If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The graph represents a network of 1,251 Twitter users whose tweets in the requested range contained "#iiot", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 14 September 2021 at 21:00 UTC. The requested start date was Tuesday, 14 September 2021 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 1-day, 16-hour, 41-minute period from Sunday, 12 September 2021 at 07:20 UTC to Tuesday, 14 September 2021 at 00:01 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.
Edge AI chip startup Deep Vision has raised $35 million in a series B round of funding led by Tiger Global, joined by existing investors Exfinity Venture Partners, Silicon Motion and Western Digital. The company began shipping its first-generation chip last year. ARA-1 is designed for power-efficient, low-latency edge AI processing in applications like smart retail, smart city and robotics. While the company's name suggests a focus on convolutional neural networks, ARA-1 can also accelerate natural language processing with support for complex networks such as long short-term memory (LSTMs) and recurrent neural networks (RNNs). A second-generation chip, ARA-2 with additional features for accelerating LSTMs and RNNs will launch next year.
Deep Learning for NLP - Part 9 Natural language processing (NLP) is a crucial part of artificial intelligence (AI), modeling how people share information. Description Since the proliferation of social media usage, hate speech has become a major crisis. On the one hand, hateful content creates an unsafe environment for certain members of our society. On the other hand, in-person moderation of hate speech causes distress to content moderators. Additionally, it is not just the presence of hate speech in isolation but its ability to dissipate quickly, where early detection and intervention can be most effective.
Take a look at how AI companies are implementing AI. By automating procedures and operations that formerly required human intervention, Artificial Intelligence (AI) is increasing company efficiency and production. AI is also capable of comprehending data at a level that no human has ever achieved. This skill has the potential to be extremely useful in the workplace. AI has the potential to enhance every function, business, and industry.
A Complete Guide on TensorFlow 2.0 using Keras API, Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0 Created by Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, Luka AnicinPreview this Course - GET COUPON CODE Welcome to Tensorflow 2.0! TensorFlow 2.0 has just been released, and it introduced many features that simplify the model development and maintenance processes. From the educational side, it boosts people's understanding by simplifying many complex concepts. From the industry point of view, models are much easier to understand, maintain, and develop. Deep Learning is one of the fastest growing areas of Artificial Intelligence.
As the demand for data science professionals grows rapidly, students are looking for data science crash courses to gain the necessary knowledge and high-end skills needed to tackle real-world challenges. Here are the top data science courses for data aspirants to pursue. The program features a five-course series formulated to boost the foundation of data scientists in the areas of machine learning, data science, and statistics. This course is best suited for students wanting to learn big data analysis. The course gives you a deep understanding of statistics, data analysis techniques, machine learning algorithms, and probability.
Music is an indispensable element in film: it establishes atmosphere and mood, drives the viewer's emotional reactions, and significantly influences the audience's interpretation of the story. In a recent paper published in PLOS ONE, a research team at the USC Viterbi School of Engineering, led by Professor Shrikanth Narayanan, sought to objectively examine the effect of music on cinematic genres. Their study aimed to determine if AI-based technology could predict the genre of a film based on the soundtrack alone. "By better understanding how music affects the viewer's perception of a film, we gain insights into how film creators can reach their audience in a more compelling way," said Narayanan, University Professor and Niki and Max Nikias Chair in Engineering, professor of electrical and computer engineering and computer science and the director of USC Viterbi's Signal Analysis and Interpretation Laboratory (SAIL). The notion that different film genres are more likely to use certain musical elements in their soundtrack is rather intuitive: a lighthearted romance might include rich string passages and lush, lyrical melodies, while a horror film might instead feature unsettling, piercing frequencies and eerily discordant notes.
Free Coupon Discount - Deep Learning: Advanced Computer Vision (GANs, SSD, More!), VGG, ResNet, Inception, SSD, RetinaNet, Neural Style Transfer, GANs More in Tensorflow, Keras, and Python Created by Lazy Programmer Inc. English [Auto], Italian [Auto] Students also bought Deep Learning: Advanced NLP and RNNs Deep Learning: Convolutional Neural Networks in Python Recommender Systems and Deep Learning in Python Deep Learning: Recurrent Neural Networks in Python PyTorch: Deep Learning and Artificial Intelligence Preview this Udemy Course - GET COUPON CODE Latest update: Instead of SSD, I show you how to use RetinaNet, which is better and more modern. I show you both how to use a pretrained model and how to train one yourself with a custom dataset on Google Colab. This is one of the most exciting courses I've done and it really shows how fast and how far deep learning has come over the years. When I first started my deep learning series, I didn't ever consider that I'd make two courses on convolutional neural networks. I think what you'll find is that, this course is so entirely different from the previous one, you will be impressed at just how much material we have to cover.
The volume of data keeps growing. Statista believe that 59 Zettabytes were produced in 2020 and that 74 Zettabytes will be produced in 2021. A Zettabyte is a trillion gigabytes! Artificial Intelligence (AI) deals with the area of developing computing systems which are capable of performing tasks that humans are very good at, for example recognising objects, recognising and making sense of speech, and decision making in a constrained environment. It was founded as a field of academic research at the Dartmouth College in 1956.
Today more than ever, people are voicing concerns regarding biases in news media. Especially in the political arena, there are accusations of favouritism or disfavour in reporting, often expressed through the emphasizing or ignoring of certain political actors, policies, events, or topics. Is it possible to develop objective and transparent data-driven methods to identify such biases, rather than relying on subjective human judgements? MIT researchers Samantha D'Alonzo and Max Tegmark say "yes," and have proposed an automated method for measuring media bias. The proposed data-driven approach produces results that are in close accordance with human-judgement classifications on left-right and establishment biases.