Heartbeat

DECEMBER 8, 2023

Action: Wikipedia Action Input: "Yann LeCun" Observation: Page: Yann LeCun Summary: Yann André LeCun ( lə-KUN, French: [ləkœ̃]; originally spelled Le Cun; born 8 July 1960) is a Turing Award winning French computer scientist working primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience.

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Flipboard

JUNE 11, 2023

While we consider ourselves computer scientists, we do research in a business school, so our perspective here very much reflects on what we see as an industry-shaping trend. Large language models are complex neural networks trained on humongous amounts of data—selected from essentially all written text accessible over the Internet.

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IBM Journey to AI blog

APRIL 18, 2024

Most importantly, no matter the strength of AI (weak or strong), data scientists, AI engineers, computer scientists and ML specialists are essential for developing and deploying these systems. Connectionist AI (artificial neural networks): This approach is inspired by the structure and function of the human brain.

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Flipboard

APRIL 4, 2023

It pitted established male EDA experts against two young female Google computer scientists, and the underlying argument had already led to the firing of one Google researcher. The score is used as feedback to adjust the neural network, and it tries again. Wash, rinse, repeat.

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Marktechpost

AUGUST 24, 2023

r/compsci Anyone interested in sharing and discussing information that computer scientists find fascinating should visit the r/compsci subreddit. r/neuralnetworks The Subreddit is about Deep Learning, Artificial Neural Networks, and Machine Learning. The posts are regular and informative, with creative discussions.

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Dlabs.ai

MARCH 17, 2021

We think it’s someone even more interesting: Yann LeCun, Chief AI Scientist at Facebook. Yann is a computer scientist working primarily in machine learning, computer vision, mobile robotics, and computational neuroscience. Geoffrey Hinton Twitter Geoffrey is a cognitive psychologist and computer scientist.

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IBM Journey to AI blog

JULY 6, 2023

IBM computer scientist Arthur Samuel coined the phrase “machine learning” in 1952. In 1962, a checkers master played against the machine learning program on an IBM 7094 computer, and the computer won. Deep learning teaches computers to process data the way the human brain does.

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Pragnakalp

JANUARY 3, 2024

Q: What is the most important skill for a computer scientist? The RBMs (Restricted Boltzmann Machines) are a type of neural network used in unsupervised learning, specifically in constructing Deep Belief Networks. Q: What is the RBMs?

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Pickl AI

JUNE 19, 2023

Students study neural networks, the processing of signals and control, and data mining throughout the school’s curriculum. They can work as computer scientists, IT analysts, AI engineers, big data and AI designers, and so on. This programme teaches students how to create autonomous machines and applications.

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Viso.ai

MARCH 26, 2024

Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. This drastically enhanced the capabilities of computer vision systems to recognize patterns far beyond the capability of humans. 1: Fraud Detection and Prevention No.2:

Computer Vision 52

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ODSC - Open Data Science

JUNE 30, 2023

In a report by The Times of Israel, archaeologists and computer scientists hope this program can assist in cuneiform interpretation. As that program also utilizes Neural machine transition. Then, the program uses a complex neural network to generate the sentence in another language.

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NVIDIA

AUGUST 29, 2023

The progress in AI has been enormous, it’s been enabled by hardware and it’s still gated by deep learning hardware,” said Dally, one of the world’s foremost computer scientists and former chair of Stanford University’s computer science department. We’re not done with sparsity,” he said. “We

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Snorkel AI

MAY 18, 2023

We have our favorite learning algorithm, which could be XGBoost or your favorite neural network. We have training data, which can come from different hospitals or different vendors, and different sources. Since these datasets contain a lot of unstructured data, it requires a lot of data cleaning, selection, and curation.

Machine Learning 52

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Snorkel AI

MAY 18, 2023

We have our favorite learning algorithm, which could be XGBoost or your favorite neural network. We have training data, which can come from different hospitals or different vendors, and different sources. Since these datasets contain a lot of unstructured data, it requires a lot of data cleaning, selection, and curation.

Machine Learning 52

Machine Learning AI AI Algorithm 52

TheSequence

DECEMBER 13, 2023

At the time, a friend of mine was studying algorithms to estimate the background for proton collisions at the Large Hadron Collider, and one day he showed me a script of TensorFlow code that trained a neural network to classify these events. Who is your favorite mathematician and computer scientist, and why?

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Applied Data Science

MARCH 11, 2022

Preface In 1986, Marvin Minsky , a pioneering computer scientist who greatly influenced the dawn of AI research, wrote a book that was to remain an obscure account of his theory of intelligence for decades to come. Today, Generative Adversarial Networks (GANs) are the most common tool used to generate many types of data.

Neural Network 52

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Viso.ai

DECEMBER 21, 2023

Over the past decade, the field of computer vision has experienced monumental artificial intelligence (AI) breakthroughs. This blog will introduce you to the computer vision visionaries behind these achievements. Andrej Karpathy: Tesla’s Renowned Computer Scientist Andrej Karpathy, holding a Ph.D.

Convolutional Neural Networks 52

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Flipboard

AUGUST 1, 2023

“Compute” regulation : Training advanced AI models requires a lot of computing, including actual math conducted by graphics processing units (GPUs) or other more specialized chips to train and fine-tune neural networks. Harvard computer scientist Yonadav Shavit has proposed one model for regulating compute.

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