Analytics Vidhya

APRIL 19, 2023

Meta AI has announced the launch of DinoV2, an open-source, self-supervised learning model. It is a vision transformer model for computer vision tasks, built upon the success of its predecessor, DINO.

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Data Science Dojo

JANUARY 30, 2025

Artificial intelligence (AI) has transformed industries, but its large and complex models often require significant computational resources. Traditionally, AI models have relied on cloud-based infrastructure, but this approach often comes with challenges such as latency, privacy concerns, and reliance on a stable internet connection.

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Data Science Dojo

MAY 27, 2024

In the recent discussion and advancements surrounding artificial intelligence, there’s a notable dialogue between discriminative and generative AI approaches. These methodologies represent distinct paradigms in AI, each with unique capabilities and applications. What is Generative AI?

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Analytics Vidhya

OCTOBER 27, 2022

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction In 2018 Google AI released a self-supervised learning model […]. The post A Gentle Introduction to RoBERTa appeared first on Analytics Vidhya.

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Towards AI

FEBRUARY 3, 2025

Author(s): Shenggang Li Originally published on Towards AI. Photo by Agence Olloweb on Unsplash Machine learning model selection has always been a challenge. Inspired by its reinforcement learning (RL)-based optimization, I wondered: can we apply a similar RL-driven strategy to supervised learning?

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Hacker News

SEPTEMBER 18, 2023

There’s a limit to how far the field of AI can go with supervised learning alone. Here's why self-supervised learning is one of the most promising ways to make significant progress in AI. How can we build machines with human-level intelligence?

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Data Science Dojo

SEPTEMBER 5, 2023

Virginia Tech and Microsoft unveil the Algorithm of Thoughts, a breakthrough AI method supercharging idea exploration and reasoning prowess in Large Language Models (LLMs). Accelerated Problem-Solving with Reduced Resource Dependency The outcome of this paradigm shift in AI? Significantly faster and resource-efficient problem-solving.

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Dataconomy

FEBRUARY 21, 2025

PositiveGrid, a manufacturer of digital music technology, has integrated artificial intelligence into its Spark series amplifiers with SparkAI, an AI-powered tone generator. Using deep learning and transformer-based models, SparkAI processes extensive audio datasets to analyze tonal characteristics and generate realistic guitar sounds.

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NYU Center for Data Science

JULY 5, 2024

Our study demonstrates that machine supervision significantly improves two crucial medical imaging tasks: classification and segmentation,” said Cirrone, who leads AI efforts at the Colton Center for Autoimmunity at NYU Langone. “The

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Data Science Dojo

AUGUST 19, 2024

The demand for AI scientist is projected to grow significantly in the coming years, with the U.S. AI researcher role is consistently ranked among the highest-paying jobs, attracting top talent and driving significant compensation packages. Bureau of Labor Statistics predicting a 35% increase in job openings from 2022 to 2032.

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NYU Center for Data Science

NOVEMBER 3, 2023

Self-supervised learning (SSL) has emerged as a powerful technique for training deep neural networks without extensive labeled data. However, unlike supervised learning, where labels help identify relevant information, the optimal SSL representation heavily depends on assumptions made about the input data and desired downstream task.

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Towards AI

AUGUST 1, 2023

Last Updated on August 2, 2023 by Editorial Team Author(s): Boris Meinardus Originally published on Towards AI. How the DINO framework achieved the new SOTA for Self-Supervised Learning! Transformers and Self-Supervised Learning. This way, the model will learn about different objects in a balanced way.

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Dataconomy

APRIL 24, 2025

Change the guest list or seating logic, and you get dimensionality reduction, self-supervised learning, or spectral clustering. Research: Googles AI eats your clicks Performance and payoff The I-Con framework isnt just theory. The I-Con framework shows that algorithms differ mainly in how they define those relationships.

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IBM Data Science in Practice

MARCH 17, 2025

On March 10, 2025, the Embed2Scale consortium launched the 2025 CVPR EARTHVISION Data Challenge , inviting researchers and AI practitioners to develop innovative EO data compression techniques. The Embed2Scale consortium invites the AI community to adopt this novel data benchmark evaluation scheme and contribute additional downstream tasks.

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Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves. That is, is giving supervision to adjust via.

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Towards AI

FEBRUARY 13, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Yet another week, and reasoning models and Deepseek are still the most talked about in AI. I will also answer one existential question that has probably haunted you: will AI take your job? AI poll of the week!

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Towards AI

JANUARY 20, 2025

Last Updated on January 20, 2025 by Editorial Team Author(s): Shenggang Li 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 Upgrade to access all of Medium.

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Data Science Dojo

MAY 10, 2024

Their impact on ML tasks has made them a cornerstone of AI advancements. Unsupervised vs. supervised learning for embeddings While vector representation and contextual inference remain important factors in the evolution of LLM embeddings, the lens of comparative analysis also highlights another aspect for discussion.

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Towards AI

JANUARY 29, 2025

Last Updated on January 29, 2025 by Editorial Team Author(s): Aleti Adarsh Originally published on Towards AI. We have seen how Machine learning has revolutionized industries across the globe during the past decade, and Python has emerged as the language of choice for aspiring data scientists and seasoned professionals alike.

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AWS Machine Learning Blog

JANUARY 31, 2025

Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset. She recently earned her MBA and PhD in Learning Technologies and is serving as an Adjunct Professor at the University of North Texas.

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Towards AI

APRIL 24, 2025

Last Updated on April 24, 2025 by Editorial Team Author(s): SETIA BUDI SUMANDRA Originally published on Towards AI. Thats the motto of Unsupervised Learning a fascinating branch of machine learning where algorithms learn patterns from unlabeled data. Join thousands of data leaders on the AI newsletter. No worries!

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Analytics Vidhya

SEPTEMBER 27, 2023

Introduction In recent years, the integration of Artificial Intelligence (AI), specifically Natural Language Processing (NLP) and Machine Learning (ML), has fundamentally transformed the landscape of text-based communication in businesses.

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NYU Center for Data Science

SEPTEMBER 13, 2024

The world of multi-view self-supervised learning (SSL) can be loosely grouped into four families of methods: contrastive learning, clustering, distillation/momentum, and redundancy reduction.

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Flipboard

NOVEMBER 27, 2024

The Nucleotide Transformer is a series of foundation models pre-trained on DNA sequences through self-supervised learning that extracts context-specific representations of nucleotide sequences. These representations can then be used to accurately predict molecular phenotypes.

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Flipboard

FEBRUARY 22, 2023

One rarely gets to engage in a conversation with an individual like Andrew Ng, who has left an indelible impact as an educator, researcher, innovator and leader in the artificial intelligence and technology realms. Fortunately, I recently had the privilege of doing so. Our article detailing the …

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Google Research AI blog

APRIL 26, 2023

Posted by Shekoofeh Azizi, Senior Research Scientist, and Laura Culp, Senior Research Engineer, Google Research Despite recent progress in the field of medical artificial intelligence (AI), most existing models are narrow , single-task systems that require large quantities of labeled data to train.

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Data Science Dojo

FEBRUARY 19, 2024

As part of the generative AI world, LLMs have led to innovation in machine-learning tasks. Roadmap to understanding an LLM project lifecycle Within the realm of generative AI, a project involving large language models can be a daunting task. The next part of this step is to explore the feasibility of a solution in generative AI.

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Dataconomy

SEPTEMBER 13, 2023

AI annotation jobs are on the rise; naturally, people started asking what exactly is data annotation. AI annotation jobs: What is data annotation? AI still needs a human hand to operate efficiently; for how long, though? Faulty data can introduce biases and lead to inaccurate predictions by AI systems.

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Analytics Vidhya

NOVEMBER 20, 2023

Introduction This article concerns building a system based upon LLM (Large language model) with the ChatGPT AI-1. Considering the enormity of the topic, […] The post Unleashing ChatGPT AI-1: Constructing an Advanced LLM-Based System appeared first on Analytics Vidhya.

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Data Science Dojo

MAY 10, 2024

Their impact on ML tasks has made them a cornerstone of AI advancements. Read on to understand the role of embeddings in generative AI Let’s take a step back and travel through the journey of LLM embeddings from the start to the present day, understanding their evolution every step of the way.

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Dataconomy

MAY 29, 2023

In the field of AI and ML, QR codes are incredibly helpful for improving predictive analytics and gaining insightful knowledge from massive data sets. These algorithms allow AI systems to recognize patterns, forecast outcomes, and adjust to new situations.

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Google Research AI blog

JULY 18, 2023

Alternatively, self-supervised learning (SSL) methods (e.g., SimCLR and MoCo v2 ), which leverage a large amount of unlabeled data to learn representations that capture periodic or quasi-periodic temporal dynamics, have demonstrated success in solving classification tasks. video or satellite imagery).

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Flipboard

MARCH 23, 2023

Marco Ramponi at Assembly AI: The creators have used a combination of both Supervised Learning and Reinforcement Learning to fine-tune ChatGPT, but it …

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Machine Learning Research at Apple

FEBRUARY 18, 2025

Specifically, our focus lies in areas such as Embodied AI, Games, UI Control, and Planning. GEA is trained with supervised learning on a large dataset of embodied experiences and To this end, we introduce a process of adapting an MLLM to a Generalist Embodied Agent (GEA).

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NYU Center for Data Science

FEBRUARY 29, 2024

However, the potential of such technologies is often hindered by biases in the data they learn from. As we increasingly rely on general-purpose, self-supervised learning (SSL) pre-trained foundation models across various tasks, the imperative to ensure these models are fair becomes paramount.

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Data Science Dojo

JULY 2, 2024

Adaptive AI has risen as a transformational technological concept over the years, leading Gartner to name it as a top strategic tech trend for 2023. It is a step ahead within the realm of artificial intelligence (AI). As the use of AI has expanded into various arenas of the world, the technology has also developed over time.

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Towards AI

APRIL 8, 2024

Last Updated on April 8, 2024 by Editorial Team Author(s): Eashan Mahajan Originally published on Towards AI. Photo by Arseny Togulev on Unsplash With machine learning’s surge of popularity in the past few years, more and more people spend hours each day trying to learn as much as they can. Let’s get right into it.

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