Artificial Intelligence, Some important facts

Artificial Intelligence, Some important facts:

• 1.Artificial intelligence is an expansive branch of computer science that focuses on building smart machines.
• 2.American computer scientist John McCarthy coined the term artificial intelligence back in 1956.
• 3.Artificial intelligence and robotics are two entirely separate fields.
• 4.The four artificial intelligence types are reactive machines, limited memory, Theory of Mind, and self-aware.
• 5.Other subsets of AI include big data, machine learning, and natural language processing.
• 6.Artificial intelligence examples include Face ID, the search algorithm, and recommendation algorithm, among others.

The words artificial intelligence may seem like a far-off concept that has nothing to do with us. But the truth is that we encounter several examples of artificial intelligence in our daily lives.

From Netflix‘s movie recommendation to Amazon‘s Alexa, we now rely on various AI models without knowing it. 

How to Make Vermicompost

 

How to Make Vermicompost | How To make Vermicompost at Home From Kitchen Waste

Vermi-composting, that is composting with worms is super easy and great for plants. All you need is a box that you put some worms in and some organic material. One can keep them inside the house (the smell is not a problem), so they are always at a comfortable temp. If you keep them outside, just pay attention to keeping them out of the sun when its hot and in the sun when its cold, that’s probably enough, depending on where you live.

To make a worm bin you need two plastic bins. One bin sits inside the other, and has some small holes drilled in the bottom so water can drain from the compost into the second bin.

The first bin don’t actually do anything to, except put some kind of spacers at the bottom. Here put some small old Tupperware containers but just about anything will work, some scraps of wood, small coffee cups just about anything you can think of. This is just to create a space that excess water can collect.We only need one lid for the system, and want to cut some holes to allow the worms to breathe.

Having a lid like this helps keep the smell down if you keep your worm bin inside. Drill a few holes in the lid, then covered it with landscape fabric, the stuff you put under rocks and mulch to keep weeds down. Just about any kind of fine netting should work fine, this is just to keep the worms from escaping.  Keep it in the basement and or below the portico  never you will be been able to smell bad.

Get the worms from any near by nurssery or there’s no reason you can’t collect your own worms if you do a little bit of digging, especially shortly after a rain, you want red wigglers or earthworms.

You can put just about any organic material in the bins, but don't use meat or dairy. you may have also heard that citrus is bad, don't use it.

After a few months the worms will have reproduced and number in the thousands. They will produce wonderful compost in much less time than a normal pile. 

 

Artificial Intelligence in Sleep Medicine

In recent years there has been a rapid emergence of artificial intelligence (AI) in the field of sleep medicine. AI refers to the capability of computer systems to perform tasks conventionally thought to require human intelligence, such as

Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. There are three main areas where sleep medicine benefits from AI. 

➤The first application is modernizing the scoring process of polysomnography (PSG). Currently, the sleep technologists play a major role on judicating the 30-second sleep epochs as awake or asleep and/or the stage of sleep. The AI has potential to improve this lengthy process, and expedite sleep reports.

 [polysomnography (PSG) Meaning➤a type of sleep study, is a multi-parameter study of sleep and a diagnostic tool in sleep medicine. The test result is called a polysomnogram, also abbreviated PSG]. 

➤The second application of AI in sleep is leveraging the longitudinal data accumulated within electronic medical records (EMR). Sleep medicine is primed to benefit from AI used in population health research. Researchers have successfully leveraged “big data” to offer new insights into sleep physiology, improve the accuracy of diagnosis of sleep disorders, predict response and adherence to treatment, and use sleep parameters as predictors of future physical and mental health. This leads to treatment optimization and personalization. 

➤The third application of AI in sleep medicine is the use of wearable sensors. The wearable sensors show promise in tracking health records and linking several digital biomarkers to the overall health condition of patients. They provide an opportunity to elevate the traditional EMR to the new level of electronic health records (EHR) by measuring several parameters and synchronizing multilevel bio-potentials and health time series.

These applications will likely become more widely available, empowering people to improve their sleep, through the possibility of better understanding their sleeping patterns. Ultimately this can result in a reduction in sleep health disparities.

The goal of this research topic is to inform advances in the use of artificial intelligence (AI) in the field of sleep medicine.

Topics of interest include (but are not limited to) Artificial Intelligence and Machine Learning related to:

1. Assisting and enhancing polysomnography scoring
2. Supporting clinical decision
3. Providing new insights to inform the clinical care of sleep disorders
3. Leveraging the electronic medical records (EMR)
4. Managing and monitoring population health
5. Advancing our understanding of the integral role sleep plays in human health
6. Harnessing the potential of wearable devices (i.e. wrist actigraphy) into sleep medicine
7. Integrating wearables devices into EMR for remote health monitoring and at-home health application
8. Understanding and addressing sleep health disparities

Difference between Artificial intelligence and Machine learning?

 

Difference between Artificial intelligence and Machine learning?

Artificial Intelligence

Artificial intelligence is a field of computer science which makes a computer system that can mimic human intelligence. It is comprised of two words "Artificial" and "intelligence", which means "a human-made thinking power." Hence we can define it as,

Artificial intelligence is a technology using which we can create intelligent systems that can simulate human intelligence.

The Artificial intelligence system does not require to be pre-programmed, instead of that, they use such algorithms which can work with their own intelligence. It involves machine learning algorithms such as Reinforcement learning algorithm and deep learning neural networks. AI is being used in multiple places such as Siri, Google?s AlphaGo, AI in Chess playing, etc.

Based on capabilities, AI can be classified into three types:

• Weak AI
• General AI
• Strong AI

Currently, we are working with weak AI and general AI. The future of AI is Strong AI for which it is said that it will be intelligent than humans.

Machine learning

Machine learning is about extracting knowledge from the data. It can be defined as,

Machine learning is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.

Machine learning enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate result or give predictions based on that data.

Machine learning works on algorithm which learn by it?s own using historical data. It works only for specific domains such as if we are creating a machine learning model to detect pictures of dogs, it will only give result for dog images, but if we provide a new data like cat image then it will become unresponsive. Machine learning is being used in various places such as for online recommender system, for Google search algorithms, Email spam filter, Facebook Auto friend tagging suggestion, etc.