Data Science Dojo

MARCH 4, 2024

In the drive for AI-powered innovation in the digital world, NVIDIA’s unprecedented growth has led it to become a frontrunner in this revolution. The rise of GPUs (1999) NVIDIA stepped into the AI industry with its creation of graphics processing units (GPUs). The company shifted its focus to producing AI-powered solutions.

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ML @ CMU

JANUARY 2, 2025

Our results shed light on the possible rationale for the brains modularity and suggest that artificial systems can use this insight from neuroscience to improve learning and generalization in natural tasks. 2018 ) to enhance training (see Materials and Methods in Zhang et al., In the emerging field of neuroAI ( Zador et al.,

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Analytics Vidhya

JUNE 26, 2019

DataHack Summit 2019 Bringing Together Futurists to Achieve Super Intelligence DataHack Summit 2018 was a grand success with more than 1,000 attendees from various. The post Announcing DataHack Summit 2019 – The Biggest Artificial Intelligence and Machine Learning Conference Yet appeared first on Analytics Vidhya.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

This post is co-written with Ken Kao and Hasan Ali Demirci from Rad AI. Rad AI has reshaped radiology reporting, developing solutions that streamline the most tedious and repetitive tasks, and saving radiologists’ time. In this post, we share how Rad AI reduced real-time inference latency by 50% using Amazon SageMaker.

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Dataconomy

MARCH 5, 2025

is dedicated to creating systems that can learn and adapt, a fundamental step toward achieving General-Purpose Artificial Intelligence (AGI). Founded in 2010, it has made significant strides since its acquisition by Google in 2014, aiming to advance AI capabilities in diverse domains. This ambitious division of Alphabet, Inc.

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NYU Center for Data Science

OCTOBER 16, 2024

The tweet linked to a paper from 2018, hinting at the foundational research behind these now-commercialized ideas. Back in 2018, recent CDS PhD grad Katrina Drozdov (née Evtimova), Cho, and their colleagues published a paper at ICLR called “ Emergent Communication in a Multi-Modal, Multi-Step Referential Game.”

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Hacker News

OCTOBER 11, 2024

The release of NVIDIA’s GeForce 256 twenty-five years ago today, overlooked by all but hardcore PC gamers and tech enthusiasts at the time, would go on to lay the foundation for today’s generative AI. From Gaming to AI: The GPU’s Next Frontier As gaming worlds grew in complexity, so too did the computational demands.

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Dataconomy

MARCH 19, 2025

Tensor Processing Units (TPUs) represent a significant leap in hardware specifically designed for machine learning tasks. They are essential for processing large amounts of data efficiently, particularly in deep learning applications.

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Data Science Dojo

SEPTEMBER 13, 2023

What are chatbots? AI chatbots are smart computer programs that can process and understand users’ requests and queries in voice and text. AI chatbots are widely used today from personal assistance to customer service and much more. AI chatbots are widely used today from personal assistance to customer service and much more.

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Hacker News

OCTOBER 15, 2024

At the Open Compute Project (OCP) Global Summit 2024, we’re showcasing our latest open AI hardware designs with the OCP community. These innovations include a new AI platform, cutting-edge open rack designs, and advanced network fabrics and components. Prior to Llama, our largest AI jobs ran on 128 NVIDIA A100 GPUs.

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Hacker News

SEPTEMBER 24, 2021

This article is part of our special report on AI, “ The Great AI Reckoning. ”. Deep learning is now being used to translate between languages, predict how proteins fold , analyze medical scans , and play games as complex as Go , to name just a few applications of a technique that is now becoming pervasive.

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AWS Machine Learning Blog

DECEMBER 2, 2024

Over the past decade, advancements in deep learning have spurred a shift toward so-called global models such as DeepAR [3] and PatchTST [4]. AutoGluon predictors can be seamlessly deployed to SageMaker using AutoGluon-Cloud and the official Deep Learning Containers. Chronos: Learning the language of time series.”

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ODSC - Open Data Science

MARCH 12, 2025

By analyzing conference session titles and abstracts from 2018 to 2024, we can trace the rise and fall of key trends that shaped the industry. The Rise of AI Engineering andMLOps 20182019: Early discussions around MLOps and AI engineering were sparse, primarily focused on general machine learning best practices.

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Dataconomy

MARCH 17, 2025

Origins and development The concept of Siri was rooted in complex AI research aimed at understanding human language. Utilizing advanced voice technology and AI, Siri relies on methods such as Automatic Speech Recognition (ASR) and Natural Language Processing (NLP). which Apple acquired in 2010.

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Towards AI

APRIL 5, 2023

Last Updated on April 6, 2023 by Editorial Team Author(s): LucianoSphere Originally published on Towards AI. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. Published via Towards AI From research to projects and ideas.

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Dataconomy

MARCH 20, 2025

TensorFlow has revolutionized the field of machine learning and deep learning since its inception. TensorFlow is an open-source framework designed for machine learning and deep learning applications. What is TensorFlow?

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Dataconomy

OCTOBER 2, 2024

— Durk Kingma (@dpkingma) October 1, 2024 Kingma wrote, “Anthropic’s approach to AI development resonates significantly with my own beliefs; looking forward to contributing to Anthropic’s mission of developing powerful AI systems responsibly. He earned his Ph.D. Durk Kingma, also known as Diederik P.

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Towards AI

DECEMBER 28, 2023

Last Updated on December 30, 2023 by Editorial Team Author(s): Sudhanshu Sharma Originally published on Towards AI. Later, Python gained momentum and surpassed all programming languages, including Java, in popularity around 2018–19. In 2023, we witnessed the substantial transformation of AI, marking it as the ‘year of AI.’

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Flipboard

MARCH 13, 2023

Yes, large language models (LLMs) hallucinate , a concept popularized by Google AI researchers in 2018. That feedback is used to adjust the reward predictor neural network, and the updated reward predictor neural network is used to adjust the behavior of the AI model. Most of what we learn has nothing to do with language.” “We

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Dataconomy

MAY 8, 2023

The constantly rising number of AI drawing generators is making it hard to find which one best fits your needs. If you are looking for an AI drawing generator list that explains the best of them, you have just found it and more information about AI art’s current state.

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AWS Machine Learning Blog

APRIL 7, 2025

These models are designed for industry-leading performance in image and text understanding with support for 12 languages, enabling the creation of AI applications that bridge language barriers. With SageMaker AI, you can streamline the entire model deployment process.

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Data Science 101

MARCH 6, 2019

Luckily, a few of them are willing to share data science, machine learning and deep learning materials online for everyone. Here is just I small list I have come across lately.

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Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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PyImageSearch

JANUARY 2, 2023

Further, significant health technology, digital technology, and artificial intelligence (AI) investments are needed to bridge the health service gap in emerging markets. COVID-19 has also accelerated the pace of transition to digital health applications, including those that integrate AI.

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Data Science Dojo

JUNE 26, 2023

In order to learn the nuances of language and to respond coherently and pertinently, deep learning algorithms are used along with a large amount of data. A prompt is given to GPT-3 and it produces very accurate human-like text output based on deep learning. AI chatbot ChatGPT is based on GPT-3.5,

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Towards AI

NOVEMBER 16, 2024

Last Updated on November 17, 2024 by Editorial Team Author(s): Shashwat Gupta Originally published on Towards AI. In particular, min-max optimisation is curcial for GANs [2], statistics, online learning [6], deep learning, and distributed computing [7]. Published via Towards AI Arjovsky, S. Chintala, and L.

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Dataconomy

OCTOBER 5, 2023

If you are interested in technology at all, it is hard not to be fascinated by AI technologies. Whether it’s pushing the limits of creativity with its generative abilities or knowing our needs better than us with its advanced analysis capabilities, many sectors have already taken a slice of the huge AI pie.

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Dataconomy

NOVEMBER 20, 2023

Co-inventing AlexNet with Krizhevsky and Hinton, he laid the groundwork for modern deep learning. His fingerprints are also on the AlphaGo paper, showcasing his knack for staying ahead in the ever-evolving AI landscape. Keynote speeches at Nvidia Ntech 2018 and AI Frontiers Conference 2018 cement his status as a thought leader.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Large-scale deep learning has recently produced revolutionary advances in a vast array of fields. is a startup dedicated to the mission of democratizing artificial intelligence technologies through algorithmic and software innovations that fundamentally change the economics of deep learning. Founded in 2021, ThirdAI Corp.

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AWS Machine Learning Blog

OCTOBER 5, 2023

For more resources on using Trainium for distributed pre-training and fine-tuning your generative AI models using NeMo Megatron, refer to AWS Neuron Reference for NeMo Megatron. Before that, he worked on developing machine learning methods for fraud detection for Amazon Fraud Detector. Dr. Huan works on AI and Data Science.

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Towards AI

FEBRUARY 10, 2023

Last Updated on February 13, 2023 by Editorial Team Author(s): Lan Chu Originally published on Towards AI. In this article, I aim to bring attention to the importance of knowing that, even though large AI models are impressive, there are often unacknowledged costs behind them.

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Mlearning.ai

JANUARY 17, 2024

Each section of this story comprises a discussion of the topic plus a curated list of resources, sometimes containing sites with more lists of resources: 20+: What is Generative AI? 95x: Generative AI history 600+: Key Technological Concepts 2,350+: Models & Mediums — Text, Image, Video, Sound, Code, etc.

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NYU Center for Data Science

OCTOBER 10, 2023

However, limiting analysis to post-training behavior restricts our understanding of training dynamics and the development of the model, which are key to establishing a mature, reliable science of AI. Their paper not only challenges prevailing notions in AI interpretability but also sets a new precedent for future research.

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AWS Machine Learning Blog

NOVEMBER 8, 2023

Medical imaging AI researchers and developers need a scalable, enterprise framework to build, deploy, and integrate their AI applications. We have developed a MONAI Deploy connector to AHI to integrate medical imaging AI applications with subsecond image retrieval latencies at scale powered by cloud-native APIs.

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Dataconomy

MAY 22, 2024

As generative AI becomes increasingly integrated into various industries, it is essential to consider the ethical implications of its use. What are some ethical considerations when using generative AI? Addressing these issues is crucial for ensuring that generative AI serves as a beneficial and responsible tool in our society.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

By harnessing the power of threat intelligence, machine learning (ML), and artificial intelligence (AI), Sophos delivers a comprehensive range of advanced products and services. The Sophos Artificial Intelligence (AI) group (SophosAI) oversees the development and maintenance of Sophos’s major ML security technology.

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ODSC - Open Data Science

APRIL 17, 2023

Minor changes in the input data that are very apparent to human intelligence are not so for deep learning models. Deep learning is essentially matrix multiplication, which means even small perturbations in the coefficients can cause a significant change in the output.

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