## Introduction:

Meta has made a milestone breakthrough it will present as its next generation large language model: a state-of-the-art open-source tool – Llama 3. This year, Meta has declared officially the start of a new phase. In this phase, they will be using the latest AI technology that is meant to empower both individuals and businesses of all kinds.

## Meta AI: An Admirable Quest to Personalize Your Everyday Life 

Lying at the core of this development Meta AI, a powerful and competent AI assistant, is made from the basis of Llama 3 technology, Meta AI, powered by Artificial Intelligence, is your constant companion. It allows you to increase your intelligence and make your life easy, and the interface is adaptable, and it works across all Meta’s apps.

Whether it is a dinner menu from the food products you have in your fridge, or seeking for the answers for an exam to come, or looking for an inspiration for your creative art, AI is there ready to assist you. Because of its impressive features, this AI assistant can come up with the band band album art, offer decor ideas for your apartment or even generate GIF animations – just name what do you need.

## Llama 3: Shoe Horn for or Release Image Depicting Rising of Bar for Open-Source LLMs. 

![Image from frimufilms](img/llama-3-shoe-horn-for-or-release-image-depicting-rising-of-bar-for-open-source-llms.jpg "Image from frimufilms")

Image from frimufilms\
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Meta's initiative on Llama3 lies at the heart of the open and collaborative AI ecosystem, which has been at the core of its developmental drive. Through this official transfer of the leading-edge models to a global community, Meta will set the stage for a spiraling catapult of next-gen breakthroughs: a blizzard of applications and tools for developers, a storm of iterative advancements in model evaluations, generation, and optimization.

State-of-the-Art Performance Llama 3 is the golden egg of all LLMs, demonstrating an exceptional level of performance on 8B and 70B parameter scenarios. Meta's model, on the other hand, is trained in advance and then via post-training technique, and it is capable of outperforming other solutions that are available in the industry, along with the demonstrated ability to improve reasoning, high performance when generating code, as well as superior instruction following.

Innovative Architecture and the Develoment of Training Approach Mane of the model challenging issues, the heart of Llama 3's success lies with its novel model architecture design and training. In spite of involving the classic decoder-only transformer architecture Meta still introduces substantial advancements illustrated by utilizing a particularly large 128K vocabulary tokenizer for more efficient encoder and training as well as by employing GQA for higher inference efficiency of the process.

On top of that, Llama 3 has been trained on a dataset (including 15T tokens) that is way too large to be imagined, thus it is made up of more than 50% of publicly available data sources, most of which is the high quality non-English multilingual data. Shengli is a super fast filtering pipeline and tough incubator. As a result, technical scientists using Llama 3 efficiently and effectively will achieve a wide range of objectives on different subjects from trivia questions, stem subjects to computer programming and historical knowledge.

## Scale-Up: Pretraining Enhanced and Instruction Fine-Tuning Modality 

Meta's AI limit expansion by Scale Project is well demonstrated as Llama 3. Through conducting meticulous scaling laws, having downstream benchmark evaluations, Meta can be confident in predicting the performance of the largest models on code generation and such other tasks before the actual training takes place. Consequently, such approach provides a strong performance in complex situations where a higher level of cognition is needed.

Furthermore, Meta has recognized the progress in the field of best practice fine-tuning (SFT) by combining SFT, rejection sampling, PPO, and DPO. Meta has done that by designing numerous prompts differently and optimizing the human preference ranking. Consequently, Llama 3 is able to learn to choose correct reasoning traces and produce truthful solutions.

## Building with Llama 3: 

Enhancement of developer's power and guarantee of responsible usage of it. Meta's ambition with Llama 3 is to achieve more than frameworks; it convinces experts to boost their actions and utilize optimal way of utilizing the model's potential. For this purpose, the company has implemented new trust and safety tools, for example, Llama Guard 2, CyberSec Eval 2 and the cutting-edge Code Shield, a safeguard protecting from insecure code that came out of LLMs inference cycle.

Meta has also been partnered with torchtune, which created pyTorch-native library to simplify the process of building, fine-tuning and experimenting in the style of large language models. The library is compatible with well-known environments, including Hugging Face, Weights and Biases, and EleutherAI, also including delagation for Executorch to run inference on mobile and edge devices.

## A System Level Approach: An Ethic System for AI. 

![Image from rawpixel.com](img/a-system-level-approach-an-ethic-system-for-ai..jpg "Image from rawpixel.com")

Image from rawpixel.com\
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Also as MA recognizes the role of responsible AI in AI construct, it has taken a holistic approach to ensure secure and ethical use of Llama 3 technology. Hence, it is conceived here in the models that Llama will serve as the basic parts of the entire system. And with this, developers can now easily make the systems catering to their areas of expertise while meeting the industry-level standards.

Instruction fine-tuning plaes a critical part in the security of Llama 3 models by fine-tuneing greatly. Meta makes efforts which are really tough to secure those technologies and other critical areas by human experts and automated method such as red-teaming which helps to assess and mitigate the risks related to misuse, chemical, biological, cybersecurity and more.

Moreover, Meta has revised the Responsible Use Guide (RUG) presenting a whole new foundation for the unrefined LLM use. This guide focus on the importance of categorization and distribution of propaganda, vigilance with regard to content guidelines and cloud providers AIs and the other content moderation tools.

## Deploying Llama 3 at Scale: 

They aggravate the problem of overexploitation and elevated consumption, due to harvesting to fulfill demand once this resources become easily available and efficient. Llama 3 AI democratization is of the same Standard with the other Meta vision of letting the tool used by the people without expense and low-cost deployment challenges. This outstanding model is going to be available on all main delivery platforms that include the cloud providers and API providers among others in the coming days making it actually ubiquitous.

It was revealed that the new Llama 3's tokenising system was more efficient than the previous generation, Llama 2, resulting in a token reduction of maximum 15%. Besides that, GQA inclusion in 8B and 70B attentions has been instrumental in achievement of the similar inference efficiency as the Llama 2 7B one, in spite of the increased model size.

Meta is able to provide an extensive collection of source code open-source for developers with its support in order to facilitate Llama 3 adoption rate. Rather than just a collection, it is neatly called "Llama Recipes. " In this, the developers are provided with examples and guidance on things like fine-tuning, deployment, model evaluation and so on.

## The Future of Llama 3: Continuous Innovation and Advanced Technologies in the Aircraft Manufacturing Market 

![Image from upklyak](img/the-future-of-llama-3-continuous-innovation-and-advanced-technologies-in-the-aircraft-manufacturing-market.jpg "Image from upklyak")

Image from upklyak\
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Even 8B and 70B Llama 3 models are the first steps in the Meta project. However, this project is not about releasing the technology - it's only the beginning of realizing this revolutionary AI technology. During the upcoming several months the company will be taking its prowess to the next level by launching a variety of new models with breath-taking capabilities like multimodality, multilingual conversational abilities, significantly longer context windows and much stronger overall performance.

To give an insight into what’s in store, Meta Corporation has revealed screenshots of its biggest LLM model; but, still there are some areas where the model is in the process of training and therefore currently excels in other areas. These abilities may not be available even in the models released today, but they set them as a stage for the future effort to explore the high level of capabilities that AI is able to reach.

Obviously, Meta features as one of the major actors in the open AI ecosystem, with the company working towards open development of AI things, responsible release practices and rapid adaptation in the market. Spreading the community-first approach, Meta plans to transfer the know-how of Llama 3 to developers, researchers, and enthusiasts, launching the community to search for new horizons which this innovative technology has opened for the society.

## Conclusion: 

The debut of Llama 3 AI by Meta and also the adding of Meta AI assistant are definitely calling stages in artificial intelligence theme. The next breakthrough in AI is aimed at providing its users with unrivalled performance, highly advanced architecture and a strong responsible development which will ultimately bring about an art form of the future that will let us access and utilize new layers of productivity, creativity and intellectual exploration.

As Meta works towards making Llama 3 even more advanced and feature rich, the horizons have possibly the widest and most astonishing landscape. AI language models are no longer just a simulation of the human language. Instead, they continuously change and improve in real-time to form a seamless communication platform in any language. AI technology will move from now simple multilingual communication to ground-breaking multimodal experience that will reshape our understanding of capabilities. This will create a future in which human intelligence can merge with machine intelligence to produce fantastic achievements.

Together with Meta AI use its innovative Llama 3 model based on AI technologies to explore with your own eyes the contributions of this revolutionary approach to the future.

Hey there, AI enthusiasts! Get ready to be amazed by Meta's latest creation – Llama 3, a next-generation AI model that's about to change the way you interact with technology.

Everything You Need to Know About Meta AI Assistant: Major AI model, Llama 3, has arrived

## The Goal

How about analyzing, which Collaboration Software Tool has the best sentiment (most mentiones with positive sentiment)?\
We’ve analyzed the mentions all over the web for a month, to check which of the following tools is used in the most positive, and negative contexts:

* [Jira](https://www.atlassian.com/software/jira)
* [Azure DevOps](https://azure.microsoft.com/en-us/products/devops/)
* [ServiceNow](https://www.servicenow.com/)
* [Asana](https://asana.com/)
* [Monday.com](https://Monday.com/)
* [ClickUp](https://clickup.com/)
* [Zendesk](https://www.zendesk.com/)

*Disclaimer: It’s not a professional research, done with sentiment analysis professionals, rather an analysis, an exercise, so some some small mistakes might have been made. We did our best to avoid them, by deleting all the noise (f.e. by setting out dedicated filters, improving the formulas from day to day based on the results we saw). But there is always a possibility, that we skipped something.  So take the results lightly. If the community will like it, we’ll prepare the next editions, trying to be better, and better.*

> There are a lot of rankings about software, G2, Capterra, Gartner, and probably many others. Most of them are focused on features, some on reviews, others on income and market share. But… none of them are about emotions, the sentiment.\
> *Jacek Wizmur, Co-Founder of [Getint.io](https://getint.io/)*

In a very competitive market, most of the available tools are very similar in terms of core functionalities.

So… what differentiates them?\
What makes people choose one over the other?

`UX? Is it really?`\
`Performance? Probably.`\
`Completeness? Maybe.`\
`Customization possibilities? Could be.`\
`Deployment option (SaaS vs OnPremise)? For enterprises, it’s one of the factors, sure.`\
`Pricing? At some point, yes.`

But… In the end, all the decisions are made by humans. It’s not B2B or B2C – it’s B2H (Business to Human). In the era of social media, and reviews (Capterra, Clutch, etc.) emotions and buzz are becoming more and more a decisive factor. Additionally, people want to work with a tool that has this positive vibe.

As getint.io, we are a platform that helps people integrate software (f.e. Jira – Jira, Jira – Azure DevOps, Asana – Azure DevOps, ServiceNow- ServiceNow, and so on), or migrate from one software to the other (f.e Monday to Jira). For us, there is no one mighty, go-to software that always is the best. We’re not biased. The practice taught us, that each is best for some scenarios, and the main goal is the Customer’s satisfaction.\
If it works, it’s good.

We did not want to prepare a report to state that one software is better than another, or more liked than the other. We wanted to see, which drives the conversation in the most positive, or negative context. In addition to that, we wanted to check the volume of mentions all over the web, to see which seems to be the most popular tool.

## A bit of history

What may affect the number of mentions, is the fact of how long each tool is on the market – how much time it had to build a customer base, willing to talk about a tool.

Let’s take a quick look.\
**Jira**: 2002\
**Azure DevOps**: 2018 (current version, its lineage can be traced back to Visual Studio Team System which was launched in 2006)\
**Monday.com**: 2012\
**ClickUp**: 2017\
**ServiceNow**: 2003\
**Zendesk**: 2007\
**Asana**: 2008

Jira is the oldest tool, it was the first to make the way for others. ServiceNow was launched just a year later. The most recent ones are ClickUp, and Monday.com – they could use the lessons learned from their predecessors.

## How we did it (**the Collaboration Software Tools, Sentiment Analysis report)**

Getint.io team was collecting data on Jira, Azure DevOps (including ADO keyword), ServiceNow (including keywords like “snow platform”, and “now platform”), Monday.com, Asana, ClickUp, and Zendesk for more than a month, but for this analysis, we will take the dates from 27.01 to 27.02.2022.

This report was possible thanks to our friends at [Brand24](https://brand24.com/?utm_source=Getint.io&utm_medium=blogpost&utm_campaign=BR24_Getint_SentimentAnalysis), the Social Media Monitoring tool, which was recognized as the best in business by f.e. Sujan Patel. The tool has great reviews all over the web (Capterra, G2, Software Advice). Brand24 was featured in TechCrunch, Entrepreneur, AdWeek, and Forbes.\
\
What does Brand24 do? The tool is collecting mentions about specified keywords, in blogs, news channels, social media (mostly Twitter, collecting the data from LinkedIn is not possible for now, and collecting data from Facebook, and Instagram is challenging, and limited only to the public mentions). Thanks to that, a brand can see what people are saying about it and can join the conversation.

We were collecting data based on keywords, topics, hashtags, and @mentions across blogs, news sites, and social networks (mostly Twitter). We analyzed more than 65,100 mentions concerning these Collaboration Software Tools to see, which have the most positive, and the most negative sentiment.

> I have to say, it wasn’t as easy, as I thought.

We had to make a lot of work to filter out the web mentions – it turned out that f.e. “Jira” is not that unique keyword, it means “wait”, and “Waxaa jira” means “there is” in some African languages (f.e. Hausa). What’s more “la jira con” means “the tour with” in Spanish. There are also a lot of Twitter users using “jira” in their username. 

On the other hand, “Asana” is a yoga position, and most of the mentions were about yoga, not the tool. Things were easier with “ServiceNow”, or “Azure DevOps” where mentions were usually about the software we wanted to analyze. In short, we needed to delete a lot of the mentions to keep the data as clean as possible.

Since it was challenging to make sure it’s done 100% correctly, I’ll present all of the data, but I’ll analyze only the ones from the following countries: United States, Spain, United Kingdom, Germany, France, Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Switzerland, Sweden, and Ukraine.

Here is an example how the data in Brand24 look like:

![clickup-infogr-countrires](https://getint.io/wp-content/uploads/2022/03/clickup-infogr-countrires.png "clickup-infogr-countrires")

## [Brand24 Sentiment Analysis](https://getint.io/collaboration-software-tools-sentiment-analysis-report/#:~:text=Brand24%20Sentiment%20Analysis)

As Tom from Brand24 writes:

> “Sentiment analysis, also known as opinion mining, or emotion AI, boils down to one thing: It’s the process of analyzing online pieces of writing to determine the emotional tone they carry, whether they’re positive, negative, or neutral.”

A sentiment analysis system for text analysis combines natural language processing (NLP) and machine learning techniques to assign weighted sentiment scores to the entities. The texts that make up the mentions are converted into numerical sequences that are much more understandable to the algorithm than pure text strings. The second neural network was based on embeddings, which we learned to distinguish between sentiments. The entire text in the found entry is analyzed.

### **First stage – Dictionary analysis.** 

Brand24 stores several thousand words related to emotions – both positive and negative. Each word has an assigned weight. In the first stage, Brand24 divides the content into sentences and analyzes each of them separately in terms of the presence of these words.

### **Stage two – Linguistic analysis.**

Implementation of language rules and context analysis is described in the first stage. The algorithm finding the word “good” should check if the word “morning” has not appeared before or after it, etc. The algorithm contains a lot of additional parameters, such as the distance of positive or negative words from the search subject. Only the qualified results (according to these parameters) are marked as positive or negative.

**So in this analysis/report, we are not stating, that Jira is better than Asana, or the other way around. We analyze the emotional tone of the posts of people writing them.**

## **TL: DR**

### **The most popular: Jira**

Undoubtedly Jira is the most popular Collaboration Software Tool. Almost 30% of all collected mentiones, were about Jira.

### **Most loved: ClickUp**

46% positive mentiones make ClickUp the most loved tool, second Asana has two times fewer positive mentiones. ClickUp has what it takes to make people love it.

### **The Controversial One: Jira**

Jira had 20.55% of negative mentiones which is the worst result, but… being the leader isn’t easy. There is a saying that “It doesn’t matter what they say about you, as long as they say it” or “there is no such thing as bad publicity”. 

## **Collaboration Software Tools, Sentiment Analysis Ranking**

### `The most-liked according to our sentiment analysis is….`

![Collaboration Software Tools, Sentiment Analysis: Summary](https://getint.io/wp-content/uploads/2022/04/Blog-post-summary.png "Collaboration Software Tools, Sentiment Analysis: Summary")

*\*Only for the following countries were taken into consideration: United States, Spain, United Kingdom, Germany, France, Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia,  Slovenia, Switzerland, Sweden, and Ukraine*

Now let’s dive more into details. Who is the most liked, and who has the most negative related mentiones? How many mentiones were there in total? Here is more in-depth comparison (again only some countries are taken into account here).

![Collaboration Software Tools, Sentiment Analysis: Selected countries](https://getint.io/wp-content/uploads/2022/04/Blog-post-1.png "Collaboration Software Tools, Sentiment Analysis: Selected countries")

Some of you may still wonder, how all the data looked like (even though they are less relevant). For those, here is the table below. As you can see, the volumes are much bigger. 

![Collaboration Software Tools, Sentiment Analysis Details (all countries)](https://getint.io/wp-content/uploads/2022/04/Blog-post-2.png "Collaboration Software Tools, Sentiment Analysis Details (all countries)")

### **ClickUp – the most positive mentiones**

The emotional tone of mentiones related to ClickUp was very positive: 46% when analyzing only some countries *(United States, Spain, United Kingdom, Germany, France, Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Switzerland, Sweden, and Ukraine – we did it because we weren’t 100% sure we filtered out all the noise from Asian, and African countries, where the keywords we use for analysis also mean totally different things – as described in the first part of the blogpost)*, and 38% when taking into account all of them. That’s a very good result. At the same time, the volume of mentiones was one of the lowest (3rd from the bottom). 

ClickUp is a relatively fresh tool (founded just 5 years ago), gaining market share, generating positive vibes around the product. We will see how it evolves.

### **Jira – the most popular one**

The biggest volume of mentiones was about Atlassian’s Jira. It’s the product that generated a lot of comments – both good and bad. About 17% of mentiones had a positive sentiment, while about 20% negative. What’s worth mentioning, is the fact that the sentiment could be negative, while it wasn’t because of the Jira itself (f.e. “I had such a bad morning, I’m late for work, and I feel terrible. Time to start my day with the Jira board”). So we can say that Jira is generating emotions 🙂 45% of all mentiones had some emotional sentiment, different that neutral.

### **Azure DevOps – the technical one**

Azure DevOps was last in our ranking, with only 16,89% of positive mentiones, and 8,45% of negative. The volume was very low, just 438 (and 5 298 globally). The possible reason? While all those tools are helping teams collaborate, they are addressing different target groups. ClickUp, Monday.com, Asana are used by all departments and are often preferred by the business side (Marketing, Product Owners, Sales). Those are the groups that are more active on social media, than developers, who are targeted by more technical Azure DevOps.

### **ServiceNow – positive/neutral**

ServiceNow is a strong player somewhere in the middle. Most of the mentiones with ServiceNow brand were neutral, 17,11% positive, and just slightly more than 2% with the negative sentiment. ServiceNow is a very expensive tool, targeting enterprises, and still, the number of mentions was second biggest, just after Jira. 

### **Asana – always second**

Second best, and second… worst. 33% of mentions with the Asana brand, had any sentiment, out of which 23,93% were positive, and 9,48% were negative. In terms of volume, Asana was 4th after Jira, ServiceNow, and Zendesk. 

### **Monday.com**

3rd place on the podium of the most positive mentiones. 4th in the negative ones, and also 4th when analyzing the volume of mentiones. 

### **Zendesk – the… stock one?**

This was a tough one – there were a lot of mentiones featuring Zendesk in February, but… just some of them were actually about the product. There was a big volume of mentiones related to Zendesk’s stocks. 

### **Most Twitter mentiones**

The most mentiones on Twitter were regarding Jira, then ServiceNow, Zendesk, Asana, ClickUp, Azure DevOps, and Monday.com. 

[Check out our integrations here](https://getint.io/integrations/)😎

Discover which collaboration software tool generates the most positive sentiment and popularity on social media, as analyzed by Getint.io using Brand24's sentiment analysis. See how Jira, Azure DevOps, ServiceNow, Asana, Monday.com, ClickUp, and Zendesk fare in terms of emotional tone and volume of mentions in selected countries. Find out why ClickUp stands out as the most loved tool, while Jira remains the most popular but also controversial one.

Collaboration Software Tools, Sentiment Analysis Report

### What’s new?

\
OpenAI's latest release, ChatGPT 4, boasts some impressive new features that are sure to excite tech enthusiasts and developers alike.\
\
1. With the ability to process up to 8 times as many words as the previous version, ChatGPT-4 can provide responses that incorporate greater context and handle larger text inputs. In addition to text inputs, GPT-4 can also handle image, audio and video inputs, paving the way for more sophisticated and diverse interactions with users.

![](https://lh3.googleusercontent.com/Ki811dIDpFiujsCoD7lkL7KqXC_eM5GY9DHnO2yHqhWGPkh7WF6sUpUgCzIAJUWAsstNkf6cYQwau4Fhy4mFU_auuwmbPuRJejDHcMUcKaTZGzRbqIVXP2u88_YrzbmLUpSaEjg6LAYLIk9pwESx4Q)



2. One particularly noteworthy feature of ChatGPT-4 is its ability to build websites from a simple image input. During a recent Developer Livestream, OpenAI demonstrated how the chatbot could take a handwritten sketch of a website and turn it into a fully functioning website that can even generate additional relevant content to fill the site.



3. It's also been [confirmed](https://blogs.bing.com/search/march_2023/Confirmed-the-new-Bing-runs-on-OpenAI%E2%80%99s-GPT-4) that ChatGPT-4 is the model behind the new Bing with ChatGPT. This collaboration marks a significant milestone in the development of natural language processing technology, and could have far-reaching implications for how we interact with search engines and other online tools.



Overall, ChatGPT-4's advanced capabilities and potential for cutting-edge applications make it a compelling tool for developers and tech enthusiasts alike. As we continue to explore the potential of AI and natural language processing, GPT-4 is sure to play a key role in shaping the future of digital interactions.

### How to access?

If you're interested in testing out ChatGPT-4, there are a few important things to know. First and foremost, access to this new technology will be limited at first. OpenAI has stated that only ChatGPT Plus users and developers using the ChatGPT API will be able to use GPT-4 initially.![](https://lh3.googleusercontent.com/yc5sDocp7vBDqKnEFJUiCYb_XMtjhvToM2mrtz6-XxHbjiJmnMikwE4BnDobOtOfyDiygMx5hJ1HtmBSy4QR99eZAZZYVcQ3TwPhi_HY-Bew9iSXV2Vvjrmb_W4Smz5XSdYqYRbDSWlMHstarC2gPw)

It's worth noting that there has been no official word yet on whether the free version of ChatGPT will receive an upgrade to GPT-4 in the future. However, given the significant improvements that GPT-4 brings, it's possible that many users may be interested in upgrading to the Plus version to take advantage of the enhanced capabilities.

### Use cases of ChatGPT-4

Right after the presentation, Conor Grogan, director of crypto trading platform Coinbase, dumped a live Ethereum contract into GPT-4, and it highlighted multiple security vulnerabilities and surface areas where the smart contract could be exploited.![](https://lh6.googleusercontent.com/NgetZZhf20Wc0CHI-vd9os14TsSrz37QL1oxlgVl9xWgmrjHM_GUTO-AkASjf8JsATqOZ0Tzf2ozdjW85UlvNH9EEkDCtM2UYwiHb8EFJ72tzDJfjXEJIInHBZQlU7vdAuKiYbhVbRawcECvgElnyg)

Also GPT-4 has already been put to the test in a [simulated lawyer's bar exam](https://www.forbes.com/sites/johnkoetsier/2023/03/14/gpt-4-beats-90-of-lawyers-trying-to-pass-the-bar/?utm_campaign=socialflowForbesMainTwitter&utm_medium=social&utm_source=ForbesMainTwitter&sh=583e58913027) and performed impressively, landing in the top 10 percent of test takers. This is a major step up from its predecessor, GPT-3.5, which scored in the bottom 10 percent. Additionally, GPT-4 has proven its mettle in other exams, such as SAT Math, where it achieved a score of 700 out of 800.

All in all, the versatility and adaptability of GPT-4 make it a promising tool for various natural language processing tasks, including chatbots, automated news writing, and creative writing. With its expanded word limit, image processing capabilities, and website-building functionality, GPT-4 is set to revolutionize the way developers and tech enthusiasts work with natural language processing technology. As OpenAI continues to improve its algorithms and make its technology more accessible, we can expect to see exciting new applications emerge in the coming years.

On March 14th, OpenAI introduced the new version of ChatGPT, their AI chatbot. The newly released GPT-4 language model has been making waves in the tech community, with many praising its significant improvements over its predecessor, GPT-3.5.  When is GPT-4 coming out? What features will be represented? Continue reading to find it out! 

Exploring the capabilities of ChatGPT 4

The game-changing features of OpenAI's ChatGPT 4

Trading used to be a domain for large-scale investors’ and funds’ activity, but things have changed today. A huge number of retail investors have entered the trading market recently, thus boosting the demand for intuitive, user-friendly trading apps. Automation is another driver for trading apps’ emergence and rapid innovation in the high-tech app world. 

Thus, the stock trading app market grew to [$13.6 billion in 2022](https://www.futuremarketinsights.com/reports/stock-trading-app-market) and is expected to move steadily to $89+ billion in 2032. These figures suggest that retail trading is here to stay, and the market growth of 20%+ a year is a huge business opportunity for forward-looking businesses today. 

So, once you’ve decided to build a robust, functional, and innovative trading app, the choice of the service provider is the key cornerstone of your success. Here’s a list of the top 7 companies I’ve hand-picked for your consideration to give your trading app project a smooth start in 2023.

## **Tips on Finding the Right Trading Software Development Agency**

The task of finding the right software developer for your business is challenging. The market is awash with companies claiming to be the best, while in reality, only a few of them can guarantee top-tier services and excellent software. To choose a genuinely reliable and professional company, you need to focus on the following criteria. 

* **Years in the industry**. Experience is vital when it comes to building trading apps in the modern hi-tech market. An experienced developer with many successful cases can give practical tips on choosing the best technology mix and features. Besides, well-established companies have standardized, smooth workflows, and working with them is more predictable regarding deadlines and quality.  
* **Online reputation**. You should choose companies with a solid online presence and a positive track record for software development. Reliable providers have nothing to conceal, so their clients and staff speak openly on social media and share their positive experiences. 
* **Number of staff**. It’s hard to plan a long-term partnership with a company that only has up to 10 employees or so. You never know what additional features or tech stack you will need in the process of upgrading your app, so it’s better to establish a working relationship with a large team of diversely skilled experts. 
* **Project portfolio**. It’s better to choose a company with a wide portfolio of trading app software projects. This way, you can ensure that the provider indeed has relevant expertise in trading app development and evaluate the real apps’ functionality and quality.
* **Client reviews**. You can check the company’s reputation and reliability by contacting its previous clients indicated on the website as satisfied partners. Checking whether they were indeed satisfied with the partnership and what positive and negative experiences they had will give you a better understanding of what to expect from working with a particular agency.

Once you double-check all the parameters mentioned above, you can be confident in the choice of your trading app development agency. Here are the top 7 companies I’ve selected using the screening checklist above.

## **Top 7 Picks for Trading Software Development**

So, what companies can deliver technically superior service and state-of-the-art trading software solutions in 2023? I sincerely recommend taking a close look at the following options.

### №1. RNDpoint

![](img/top-7-trading-software-development-companies-in-2023_1-scaled.jpg)

RNDpoint has been at the forefront of FinTech software development since 2014. The company employs a large team of experts with in-depth domain-specific expertise and delivers superior software engineering, integration solutions, DevOps, and team augmentation services.

**Year of foundation:** 2014 

**Headquarters:** London, UK 

**Key benefits**: The provider has been specializing in FinTech and banking software for almost a decade. So, it offers state-of-the-art trading software solutions by integrating innovative tools and technologies into the clients’ products. 

**Size:** 250+ employees 

**Major clients:** FICO, Breaking Equity, Loop Wallet, Danske Bank, First Abu Dhabi Bank, Teradata.

**Website:** [www.rndpoint.com](http://www.rndpoint.com/)

### №2. EffectiveSoft

![](img/top-7-trading-software-development-companies-in-2023_3-scaled.jpg)

This development agency has been in the development market for 20+ years and has a huge team of in-house staff exceeding 300 experts. It serves small, medium-sized, and large companies and specializes in tech products for healthcare, finance, and trading industries. The company possesses a Microsoft Gold Application Development certificate and complies with ISO 9001 and ISO / IEC 27001: 2013. 

**Year of foundation:** 2000

**Headquarters:** San Diego, CA 

**Key benefits:** The company has a large customer base and boasts 1,500+ completed projects in various business niches. Its team can create cutting-edge trading app solutions and deliver development, customization, and integration services for stock and crypto trading apps. 

**Size:** 300+ employees 

**Major clients:** Cityindex trading applications, trade execution system EdgeTrade, Cloud Call (cross-platform app as SaaS), BOSS™ instrument console, and Plato (a reporting app). 

**Website:** <https://www.effectivesoft.com/> 

### №3. Empirica

![](img/top-7-trading-software-development-companies-in-2023_4-scaled.jpg)

Empirica is a software development agency specializing in crypto trading and delivering top-notch solutions for crypto market participants. Its services cover crypto market-making software, provision of liquidity in crypto trading platforms, and support of new token listings.  

**Year of foundation:** 2010

**Headquarters:** Turku, Finland 

**Key benefits:** The company is focused on innovation and excellence, so it can deliver effective, trailblazing software for companies entering the crypto industry. Clients of any scale can turn to Empirica for software solutions relating to arbitrage, quantitative trading algorithms, ML and AI solutions for the crypto market, and any other data science, Web3, and blockchain software products. 

**Size:** 25+ employees 

**Major partners:** Coindeal, BitMEX, Bitpanda, Binance, FTX, Coinbase

**Website:** <https://empirica.io/>

### №4. Artezio

![](img/top-7-trading-software-development-companies-in-2023_5-scaled.jpg)

Artezio is a US-based software developer with 20+ years in the industry and 1,000+ award-winning projects. The company hosts a team of over 500 coders to cover its clients’ diverse software needs in the banking, finance, hospitality, and healthcare industries. Its present-day service range covers data analysis solutions, financial trading solutions, currency exchange software, and stocks and equities trading tools.

**Year of foundation:** 2000

**Headquarters:** Princeton, NJ 

**Key benefits:** Artezio has broad expertise in the trading software niche, as the company has dealt with traders and financial organizations. So, it can create custom-tailored trading platforms, mobile trading apps, and various kinds of trading software on demand. 

**Size:** 500+ employees 

**Major clients:** Illumina, InterSystems, RedHat, Xamarin, Sencha, etc. 

**Website:** <https://www.artezio.com/>

### №5. 4IRE

![](img/top-7-trading-software-development-companies-in-2023_2-scaled.jpg)

4IRE is a leading provider of blockchain, FinTech, and banking software development services with a global presence. It is an official integrator of NEAR protocol and partners with Stockholm Digital Finance and Stockholm Sustainable Finance Centre to develop innovative financial solutions.

**Year of foundation:** 2010

**Headquarters:** Tallinn, Estonia

**Key benefits:** 4IRE has a large team of development experts with a solid FinTech background. The company has many finance-related projects in its track record and offers a broad tech stack to design trading apps of any complexity. 

**Size:** 250+ employees 

**Major clients:** Aurora layer-2 protocol for Ethereum, Green Assets Wallet, Maitres, Aztec Protocol, Ondo Finance DeFi protocol. 

**Website:** <https://4irelabs.com/>

### №6. Softvelopers

![](img/top-7-trading-software-development-companies-in-2023_6-scaled.jpg)

Softvelopers has in-depth industry expertise in trading software creation and offers a wide range of AI/ML software solutions, trading robots, and full-scale trading platforms with multiple user-friendly features. The company is a trusted software provider in banking and finance, trading, logistics, and transportation. It also provides innovative software solutions for e-learning, education, and knowledge management businesses. 

**Year of foundation:** 2000

**Headquarters:** Boston, MA 

**Key benefits:** Softvelopers delivers top-tier software services and has a large team of 140+ in-house coders with a broad tech stack covering C++, Java, .NET, Node.js, PHP, and JavaScript. Its experts can create customized trading platforms, analytical solutions for professional traders, automated trading systems, and mobile apps covering Forex, stock exchanges, and cryptocurrencies. 

**Size:** 140+ employees 

**Major clients:** Ship-Ahoy, Digitalchemy, Access, and CityIndex. 

**Website:** <https://www.softvelopers.com/>

### №7. TradingSoft

![](img/top-7-trading-software-development-companies-in-2023_7-scaled.jpg)

The company has a wide range of software solutions for trading businesses, such as physical exchanges, prop shops, brokers, and FCMs. It can create advanced web, mobile, and desktop trading apps that cover all modern feature and functionality demands.

**Year of foundation:** 2012

**Headquarters:** Chicago, IL 

**Key benefits:** TradingSoft can provide for all trading software needs of businesses of all scales. Its experts handle software development (hedging, trading, infrastructure, and trading platforms for physical exchanges), set up the IT infrastructure for trading companies (hardware, colocation, connectivity, cloud, and software infrastructure integrations) and provide 24/7 maintenance and support. 

**Size:** 20+

**Major clients:** Zaner, One Exchange, Typhoon Forex Exchange for Peregrine Financial Group, EDF & Man, PRAXIS. 

**Website:** <https://tradingsoft.com/> 

## Conclusion

As you can see, the market is abundant in trading app developers who can deliver top-notch services without breaking the bank or undermining your deadlines. 

The trading industry is gaining immense popularity and witnessing an influx of retail investors, so the market potential of this niche is still immense. So, you can easily set up a stable revenue stream for your business by launching a safe, functional, and user-friendly trading platform or app. 

Once you’re ready to start the development work, I recommend contacting several companies to check their response speed, communication quality, and the offered pricing. This basic input will guide you in making the final choice and heading to your successful trading app. 

https://4irelabs.com/

If you’ve decided to build a robust, functional, and innovative trading app, the choice of the service provider is the key cornerstone of your success. Here’s a list of the top 7 companies to give your trading app project a smooth start in 2023

Top 7 Trading Software development Companies in 2023

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