To properly prioritize sought-after competencies and prepare your workforce for the coming challenges and opportunities, a data-driven approach is needed.  

According to the third annual Coursera’s Job Skills Report, which stands as a valuable reference for developing innovative skill strategies, there are 8 key fastest-growing skills for 2024: 

• Leading Teams with Empathy  
• AI-Related Skills for Increased Productivity  
• Cybersecurity and Information Security  
• Business Skills & Digital Marketing as Core 
• Data Visualization for Faster Decision-Making  
• Cloud Computing  
• Audit and Compliance Skills  
• Customer Retention 

Top Job Skills Driving Innovation in 2024: Overview 

Here’s a quick summary of the fastest-growing job skills in business, technology, AI, data science, and cybersecurity for 2024: 

Fastest-Growing AI Skills  

Estimates at Bloomberg Intelligence show the market for AI solutions is set to grow to $1.3 trillion over the next decade, while job listing site Upwork reported a 1000% increase in the number of generative AI job posts made in the first half of 2023.  

Not surprised? So are we. Explore below the fastest-growing AI skills enabling learners to build ML models, facilitate automation, and more.  

Cloud Computing  

Gartner expects the global cloud computing market to have skyrocketed from $490.3 billion in 2022 to $591.8 billion in 2023.  

It presents an exciting opportunity for businesses and job seekers, with cloud computing jobs being some of the most in-demand roles in the tech industry.  

Cybersecurity  

With the critical need to protect against growing numbers of cyberattacks worldwide and the increasing capabilities of AI creating new security considerations, investment in cybersecurity skills will benefit employees and institutions alike in the year ahead.  

There’s an estimated shortfall of more than 3.4 million cybersecurity workers. That figure is likely to climb, with employment of information security analysts expected to grow 32% from 2022 to 2032 in the United States alone. 

Audit and Compliance Challenged by AI Regulations 

Only 37% of HR leaders, in-house counsel, and executives guide employees in using AI tools.   

Meanwhile, data privacy and security rank as the top concerns of Chief Intelligence Officers regarding AI.  

With generative AI transforming productivity, it will be crucial to develop the capability of employees to review and evaluate an organization’s compliance.  

Customer Success 

Customer success and relationship management skills are among the top ten fastest-growing business skills.   

According to McKinsey, unlocking new revenues from existing customers accounts for 80% of value creation in leading growth companies.  

So, there is a burning need for businesses to navigate customer retention and expand the value delivered to both current and potential customers. 

Leadership   

“Manager effectiveness” is ranked as the top priority for HR leaders—and employees are facing change fatigue, with willingness to support organizational change collapsing from 74% in 2016 to 43% in 2022.  

To effect change, the leaders of tomorrow will need to be agile, compassionate, and able to keep individuals and businesses aligned.  

Data-Literacy as a Baseline Expectation for Employers  

Today, only 11% of employees are confident in their ability to read, analyze, work with, and communicate with data—showcasing the vast need for upskilling and learning.  

Institutional leaders recognize the need to respond, with 85% of C-suite executives believing that being data-literate will be as vital in the future as the ability to use a computer is today.  

So, data visualization with the help of business intelligence software also joined the top of the fastest-growing skills.  

Digital Marketing   

The rapid growth of the global advertising and marketing industry, which is expected to rise to $1.5 trillion in 2030, illustrates the spurred demand for digital marketing skills. In the US alone, employment in digital marketing-related professions is projected to grow rapidly up to 2032.  

Meanwhile, shifting consumer behaviors—powering trends like increased social selling—with 76% of people making buying decisions on social media—call for upgraded skills from digital marketers.  

To adapt to a new paradigm, organizations should invest now in equipping learners with the skill sets to deliver modern marketing strategies. 

Your Workforce Check  

By addressing these questions, you may check if your organization has the right skills.  

Strategic Alignment:  

• Which job skills are most critical for achieving your business goals and strategic initiatives?  
• How do these skills differ across departments and levels within the organization?  
• Are there any skills gaps that could hinder our progress, and how can we address them?  

Talent Acquisition & Retention:  

• How can we attract and retain top talent who possess these critical skills?  
• What are our competitors doing regarding these skills, and how can we compete effectively?  
• How can we develop and upskill our workforce to meet these changing demands?  

Future-Proofing the Organization:  

• What emerging technologies and trends might impact the skillset we need in the future?  
• How can we invest in skills that will remain relevant and valuable in the long term?  
• What kind of culture and learning environment do we need to foster continuous skill development? 

How to Find and Hire Sought-After Specialists with Digital Mindsets in 2024 

While a business-driven digital mindset is critical for increasing competitive advantage, leaders need well-established best practices to find and onboard it or unlock it in current employees.  

Wherever you are on your digital journey, we’re ready to help. Our experts can support you with extracting your potential to transform, innovate, and grow by:    

• Delivering digital mindset—the only one that can help with innovation: technical expertise ensures your digital programs and processes are up to date and as efficient as can be.  
• Integrating top talents with your current team through the Remote In-Sourcing® model.  
• Forming the most efficient distributed teams through the just-right Team Formation methodology. 

With a digital mindset, you’ll ask the right questions, make smart decisions, and appreciate new possibilities for a digital future. Leaders who adopt advanced approaches will be able to develop their organization’s talent and prepare their company for successful and continued digital transformation. 

Feel free to connect with our experts to discuss your unique needs and what it really takes for your business to thrive in the age of data, algorithms, and AI.  

Summing Up  

All in all, companies looking to boost competitiveness in 2024 have a wealth of opportunities:  

• Make data-driven decisions while identifying priority skills.  
• Invest in upskilling and reskilling of your workforce. 
• Embrace automation and AI with qualified audit, cybersecurity, management, and marketing professionals on board. 
• Rely on a trusted technology partner to help you source and acquire sought-after specialists with Digital Mindsets. 

The post Futureproof Your Organization with Digital Minds: Top Job Skills Driving Innovation in 2024 appeared first on Intetics.

As we bid farewell to this remarkable year, it’s impossible to ignore the exhilarating journey of technological breakthroughs that have unfolded before us.

While AI certainly stole the spotlight, it wasn’t the sole hero of this tale. Generative AI models took center stage, captivating industry giants and innovative newcomers.   

However, the 2023 revolution extended far beyond just AI; Web3, AR/VR, and quantum computing emerged as catalysts, propelling generative AI into uncharted territories and promising an exciting future filled with endless possibilities.   

Join us on a journey through the top innovations of 2023, a year that redefined the IT industry and offered a glimpse into the tech-driven world of tomorrow tailored to your needs and interests. 

I. ChatGPT: Impacting Industries and Shaping the Workforce

ChatGPT, despite technically being launched in November 2022, became the standout narrative of 2023. The key breakthrough lay in ChatGPT’s ability to humanize technology. Unlike traditional search methods requiring specific phrases, ChatGPT responded to natural language.  

Now, it’s transforming industries, including software development, and raising questions about its impact on jobs as it takes over tasks once done by humans. 

Evolution and Advancements 

Over the past year, ChatGPT has learned to adapt to a range of user needs, from writing emails to enhancing resumes and even supporting the creation of businesses.  

At the start of 2023, there was only a free version with text-based responses available.  

Now, users can subscribe to ChatGPT Plus to access the latest version, ChatGPT-4. 

According to OpenAI, ChatGPT-4 has seen improvements in training on more data, generating fewer errors, and understanding nuanced instructions.  

A notable addition is its ability to “see, hear, and speak,” which allows subscribers to have voice conversations and share images for ChatGPT to process. For example, they can take a picture of a flower and ask about its type and care instructions. 

At the core of ChatGPT’s prowess are Large Language Models, and OpenAI’s GPT-4 served as the driving force. The LLM landscape expanded in 2023 and featured newcomers like Google’s Gemini LLM (empowering Bard, a ChatGPT competitor) and others, including Meta’s Llama 2 and Amazon’s Olympus. 

Google programmer Kenneth Goodman tested ChatGPT on examinations; it scored 70% on the US Medical Licensing Exam and a legal Bar Exam. It also did well on other tests—78% on a high school chemistry exam and reached the 40th percentile on the Law School Admission Test. 

The Use of ChatGPT in Software Development Tasks 

One key advantage of ChatGPT for developers is its ability to comprehend and execute precise coding instructions. Developers can articulate the purpose, parameters, and expected outcomes of their tasks in a conversational manner. They can also engage ChatGPT in a dialogue to explore various AI libraries and coding resources.  

Read also: ChatGPT for Software Developers: Better Code, Increased Productivity, and Premier Product Quality [With Examples of Prompts] 

ChatGPT as the Biggest Fear in Replacing the Workforce 

2023 was full of debates about work replacement. Can ChatGPT replace developers, for example? Not in the present moment, or at least not as of now.  

ChatGPT operates at the proficiency level of a skilled first-year programming student with a tendency towards idleness. The tool makes coding easier for programmers and saves time, especially for those with less experience; however, it can’t handle complex projects on its own now.  

However, the chatbot’s capabilities have exceeded expectations. According to Google, the search engine would consider hiring the bot as an entry-level coder based on its performance. Moreover, according to a recent study by Goldman Sachs, generative AI tools may impact around 300 million full-time jobs globally. 

Anu Madgavkar, a partner at the McKinsey Global Institute, emphasized seeing these tools as helpers for productivity, not total replacements. She also highlighted the need for a careful approach to using them. 

II. First AI Legislation in the US

The surge in popularity of ChatGPT was followed by concerns about AI’s impact on jobs, misinformation, and its potential intelligence, and this has led to regulatory efforts. In November 2023, President Biden issued an executive order introducing the first set of rules for AI systems in the United States.  

The regulations require rigorous testing for advanced AI products to prevent their misuse in biological or nuclear weapons. Also, to address fears of AI-generated deep fakes and disinformation, there are recommendations (though not requirements) for watermarks on AI-generated photos, videos, and audio. 

For now, these rules apply only to American companies. To overcome this, the US administration is urging other countries, both allies and adversaries, to adopt similar regulations. The European Union’s AI Act was finally agreed in December. 

III. New AI-Driven Marketing and Design: Midjourney, Genmo, and AI Podcasts

In 2023, AI-based text-to-image generators like Midjourney, Genmo, DALL-E, and Stable Diffusion reached new levels of realism. This led to a wave of viral AI-generated photos, like a Midjourney-generated image of Pope Francis in a white puffer coat. What this showed to industry professionals and the public is that creating viral marketing campaigns could now be done with just a few prompts. 

There was also an interesting case of Coca-Cola collaborating with OpenAI and launching the Create Real Magic campaign, inviting consumers to create Coke-related artwork using generative AI. 

In the podcasting space, text-to-speech systems convert written content into natural-sounding audio. The first AI-generated podcast that gained traction took a unique approach — it used the cloned voice of popular podcaster Joe Rogan. The Joe Rogan AI Experience simulated conversations between AI Rogan and fake guests like OpenAI CEO Sam Altman and former President Donald Trump. 

Despite its AI nature, the episode garnered over half a million views on YouTube, with some listeners overlooking its artificial origin. It’s unclear, though, whether people’s initial interest was just because it was something new and different or a lasting attraction.

IV. Growth of AI Assistants

2023 was also the year of AI assistants. Microsoft is investing heavily in gen AI tools to transform how users engage with Windows PCs using the AI assistant. 

The idea is simple: with just one click on the taskbar, more than half a billion Windows 11 users can use Copilot for various tasks, like creative support in Microsoft 365, shopping advice on Edge, and meeting summaries on Teams. No third-party application or extension is needed. 

MIT Technology Review already reports that if you asked a group of computer science students or programmers if they used Copilot, many would raise their hands. According to Iansiti, a Keystone Strategy co-founder, professor at Harvard Business School, and one of the interviewees, Copilot and similar tools might add $1.5 trillion to the global economy by 2030. 

Though it’s a rough estimate, Iansiti thinks the actual impact could be even larger. On the one hand, companies could obtain more code for less money. On the other hand, they could expect more people to become coders because these tools make it easier to get into software development. 

For example, Intetics has adopted AI in its teams and uses it for tasks like development, testing, business analysis, UI/UX design, and management, including talent acquisition and talent management. This confirms the growing recognition of AI’s transformative impact on business functions. 

V. Interest and Practical Applications of Digital Twins

Digital twins, virtual replicas used to simulate real-world behavior, are proving invaluable and notably reduce time to market. McKinsey reports revenue increases of up to 10% through customer-focused digital twins. Daimler’s customer twins, that allow virtual “test drives,” are a perfect example of this. 

Mercedes-Benz and Daimler Truck are digitizing their entire automotive value chain, which sets the stage for the future of manufacturing. Their breakthrough solutions are set to enhance data flow, reduce costs, and boost operational agility. 

Several other developments were showcased at SPS 2023 by AWS Partners, including:  

• Bosch demonstrated an Integrated Asset Performance Management solution using AI/ML to prevent asset failures and reduce unplanned downtime. 
• Software AG can now help equipment manufacturers build digital twin platforms for connected machinery. These allow manufacturers to create precise digital representations of their asset fleets and incorporate real-time performance data. 

VI. Metaverse for Enterprises: A New Platform for Leads Generation, Sales & Marketing, Events, and HR

The metaverse is enhancing the ongoing trend of personalized user experiences driven by mobile internet. Consumers are expected to use the metaverse as an advanced virtual space to enrich their real-world experiences. 

In 2023, businesses became better at harnessing the potential of the metaverse as the preferred digital realm for consumer engagement. For example, TCS, a major IT service provider, is investing in its metaverse project, ThemaTICS, and aiming to create immersive experiences in areas like e-commerce and workplace training. Nike is doing Nikeland, a “micro metaverse” within the Roblox ecosystem. And there is more to come. 

Like any evolving trend, the move to the metaverse will unfold gradually and continually, without a clear start or end point for the metaverse era. 

VII. AR and VR Experiences: Apple Vision Pro

Generative AI amplifies the potential of AR and VR and leads to better products as a result. The game-changer this year was Apple’s headset. 

Apple’s Vision Pro headset was unveiled at the Worldwide Developer Conference after seven years of development. The project is described not as a mobile device but as a “spatial computer.” 

Despite its $3,500 price tag and limited initial audience, the Vision Pro is anticipated to open the door to a new level of mixed reality experiences. ZDNET’s Editor in Chief, Jason Hiner, left WWDC convinced that Apple’s breakthroughs would redefine the next decade. It became available for purchase on February 2, 2024, in the United States. A worldwide launch has yet to be scheduled.

VIII. Hyperautomation

The term Hyperautomation, referring to a methodical, business-centric strategy, was first coined by Gartner in 2020. So, it isn’t new. The key change from previous years to 2023 is that hyperautomation is speeding up. There is an increasing shift towards digital-first strategies, which is why IT teams are dealing with a surge in processes and data, and they need automation more than ever.  

Boris Krumrey, UiPath’s Global VP of Automation Innovations, highlighted in a recent talk with Technology Magazine that AI-powered automation is going through a big change with the introduction of generative AI. Krumrey believes that when generative AI collaborates with automation, it brings revolutionary benefits to businesses and ushers in a new era of efficiency and innovation. 

IX. Quantum Computing

McKinsey estimates that by 2030, there will be around 5,000 operational quantum computers. Despite their limited number, Quantum AI is believed to be one of the key reasons quantum computers stand out from the computers we use today. So, what happened in the field in 2023? 

IBM introduced the Heron processor at its Quantum Summit, and the product featured architecture designed to provide the highest performance and lowest error rates among all its quantum processors. Additionally, IBM presented the Quantum System Two, its first modular quantum computer, located in Yorktown Heights, New York. The system operates with three IBM Heron processors and control electronics. 

UC Berkeley, Harvard University, University of Cologne, University of Washington, Argonne National Laboratory, The University of Tokyo, Fundacion Ikerbasque, Qedma, Algorithmiq, and Q-CTRL all focus on the potential of large-scale quantum computing. This goes beyond solving problems native to quantum computing, as they’re also figuring out how to combine quantum and classical systems. 

Recent breakthroughs in AI have brought new energy and optimism to the tech industry, and some would even say they’re filling a void from previous years. 

Think about this: ChatGPT has over 100 million active users, and even C-suite executives personally leverage gen AI tools for work. Ignoring or dismissing gen AI as a passing trend is no longer an option.  

Extend your business opportunities with advanced solutions and stay tuned with Intetics, AI-First SoftDev Company. 

The post 2023: IT Revolution–Top Innovations That Redefined the Industry appeared first on Intetics.

Conversational AI is a highly lucrative technology for enterprises, helping businesses prevent customer attrition, enhance experience, and become more profitable.   

While AI-powered chatbots and virtual assistants are the most popular forms of conversational AI, many other use cases exist across industries.    

Discover business applications, benefits, and strategies for implementing Conversational AI within an organization, peer-reviewed by the global academic community.   

Conversational AI for Business Success: How to Amplify Artificial Intelligence 

On January 4, Pavlo Yalovol, Intetics VP of Innovation, presented the scientific paper ‘Conversational AI for Business Success: How to Amplify Artificial Intelligence’ written by Boris Kontsevoi, Intetics CEO and President, at the virtual stage of the eighth edition of International Conference on Information System Design and Intelligent Applications (ISDIA). 

Read also: AI-Powered Coding Assistants—Friend or Foe for Developers? Pavlo Yalovol, Intetics Vice President of Innovation for ITID Lviv 

The ISDIA 2024 conference brought together researchers, scientists, engineers, students, and industry practitioners to exchange theories, methodologies, new ideas, experiences, products, and applications in all areas of intelligent computing methodologies. Participants explored how AI, ML, and other innovative technologies enhance and safeguard our interconnected world.  

Get a glimpse of the key presentation insights, and feel free to access the full paper by reaching out. 

AI in Action: Advancements, Capabilities, and Transformative Benefits 

Conversational AI and virtual voice assistants with natural language processing (NLP) and machine learning under the hood have emerged to simplify daily routines by handling tedious, time-consuming, or complex tasks. NLP deciphers human language, while ML enables learning from data, making these technologies proficient in human-like interactions.  

The adoption of AI experienced a 10% surge from 2021 to 2023, attributed to the proactive efforts of IT professionals. Projections indicate a substantial annual increase of 38% in the global AI market value from 2022 to 2030.   

Recent research by McKinsey highlights the financial advantages of incorporating conversational AI, positioning companies with a competitive edge, and driving heightened investments in AI development. 

Conversational AI’s Potential across Industries 

AI-driven chatbots and virtual assistants enable seamless conversations, automate mundane tasks, and gather valuable customer insights across Healthcare, Finance, E-commerce, Education, and other industries:

Featured Case Study: AI-Powered Virtual Nurse Helps Over 100,000 Patients Worldwide to Monitor Their Health Daily 

Advancements in NLP: Models & Algorithms 

Recurrent neural networks for generating word sequences enable tasks like text prediction, handwriting recognition, and speech recognition. Explore the newer NLP models, which can answer intricate research questions and process information across multiple languages. 

Different Types of NLP Models 

There are four key neural network architectures:  

• Feedforward Neural Networks (FNNs): Process data unidirectionally from input to output. Suited for tasks without sequential/temporal dependencies. Applied in classification and regression.  
• Convolutional Neural Networks (CNNs): Ideal for grid-structured data like images. Use convolutional layers to detect patterns. CNNs are used in image recognition and object detection.  
• Generative Adversarial Networks (GANs): Composed of a generator and discriminator network. The generator creates data; the discriminator differentiates from accurate data. GANs are employed in image generation and data augmentation.  
• Recurrent Neural Networks (RNNs): Designed for sequential data processing. Feedback loops allow the learning of patterns in sequences. RNNs are applied in language processing and time series analysis. Challenges like vanishing gradients are addressed by LSTM and GRU variants. 

The Ethical and Reliability Challenges of AI 

Discover core challenges faced by conversational AI that businesses should be aware of: 

• Understanding Context: AI may struggle with broad contexts and subtle nuances, leading to misinterpretations.  
• Data Bias Risks: Reliance on incomplete or biased training data can lead to skewed and unfair interaction outcomes. 
• Human Oversight Necessity: Expert review is essential to mitigate risks of unexpected consequences from AI autonomy.  
• Vulnerabilities to Exploitation. AI systems can be exploited for disinformation and propaganda. 
• Consumer Trust. McKinsey survey reveals high consumer trust in AI, often surpassing human expertise. 
• Realism and Validation. AI should not be the sole decision-making tool; rigorous human testing and validation are crucial. 

NLP API Options: A Look into Leading Choices 

There are various APIs (Application Programming Interfaces), which encompass a range of functionalities, including sentiment analysis, entity recognition, text categorization, language detection, text generation, and more.  

Therefore, when selecting an API, several key factors should be taken into consideration: customization and control, complexity of use case, platform compatibility, and integration ease. Some of the prominent NLP APIs are OpenAI GPT, Google Cloud Natural Language API, Google Dialogflow, Amazon Comprehend & Lex, IBM Watson NLU & Assistant, Microsoft Azure Cognitive Services, Wit.ai, spaCy, Algorithmia, and others. 

Key Steps to Developing a Successful Conversational AI Business Model 

Formulating a successful conversational AI business model implies these crucial steps:  

• Defining the niche. Identify a specific domain where conversational AI solutions can provide value. The niche should align with the expertise of the business and cater to a genuine market need.  
• Creating a high-quality product. The product must possess natural communication, complex query understanding, accurate responses, and scalability.  
• Leveraging NLP tools. Integrating NLP enhances the AI’s ability to engage with users intuitively.  
• Integration with existing systems. Seamless integration with established business systems (CRM, ERP, help desk software, etc.) bolsters the AI’s capabilities and elevates the overall customer experience.  
• Developing a go-to-market strategy. This strategy should encompass the following elements: target audience definition, needs and preferences analysis, and marketing plan.  
• Monitoring and optimization. Utilize analytics tools to glean insights from customer inquiries and employ these insights to drive continuous improvements that enhance system performance. 

Conversational AI can enhance lives when used appropriately and aligned with user expectations. Here are a few examples and numbers:  

• Business Process Optimization. Up to 25% cost reduction and 30% productivity growth with record management, task management, auto-scheduling, email filtering, and fast onboarding and training powered by CAI.  
• Enhanced Decision-Making. Up to 95% of information accuracy thanks to easy report generation, advanced analytics, and smart recommendations.  
• Advanced Customer Interactions. Customer satisfaction increases by up to 50% with service/product recommendations, intelligent comparison, and a robust sales funnel.  

Successful implementation demands meticulous planning, experimentation, and continuous monitoring to achieve desired outcomes.  

Are you considering starting to plan and implement conversational AI technologies for your niche? Get started with advanced approaches and industry solutions now. 

More about Conversational AI Business Applications: 

• Conversational AI. The New Era of Human-like Automated Communication. 
• AI Transforming Healthcare Solutions with Conversational Intelligence in Medical Virtual Assistants 
• Chatbot Center of Excellence: Chatbots Turnkey Development 

The post Conversational AI for Business Success: Peer Reviewed Strategy to Build Profitable AI Model [Paper Presentation at ISDIA 2024] appeared first on Intetics.

But! Copilot may not be a one-size-fits-all solution. Different developers have different preferences, workflows, and needs. Recognizing this diversity, let’s explore alternative tools that offer similar code completion features (and more). 

Quick Intro to Useful Alternative Plugins to GitHub Copilot 

We’ll delve into three notable alternatives of GitHub Copilot: Tabnine, AWS Codewhisperer, and Bito.  

Before diving into the distinctive features of each tool, here’s a quick look at what each one brings to the table: 

Tabnine 

Tabnine was an early player in terms of code completion tools, and it provides a practical plugin compatible with your preferred code editor. It offers suggestions for whole lines of code and full-function completions across various languages, libraries, and frameworks. And it does so based on natural-language comments. 

One noteworthy aspect of Tabnine is its efficiency with minimal context compared to Copilot. It suggests code midline as you type, without waiting for one line to be finished before moving to the next.  

For teams and organizations, Tabnine offers the capability to host and train their own AI models. This feature facilitates collaborative autocompletion across IDEs, which enhances teamwork and contributes to code security. 

Beyond code completion, Tabnine tackles unit test support. Using advanced AI, it automatically generates unit tests for your code, a helpful feature for ensuring thorough testing and code stability, especially on larger projects. 

The interface is user-friendly, requiring minimal configuration. As you use it more, Tabnine adapts and tailors unit test suggestions to your coding style.  

AWS CodeWhisperer 

Amazon CodeWhisperer understands natural language comments in English and offers suggestions ranging from snippets to entire functions—up to 10–15 lines—in various IDEs. Similar to Tabnine, CodeWhisperer adapts to your coding style and ensures a personalized coding experience. It also extends its capabilities to the command line with inline documentation and AI-driven natural-language-to-code translation.  

For those leveraging AWS services, CodeWhisperer analyzes code in real time, with suggestions tailored to AWS APIs like Amazon EC2 and AWS Lambda and aligned with best practices for cloud-based projects. 

To ensure responsible coding, the tool introduces a reference tracker for open-source code. This feature flags suggestions resembling public code with detailed annotations for review. The goal here is to actively avoid biases in code suggestions. 

If you’re choosing between AWS CodeWhisperer and Tabnine, consider what you prioritize. Let’s say you value versatility and broad language support across various editors; then Tabnine is your pick. CodeWhisperer, on the other hand, is for those who focus on precision — the tool learns from in-house code and tailors suggestions to an organization’s practices. 

Bito 

Bito allows users to generate code in any language, create comprehensive test cases, and gain insights into selected code snippets with the Explain Code feature. For documentation, Bito offers a Comment Method tool, while the Improve Performance feature provides tips for enhancing code efficiency. Security concerns are addressed through the Check Security function, which lets you inquire about potential issues.  

What sets Bito apart from GitHub Copilot is its integration with Visual Studio Code — it leverages embeddings and a vector database to understand your local codebase. This ensures context-aware suggestions, a distinctive advantage over Copilot. 

Another noteworthy feature is the Generate Unit Test Shortcut:  

The shortcut allows developers to efficiently generate test cases for different code paths and scenarios. This ensures comprehensive testing coverage and reduces the risk of undetected bugs.  

The consistent testing standards promoted by Bito foster collaboration and codebase maintainability within development teams, as all members can adhere to the same testing practices.  

On Ethics for AI Code Completion Plugins in Software Development 

Respecting intellectual property rights and privacy is crucial for ethical software development, fostering trust in the industry.

Developers using code completion tools like Tabnine, Bito, etc. should: 

• ensure that sensitive or confidential data is not intentionally or unintentionally exposed, 
• be mindful not to breach non-disclosure agreements (NDAs), 
• seek explicit consent from clients or stakeholders before employing coding assistant tools in projects involving their codebases. 

On the level of software development organizations, it’s a best practice to regulate AI tools usage in processes. Many responsible engineering companies already create and implement AI tools usage policies for employees on how to be safe and secure when using generative AI, especially when it involves the sharing of potentially sensitive company and customer information. 

Summing Up

The implementation of AI assistants like Tabnine, AWS CodeWhisperer, and Bito has resulted in tangible time savings and enhanced productivity. And we have the numbers to back this up. 

In just two weeks, Tabnine contributed to a nearly 13-hour timesaving for an Intetics engineer. That month, 27% of that engineer’s code was produced by the tool.  

With AWS CodeWhisperer, the official figures claim a 57% acceleration in developer productivity and a 27% increase in the likelihood of project success.  

As for Bito, the subjective experience reveals improvements in speed, particularly in implementing new features. The initial estimate suggested a potential 27% code contribution, but real-world results prove a more conservative productivity boost of 10-20%. Also, Bito offers remarkable efficiency, potentially saving up to 80% of time spent on writing unit tests.  

To wrap it up, embrace the tools that empower you to code better and faster. 

Featured materials: 

• ChatGPT for Software Developers: Better Code, Increased Productivity, and Premier Product Quality [With Examples of Prompts]
• Why GitHub Copilot Is the Ultimate Game-Changer for Software Developers
• AI-Augmented Project Management: 15 Ways to Automate Time-Consuming Tasks with ChatGPT [+12 Other AI Assistants]

The post Alternatives to GitHub Copilot: Tabnine, AWS CodeWhisperer, and Bito to Increase Developers’ Productivity by 20% appeared first on Intetics.

Let’s break it down and see why it’s a handy tool for programmers to speed up the coding process, learn new frameworks or libraries, or explore different ways of solving problems.  

What Is GitHub Copilot? 

GitHub Copilot is an AI pair programmer providing auto-complete style recommendations as you code. It accelerates your coding process by analyzing contextual elements like variable names, surrounding code, and function signatures, generating relevant suggestions in real time.  

The concept of an “AI pair programmer” underscores its collaborative nature, emphasizing that it complements and augments your coding efforts—it cannot work without you. 

GitHub Copilot is powered by a generative AI model developed by GitHub, OpenAI, and Microsoft. 

Once installed, the coding assistant analyzes the developer’s code, providing suggestions for completing code snippets, suggesting relevant functions, and even refactoring existing code. 

Read also: ChatGPT for Software Developers: Better Code, Increased Productivity, and Premier Product Quality [With Examples of Prompts]

Installing GitHub Copilot: Step-by-Step Guide 

GitHub Copilot integrates with various popular integrated development environments (IDEs), such as Visual Studio Code, Visual Studio, Neovim, and JetBrains IDEs.  

GitHub Copilot can be accessed through personal accounts with GitHub Copilot Individual or organizational accounts with GitHub Copilot Business. GitHub Copilot is free for verified students, teachers, and maintainers of popular open-source projects. 

You can try GitHub Copilot for free with a one-time 30-day trial. After the free trial, you will need a paid subscription for continued use. Billing plans are available at GitHub Docs. 

To get started, you’ll need the following: 

• An active GitHub Copilot subscription; 
• Microsoft Visual Studio Code (or another preferred IDE); 
• The GitHub Copilot extension installed in the Visual Studio Code. 

How to Install GitHub Copilot? 

• Find the GitHub Copilot extension page in the Visual Studio Code Marketplace and click Install. 
• Click Open Visual Studio Code in the pop-up window that appeared.  
• Click Install in the “Extension: GitHub Copilot” tab in Visual Studio Code.  
  • If you have not previously authorized Visual Studio Code in your GitHub account, you will be prompted to sign into GitHub in Visual Studio Code.  
  • If you have previously authorized Visual Studio Code for your account on GitHub, GitHub Copilot will be automatically authorized.  
• If you don’t get the prompt to authorize, click the bell icon in the bottom panel of the Visual Studio Code window. 

• In your browser, GitHub will request the necessary permissions for GitHub Copilot. To approve these permissions, click Authorize Visual Studio Code.  
• To confirm the authentication, in Visual Studio Code, in the “Visual Studio Code” dialog box, click Open. 

GitHub Copilot can be customized to align with your coding style. Configure settings like indentation, line length limits, and suggestion verbosity to make Copilot an extension of your coding preferences. 

Creation of UI Elements with Prompts in GitHub Copilot 

GitHub Copilot’s capability to generate code suggestions extends to creating user interface (UI) elements. By providing clear and concise prompts, developers can elicit relevant code snippets for various UI components, such as buttons, dropdown menus, and text fields.  

Example: We need to create a tracker of monthly income and expenses.

Let’s generate a prompt for GitHub Copilot: 

<!–bootstrap grid with 12 rows and 1 column for small screens, and 6 rows and 2 columns for medium screens and above, each cell contains label of the month from January to December, and 2 bootstrap number inputs side by side with labels, 1 for income and 1 for expenses –>) 

Based on the input, GitHub Copilot starts to suggest the code to generate the desired output. 

To accept the suggested code, just press Tab, and the assistant will write the code. 

It’s crucial to understand that Copilot isn’t flawless enough to write code independently, as we highlighted earlier, its “pair programmer” nature. You are responsible for crafting the overall logic, guiding the tool with well-thought-out prompts, and overseeing the suggestions it generates. You steer the process through practical and precise instructions while the tool accelerates the code-writing process for you.  

So, after a brief review, the developer reviews and improves the proposed structure and creates the desired table faster. 

GitHub Copilot proves to be a valuable tool for frontend developers to elicit relevant code snippets for various UI components efficiently. The example illustrates the importance of reviewing Copilot’s suggestions by an experienced developer to ensure correctness and code optimization.   

While Copilot accelerates the code-writing process, user intervention remains essential for ensuring logic, accuracy, and adherence to specific requirements. Let’s focus on how to engineer prompts that guarantee Copilot’s efficient assistance. 

Getting Desired Outcomes with Prompts: Best Practices 

Once we have reviewed the capabilities to generate entire functions, classes, or blocks of code faster, let’s touch on the best practices for prompt engineering to give clear instructions to GitHub Copilot and generate desired results. 

• High-level context in comments: Provide high-level context in a comment at the top of the file and leave more detailed instructions in the form of comments and code. 
• Provide specific details: For precise code suggestions from GitHub Copilot, provide specific details. If you aim, for example, to fetch data from an API, specify the type of data, processing method, and the target API endpoint. 
• Provide examples: Apart from instructing GitHub Copilot verbally, you can also demonstrate desired actions using examples in your preferred coding style.  
• Iterate and refine: Continuously refine your code with Copilot’s suggestions. Start with its recommendations and customize them to meet your specific requirements. Regularly review and adjust the generated code to match your coding style and project needs. 
• Validate generated code: Validate Copilot-generated code for correctness, efficiency, and adherence to standards. Conduct thorough code reviews, run comprehensive tests, and make necessary adjustments to maintain codebase quality. 

In turn, GitHub is experimenting with LLMs to evolve Copilot, focusing on creating a developer-friendly AI experience that is predictable, tolerable, steerable, and verifiable to enhance overall productivity and effectiveness. All this is done to extend GitHub Copilot across the developer lifecycle. 

Other Ways to Enhance Your Coding Workflow with GitHub Copilot 

Explore additional capabilities of GitHub Copilot to refine your coding process:  

• Code refactoring: GitHub Copilot aids in refactoring by suggesting concise and efficient alternatives, identifying redundancies, simplifying complexity, and recommending improved coding patterns for cleaner, more maintainable code.  
• Error & exception handling: Copilot assists in error handling by suggesting mechanisms and blocks for exceptions, enhancing code robustness and resilience to unexpected scenarios.  
• Customization: Enhance GitHub Copilot by customizing its training with your codebases, allowing it to generate more accurate, context-aware suggestions tailored to your specific application domain.  
• Consistency across teams: GitHub Copilot is valuable for team development, aiding in maintaining coding standards by suggesting consistent styles and practices. Its suggestions are discussion starters in code reviews, fostering collaboration, and knowledge sharing among team members. 

Summing Up 

It still requires profound expertise to build software. Even with Copilot’s help, a developer should verify and understand generated code. Non-programmers can’t jump on Copilot and make whatever they want. Or is it so yet?   

Keep a keen eye on the dynamic AI assistant’s landscape—experiment with emerging options in your environment to identify the ones that align best with your requirements. Explore tools like GitHub Copilot, and stay tuned to learn more about alternatives: Bito, Amazon CodeWhisperer, Tabnine, etc.  

Join us to empower developers to be more productive at every stage of the software development lifecycle. 

The post Why GitHub Copilot Is the Ultimate Game-Changer for Software Developers appeared first on Intetics.

Here is a fairy tale inspired by this dream. Dreams should come true, and stories should have happy endings that continue…not just in our time, but in the hearts of generations to come, and their generations to come.  

The secret Red Botanic Garden stands at the heart of this tale about a white lion and his cub, Leo, and makes the impossible possible. 

It’s an incredibly great Fairy Tale. AI is like a superpower, but the magnitude of its potential in the future is beyond imagination.

Boris Kontsevoi President and Founder

The concept and the video production is fully realized by Intetics Digital Marketing Team using AI technologies.

This story is a testament to the incredible possibilities of new technologies for creativity, design, and marketing. Just yesterday, it was impossible to create something like this on our own. At Intetics, AI has become an everyday tool for our team. However, with exceptional expertise in the domain, creating such a project solely with AI is possible. Thanks to Boris for sharing the idea for inspiration and my designer for daring to bring this project to life. This fairy tale is a gift for Boris`s Birthday that became, at the same time, a gift within a gift – for adults, children, and their children. I hope each of you will find something meaningful within it.

Irina Dubovik, Digital Marketing Director

The video is made by the Intetics team with AI:
1. Voice – Boris Kontsevoi, CEO and Founder
2. Author and project manager – Irina Dubovik, Digital Marketing Director 3. Design and Production – Dmitry Mokhar, UX/UX Designer

The post The Story of the Red Botanic Garden: AI Fairy Tale Inspired by Intetics Founder’s Startup Dream appeared first on Intetics.