Prizilla Shinjini Introduction
Artificial Intelligence is an ocean with vast improvements and advancements in the industry that has actually revolutionised the phase of website interaction (Chatbots), Robots manufacturing in factories and smart assistants in robots, Social media monitoring, automated financial investing, accounting and management, Proactive healthcare management, Virtual travel and hotel booking, Disease mapping, Self-driving cars (out of which Tesla is rewriting the manufacturing history of cars.
What is AI? (AI and Big data)
AI or artificial intelligence is an advanced technology that replicates the sense of thinking that only humans were able to do for years in robots and machines. Smart machines, sensors built devices, self–thinking robots and a lot more are made with this technology and today AI is reshaping the world-dominating in all domains such as agricultural, educational, industrial, technical and scientific domains. It is highly influenced by our day to day life that we can’t survive without AI. In such a way the advancement has got attachment with our society and eventually the world.
This has the power of handling performance much similar to a digital computer or a robot which is controlled with a computer with a code embedded to perform tasks which may be associated with intelligence and productivity to the human needs and desires. This term is frequently used in the case of project development systems that are endowed with highly intellectual processes. It is so complicated that, it resembles so many characteristics handled by a human. They include the ability to reason, generalize, or learn from experience and to discover meaning all via self-analysis, experiencing and teaching. Since the development of the computer with digital aspects was done in the 1940s, it has been proved and confirmed that computers can be programmed to carry out very complex tasks such as discovering proofs for mathematical theorems. But this advancement is the next level of this revolution.
5 Key elements of AI
- Machine Learning,
- Conversional AI,
- Compute Vision,
- Natural Language Processing and
- Deep Learning is the 5 key elements or core concepts that have framed AI to meet this big success with different invention in different industries.
Types of AI
- Artificial Narrow Intelligence,
- Artificial General Intelligence and
- Artificial super Intelligence
Are the three types of artificial intelligence that are classified to date.
Artificial Narrow Intelligence is the basic intelligence level that a basic calculator and software have. It works only when it is instructed to work.
Artificial General Intelligence – This is the advanced AI that is sensing listening, responding along with the thinking ability. It is free to explore the given patterns as an idea to find the solution or explore the habitat given to find how to learn new things and act as per it.
Artificial Super Intelligence – This is the ultra-level AI which is believed to emerge via super brained computers and software that thinks like a human and is capable of performing tasks so much percentage higher than humans. Scientists and Hypocrites believe and say that ASI may conquer and rule humans and eventually the earth. But this AI is in the beginning stage.
Turing Test
Turing test is a test every AI trained or under training machine should take. This test is taken to check whether the software is capable of thinking and working like a human. No software or trained and undertraining device has scored above 6 to date. But, AI is constantly evolving and the evolution has led this advancement to reach a score of 6 out of 10 in thinking and solving ability as a human.
Why is AI in huge demand? Is it revolutionising the industries and lifestyles?
- Unlike the previous centuries and decades in specific, the usage of computers in our daily or probably storage, assignment, work from home, meetings and a lot more. As a whole the increase in computational power in the past one and a half decade has lead this drive towards AI.
- Big Data – Another important reason is the increased data created every day via emails, social media and websites such as ecommerce websites, and gaming websites and a lot more makes AI efficient to solve database servers from over loading. Similarly the term dark web which many may not know is an important concept. All the data that is generated by every individual surfers is the basic generation of data.
- But, the data that you tend to consume which has the details about what you like watching, you interests, your personal details and each and every page you surfed through internet is stored somewhere. Generally the website holders, you and the connection providers has access to this. 70 % of this data every day surfed which is not used the next day is called dark data and is stored in the form of cookies or super cookies. Controlling and monitoring this is beyond the manual abilities but, AI has got solutions for it,
- Better Algorithm – The need of having a better algorithm has always bothered the technical industry a lot. This also has made the advancement of project management and SDLC in the software development and corporate companies have adopted such to enhance their results to the core.
- Broad Investment – AI is now-a –days seen a human to an unexpected extent that, the investments handled by a company, a group of companies or a individual is highly invested and monitored by AI powered systems. And the reason that rely behind this seems to be that AI powered systems have all the ability to surf and understand the current scenario and stocks, bonds and block chain stuffs. So its prediction and investment will not go vain is the belief and it has proved right several times too.
- These are the reasons why AI is highly in demand in the industry.
IoT and MI
Internet of things and machine learning are the backup key elements of AI.
Types of MI
- Supervised machine learning or labelled machine learning
- Regression
- Continuous data
- Graph data or similar once
- Classification
- Data classified in columns ( used to sort queries)
- Regression
- Unsupervised machine learning or non-labelled machine learning
- Association
- Associate between similar items – One needs another.
- Clustering
- Targeted marketing
- Based on similarity – it should form a cluster.
- Association
- Reinforcement or robust method – Trial and error method
What is DL?
Deep learning is a part of or in-depth, a subset of machine learning and artificial intelligence that has networks capabilities that can do learning unsupervised from the given data that is unlabelled or unstructured.
Deep learning’s evolution has got hand-in-hand with the digital era. This has brought about an explosion of data in all forms and from every region of the world. This data which is known as big data is generated from social media, eCommerce platforms, internet search engines, and online cinemas, among others. This enormous amount of data is readily available and accessibility is provided due to which this can be shared via fine tech applications like cloud computing.
However, the data is so vast that it could take decades for humans to understand and modify it to extract the relevant content.
Types of DL
| Feedforward neural network |
| Radial basis function neural networks |
| Multi-layer perceptron |
| Convolution neural network (CNN) |
| Recurrent neural network |
| Modular neural network |
| Sequence to sequence models |
Conclusion
AI or artificial intelligence is an advanced technology that replicates the sense of thinking that only humans were able to do for years in robots and machines. Smart machines, sensors built devices, self–thinking robots and a lot more are made with this technology and today AI is reshaping the world-dominating in all domains such as agricultural, educational, industrial, technical and scientific domains. Machine learning, Conversational AI, Computer Vision, Natural Language Processing are the core key elements of AI.
Artificial Narrow Intelligence, Artificial General Intelligence and Artificial super Intelligence are the three types of artificial intelligence that are classified to date.
Speaking about machine learning a machine tends to learn to identify and solve problems via algorithms. Types of machine learning include supervised machine learning, unsupervised machine learning and reinforcement. Each has its own subtopics and are also vast individually.
The demand for AI has touched high in this decade in specific and this is because, more computational power, big data, better algorithms, need for broad investment has contributed reasons and provided space to AI. Deep Learning is an advanced technic to make machines artificially intelligent via the system of neural networks. There are different types of deep learning neural networks. This test is taken to check whether the software is capable of thinking and working like a human. And AI is constantly evolving that the evolution has led this advancement to reach a score of 6 out of 10 in thinking and solving ability as a human.
[…] Echo Show 5 Gen 2 Virtually (2021) All you need to know about Artificial Intelligence […]