What is needed for instructions to be an algorithm?

❗️ Not all written instructions for programming are an algorithm.

✍️ For some instructions to be an algorithm, it must have the following characteristics:

✔️ Clear and Unambiguous
The algorithm should be unambiguous. Each of its steps should be clear in all aspects and must lead to only one meaning.

✔️ Well-Defined Inputs
If an algorithm says to take inputs, it should be well-defined inputs. It may or may not take input.

✔️ Well-Defined Outputs
The algorithm must clearly define what output will be yielded and it should be well-defined as well. It should produce at least one output.

✔️ Finite-ness
The algorithm must be finite, i.e. it should terminate after a finite time.

✔️ Feasible
The algorithm must be simple, generic, and practical, such that it can be executed with the available resources. It must not contain some future technology or anything.

✔️ Language Independent
The algorithm designed must be language-independent, i.e. it must be just plain instructions that can be implemented in any language, and yet the output will be the same, as expected.

✔️ Input
An algorithm has zero or more inputs. Each that contains a fundamental operator must accept zero or more inputs.

✔️ Output
An algorithm produces at least one output. Every instruction that contains a fundamental operator must accept zero or more inputs.

✔️Definiteness
All instructions in an algorithm must be unambiguous, precise, and easy to interpret. By referring to any of the instructions in an algorithm one can clearly understand what is to be done. Every fundamental operator in instruction must be defined without any ambiguity.

✔️ Finiteness
An algorithm must terminate after a finite number of steps in all test cases. Every instruction that contains a fundamental operator must be terminated within a finite amount of time. Infinite loops or recursive functions without base conditions do not possess finiteness.

✔️ Effectiveness
An algorithm must be developed by using very basic, simple, and feasible operations so that one can trace it out by using just paper and pencil.

Subscribe- t.me/askmenow

What are types of algorithms?

ℹ️✍️ There are several types of algorithms available.

1️⃣1️⃣ important algorithms are:

🔹 Brute Force Algorithm: a straightforward approach that exhaustively tries all possible solutions, suitable for small problem instances but may become impractical for larger ones due to its high time complexity.

🔹 Recursive Algorithm: a method that breaks a problem into smaller, similar subproblems and repeatedly applies itself to solve them until reaching a base case, making it effective for tasks with recursive structures.

🔹 Encryption Algorithm: utilized to transform data into a secure, unreadable form using cryptographic techniques, ensuring confidentiality and privacy in digital communications and transactions.

🔹 Backtracking Algorithm: a trial-and-error technique used to explore potential solutions by undoing choices when they lead to an incorrect outcome, commonly employed in puzzles and optimization problems.

🔹 Searching Algorithm: designed to find a specific target within a dataset, enabling efficient retrieval of information from sorted or unsorted collections.

🔹 Sorting Algorithm: aimed at arranging elements in a specific order, like numerical or alphabetical, to enhance data organization and retrieval.

🔹 Hashing Algorithm: converts data into a fixed-size hash value, enabling rapid data access and retrieval in hash tables, commonly used in databases and password storage.

🔹 Divide and Conquer Algorithm: breaks a complex problem into smaller subproblems, solves them independently, and then combines their solutions to address the original problem effectively.

🔹 Greedy Algorithm: makes locally optimal choices at each step in the hope of finding a global optimum, useful for optimization problems but may not always lead to the best solution.

🔹 Dynamic Programming Algorithm: stores and reuses intermediate results to avoid redundant computations, enhancing the efficiency of solving complex problems.

🔹 Randomized Algorithm: utilizes randomness in its steps to achieve a solution, often used in situations where an approximate or probabilistic answer suffices.

Subscribe- t.me/askmenow

What is artificial intelligence (AI)?

🧠🤖Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.

AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states.

AI programming focuses on cognitive skills that include the following:

▪️Learning: acquiring data and creating rules for how to turn it into actionable information. The rules – algorithms – provide computing devices with step-by-step instructions for how to complete a specific task.

▪️Reasoning: choosing the right algorithm to reach a desired outcome.

▪️Self-correction is designed to continually fine-tune algorithms and ensure they provide the most accurate results possible.

▪️Creativity uses neural networks, rules-based systems, statistical methods and other AI techniques to generate new images, new text, new music and new ideas.

Subscribe- t.me/askmenow

Who is the father of AI?

ℹ️ The term “artificial intelligence” is coined in a Proposal for the Dartmouth summer research project on artificial intelligence submitted on the 31st of August 1955 by a group of researchers.

🎂The workshop, which took place in July-August 1956, is considered as the official birthdate of AI.

🔺John McCarthy (1927-2011)⬆️, a prominent computer scientist, is recognized as the father of AI.

🔺He created Lisp, a standard programming language widely employed in robotics, various applications and services, and also worked on such innovations as self-driving car, robot consciousness and computer data sharing.

🔺After years of research, McCarthy offered the following definition of AI:
“It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, AI does not have to confine itself to methods that are biologically observable.”

Subscribe- t.me/askmenow

What is the AI of today and that of the future?

🔲 Most of the AI that surrounds us today is trained and focused to perform specific tasks. Researchers call this AI weak or narrow - Artificial Narrow Intelligence (ANI). ‘Narrow’ might be a more accurate descriptor for such AI systems as they are anything but weak; enabling some very robust applications, and autonomous vehicles.

🔳 The AI of the future is called strong and is made up of Artificial General Intelligence (AGI) and Artificial Super Intelligence (ASI).

AGI is a theoretical form of AI where a machine would have an intelligence equaled to humans and a self-aware consciousness in order to learn and plan.

ASI—or superintelligence—would surpass the intelligence and ability of the human brain. In the meantime, the best examples of ASI might be from science fiction.

❗️According to researchers, there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years.

Subscribe- t.me/askmenow

How Many Types of Artificial Intelligence are there?

According to scientists, there are 4️⃣ types of AI:

• Type 1️⃣: Reactive machines. These AI systems have no memory and are task-specific. Nevertheless, computer chess programs, which are examples of these systems, can beat human chess masters.

• Type 2️⃣: Limited memory. These AI systems have memory, so they can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way.

• Type 3️⃣: Theory of mind is a psychology term. When applied to AI, it means the system would have the social intelligence to understand emotions, to infer human intentions and predict behavior. It will be a necessary skill for AI systems to become integral members of human teams.

• Type 4️⃣: Self-awareness. In this category, AI systems have a sense of self, which gives them consciousness. This type of AI does not yet exist.

Subscribe- t.me/askmenowy

What are real-world AI applications?

Here are some of the most used real-world applications of AI:

✔️Speech recognition: Also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, it is a capability which uses natural language processing (NLP) to process human speech into a written format, e.g. in mobile devices.

✔️Customer service: Online virtual/voice assistants are replacing human agents to answer frequently asked questions (FAQs) around topics, like shipping, or provide personalized advice.

✔️Computer vision enables systems in social media, healthcare, and automotive industry to derive meaningful information from digital visual inputs and, unlike image recognition tasks, to provide recommendations.

✔️Recommendation engines can help retailers to develop more effective past consumption cross-selling strategies.

✔️Automated stock trading: AI-driven high-frequency trading platforms make trades without human intervention.

Subscribe- t.me/askmenow

What are differences between AI, machine learning and deep learning?

📌 AI, machine learning and deep learning are common terms in enterprise IT and sometimes used interchangeably, but there are distinctions.

📌 Both deep learning and machine learning are sub-fields of artificial intelligence, and deep learning is actually a sub-field of machine learning.

📌 Machine learning enables software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values. This approach became vastly more effective with the rise of large data sets to train on.

📌 Deep learning is based on our understanding of how the brain is structured. Unlike machine learning, it doesn't require human intervention to process data. Deep learning's use of artificial neural networks structure is the underpinning of recent advances in AI, including self-driving cars and ChatGPT.

Subscribe- t.me/askmenow

If a machine can learn, can it dream?

A visual artist Refik Anadol tried to answer this question, using AI, together with the Philadelphia Orchestra.

A 12/meter (40-foot) tall digital screen with 8.2 million pixels, each controlled by AI, was installed on the stage.

As the orchestra played Beethoven’s “Missa Solemnis,” the screen came alive with swirls and cascades of color.

The system used fluid dynamics algorithms to generate animation effects resembling flowing water and wind through hair. For this performance, Anadol “taught” his system by feeding it thousands of images of Renaissance art and architecture, the kind of aesthetics that Beethoven himself would have been consuming when he wrote his celebrated works.

The developer didn’t give his artificial intelligence machine an anthropomorphic name, but refered to it as a “thinking paintbrush.”

The performance that used AI technologies was nevertheless negatively received by many musical critics.

Have a look ⬆️.

Subscribe- t.me/askmenow

What is the Turing test?

In an essay “Computing Machinery and Intelligence”, published in 1950, the English mathematician and computer pioneer Alan Turing proposed the Turing test.

The test is performed by placing a human in one room and a machine in another. Then a judge, or panel of judges, addresses each room with questions regarding any topic to which a human should be able to respond.

Originally called the Imitation game, this test examines whether humans can tell if they are talking to a machine or a human and has become one of the most important milestones in the research and development of artificial intelligence.

ℹ️ Alongside John McCarthy, Alan Turing (1912-1954) is also seen as a founder of AI and often called the "father of computer science". His Touring machine provided the concepts of algorithm and computation that led to general-purpose computers. Named after him, the Touring Award is the highest distinction in computer science.

Subscribe- t.me/askmenow

Can machines think?

❓🤖💭That was the question Alan Turing ⬆️posed at the top of his landmark 1950 paper, “Computing Machinery and Intelligence.” It was a time when rudimentary electronic computers were just starting to emerge.

Turing realized that his test was not designed to determine whether a computer can “think.” After all, it might be fundamentally impossible to know what’s happening in the “mind” of a computer, and even if computers do think, the process might be fundamentally different from the human brain.

❓↔️❓That’s why Turing replaced his original question with one we can answer: “Are there imaginable computers which would do well in the imitation game?” This question established a measurable standard for assessing the sophistication of computers over the past seven decades.

🆒According to modern scientists, the new question was also a clever way of sidestepping the philosophical questions associated with defining words like “intelligence” and “think”.

Subscribe- t.me/askmenow

Can AI really pass the Turing test?

One of John McCarthy’s objectives was that a computer would pass the Turing test.

❎❓ According to most computer scientists and AI researchers, to date, no computer has decidedly passed the Turing test. Nevertheless, there have been some convincing contenders.

ℹ️ In 2018, Google unveiled an informal Turing test when he published a video of the company’s virtual assistant, called Duplex, calling a hair salon and successfully booking an appointment. The woman who answered the phone seemed to have no idea she was talking to a computer.

✅ So, it looks like today’s AI algorithms can pass the Turing test in some way.

❗️ However, for many modern researchers, the question of whether or not a computer can pass this test has become irrelevant. Instead of focusing on how to convince someone to talk to a human, rather than the computer program, they think that our real focus should be on how to make human-computer interaction as smooth as possible.

Subscribe- t.me/askmenow

What is the Six Degrees of Separation?

ℹ️ The Six Degrees of Separation is the idea that all people are connected with each other by at most six social connections.

✔️ It was originally set out by Hungarian writer Frigyes Karinthy (1887-1938) in 1929. Theories based on the idea were already discussed before him, but it was Karinthy who published a story called the “Chain-Links”. In this story, he particularly tells that the modern world was ‘shrinking’ due to this ever-increasing connectedness of human beings and that any two individuals in the world could be connected through at most five acquaintances.

✔️ Today, this concept is also known as “The Six Handshakes Rule/Theory”. It was put forward in 1969 by two American psychologists: Stanley Milgram and Geoffrey Travers. They conducted a “Small-world experiment” in 2 cities with 300 envelopes that participants handed only over to acquaintances. The conclusion was that each envelope went through six hands.

Subscribe- t.me/askmenow

How to explain the Six Handshakes Rule?

❇️This rule has a formula that establishes that each person in the world may know 100 people in average.

❇️If each one of your 100 acquaintances is connected somehow to another 100 people, then, the number would increase to 10,000 in the second link in the chain.

❇️In the third link you could increase the number of people you could possibly meet to 1,000,000 and 100,000,000 in the fourth link.

❇️In the fifth one, you would reach 10,000,000,000 people and 1,000,000,000,000 people in the sixth level.

✅⬆️This amount far exceeds the total population of the planet, so the relationships that the members of the chain have in common could be compensated without problems.

ℹ️This formula considers that, of your 100 personal connections, none might have a mutual connection with the 10,000. It is not the case in the real world, but it’s quite likely for your acquaintances to be connected to more than 100 people. So, this would balance it all.

Subscribe- t.me/askmenow

What is the chemical backbone of life on Earth?

⚫️Carbon is the chemical backbone of life on Earth, required to form complex molecules like proteins and DNA.

⚪️This element is also found in our atmosphere in the form of carbon dioxide (CO2).

🟢Carbon compounds regulate the Earth’s temperature, make up the food for living organisms, and provide energy that fuels human’s economy.

🪨🌊💨Most of Earth’s carbon is stored in rocks and sediments. The rest is located in the ocean, atmosphere, and in living organisms. These are the reservoirs through which carbon cycles.

🌀The carbon cycle is nature's way of recycling carbon atoms.

⚫️Carbon is released back into the atmosphere when organisms die, volcanoes erupt, fires blaze, fossil fuels are burned, and through a variety of other mechanisms.

🌊💨In the case of the ocean, carbon is continually exchanged between the ocean’s surface waters and the atmosphere, or is stored for long periods of time in the ocean depths.

Subscribe- t.me/askmenow

What is the greenhouse effect and why is it important?

✅ The greenhouse effect is the way in which heat is trapped close to Earth's surface by “greenhouse gases.” These heat-trapping gases can be thought of as a blanket wrapped around Earth, keeping the planet toastier than it would be without them.

✅ Scientists have determined that carbon dioxide's warming effect helps stabilize Earth's atmosphere. Remove carbon dioxide, and the terrestrial greenhouse effect would collapse. Without carbon dioxide, Earth's surface would be some 33°C (59°F) cooler.

✅ Greenhouse gases occur naturally and are part of our atmosphere's makeup. For that reason, Earth is sometimes called the “Goldilocks” planet – its conditions are not too hot and not too cold, but just right to allow life (including humans) to flourish. Part of what makes Earth so amenable is its natural greenhouse effect, which keeps the planet at a friendly 15 °C (59 °F) on average.

Subscribe- t.me/askmenow

What is the difference between global warming and climate change?

🌏🌡📈Global warming is the long-term warming of the planet’s overall temperature. Though this warming trend has been going on for a long time, its pace has significantly increased in the last hundred years due to human activities. As the human population has increased, so has the volume of fossil fuels burned. Fossil fuels include coal, oil, and natural gas, and burning them accelerates what is known as the “greenhouse effect” in Earth’s atmosphere. Scientists continue to study global warming and its impact on Earth.

🌦🌪🌊Global warming has presented another issue called climate change. Sometimes these terms are used interchangeably, however, they are different. Climate change refers to changes in weather patterns and growing seasons around the world. It also refers to sea level rise caused by the expansion of warmer seas and melting ice sheets and glaciers.

Global warming causes climate change.

Subscribe- t.me/askmenow

What are possible future effects of global warming and climate change?

❗️According to researchers, since 1906, the global average surface temperature has increased by more than 0.9 °C (1.6 °F) - even more in sensitive polar regions.

Effects that could take place later, if warming continues, include:

🌊🆙Sea levels could rise between 26 and 82 cm (10 and 32 inches) or higher by 2100.

🌪🌀🌨☀️Storms, floods and droughts could become stronger and more common.

💧🆘Less freshwater could be available, since glaciers store about three-quarters of the world's freshwater.

🦠Some diseases could spread, such as mosquito-borne malaria.

🌏Ecosystems could continue to change: some species could move farther north or become more successful; others could not be able to adapt and become extinct.

☹️More health, social and economic risks for humans.

ℹ️Scientists claim that atmospheric levels of CO2 are now similar to where they were during the mid-Pliocene epoch, about 3-4 million years ago.

Subscribe- t.me/askmenow