Artificial Intellegence

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Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.

How does AI work?

As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use AI. Often what they refer to as AI is simply one component of AI, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI, but a few, including Python, R and Java, are popular.

In general, 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. In this way, a chatbot that is fed examples of text chats can learn to produce lifelike exchanges with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples.

AI programming focuses on three cognitive skills: learning, reasoning and self-correction.

Learning processes. This aspect of AI programming focuses on acquiring data and creating rules for how to turn the data into actionable information. The rules, which are called algorithms, provide computing devices with step-by-step instructions for how to complete a specific task.

Why is artificial intelligence important?

AI is important because it can give enterprises insights into their operations that they may not have been aware of previously and because, in some cases, AI can perform tasks better than humans. Particularly when it comes to repetitive, detail-oriented tasks like analyzing large numbers of legal documents to ensure relevant fields are filled in properly, AI tools often complete jobs quickly and with relatively few errors.

This has helped fuel an explosion in efficiency and opened the door to entirely new business opportunities for some larger enterprises. Prior to the current wave of AI, it would have been hard to imagine using computer software to connect riders to taxis, but today Uber has become one of the largest companies in the world by doing just that. It utilizes sophisticated machine learning algorithms to predict when people are likely to need rides in certain areas, which helps proactively get drivers on the road before they’re needed. As another example, Google has become one of the largest players for a range of online services by using machine learning to understand how people use their services and then improving them. In 2017, the company’s CEO, Sundar Pichai, pronounced that Google would operate as an “AI first” company.

Today’s largest and most successful enterprises have used AI to improve their operations and gain advantage on their competitors.

What are the advantages and disadvantages of artificial intelligence?

Artificial neural networks and deep learning artificial intelligence technologies are quickly evolving, primarily because AI processes large amounts of data much faster and makes predictions more accurately than humanly possible.

While the huge volume of data being created on a daily basis would bury a human researcher, AI applications that use machine learning can take that data and quickly turn it into actionable information. As of this writing, the primary disadvantage of using AI is that it is expensive to process the large amounts of data that AI programming requires.

Advantages

  • Good at detail-oriented jobs;
  • Reduced time for data-heavy tasks;
  • Delivers consistent results; and
  • AI-powered virtual agents are always available.

Disadvantages

  • Expensive;
  • Requires deep technical expertise;
  • Limited supply of qualified workers to build AI tools;
  • Only knows what it’s been shown; and
  • Lack of ability to generalize from one task to another.

 

Quantum Entanglement

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  • Quantum entanglement is a quantum mechanical phenomenon in which the quantum states of two or more objects have to be described with reference to each other, even though the individual objects may be spatially separated.
  • This leads to correlations between observable physical properties of the systems.
  • For example, it is possible to prepare two particles in a single quantum state such that when one is observed to be spin-up, the other one will always be observed to be spin-down and vice versa, this despite the fact that it is impossible to predict, according to quantum mechanics, which set of measurements will be observed.
  • As a result, measurements performed on one system seem to be instantaneously influencing other systems entangled with it.
  • But quantum entanglement does not enable the transmission of classical information faster than the speed of light.
  • Quantum entanglement has applications in the emerging technologies of quantum computing and quantum cryptography, and has been used to realize quantum teleportation experimentally.
  • At the same time, it prompts some of the more philosophically oriented discussions concerning quantum theory.
  • The correlations predicted by quantum mechanics, and observed in experiment, reject the principle of local realism, which is that information about the state of a system should only be mediated by interactions in its immediate surroundings.
  • Different views of what is actually occurring in the process of quantum entanglement can be related to different interpretations of quantum mechanics.

 

 

Einestiens Spooky Action at a Distance

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One of the strangest aspects of quantum physics is entanglement: If you observe a particle in one place, another particle—even one light-years away—will instantly change its properties, as if the two are connected by a mysterious communication channel. Scientists have observed this phenomenon in tiny objects such as atoms and electrons. But in two new studies, researchers report seeing entanglement in devices nearly visible to the naked eye.

“There really is an interesting open question, which is: ‘How far can you go up in scale?’” says Andrew Armour, a physicist at the University of Nottingham in the United Kingdom who wasn’t involved in the work. The advance could also pave the way for ultrasensitive measurements of gravity and a hack-proof quantum internet.

Albert Einstein colorfully dismissed quantum entanglement—the ability of separated objects to share a condition or state—as “spooky action at a distance.” Over the past few decades, however, physicists have demonstrated the reality of spooky action over ever greater distances—even from Earth to a satellite in space. But the entangled particles have typically been tiny, which makes it easier to shield their delicate quantum states from the noisy world.

https://www.youtube.com/watch?v=ZuvK-od647c