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School of fish swimming in heart formation stuns onlookers: Drone footage
Paul Dabill captured stunning drone footage of a school of fish swimming in a heart-shaped formation in Palm Beach, Florida. These Palm Beach fish deserve a gold medal in artistic swimming. Take a look at this school of Crevalle jack fish that were spotted swimming in a heart-shaped formation right off the shores of Juno Beach, according to South West News Service (SWNS). FLORIDA FISHERMEN CATCH A WARSAW GROUPER THAT WAS BIGGER THAN A MAN: 'IT WAS A MONSTER' The stunning footage was captured by Paul Dabill, who reportedly took his DJI Mavic Air 2 drone out for a spin Tuesday morning. Restaurant owner Paul Dabill captured stunning aerial drone footage of a school of fish swimming in a heart-shaped formation on Oct. 5, 2021.
Recommender Engines: AI On Steroids For E-commerce - Liwaiwai
When I open any website offering services or goods, I always check how well a recommender system works. Big business also adores recommender engines as much as I do, so I am in good company. "Recommender engines or recommenders, as they are sometimes called, are the most useful applications of Machine Learning Algorithms." – Harvard Business Review. And they help me to choose another plant to the disappointment of my husband ( "One more plant? We have a dozen of them already!").
How Musicologists and Scientists Used AI to Complete Beethoven's Unfinished 10th Symphony
When Ludwig van Beethoven died in 1827, he was three years removed from the completion of his Ninth Symphony, a work heralded by many as his magnum opus. He had started work on his 10th Symphony but, due to deteriorating health, wasn't able to make much headway: All he left behind were some musical sketches. Ever since then, Beethoven fans and musicologists have puzzled and lamented over what could have been. His notes teased at some magnificent reward, albeit one that seemed forever out of reach. Now, thanks to the work of a team of music historians, musicologists, composers and computer scientists, Beethoven's vision will come to life. I presided over the artificial intelligence side of the project, leading a group of scientists at the creative AI startup Playform AI that taught a machine both Beethoven's entire body of work and his creative process.
Black women, AI, and overcoming historical patterns of abuse
The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. After a 2019 research paper demonstrated that commercially available facial analysis tools fail to work for women with dark skin, AWS executives went on the attack. Instead of offering up more equitable performance results or allowing the federal government to assess their algorithm like other companies with facial recognition tech have done, AWS executives attempted to discredit study coauthors Joy Buolamwini and Deb Raji in multiple blog posts. More than 70 respected AI researchers rebuked this attack, defended the study, and called on Amazon to stop selling the technology to police, a position the company temporarily adopted last year after the death of George Floyd. But according to the Abuse and Misogynoir Playbook, published earlier this year by a trio of MIT researchers, Amazon's attempt to smear two Black women AI researchers and discredit their work follows a set of tactics that have been used against Black women for centuries.
Restricted Boltzmann Machine (RBM)
Restricted Boltzmann Machine is used to detect patterns in data, in an unsupervised way. If you haven't read the previous posts yet, you can read them by clicking the below links. RBMs are self-learning shallow neural networks that learn to reassemble data. They're significant models because they can extract meaningful features from a given input without having to identify them. Let's start with the fact that we have access to a matrix of viewer ratings for a specific number of Netflix movies, where each row represents a movie and each column represents a user's rating.
Staff Data Scientist - Freemium
The Freemium R&D team oversees the entire user journey on Spotify and ensures we engage with people in innovative ways, every step of the way. Our team grows Spotify's audience by finding future listeners around the world and delivering the right value to them, at the right time. With research, product development, product design, engineering, and marketing all collaborating in one organization, we're able to quickly create meaningful features and services for millions of people around the world, resulting in joyful, long-lasting relationships with Spotify. We are looking for a Staff Data Scientist to join the Freemium Product Insights team. The team consists of 85 highly motivated, friendly individuals, specialising in both Data Science and User Research, using their skills to build a holistic understanding of our Free and Premium users.
Time Is Ripe For Responsible AI In Aviation
In the movie '2001: A Space Odyssey', there is a chilling interaction between an astronaut – David Bowman, and a sentient computer- HAL (Heuristically programmed Algorithmic computer). I'm afraid I can't do that." The story goes that HAL learns, by reading their lips, that the astronauts are going to shut it down, fearing that it is malfunctioning. HAL then decides to kill the astronauts so that it can continue its programmed directives. The movie came out in 1968, and some of the novels in the Space Odyssey series by Arthur C. Clarke are even older.
Google AI Introduces FLAN, A Language Model with Instruction Fine-Tuning
Google AI recently introduced their new Natural Language Processing (NLP) model, known as Fine-tuned LAnguage Net (FLAN), which explores a simple technique called instruction fine-tuning, or instruction tuning for short. In general, fine-tuning requires a large number of training examples, along with stored model weights for each downstream task which is not always practical, particularly for large models. FLAN's instruction fine-tuning technique involves fine-tuning a model not to solve a specific task, but to also make it more amenable to solving NLP tasks in particular. FLAN is fine-tuned on a large set of varied instructions that use a simple and intuitive description of the task, such as "Classify this movie review as positive or negative," or "Translate this sentence to Danish." Creating a dataset of instructions from scratch to fine-tune the model would take a considerable amount of resources.