Towards AI

SEPTEMBER 10, 2023

What I’ve learned from the most popular DL course Photo by Sincerely Media on Unsplash I’ve recently finished the Practical Deep Learning Course from Fast.AI. So you definitely can trust his expertise in Machine Learning and Deep Learning. Luckily, there’s a handy tool to pick up Deep Learning Architecture.

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AssemblyAI

MARCH 21, 2023

Top 50 keywords in submitted research papers at ICLR 2022 ( source ) A recent bibliometric study systematically analysed this research trend, revealing an exponential growth of published research involving GNNs, with a striking +447% average annual increase in the period 2017-2019.

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Google Research AI blog

FEBRUARY 14, 2023

As we do this, we’re transforming robot learning into a scalable data problem so that we can scale learning of generalized low-level skills, like manipulation. In this blog post, we’ll review key learnings and themes from our explorations in 2022.

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Robotics LLM Algorithm Computer Vision 139

Flipboard

NOVEMBER 6, 2024

We developed and validated a deep learning model designed to identify pneumoperitoneum in computed tomography images. Delays or misdiagnoses in detecting pneumoperitoneum can significantly increase mortality and morbidity. External validation included 480 scans from Cedars-Sinai Medical Center. and a specificity of 0.97–0.99

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Unite.AI

SEPTEMBER 25, 2023

Initially, the attempts were simple and intuitive, with basic algorithms creating monotonous tunes. However, as technology advanced, so did the complexity and capabilities of AI music generators, paving the way for deep learning and Natural Language Processing (NLP) to play pivotal roles in this tech.

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Unite.AI

MAY 8, 2024

Driven by his aspiration to work with a tech giant, he joined Google in 2022 as a Senior Software Engineer, focusing on the Google Assistant team (later Google Bard). Launched in 2022, Perplexity generates answers using the sources from the web and cites links within the text response.

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Google Research AI blog

FEBRUARY 21, 2023

In 2022, we leveraged recent advances in deep learning to accurately predict protein function from raw amino acid sequences. Feeding data from quantum sensors directly to quantum algorithms without going through classical measurements may provide a large advantage.

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Google Research AI blog

FEBRUARY 23, 2023

Commensurate with our mission to demonstrate these societal benefits , Google Research’s programs in applied machine learning (ML) have helped place Alphabet among the top five most impactful corporate research institutions in the health and life sciences publications on the Nature Impact Index in every year from 2019 through 2022.

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AI News

JULY 3, 2024

The figure is 48% higher than in 2019, the company said, and 13% higher than in 2022. AI technologies , especially those that involve deep learning and large language models, are notoriously energy-intensive. Still, more must be done to optimise AI algorithms’ energy efficiency. million metric tons in 2023.

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Unite.AI

AUGUST 7, 2023

Amir Hever is the CEO and co-founder of UVeye , a deep learning computer vision startup that is setting the global standard for vehicle inspection with fast and accurate anomaly detection to identify issues or threats facing the automotive and security industries. UVeye is Hever’s third venture. We completely changed the game.

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Towards AI

NOVEMBER 16, 2024

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

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Algorithm ML Deep Learning Machine Learning 105

BAIR

APRIL 6, 2023

These robots use recent advances in deep learning to operate autonomously in unstructured environments. By pooling data from all robots in the fleet, the entire fleet can efficiently learn from the experience of each individual robot. Using this formalism, we can now instantiate and compare IFL algorithms (i.e.,

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Robotics Algorithm Continuous Learning Artificial Intelligence 246

IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences.

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AI Weekly

NOVEMBER 23, 2023

forbes.com Applied use cases From Data To Diagnosis: A Deep Learning Approach To Glaucoma Detection When the algorithm is implemented in clinical practice, clinicians collect data such as optic disc photographs, visual fields, and intraocular pressure readings from patients and preprocess the data before applying the algorithm to diagnose glaucoma.

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Unite.AI

JANUARY 24, 2025

Claudionor Coelho is the Chief AI Officer at Zscaler, responsible for leading his team to find new ways to protect data, devices, and users through state-of-the-art applied Machine Learning (ML), Deep Learning and Generative AI techniques. He also held ML and deep learning roles at Google.

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Deep Learning AI AI Generative AI 246

PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. As soon as the system adapts to human wants, it automates the learning process accordingly.

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Unite.AI

AUGUST 4, 2023

In 2022, research showed that around 60 Twitter accounts were used to make 22,000 tweets and spread false or misleading information about climate change. In 2022, several disturbing attempts to spread climate misinformation came to light, demonstrating the extent of the challenge.

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IBM Journey to AI blog

SEPTEMBER 3, 2024

Indeed, this perspective characterized much of the coverage around generative AI as the release of ChatGPT and other tools mainstreamed the technology in 2022, with some analysts predicting that we were on the brink of a revolution that would reshape the future of work. But when you have constraints, you become more creative.”

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Google Research AI blog

FEBRUARY 28, 2023

In 2022, we expanded our research interactions and programs to faculty and students across Latin America , which included grants to women in computer science in Ecuador. We also help make global conferences accessible to more researchers around the world, for example, by funding 24 students this year to attend Deep Learning Indaba in Tunisia.

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John Snow Labs

JUNE 2, 2023

Spark NLP’s deep learning models have achieved state-of-the-art results on sentiment analysis tasks, thanks to their ability to automatically learn features and representations from raw text data. During training, the model learns to identify patterns and features that are indicative of a certain sentiment.

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IBM Journey to AI blog

JUNE 26, 2023

Generative AI uses an advanced form of machine learning algorithms that takes users prompts and uses natural language processing (NLP) to generate answers to almost any question asked. It uses vast amounts of internet data, large-scale pre-training and reinforced learning to enable surprisingly human like user transactions.

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Bugra Akyildiz

FEBRUARY 26, 2023

We are heavy Google Research posts this week, enjoy specifically the 2022 & Beyond series! Libraries MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

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Towards AI

MAY 13, 2024

Since the emergence of ChatGPT in 2022, AI has dominated discussions. This synergy enables AI supercomputers to leverage HPC capabilities, optimizing performance for demanding AI tasks like training deep learning models or image recognition algorithms.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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Google Research AI blog

FEBRUARY 2, 2023

Great machine learning (ML) research requires great systems. With the increasing sophistication of the algorithms and hardware in use today and with the scale at which they run, the complexity of the software necessary to carry out day-to-day tasks only increases. You can find other posts in the series here.)

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IBM Journey to AI blog

SEPTEMBER 6, 2023

Content generation: The recent launch of OpenAI’s generative AI platform ChatGPT in November of 2022 has prompted a flood of new use cases for AI. AI can help by performing predictive analytics on customer data, analyzing huge amounts in seconds using fast, efficient machine learning (ML) algorithms.

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Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. The global MLOps market was valued at $720 million in 2022 and is projected to grow to $13,000 million by 2030, according to Fortune Business Insights.

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Sebastian Ruder

FEBRUARY 23, 2023

This post gives a brief overview of modularity in deep learning. For modular fine-tuning for NLP, check out our EMNLP 2022 tutorial. Fuelled by scaling laws, state-of-the-art models in machine learning have been growing larger and larger. We give an in-depth overview of modularity in our survey on Modular Deep Learning.

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Viso.ai

DECEMBER 3, 2023

This article will provide an introduction to object detection and provide an overview of the state-of-the-art computer vision object detection algorithms. The recent deep learning algorithms provide robust person detection results. Most modern person detector techniques are trained on frontal and asymmetric views.

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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Computer Vision Deep Learning NLP Neural Network 52

PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

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Computer Vision Deep Learning Neural Network Machine Learning 52

ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. Developing NLP tools isn’t so straightforward, and requires a lot of background knowledge in machine & deep learning, among others.

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Unite.AI

APRIL 3, 2024

As AI algorithms advance, the demand for computational power increases, straining existing infrastructure and posing challenges in power management and energy efficiency. This makes them ideal for computationally intensive tasks like deep learning and neural network training.

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Marktechpost

JULY 17, 2023

With a lifetime of context, human sight has the advantage of learning how to distinguish between things, determine their distance from the viewer, determine whether they are moving, and determine whether an image is correct. The algorithm, for instance, can identify a dog among all the items in the image. Identification of the item.

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Applied Data Science

DECEMBER 23, 2022

Just wait until you hear what happened in 2022. In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. In 2022 we got diffusion models ( NeurIPS paper ).

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Heartbeat

FEBRUARY 28, 2023

The past few years have witnessed exponential growth in medical image analysis using deep learning. In this article we will look into medical image segmentation and see how deep learning can be helpful in these cases. Finally, we will look at some of the recent semi-supervised medical image segmentation algorithms.

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