There are various types of video datasets that can be used for machine learning. YouTube-8M segments, CIFAR100, CODAHCODAH or TACO are just a few examples. Below is a listing of each. For more information, please visit our website. Let us know your thoughts! Please leave your comments! Don't forget about our curated list with the top video datasets.
CIFAR-100
The CIFAR 100 video datasets contain images that are classified according to the WordNet hierarchy. These images contain hyperlinks which describe each pixel. These datasets were created in order to fulfill two basic requirements of computer vision as well as to support other machine learning techniques. CIFAR-100 and the BDD-100K are driving datasets for independent multitasking learning. They consist of ten tasks, 100K videos, and ten tasks. This dataset is being used to estimate progress in the development of image recognition algorithms for autonomous vehicles.
YouTube-8M Segments
YouTube-8M is large labeled and contains millions of YouTube videos IDs. This dataset can be used for your machine learning project. These videos have been labeled with high-quality, machine-generated annotations and audio-visual features. The data is broken down into segments of 5 seconds each. It is very easy to use the dataset: All you have to do to create a CloudFormation template and AWS Glue Catalog entries is a matter of minutes.
CODAHCODAH
Machine learning applications that analyze video content require specific data in order to train their models. The majority of public video datasets don't meet these requirements, either because there is not enough diversity or low amounts, or because it is difficult to train algorithms. Here are some tips to help you select the best datasets to support machine learning. Identify the source of your datasets. YouTube videos include many different content, including news and sports.
TACO
This paper proposes a new machine learning approach to recognize natural sentences using TACO video datasets. This framework uses contextual information to find video segments that corresponds to a given naturally-language sentence. This method outperforms state-of-the-art approaches. It can be used for machine learning and speech recognition. Here, we describe its main characteristics and demonstrate its effectiveness on the TACO video datasets.
CMU-MOSEI
Multimodal Corpus of Sentiment Intensity, or CMU-MOSI, is a large dataset of 2199 opinion videos that have been annotated and annotated using subjectivity. It also includes various audio and visual features. This dataset is rich in terms of statistics and is ideal for machine learning studies. It contains annotated videos on every single frame. The largest global dataset of this kind contains a variety of emotion labels.
Facebook BISON
Facebook's BISON data dataset for video focuses on finer-grained visual grounding. This is in contrast to the COCO Captions dataset. This dataset complements COCO Captions. It measures the ability of systems and linguistic content to be compared to visual content. BISON helps to evaluate caption-based retrieval systems.
FAQ
Who created AI?
Alan Turing
Turing was born 1912. His father was a clergyman, and his mother was a nurse. He was an exceptional student of mathematics, but he felt depressed after being denied by Cambridge University. He discovered chess and won several tournaments. He worked as a codebreaker in Britain's Bletchley Park, where he cracked German codes.
He died in 1954.
John McCarthy
McCarthy was born in 1928. McCarthy studied math at Princeton University before joining MIT. There he developed the LISP programming language. In 1957, he had established the foundations of modern AI.
He died in 2011.
Is there another technology that can compete against AI?
Yes, but this is still not the case. Many technologies have been created to solve particular problems. All of them cannot match the speed or accuracy that AI offers.
What industries use AI the most?
The automotive industry is one of the earliest adopters AI. For example, BMW AG uses AI to diagnose car problems, Ford Motor Company uses AI to develop self-driving cars, and General Motors uses AI to power its autonomous vehicle fleet.
Other AI industries are banking, insurance and healthcare.
How does AI work
It is important to have a basic understanding of computing principles before you can understand how AI works.
Computers store information in memory. Computers process data based on code-written programs. The code tells a computer what to do next.
An algorithm is a set or instructions that tells the computer how to accomplish a task. These algorithms are usually written as code.
An algorithm can also be referred to as a recipe. A recipe can include ingredients and steps. Each step may be a different instruction. For example, one instruction might read "add water into the pot" while another may read "heat pot until boiling."
Is Alexa an Artificial Intelligence?
Yes. But not quite yet.
Amazon developed Alexa, which is a cloud-based voice and messaging service. It allows users interact with devices by speaking.
The Echo smart speaker was the first to release Alexa's technology. Other companies have since used similar technologies to create their own versions.
Some of these include Google Home, Apple's Siri, and Microsoft's Cortana.
How does AI work?
An artificial neural system is composed of many simple processors, called neurons. Each neuron processes inputs from others neurons using mathematical operations.
Neurons can be arranged in layers. Each layer has its own function. The raw data is received by the first layer. This includes sounds, images, and other information. It then sends these data to the next layers, which process them further. Finally, the output is produced by the final layer.
Each neuron has an associated weighting value. This value is multiplied each time new input arrives to add it to the weighted total of all previous values. If the result is greater than zero, then the neuron fires. It sends a signal down the line telling the next neuron what to do.
This process repeats until the end of the network, where the final results are produced.
What is the state of the AI industry?
The AI industry is growing at an unprecedented rate. There will be 50 billion internet-connected devices by 2020, it is estimated. This will enable us to all access AI technology through our smartphones, tablets and laptops.
This means that businesses must adapt to the changing market in order stay competitive. If they don't, they risk losing customers to companies that do.
Now, the question is: What business model would your use to profit from these opportunities? You could create a platform that allows users to upload their data and then connect it with others. Or perhaps you would offer services such as image recognition or voice recognition?
Whatever you choose to do, be sure to think about how you can position yourself against your competition. Even though you might not win every time, you can still win big if all you do is play your cards well and keep innovating.
Statistics
- Additionally, keeping in mind the current crisis, the AI is designed in a manner where it reduces the carbon footprint by 20-40%. (analyticsinsight.net)
- That's as many of us that have been in that AI space would say, it's about 70 or 80 percent of the work. (finra.org)
- While all of it is still what seems like a far way off, the future of this technology presents a Catch-22, able to solve the world's problems and likely to power all the A.I. systems on earth, but also incredibly dangerous in the wrong hands. (forbes.com)
- More than 70 percent of users claim they book trips on their phones, review travel tips, and research local landmarks and restaurants. (builtin.com)
- According to the company's website, more than 800 financial firms use AlphaSense, including some Fortune 500 corporations. (builtin.com)
External Links
How To
How to create an AI program that is simple
To build a simple AI program, you'll need to know how to code. There are many programming languages out there, but Python is the most popular. You can also find free online resources such as YouTube videos or courses.
Here's an overview of how to set up the basic project 'Hello World'.
You will first need to create a new file. This can be done using Ctrl+N (Windows) or Command+N (Macs).
Enter hello world into the box. Enter to save this file.
Press F5 to launch the program.
The program should display Hello World!
This is just the beginning, though. These tutorials can help you make more advanced programs.