Meet Flippy, our new kitchen assistant

 

Flipping Burger by Flippy

Flippy is the robot that is an expert at flipping burgers in hamburger restaurant CaliBurger and put them on the bun. It can grill 150-300 patties with excellence in one hour. It's a robot that doesn't need to wear a hairnet while working in the kitchen. Flippy can also change the sides of patties and can select spatulas that are needed at a specific time. David Zito, the CEO of Miso and manufacturer of Flippy shared his thoughts:

''Flippy is the world’s first autonomous robotic kitchen assistant that can learn from its surrounding and acquire new skills over time.''

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How Machine Learning Algorithms Make Self-Driving Cars a Reality

 

Machine learning algorithms make it possible for self-driving cars to exist. They allow a car to collect data on its surroundings from cameras and other sensors, interpret it, and decide what actions to take. Machine learning even allows cars to learn how to perform these tasks as well as (or even better than) humans.

List of Common Machine Learning Algorithms

• Linear Regression.
• Logistic Regression.
• Decision Tree.
• SVM.
• Naive Bayes.
• kNN.
• K-Means.
• Random Forest.

Machine learning in autonomous driving can be supervised or unsupervised. The main difference between the two options lies in the amount of human input required for learning. In supervised learning, a computer interprets data and makes predictions based on input data, then compares those predictions to correct output data in order to improve future predictions. In unsupervised learning, data isn’t labeled. So the computer learns to recognize the inherent structure based on input data only.

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11 Facts about Data Science that you must know

 

 Statistics, Machine Learning, Data Science, or Analytics – whatever you call it, this discipline is on rising in last quarter of century primarily owing to increasing data collection abilities and an exponential increase in computational power. The field is drawing from the pool of engineers, mathematicians, computer scientists, and statisticians, and increasingly, is demanding a multi-faceted approach for successful execution. 

11 Facts about Data Science,  more details:

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Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges.

 Cancer is an aggressive disease with a low median survival rate.

We explore how AI assists cancer diagnosis and prognosis, specifically with regard to its unprecedented accuracy, which is even higher than that of general statistical applications in oncology. We also demonstrate ways in which these methods are advancing the field. Finally, opportunities and challenges in the clinical implementation of AI are discussed. Hence, this article provides a new perspective on how AI technology can help improve cancer diagnosis and prognosis and continue improving human health in the future.

Highlights

•

Artificial intelligence (AI) has reached new heights in clinical cancer research in recent years.

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AI is applied to assist cancer diagnosis and prognosis, given its unprecedented accuracy level, which is even higher than that of a general statistical expert.

•

An overview of how AI applied in clinical cancer could be leveraged in this area and thereby contribute to improved human health.

For more information: 

And also include How AI cure Cancer 

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Data Science vs. Data Analytics vs. Machine Learning: Expert Talk

Data science is a concept used to tackle big data and includes preparation, and analysis. A data scientist gathers data from multiple sources and applies machine learning, predictive analytics, and sentiment analysis to extract critical information from the collected data sets.

A data analyst is usually the person who can do basic descriptive statistics, visualize data, and communicate data points for conclusions. They must have a basic understanding of statistics, a perfect sense of databases, the ability to create new views, and the perception to visualize the data.

Machine learning can be defined as the practice of using algorithms to extract data, learn from it, and then forecast future trends for that topic. Traditional machine learning software is statistical analysis and predictive analysis that is used to spot patterns and catch hidden insights based on perceived data. 

Do you know more about this?

1. Data Science vs. Data Analytics

2. Data Science vs. Machine Learning

3. Enroll in Our PGP in Data Analytics, Data Science, AI and Machine Learning Today

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Researchers develop artificial intelligence that can detect sarcasm in social media

" SARCASM "

"Sarcasm has been a major hurdle to increasing the accuracy of sentiment analysis, especially on social media, since sarcasm relies heavily on vocal tones, facial expressions, and gestures that cannot be represented in text," says Brian Kettler, a program manager in DARPA's Information Innovation Office (I2O). "Recognizing sarcasm in textual online communication is no easy task as none of these cues are readily available."

The team, which includes computer science doctoral student Ramya Akula, began working on this problem under a DARPA grant that supports the organization's Computational Simulation of Online Social Behavior program.

The team's findings were recently published in the journal Entropy.

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AI and biometrics in 2021: Predictions, trends, and insights for what might lie ahead.

Biometrics and AI: Biometric security solutions and AI-powered fraud prevention technologies have, for several years now, been transforming the ways in which organizations protect their business, their customers, and their employees. In fact, some industry estimates reveal that AI and biometrics have combined to prevent billions of dollars in losses from fraud—already.

let's see
AI and biometrics in 2021: Predictions, trends, and insights for what might lie ahead.

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