The Ultimate Guide To AI (Artificial Intelligence)
Still don’t know what is artificial intelligence? Let’s recall the artificial intelligence definition once again. Artificial intelligence (AI) is a combination of scientific and technical means of designing smart machines, especially highly-intelligent computer programs. To put it simply, this is a field of computer science designed to create software and hardware that imitates the activity of the human brain and can make decisions independently – i.e., without a clearly predetermined algorithm. Below we will talk about what AI is and how other modern technologies combined with AI help developers create progressive technological solutions.
Types of AI
To date, there are several subsections of artificial intelligence. Let’s look at them briefly.
Artificial neural networks
A neural network is a virtual network that consists of interconnected blocks that process information taking into account external data, and send this information between blocks. The blocks work on the same principle as the neurons of the human brain, so the results that such networks obtain are similar to those generated in our heads.
If we turn to the original source, Dr. Robert Hecht-Nielsen, the creator of the first neurocomputer in the history of mankind, defines neural networks as complex computing systems consisting of simple, interconnected elements that process information by dynamically responding to external input signals.
Note that the concept of neural networks appeared in the mid-60s of the last century. However, only modern computing resources allow developers to implement them in such a way that the results they generate have a minimum error.
Machine learning
Just like artificial intelligence, AI machine learning encompasses the scientific methods of statistics, physics, mathematics, and other hard sciences. The ML uses ready-made data samples that provide training models with information about the input features and parameters necessary to generate the correct answer. Neural networks also take part here to search for hidden patterns in the data, especially those for which specific hardware was not originally programmed to search.
In general, AI and machine learning are often used to process Big Data since other digital technologies do not allow drawing conclusions based on them so quickly and accurately without a clear algorithm.
Deep Learning
Deep learning uses the powerful computational resources of neural networks and hardware to search for and identify patterns. Typically, such solutions work with colossal data sets – in this case, the results that they generate turn out to be as accurate as possible. As examples, we can consider smart software for recognizing objects in images, such as Google Image Search, or any of the smart assistants, such as Amazon Alexa or Siri.
Natural Language Processing
The concept of “natural language”, in this case, means the language used by people, that is, one that is not used by machines to implement certain commands (i.e., it is not a programming language). Thanks to the AI algorithms responsible for its processing, communication with programmable AI systems is carried out.
From a formal point of view, natural language processing consists of two components: understanding and generation. The ‘understanding’ component is about matching natural language input to existing representations and analyzing various aspects of natural languages. Next comes the ‘generation’ component – it is the process of forming the correct output in the form of words and sentences. Specific examples of NLP implementation are the Amazon Echo and Alexa assistants.
Cognitive Computing
Cognitive computing is based on artificial intelligence and signal amplification. In practice, cognitive computing brings together various subsets of artificial intelligence, including machine learning and natural language processing, but so far, in this relatively new field, the more accurate definition remains blurry.
Ultimately, this technology will help create automated IT models that can solve problems without human assistance. As for particular examples of cognitive computing, we can consider the IBM Watson supercomputer.
Computer Vision
Computer vision is another interdisciplinary field within the concept of artificial intelligence. With its help, computers are trained on the basis of samples consisting of images and videos. Thus, they independently perform tasks for which people usually use their vision: for example, to determine what exactly is depicted in a photo.
At the same time, in practice, computer vision-based solutions can also perform much more complex processes, such as diagnosing diseases based on ultrasound or MRI images or identifying manufacturing defects.
Impact Of Artificial Intelligence On Society
Despite the undeniable benefits of artificial intelligence in past years, now people around the world, regardless of their social status and religion, are sounding the alarm. Already today, AI puts many workers out of work, both intellectual and manual ones.
In general, the second situation is not new since, with the advent of robotics, primitive manual labor has become out of demand. As for intellectual tasks, from writing code to creating movie scripts, the mass strikes in Hollywood already mean a lot, namely that today, AI is perceived more hostilely than ever before.
Along with this, it is extremely difficult to overestimate its usefulness in analytical, predictive, and diagnostic decisions. Therefore, if you are considering AI as one of the possible USPs for your business, you should definitely consider implementing it today before it becomes regulated at the legislative level.
AI in Everyday Life
In everyday life, it is difficult to find a person who would not have at least indirect experience of interacting with AI. In particular, if you have ever bought something on the online marketplace or turned to the voice assistant on your smartphone for help, you have already become an “AI witness”.
Therefore, as an end user, you get the desired personalization in service and quick assistance from AI in a way that is the most convenient for you, as if you had a personal know-it-all live assistant.
What Is Natural Language Processing (NLP)?
Natural Language Processing (NLP) is a machine-learning technology that gives computers the ability to interpret human language. And it can be extremely useful, given that modern companies usually have large volumes of voice and text data from various communication channels, such as emails, text messages, social network news feeds, video, audio, etc.
In particular, these companies are more likely than others to use NLP-based software to automatically process this data, analyze the intent or sentiment in the message, and respond to human interaction in real time.
Natural language processing is critical to the efficient analysis of text and speech data. In this way, businesses can overcome differences in dialects, slang, and grammatical irregularities that are common in everyday communication. Companies use this method to automate tasks such as:
- Processing, analysis, and archiving of large documents
- Analysis of customer reviews and call center records
- Implementation of chatbots for automated and personalized customer service
- Quick answers to “who, what, when, and where” questions
- Text classification and interpretation
You can also integrate NLP into customer-facing applications to provide more immersion into his/her problems during the conversion. For example, a chatbot can independently analyze and sort customer requests according to their priority, answer the most standard ones, and redirect complex and ambiguous ones to a live support team. Thus, you will quickly achieve cost reductions without compromising the quality of your services and the accuracy of your business decisions.
Robotics Based on Artificial Intelligence
Robots are among the technological solutions that will have the greatest impact on business and commercial viability in the future. Indeed, for decades they have been taking on most of the routine work even without artificial intelligence control, which means that with its help, their range of tasks will become even wider. At the same time, this does not mean that all employees who once performed routine duties before will lose their jobs. With the right specialized training, they will be able to become responsible for maintaining, controlling, programming, and repairing these robots.
Moreover, robotics can be used in conjunction with an AI system, thus forming the concept of Co-Bots, which “cooperate” with living people to reduce the risk of workplace injuries. Such solutions have already found active use in the auto industry, and many companies that remain supporters of manual assembly lose from this (as in the case of Tesla, which only lost profits from abandoning this innovation).
A similar example of interaction is also AI-driven robots that reveal a manufacturing defect at the assembly stage. An attempt to introduce such an innovation can be caught by Apple. However, at present, the “skill” of such robots is not enough to determine that something functions or looks incorrect, and people still cope with this task more efficiently.
On a smaller scale, AI-based robotics can take on the responsibility of repetitive tasks, freeing up the human workforce to work on processes that require a high level of dexterity or critical thinking.
AI in The Cloud
Given the considerable age of the concept of AI, its development is hindered, first of all, by limited resources, both informational and computing. Fortunately, as world technology advances, this problem is no longer a challenge, even for small businesses and startups. And it’s all thanks to the cloud.
Indeed, with a powerful and flexible infrastructure hosted in the cloud, any company, regardless of its size, sector, or region, can take a leading position in the market. All this means the democratization of the introduction of new technologies, which is especially noticeable in the field of corporate AI-driven developments. These days, almost any company can get access to AI advancements, which makes it a great prospect for various research.
In practice, without cloud computing and storage, companies would not have modern artificial intelligence capabilities that use huge amounts of disparate data. The power of the cloud enables organizations to capture, store, process, and analyze the staggering amount of data they need today.
It is worth noting that just as the rise of cloud computing allowed the AI sector to develop, today’s investments in AI are also the main fuel of the life of the cloud industry. As AI embraces more and more complex tasks, it needs more and more powerful platforms to work with. And the enthusiastic cloud industry responds with new investments, helping to take the AI industry to the next level.
Future of AI
Now you know a little about AI history and, in particular, about the main directions of its development, which means it’s time to highlight its prospects as well.
Specifically, when talking about the most significant facts about the current situation and the future of AI, let’s check these ones:
- 35% of businesses have already adopted AI
- 9 out of 10 organizations support AI as their USP
- AI will contribute $15.7 trillion to the global economy by 2030
Indeed, in the coming years, the future of digital intelligence will be determined mainly by solutions for public use, such as ChatGpt, MidJourney, DALL-E, etc. They already demonstrate their mastery in creating texts, media, and program code, and all this is achievable in just a few moments.
As for the niche market players that provide business solutions, Microsoft and Google already actively use AI and its variations in their cloud services, allowing companies to globally automate their usual business processes.
Finally, when considering the development of AI within the next decade, it promises to significantly transform the labor market, from the healthcare to the banking sector. However, only those employees (companies) whose tasks require almost no improvisation should really beware of the introduction of AI.
Application of Artificial Intelligence in Business
The use of AI in business is an opportunity to offload boring and repetitive tasks associated with processing large amounts of data, making data-driven decisions, and compiling reports onto machines. And all this is thanks to software that independently collects information, analyzes it, determines patterns, classifies data, and generates correct results.
The artificial intelligence benefits and advantages are already actively used in such processes:
- Ensuring cyber security (protection against cyber scammers and phishing programs)
- Sales and demand forecasting
- Personalization of customer service (from replacing call center employees with chatbots to choosing goods/services that a particular customer will like)
- Smart vehicles control
- Surgery and diagnostics
- Supply chain optimization
- Evaluation of customer history in the field of lending and insurance
In general, this list can be continued for a long time –- the main thing is to consider this tool as an assistant to your business and not an enemy to your living employees.
AI Tools for Upwork
Now let’s talk about how artificial intelligence copes with tasks, without which such a thing as a business would not exist at all, namely, interaction with customers and performers. If we consider the most advanced digital solutions based on artificial intelligence, we cannot ignore the Upwork web platform.
Indeed, this website is one of the most popular in the world for those who have a job and those who want to find it without limiting their physical location. Together with the time-tested usability, this project is still not perfect – that’s why some third-party development companies implement their own projects to integrate with Upwork and expand (optimize) its functionality. One such AI tool is the Upwex product.
Pricing on AI Tools for Upwork
Let’s start with pricing – This product has a three-day free period during which you can check its functionality without any obligations. Next, you only have to pay $25 per month to get the following:
- Job rating;
- AI-powered Q&A;
- AI-powered proposal generator;
- 500 AI requests;
- Full analytics for the last year;
- Technical support;
- Pipedrive CRM sync;
- Priority support and training.
Benefits – Upwex
Currently, Upwex has already been chosen by more than 1000 businesses around the world, helping them to boost their Upwork’s success. In fact, this is a browser extension that brings together specialists with companies within the Upwork platform using the capabilities of artificial intelligence. In particular, you can delegate the following tasks to this extension:
- Job Scoring;
- AI Proposal and Q&A;
- Job Post Rating;
- Deal Management;
- Reporting and Analytics;
- Pipedrive CRM synchronization contacts and deals.
Conclusion
Now you know the answer to the question: “What does AI stand for?” and also understand what types of AI can be used and for what purposes. In general, in the context of business, despite the hostile image created by the media, artificial intelligence can be extremely useful.
On the other hand, it can be difficult for companies that have not previously dealt with such advanced technologies to realize what internal and external business processes can be optimized using AI and its derivatives. In this case, the time and financial costs may not meet expectations. To prevent this, you can seek advice from Synapse Team, a team of specialists who have successfully implemented dozens of custom AI-based solutions. To learn about our case studies in detail, you can also check out our portfolio.