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Screenwriter Akela Cooper on how TikTok led to 'M3GAN' Unrated

Mashable

M3GAN is what you'd get if I, Robot came with an American Doll skin and someone forgot to update its Zeroth Law(Opens in a new tab) code. The pint-sized slasher is a foul-mouthed bot with a continuously learning AI whose prime directive is to kill anyone who even thinks about taking her away from her child bestie. Screenwriter Akela Cooper (Malignant, The Nun II) never predicted her screenplay about a little girl struggling with grief would be a huge hit at the box office, much less end up with a PG-13 rating -- a rare rating for horror films. Directed by Gerard Johnstone (Housebound), with a screenplay by Cooper based on a story from Cooper and James Wan, M3GAN centers around Gemma (Allison Williams), an engineer at a tech toy company who enlists a life-sized android called M3GAN to help care for her orphaned niece Cady (Violet McGraw). In February, the theatrical cut and the unrated version were released on Peacock's streaming service.


How to be more mindful by taking more selfies

Mashable

March Mindfulness is an annual Mashable series that explores the intersection of meditation practice and technology. The psychology professor and the brain expert did not set out to study selfies, exactly. But what they found might just make you want to snap more of them. The scientists were in search of awe, a complex but key human emotion that we've only just started to explore through an experimental lens. As UC Berkeley psychologist Dacher Keltner relates in Awe: The New Science of Everyday Wonder(Opens in a new tab) (2023), he and UCSF neuroscientist Virginia Sturm asked two groups of seniors to document a walk once a week for eight weeks.


[Project] Machine Learning for Audio: A library for audio analysis, feature extraction, etc : MachineLearning

#artificialintelligence

First, librosa is a very good audio feature library. Our team wants to do audio MIR related business at mobile end, all operations of feature extraction must be fast and cross-platform support for the mobile end. For training, we used the librosa method to extract CQT-related features at that time. It took about 3 hours for 10000 sample data, which was really slow. Each sample data is 128ms(sampling rate: 32000, data length: 4096). The total time it takes to extract features from 1000 sample data.


From Centralized to Federated Learning

#artificialintelligence

Federated Learning (FL) is a method to train Machine Learning (ML) models in a distributed setting [1]. The idea is that clients (for example hospitals) want to cooperate without sharing their private and sensitive data. Each client holds their private data in FL and trains an ML model on it. Then a central server collects and aggregates the model parameters, thus building a global model based on information from all the data distribution. Ideally, this serves as privacy protection by design.


Verify you are not a bot

#artificialintelligence

Before viewing the Assistant Director for Operations at University of Texas at Austin job, please verify that you are a human and not a robot overlord.


Nvidia set to reveal new AI technologies at annual conference

#artificialintelligence

Analysts will be watching for the Santa Clara, California-based company to give more details about how it plans to widen accessibility to processing power like to that used to develop fast-rising technologies such as the chatbot ChatGPT. Last month, Huang told investors it would launch its own cloud computing service to offer more readily available access to large systems built with its chips. At the Tuesday conference, he will discuss "what's coming next" in AI, the company said on its website. Nvidia has come to dominate the field for selling chips used to developing generative AI technologies, which can answer questions with human-like text or generate fresh images based on a text prompt. Those new technologies rely on the use of thousands of Nvidia chips at once to train the AI systems on huge troves of data.


@danvillalba stories

#artificialintelligence

If you have been using twitter recently I bet that from the last 10 tweets 5 of them are linked to AI and the rise of chatGPT. Looking at those tweets AI tools are going to change the world as we know it. This is even more significant in the case of Education and in particular in Higher Education where most of the traditional methods of assessments are based on essay that consists on pieces of written work where students have to answer questions in a specific number of words. A lot of messages that I hear from institutions, and normally from traditional institutions, is that we need to ban chatGPT as this is a danger and a temptation to student to cheat and create this contractual cheating situation were students are submitting work that is not they original work. I think that this view is completely wrong and it is just a way to avoid the problem without thinking first why there is a problem and second what is actually AI and the possible benefits that can bring to education, learning outcomes and yes to assessments.


AI Text Generators: The Key to Unlocking Limitless Writing Creativity

#artificialintelligence

AI text generators, also known as language models, are algorithms that use artificial intelligence to generate human-like text based on a given prompt or seed text. These models are trained on vast amounts of text data, learning patterns, and relationships within the data to produce coherent and meaningful responses. AI or ML text generators can be used in a wide range of applications, including chatbots, customer service, content creation, and even creative writing. The Global AI Text Generator Market was valued at USD 360 million in 2022 and is expected to grow at a CAGR of 18% during the forecast period of 2023-2032 to reach USD 1,808 million. AI/ML generators can be used to produce responses to user queries in a conversational and natural manner, making them useful in developing chatbots for customer service or online support.


The Quest for Injectable Brain Implants Has Begun

WIRED

Our world is populated by hundreds of thousands of cyborgs. Some are Parkinson's patients, who can shut off their tremors by activating metal electrodes implanted deep within their brains. Others--albeit far fewer--are completely paralyzed people who can move robotic limbs with their minds, thanks to their own implants. Such technologies can radically improve someone's quality of life. But they have a major problem: Metal and the brain get along very, very poorly.


Back Propagation. Backpropagation is a popular algorithm…

#artificialintelligence

Backpropagation is a popular algorithm used for training neural networks. Here, X is the input data, y is the corresponding output data, hidden_layer_size is the number of neurons in the hidden layer, learning_rate is the learning rate, and num_iterations is the number of iterations to train the model for. The sigmoid() function computes the sigmoid activation function. Here, we define the sigmoid activation function, which takes in an input value x and returns the output of the sigmoid function. Next, we define the derivative of the sigmoid function, which takes in an input value x and returns the derivative of the sigmoid function with respect to x.