Drawbacks of Artificial Intelligence

Artificial Intelligence is a terminology used in machines as simulated or artificially generated intelligence. These machines are totally programmed to think as human think and to mimic in the same manner a person acts. The best out of artificial intelligence is that has the ability to rationalize and react as per the situations because it totally works on the command and commands are programmed in these machines.

Artificial Intelligence can be best utilised in order to achieve specific goals. Scientists are using their minds to exhibit traits in these machines in order to understand problems and resolve it. Although, this intelligent technology has some drawbacks also, which you must know upfront.

Malfunction of Artificial Intelligence

The aim of artificial intelligence include learning, reasoning and perception and machine are wired using of a cross-disciplinary approach based in science, maths & psychology. As technology advances, previous benchmarks that defined artificial intelligence become outdated.
Examples of artificial intelligence are self-driven cars; computers that play chess are the new development in this field. Computers need to predict the situations and react accordingly like in chess; the end result is winning the game. Same as in the case of self-driven cars, a computer needs to consider all the external data and analyse it in order to get prevented from any disaster or accident.

Disputes on Artificial Intelligence

One common phenomenon is that machines will become so highly developed that human civilisation won’t be able to keep up with it. Another is that these machines can actually hack into human’s privacy and could use it as a weapon against humanity. It came to notice that people are arguing for making code of conduct or ethics for artificial intelligence also or otherwise they should also be treated same like as humans.
Self-driven cars are a subject matter of controversy, as their machines are designed for lowest possible risks and least casualties. While they remove the incidence of human error, it means if they were put in a situation in which they had to decide between a crash with one person and a crash with another then, they would calculate which crash would lead to fewer amounts of damage and the risks but yes, it would need to choose one. People are disagreeing with the fact that lives of humans should not be put at the mercy of a machine.

Artificial Intelligence

3 Driving Factors of Artificial Intelligence

Artificial Intelligence is no doubt the next generation technology everyone is looking forward to. China who wants to be the world leader in Artificial Intelligence has added AI in the school curriculum of high-school students. Now, you can imagine the importance of AI in the coming future.

AI has already put his legs on various verticals of the industry including automobile, healthcare, finance, manufacturing and retail to name a few. From robotic surgery to self-driving cars, AI has proven its implications on each and every application. But what actually is driving the Artificial Intelligence?

Well, companies like Amazon, Facebook, Apple, Google, IBM as well as Microsoft are investing in the research and development of AI. However, there are 3 factors which are accelerating the growth of Artificial Intelligent.

Next-Generation Computing Architecture (GPU)

Machine Learning and Artificial Intelligence require speedy processors. The traditional microprocessors and CPUs are not meant for Machine Learning. They require a new breed of processors. This made the rise of GPU. The Graphics Processing Units which used to be the part of high-end gaming PC’s and workstations have seen a tremendous growth after the evolution of AI.

GPU’s come with numerous cores that speed up the ML training process. Seeing the growth of AI, it might happen that down the line each CPU will come paired-up with a GPU.

Availability of Cloud

Data Scientists require large data sets and historic data for ML models to predict with more accuracy. In order to predict the weather or solve problems like detecting cancers, data scientists need a large amount of data to analyze. The efficiency of ML models depends merely on the size of data. The more the data, the better is the accuracy.

With the use of cloud and businesses, government and academia (the major data holders) unlocking their data on cloud, helped the Artificial Intelligence to grow by leaps and bounds.

Advancement in Deep Learning

Artificial Neural Network is replacing the conventional Machine Learning system. The advancement in Machine Learning Models with the new technologies like Capsule Neural Network and Transfer Learning have changes the way ML models are trained and implemented. These techniques are so advanced that they are able to produce the most accurate results with a limited data.


Various companies like IBM through IBM Watson, Microsoft with Corona, Amazon with its Alexa and major players like China are investing billions in Artificial Intelligence to make the world mobile. With selecting the clothes to turning off lights through voice and self driving cars, they want the automation to rule the world by 2030.




Use of Artificial Intelligence in Agriculture

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Artificial Intelligence is in a way too wide to understand for a common man. Still farmers are receiving text messages telling them when to sow the seeds. Farmers in Madhya Pradesh and Telangana receive automated voice calls informing them whether their crops are at risk of pest attack or not. This is what is known as Digital Agriculture. Technologies like Artificial Intelligence, Machine Learning, Satellite Imagery and Advanced Analytics combines to provide small farmers to increase their income through higher crop yield and greater price control.

Benefits of using AI in agriculture are as follows-

Use of IoT to its best

With the help of IBM Watson’ machine learning program, we can utilize drones to have a track of and calculation of data such as historic weather data, social media posts, research notes, soil information, market place data, images, etc. The drones would also monitor the crops and thus, facilitate the farmers to easily identify the area of concern. This would help the organizations, farmers and research institutes with richer insights and recommendations to take action and improve yields.

Skills and Workforce

With growing urbanisation, people prefer to live in big cities making a gap for farm workers. Cognitive technologies will help address this challenge by easing farmers’ work. Many operations will be done remotely and processes will be automated, thus, eliminate the need for several other workers. Farmers will be able to take more informed and rapid decisions.

Chatbots for Farmers

AI with the help of machine learning could facilitate the farmers with virtual assistants who could help them in real time. They could be able to interact with the farmers in their native language so that they can understand them well. This will educate the farmers at any point of time. Farmers could be leveraged to take advice and recommendations from agriculture pro chatbots.

Price Forecast

Microsoft has developed a price forecasting model which predicts the future commodity arrival ad their corresponding prices. This model uses the IoT devices and remote sensing data from geo-satellite areas to predict the historical data, other information like soil information, crop fertility, etc to depict their prices in the market.

AI will definitely bring the digital agriculture revolution. Although the road ahead is not very smooth. We have to calculate the feasibility, sustainability and efficiency meeting the world’s food needs. However, it would be interesting to see how the farmers, agri-businessmen and the consumers will utilize the power of Artificial Intelligence to shape the future of this industry.


Enrich Your Shopping Experience with AI

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Developers follow a simple dress code but this hasn’t pushed them back to help others enrich their shopping experience with Artificial Intelligence. With AI, retailers can go far beyond providing online shopping to better customize the customer’s shopping experience.

By finding a similar product online to experimenting with your makeup and hair dye from the comfort of your couch, AI provides you with everything. Now, it’s not just buying a product but enjoying your shopping without leaving your couch.

Snap and Shop

It happens manier times that you want to purchase a similar product your friend has. But, it becomes very tough to find the same product. You need to perform thorough search. But imagine if you find the same product just by posting the pic of it. Isn’t it great and time saving? You can do so by using Snap and Shop app. Just click the picture and upload it to the app, it will give you the exact or similar items. You can buy them directly through the app or at least you will get the vendor’s detail.


The AI engine which drives this app identifies the products within seconds from a large number of retailers across the globe.

Enhance your Movie Watching Experience

Do you want to wear the similar dress as Emma Stone in La La Land? Or you wish to dive into the sea where Chiron learned to swim in the movie Moonlight? Yes, your wishes can come true with TheTake. This AI based app finds the exact similar products and location you see in the movie and let you purchase them. Using machine learning technique, the app finds the most similar results available for you to purchase from its millions of products within its database.


TheTake is also working with entertainment studios, such as Universal Pictures, Sony and Comcast, to augment the viewing experience for their users while providing insights to advertisers.

Apply to Find its Suitability

It is important that you try the makeup before you purchase. It is something which costs a lot and a small variation can make it unfits for your use. However, trying the makeup consumes hours of your precious time. Just to leverage its users by saving their time applying makeup before purchase, ModiFace has created an augmented reality app which lets you apply makeup in virtual time.


ModiFace uses facial modeling technology that helps people discover products tailor-made for them. Its AI technology is already used by over 150 web and mobile apps, including L’Oreal. Partnering with Sephora, ModiFace also developed the “Sephora Virtual Artist,” a tool that allows shoppers to experiment with new makeup on their own faces using a computer screen.

AI in Chemical Industry

How Artificial Intelligence will Revolutionize the Chemical Industry

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The technological revolution has headed towards most of the industries. Even the chemical industry is untouched with this AI swift. According to the latest study, IBM, the biggest player in Artificial Intelligence has developed a program which predicts the outcomes of organic chemical reactions. This program is based on language translation software, where it thinks atoms as letter and molecules as words.

“Instead of translating English into German or Chinese, we had the same artificial intelligence technology look at hundreds of thousands or millions of chemical reactions and had it learn the basic structure of the ‘language’ of organic chemistry, and then had it try to predict the outcomes of possible organic chemical reactions,” says study co-author Teodoro Laino at IBM Research in Zurich.

“We want to help chemists design new synthesis routes for organic compounds,” Laino says. Synthesizing pharmaceuticals and other complex organic compounds is often a difficult task, “maybe requiring 30 or 40 steps,” he explains. “There’s a huge effort in the commercial sector to find shortcuts to skip a couple of steps, with the benefit of decreasing time and increasing yields.”

This Artificial Intelligence program is basically an artificial neural network where neurons are fed with data and cooperate to solve the problems. The network repeatedly adjusts the connections between its neurons to solve the problem. The task is done in a loop to find the best computing results.

This program is based on the principle where it doesn’t have to learn organic chemistry to predict the outcome reaction. It is as similar as a child who grows up speaking a native language can speak it efficiently but doesn’t know the rules of it. It also provides multiple solutions when it thinks the components can have more than two chemical reaction outcomes.

According to Philippe Schwaller, “This AI based IBM program achieves up to 80% accuracy.” The largest molecule, this program has processed has 150 atoms. However, it is just a number, there’s no theoretical reason IBM can’t work with larger molecules.

Predicting the future of this program, Mr. Gaudin of IBM Research, Zurich says that, “we plan to make this available to everyone through a cloud service, we also want to reach accuracies of 90 percent or even above. One way to do that is instead of having just a general organic chemistry model, we have more specialized models focused on specific classes of organic chemical reactions.”

Not only this, IBM plans to include factors like temperature, solvent, and pH in their AI learn. This program can thus speed up the formation of new drugs and could come out as a boon in the chemical industry. However, since the AI is not perfect, we can’t list the organic chemists in the list of jobs that AI will take over by 2030. We still need organic chemists to monitor the process and analyze the outcome reactions.