall working of the game once they have the foundation established.

The fact that GPT4 can create something as complex as a game shows that this is only the tip of the iceberg. Users can easily expect GPT4 to bring forward even more astounding creations and take the world of technology by storm. Who knows what the next year in the tech world will bring, but what we know is that we will be here to keep you updated!

GPT-4 Can’t Stop Helping Hackers Make Cyber Criminal Tools

OpenAI released the latest version of its machine learning software, GPT-4, to great fanfare this week. One of the features the company highlighted about the new version was that it was supposed to have rules protecting it from cybercriminal use. Within a matter of days, though, researchers say they have tricked it into making malware and helping them craft phishing emails, just as they had done for the previous iteration of OpenAI’s software, ChatGPT. On the bright side, they also were able to use the software to patch holes in cyber defenses, too.

Researchers from cybersecurity firm Check Point showed Forbes how they got around OpenAI blocks on malware development by simply removing the word “malware” in a request. GPT-4 then helped them create software that collected PDF files and sent them to a remote server. It went further, giving the researchers advice on how to make it run on a Windows 10 PC and make it a smaller file, so it was able to run more quickly and have a lower chance of being spotted by security software.

To have GPT-4 help craft phishing emails, the researchers took two approaches. In the first, they used GPT-3.5, which didn’t block requests to craft malicious messages, to write a phishing email impersonating a legitimate bank. They then requested GPT-4, which had initially refused to create an original phishing message, to improve the language. In the second, they asked for advice on creating a phishing awareness campaign for a business and requested a template for a fake phishing email, which the tool duly provided.

“GPT-4 can empower bad actors, even non-technical ones, with the tools to speed up and validate their activity,” the Check Point researchers noted in their report, handed to Forbes ahead of publication. “What we’re seeing is that GPT-4 can serve both good and bad actors. Good actors can use GPT-4 to craft and stitch code that is useful to society; but simultaneously, bad actors can use this AI technology for rapid execution of cybercrime.”

“GPT-4 can empower bad actors, even non-technical ones, with the tools to speed up and validate their activity,” the Check Point researchers noted in their report, handed to Forbes ahead of publication. “What we’re seeing is that GPT-4 can serve both good and bad actors. Good actors can use GPT-4 to craft and stitch code that is useful to society; but simultaneously, bad actors can use this AI technology for rapid execution of cybercrime.”