Technology

Artificial intelligence: what is it and how is it evolving?

Published

3 weeks ago

September 8, 2023

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Artificial intelligence (AI) is today a sensitive topical subject and at the heart of numerous debates, documentaries and controversies. The reason is simple: It is disrupting all professions directly or indirectly linked to IT.

To better understand this concept and use it to your advantage, you must first study it in depth. To this end, this article provides you with everything you need to know about the concept of artificial intelligence and its various implications.

In addition to presenting the history of this concept, this article will talk about the evolution of this technology as well as its challenges and opportunities. Finally, he will present the procedure to follow to develop artificial intelligence yourself.

The history of Artificial Intelligence

In reality, this concept dates back to the 1950s. Despite the limitations of their computers, scientists began to lay the first foundations of neural networks and to evoke the idea of machines capable of thinking.

Later, from 1950 to 2010, progress in the computer industry made it possible to expand the possibilities of computing machines and promote the development of machine learning. The terrain was therefore marked out for artificial intelligence. Until then, it has progressed on an expressway.

Today, artificial intelligence has reached dimensions that would not have been possible to imagine a few years ago. It is defined as a technology which aims to produce machines and systems capable of imitating, thinking and acting like human beings.

What is AI?

Artificial intelligence is a broad concept. To better understand it, let’s first look at its definition, its typology and the different techniques associated with it.

The key concepts related to Artificial Intelligence

Simply put, artificial intelligence is technology capable of learning and performing tasks normally associated with human intelligence through computer programs and computers.

This technology represents a real achievement for computer research. Its goal is to create high-performance machines capable of thinking and acting autonomously, like human beings.

Rest assured: these machines will not be destined to overthrow humanity! On the contrary, they will solve complex problems, improve our quality of life and advance us in various areas of society.

For the implementation of this vision, experts generally distinguish between three types of artificial intelligence:

Weak artificial intelligence: it refers to specialized and limited AI systems, which are designed to perform clear tasks according to rules or pre-programmed learning models;
Strong artificial intelligence: it aims to create systems with general intelligence comparable to that of human beings;
General artificial intelligence: it refers to versatile systems, capable of learning and adapting to new areas without requiring specific programming.

Aside from weak artificial intelligence, the other two types of AI are still largely theoretical or in the development phase.

During this phase, several techniques are used to enable machines and systems to perform tasks requiring human intelligence. These are the most common:

Machine learning;
Artificial neural networks;
Natural Language Processing (NLP);
Computer vision;
Fuzzy logic.

These techniques provide tools and methods for the design, development and optimization of AI systems. They are therefore of great importance.

AI, how is it evolving?

Computational research efforts have led to notable advances in AI. Let us first analyze them.

Recent advances in AI

We will present two recent and significant advances in artificial intelligence: ChatGPT and Google Bard.

ChatGPT

ChatGPT is an artificial intelligence model designed to produce consistent and relevant responses to its users’ queries. It is part of a family of language models developed by Open AI and based on the GPT (Generative Pre-trained Transformer) architecture.

ChatGPT answers questions, provides explanations and can initiate a conversation. It is versatile, fast and precise. Its features are constantly improving.

The use of ChatGPT, although advantageous, highlights the limitations of this tool:

Technological dependence: ChatGPT users may become dependent on this tool. This can harm their ability to produce content independently;
The security issue: it is possible that user data collected by the tool could be leaked or used for dishonest purposes;
Vulnerability to bias: the data collected and presented by ChatGPT may contain biases or errors;
The lack of originality of the content generated by ChatGPT

In the future, this language model could be used to provide automated, personalized customer support or to serve as a virtual educator for students.

Google Bard

Bard is a conversational tool developed by Google as an alternative to ChatGPT. It can provide clear and concise answers to Internet users’ questions.

Based on LaMDA, Google’s large language model (LLM), Bard can summarize articles and web pages, generate content ideas or write short, relevant content.

It also allows Internet users to easily carry out their searches. For example, we can use it to compare two products and choose the best one.

However, Bard has some limitations:

It doesn’t offer many features. For example, it is not able to generate images or make collages from prompts;
He has limited editorial capabilities: the content he generates is of lower quality than what men already write;
He does not indicate the sources of his information.

Despite its rocky start, Bard has support from developers and businesses. This AI intends to revolutionize the way in which IT professionals work and share information.

The challenges and opportunities of AI

Now let’s talk about the challenges and opportunities facing artificial intelligence.

Ethical, technical and social challenges

The development of artificial intelligence raises delicate ethical questions, particularly in relation to automated decision-making, the autonomy of AI systems and the economic consequences of their deployment.

Security and privacy are the main technical challenges faced by AI. No matter how good AI models are, they are vulnerable to cyber attacks and malicious data manipulation. Their protection must therefore be a priority.

AI also comes up against social challenges. Empowerment and the use of AI can profoundly affect the job market. Some jobs may be replaced by intelligent machines, which can lead to economic disruption and job losses.

Opportunities for innovation, competitiveness, growth

Artificial intelligence will enable innovation in many areas. For example, in health, AI will improve medical diagnosis by analyzing medical images, genetic data and patient records.

In the agriculture and food sector, AI systems will improve crop management. They will detect plant diseases, optimize the use of resources and automate agricultural processes.

In terms of competitiveness, artificial intelligence can help businesses automate repetitive tasks and processes. It can also analyze large amounts of data and extract valuable information. These will allow businesses to better serve their customers.

Finally, it is obvious that artificial intelligence is a significant vector of growth for businesses in particular, and for the economy in general. This opportunity remains one of the most important to seize.

Trends to follow

The evolution of AI over the last ten years has been dazzling. However, she is not about to stop. New trends in AI are already at the heart of current debates and work.

Ethical and responsible AI

The growing adoption of AI puts the issue of ethics and accountability at the top of the agenda. Soon, companies will only collaborate with partners committed to data ethics and adopt practices that reflect their values and those of their customers.

Fortunately, AI researchers and practitioners are already working on standards and guidelines that will ensure its ethical, transparent and responsible use.

Explainable AI

AI suffers from trust issues related to the fact that it is often impossible to explain how an AI system arrived at a given conclusion.

Thus, explainable AI was designed to explain and visualize the decisions made by AI systems. This will allow these systems to be used transparently and any biases to be easily corrected.

Augmented AI

Augmented AI refers to the use of artificial intelligence to enhance human capabilities instead of replacing them.

Thus, it aims to collaborate with humans by providing them with information, advice and tools to make better decisions and work more efficiently.

What are the applications of AI today?

The applications and use cases for this technology are numerous and extend to almost every industry.

Health

AI helps diagnose diseases, suggest treatments, detect vital signs, perform robot-assisted surgeries and manage medical records

In the health field, it is used to develop personalized treatments. In commerce, AI is used to recommend products to customers.

E-commerce

AI helps create personalized recommendation engines, virtual assistants and chatbots, and prevent credit card fraud or fake reviews.

facial recognition

Facial recognition is a great example of using artificial intelligence.

This technology uses AI techniques, including machine learning and computer vision, to identify and recognize people based on their unique facial features. It operates in several areas:

Unlocking smartphones: Most modern smartphones offer Face ID functionality which allows users to unlock their device simply by holding it close to their face;
Security and access control: security systems use facial recognition to identify people authorized to enter certain secure areas;
Financial services: Some banks use facial recognition as an additional means of authentication for online financial transactions.

Voice assistants

Voice assistants are very widespread examples of the use of artificial intelligence in our daily lives. Their operation is based on AI techniques such as voice recognition, machine learning and natural language processing.

These assistants are able to understand their users’ voice commands and provide appropriate responses. For example, they can search for information or control connected objects in their environment.

Siri, Alexa and Google Assistant are the most popular voice assistants on the market.

Autonomous cars

Appearing in the 2010s, autonomous cars are gradually gaining ground on the automobile market with brands like Tesla or Mercedes.

These little wonders drive themselves, thanks to artificial intelligence. In fact, they are equipped with AI systems which, using sensors, collect data on the environment in real time and analyze it in order to make the safest decisions.

AI systems also control vehicle actions, including acceleration, braking and steering. They learn from their experiences to correct their mistakes and improve the quality of driving. Isn’t that wonderful?

Social networks

To strengthen user engagement and improve their experience, social networks do not hesitate to equip themselves with artificial intelligence.

This addition provides a strategic advantage. Indeed, it allows networks to personalize content feeds based on each user’s history, preferences and interests. Also, AI helps filter content to detect inappropriate or unwanted content.

The dazzling success of the TikTok platform is precisely due to the artificial intelligence that supports its algorithms. His example illustrates very well the appeal of this technology for social networks.

Financial services

Let’s end this list of concrete examples of the use of AI by mentioning the case of financial services.

Banks and financial institutions are making strategic use of artificial intelligence. For example, they leverage it to detect fraudulent activities, analyze customer investment trends, offer personalized advice, etc.

AI systems can also be used to study their customers’ preferences, requirements and financial strength. This information will make it possible to offer them more relevant products.

These different examples fit very well into the dynamics of the challenges of artificial intelligence. All experts agree that this technology has the potential to transform the job market, change the economy and generate considerable social impact.

Artificial Intelligence, how to develop one?

It is possible to develop an AI yourself, given the appropriate tools and resources. However, this challenge is only within the reach of people with the knowledge required to take it up.

The first step towards creating artificial intelligence is therefore to train to become an artificial intelligence developer.

Definition

The AI developer is a specialist responsible for designing products based on artificial intelligence and big data to help companies run their business, solve a problem or to offer them a competitive advantage.

This professional uses advanced technologies to translate a company’s mass of data and derive useful predictions and recommendations. It develops solutions that can be used by AI specialists and non-specialists.

Required Skills

Several skills are necessary to work as an AI developer:

In-depth knowledge of mathematics, to understand the underlying concepts of AI;
A mastery of programming methods and techniques, as well as good experience in this field;
An excellent understanding of deep learning, machine learning and computer vision;
An analytical mind and good problem-solving skills.

Tools available

AI developers have several tools for developing, implementing, and reviewing their AI models. Here are the most used:

The Python language;
Machine learning and deep learning frameworks;
Data visualization tools, such as Matplotlib and Plotly;
Data preprocessing tools such as scikit-learn and spaCy;
Cloud computing platforms;
Version management tools, like Git;
Release tools such as Docker and Kubernetes.

The most powerful existing technologies on the market to develop AIs

Several technologies are specifically designed for the creation and development of artificial intelligence. So, after training, the second step to follow to design AI is to appropriate and use these technologies.

So let’s discover the three most powerful technologies for developing AIs.

cloud computing

Cloud computing is a technology that provides access to a variety of computer services via the Internet. Its use in the creation of an AI offers the following advantages:

Scalable computing power and therefore adaptable to your needs;
Storage and data management services, very practical to easily save and manage all the data necessary for AI;
Access to AI services and APIs: Cloud providers typically offer ready-made AI services, which can be easily used to add AI capabilities to your applications without having to build the models from scratch.

Big data

Big data plays a decisive role in the development of artificial intelligence. Here are the advantages of this technology:

Training AI models: Big data provides the massive amounts of data needed to train AI models and improve their performance;
Improving the accuracy of models: by relying on the voluminous, varied and representative data of big data, AI models manage to take into account a greater diversity of use cases;
The diversity of data sources: big data collects data from sources as rich as they are varied. This feeds the AI models and therefore improves the quality and relevance of their results.

edge computing

Edge computing is the third most powerful technology for developing AI. It offers three strategic advantages:

Reducing real-time response time, thanks to local processing of data, near the sensors and devices where they are generated;

Reduction of bandwidth and therefore of costs associated with data transfer;
Privacy and security of sensitive data by backing it up on edge devices rather than the cloud.

Good practices to adopt before developing an AI

This involves respecting a set of best practices to guarantee the reliability and quality of your AI. Here are three of them.

Respect ethical principles

The Commission of the European Union has defined seven ethical principles to be respected to achieve trustworthy artificial intelligence. These principles guarantee the fundamental rights of individuals and avoid discrimination.

As an AI developer, it is your duty to respect these principles when designing your artificial intelligence. This will reinforce the relevance of your product and its legality.

Test and validate models

Every AI developer must test and validate the AI models they develop. This approach is essential insofar as it makes it possible to verify their performance, identify errors, optimize the hyperparameters and evaluate their robustness.

So devote a good part of your time to this step. This will ensure that your artificial intelligence models meet user needs and expectations.

Document and explain results

Finally, make it a point to document and explain the results obtained in the creation of your artificial intelligence. This helps ensure transparency of the process and promotes ethical and responsible use of AI.

Conclusion

In summary, artificial intelligence is defined as technology capable of performing performances usually associated with human intelligence, using computer programs and computers.

Despite the ethical, technical and social challenges to be met, we can naturally imagine a world where the various applications of AI improve the quality of life, eliminate human error and promote economic and social development.

Technology

Svelte: The Revolutionary JavaScript Framework

Published

2 days ago

September 28, 2023

admin

Being ahead of the curve is crucial in the ever changing field of web development. JavaScript frameworks have been essential in streamlining and expediting the development of online applications. Out of all the competitors in this field, Svelte has become a game-changer. This essay dives into the world of Svelte, examining its history, distinguishing characteristics, and benefits for web developers.

The Birth of Svelte

Rich Harris unveiled Svelte in 2016, and it’s often heralded as the next breakthrough in front-end development. Harris, a former writer who is now a developer, was driven to create web apps more quickly. Even while well-known frameworks like Angular, Vue, and React have advanced significantly, they still had some fundamental problems.

Harris discovered a basic issue: frameworks like as React depend on a virtual Document Object Model (DOM) in order to effectively refresh the user experience. But there’s a performance overhead to this operation. He thus started working on creating a framework that would get rid of this obstruction.

Svelte’s Core Concept: The Compiler

Svelte’s compiler is what makes it so special. In contrast to conventional frameworks, which run code inside the browser, Svelte moves the labor to the construction stage. This indicates that Svelte converts the components into highly efficient JavaScript code during development. Because no framework-specific runtime library is included in the final product, the program is very light and quick.

Your code is examined by the compiler, which also finds dependencies and produces efficient code. By ensuring that no extra work is done in the browser, this method produces a web application that is more responsive and has a reduced bundle size.

Declarative Component-Based Architecture

React, Vue, and Angular are examples of component-based architectures that are embraced by Svelte. Svelte, on the other hand, offers a clearer and more simple method of specifying components. Svelte allows you to develop components in a single file by combining HTML, CSS, and JavaScript.

This simple syntax lowers the learning curve and facilitates developers in concentrating on creating the component’s real functionality.

Reactive Declarations

Svelte manages the state in a reactive manner. Developers may build reactive variables that update the user interface (UI) automatically as their values change, as an alternative to depending on sophisticated state management frameworks like Redux. Code is made simpler and easier to maintain with this feature.

In this case, there is no need for explicit event handling or manual DOM modification since the doubled variable updates automatically anytime the count changes.

The Shadow DOM

Encapsulation and web components are essential for developing scalable and maintainable systems. Svelte uses the Shadow DOM to automatically encapsulate components. The styles and structure of each Svelte component are contained, preventing them from escaping and creating conflicts with other components.

By preventing unintentional modifications to one component from affecting others, this encapsulation improves the modularity and reusability of the code.

Seamless Animations

In web development, producing fluid and dynamic animations is often a difficult challenge. Svelte’s integrated transition directive makes this procedure easier. With the help of this directive, developers can easily build animations. An example of fading in an element when a condition is satisfied is as follows.

Without the need for third-party animation libraries, Svelte makes it simple to create visually striking animations.

A Thriving Ecosystem

Due to Svelte’s quick uptake, an expanding ecosystem of tools and libraries that enhance its features has emerged. For instance, SvelteKit is a framework that streamlines server-side rendering and routing by building upon Svelte. Furthermore, server-rendered apps are still being built using Sapper, the precursor to SvelteKit.

Additionally, Svelte has a vibrant and friendly community. Svelte’s capabilities may be expanded by developers via third-party packages, tutorials, and copious documentation, which further enhances its allure for web development.

Performance Wins

Svelte’s unmatched performance is one of its main selling factors. Virtual DOM reconciliation incurs runtime cost, which Svelte removes with its compiler-driven solution. This results in less memory use, more fluid interactions, and quicker initial page loads.

Svelte’s small bundle size, when compared to standard frameworks, helps with load times, which is important for a great user experience. Performance is further improved by Svelte’s effective reactivity mechanism, which makes sure that only the essential DOM changes are done.

When to Choose Svelte

Although Svelte’s method of web development is clearly intriguing, it may not be the ideal option for all projects. Think of Svelte when:

Performance is Critical: Svelte is a strong option if your project requires outstanding performance and small bundle sizes.

Learning Curve: Teams wishing to swiftly onboard developers or novices may find Svelte to be a great option due to its simplicity.

Animations: Svelte’s built-in support excels when producing animations and transitions is a crucial component of your program.

Encapsulation: Svelte’s usage of Shadow DOM is a huge plus if you value component encapsulation and wish to avoid style clashes.

Svelte may not be the best option, however, for companies that depend significantly on the React, Angular, or Vue ecosystems already in place, since migration might take a lot of work.

Conclusion

Within the constantly changing realm of web development, Svelte is a welcome change of pace. Its declarative syntax, novel compiler-driven methodology, and outstanding performance make it a serious rival to well-known frameworks. Although there may not be a single solution that works for everyone, Svelte’s ease of use, speed, and expanding community make it a desirable option for contemporary web development. Svelte is definitely something you should look at for your future project, regardless of experience level as a developer. Experience the difference that Svelte can make in developing online applications that are quicker to load, more responsive, and simpler to manage by embracing the future of web development.

Technology

crewsense login

Published

2 days ago

September 28, 2023

admin

Are you looking for information on crewsense login? You have come to the right place! In this blog post, we will provide a step-by-step guide on crewsense login

Stock News World

Artificial intelligence: what is it and how is it evolving?

The history of Artificial Intelligence

What is AI?

The key concepts related to Artificial Intelligence

AI, how is it evolving?

Recent advances in AI

ChatGPT

Google Bard

The challenges and opportunities of AI

Ethical, technical and social challenges

Opportunities for innovation, competitiveness, growth

Trends to follow

Ethical and responsible AI

Explainable AI

Augmented AI

What are the applications of AI today?

Health

E-commerce

facial recognition

Voice assistants

Autonomous cars

Social networks

Financial services

Artificial Intelligence, how to develop one?

Definition

Required Skills

Tools available

The most powerful existing technologies on the market to develop AIs

cloud computing

Big data

edge computing

Good practices to adopt before developing an AI

Respect ethical principles

Test and validate models

Document and explain results

Conclusion

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Technology

Svelte: The Revolutionary JavaScript Framework

The Birth of Svelte

Svelte’s Core Concept: The Compiler

Declarative Component-Based Architecture

Reactive Declarations

The Shadow DOM

Seamless Animations

A Thriving Ecosystem

Performance Wins

When to Choose Svelte

Conclusion

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