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Experts predict when machines will be better than you at your job

#artificialintelligence

The experts predict that AI will outperform humans in the next 10 years in tasks such as translating languages (by 2024), writing high school essays (by 2026), and driving trucks (by 2027). Forty years is an important number when humans make predictions because it is the length of most people's working lives. To find out if different groups made different predictions, Grace and co looked at how the predictions changed with the age of the researchers, the number of their citations (i.e., their expertise), and their region of origin. While North American researchers expect AI to outperform humans at everything in 74 years, researchers from Asia expect it in just 30 years.


Experts predict when machines will be better than you at your job

#artificialintelligence

The experts predict that AI will outperform humans in the next 10 years in tasks such as translating languages (by 2024), writing high school essays (by 2026), and driving trucks (by 2027). Forty years is an important number when humans make predictions because it is the length of most people's working lives. To find out if different groups made different predictions, Grace and co looked at how the predictions changed with the age of the researchers, the number of their citations (i.e., their expertise), and their region of origin. While North American researchers expect AI to outperform humans at everything in 74 years, researchers from Asia expect it in just 30 years.


Experts predict when machines will be better than you at your job

#artificialintelligence

The experts predict that AI will outperform humans in the next 10 years in tasks such as translating languages (by 2024), writing high school essays (by 2026), and driving trucks (by 2027). Forty years is an important number when humans make predictions because it is the length of most people's working lives. To find out if different groups made different predictions, Grace and co looked at how the predictions changed with the age of the researchers, the number of their citations (i.e., their expertise), and their region of origin. While North American researchers expect AI to outperform humans at everything in 74 years, researchers from Asia expect it in just 30 years.


How to Solve the New $1 Million Kaggle Problem - Home Value Estimates

@machinelearnbot

More specifically, I provide here high-level advice, rather than about selecting specific statistical models or algorithms, though I also discuss algorithm selection in the last section. If this is the case, an easy improvement consists of increasing value differences between adjacent homes, by boosting the importance of lot area and square footage in locations that have very homogeneous Zillow value estimates. Then for each individual home, compute an estimate based on the bin average, and other metrics such as recent sales price for neighboring homes, trend indicator for the bin in question (using time series analysis), and home features such as school rating, square footage, number of bedrooms, 2- or 3-car garage, lot area, view or not, fireplace(s), and when the home was built. With just a few (properly binned) features, a simple predictive algorithm such as HDT (Hidden Decision Trees - a combination of multiple decision trees and special regression) can work well, for homes in zipcodes (or buckets of zipcodes) with 200 homes with recent historical sales price.


Experts predict when machines will be better than you at your job

#artificialintelligence

The experts predict that AI will outperform humans in the next 10 years in tasks such as translating languages (by 2024), writing high school essays (by 2026), and driving trucks (by 2027). Forty years is an important number when humans make predictions because it is the length of most people's working lives. To find out if different groups made different predictions, Grace and co looked at how the predictions changed with the age of the researchers, the number of their citations (i.e., their expertise), and their region of origin. While North American researchers expect AI to outperform humans at everything in 74 years, researchers from Asia expect it in just 30 years.


Experts predict when machines will be better than you at your job

#artificialintelligence

The experts predict that AI will outperform humans in the next 10 years in tasks such as translating languages (by 2024), writing high school essays (by 2026), and driving trucks (by 2027). Forty years is an important number when humans make predictions because it is the length of most people's working lives. To find out if different groups made different predictions, Grace and co looked at how the predictions changed with the age of the researchers, the number of their citations (i.e., their expertise), and their region of origin. While North American researchers expect AI to outperform humans at everything in 74 years, researchers from Asia expect it in just 30 years.


AI and ML Futures 2: The Quiet Revolution

#artificialintelligence

First of all, I want to highlight something that seems to go missing in the current hype. There is a lot more to machine learning than deep convolutional neural nets and recurrent nets. I don't want to diminish the contribution of those methods, there have been some really cool breakthroughs in these domains. However, they rely on very large data and massive computational capabilities. However, many problems involve less data and even when there is large data it can be the case that the computational demands of conv-nets and recurrent networks are too high (just like they were 20 years ago when these methods were first proposed!).


Blueoptima

#artificialintelligence

Machine Learning is most often considered a branch of the broad pursuit of Artificial Intelligence in which it is used to process unstructured data, such as text. But there is an even greater potential for its application in enhancing analytics of structured numerical data. In this domain, we predict Machine Learning capabilities will continue to offer further insights by discovering patterns in our extensive data set of more than 4.2 billion observations of software development revisions. Machine Learning offers an extension of the sophistication of data analytics, from automating analyses that our statisticians carry out, to discovering patterns that humans cannot. For example, our data scientists recognise that a software application that is no longer being worked on is likely to be no longer in use and can be retired.


How to Make Baseline Predictions for Time Series Forecasting with Python - Machine Learning Mastery

#artificialintelligence

Establishing a baseline is essential on any time series forecasting problem. A baseline in performance gives you an idea of how well all other models will actually perform on your problem. In this tutorial, you will discover how to develop a persistence forecast that you can use to calculate a baseline level of performance on a time series dataset with Python. How to develop a persistence model from scratch in Python. How to evaluate the forecast from a persistence model and use it to establish a baseline in performance.


How to Get Started as a Developer in AI

#artificialintelligence

The promise of artificial intelligence has captured our cultural imagination since at least the 1950s--inspiring computer scientists to create new and increasingly complex technologies, while also building excitement about the future among regular everyday consumers. What if we could explore the bottom of the ocean without taking any physical risks? While our understanding of AI--and what's possible--has changed over the the past few decades, we have reason to believe that the age of artificial intelligence may finally be here. So, as a developer, what can you do to get started? While there are a lot of different ways to think about AI and a lot of different techniques to approach it, the key to machine intelligence is that it must be able to sense, reason, and act, then adapt based on experience.