A Comprehensive Guide on i-Transformer
Analytics Vidhya
MAY 13, 2024
Introduction Transformers have revolutionized various domains of machine learning, notably in natural language processing (NLP) and computer vision.
AI Research Machine Learning Natural Language Processing NLP 
Meta AI Researchers Introduce GenBench: A Revolutionary Framework for Advancing Generalization in Natural Language Processing
Marktechpost
OCTOBER 28, 2023
A model’s capacity to generalize or effectively apply its learned knowledge to new contexts is essential to the ongoing success of Natural Language Processing (NLP). To address that, a group of researchers from Meta has proposed a thorough taxonomy to describe and comprehend NLP generalization research.
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LLMOps: The Next Frontier for Machine Learning Operations
Unite.AI
FEBRUARY 7, 2024
Machine learning (ML) is a powerful technology that can solve complex problems and deliver customer value. This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses. They are huge, complex, and data-hungry.
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Can AI Really Understand Sarcasm? This Paper from NYU Explores Advanced Models in Natural Language Processing
Marktechpost
DECEMBER 30, 2023
Natural Language Processing (NLP) is useful in many fields, bringing about transformative communication, information processing, and decision-making changes. In conclusion, the study is a significant step for effective sarcasm detection in NLP. The post Can AI Really Understand Sarcasm?
Enhancing Autoregressive Decoding Efficiency: A Machine Learning Approach by Qualcomm AI Research Using Hybrid Large and Small Language Models
Marktechpost
MARCH 3, 2024
Central to Natural Language Processing (NLP) advancements are large language models (LLMs), which have set new benchmarks for what machines can achieve in understanding and generating human language. One of the primary challenges in NLP is the computational demand for autoregressive decoding in LLMs.
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Knowledge Fusion of Large Language Models (LLMs)
Analytics Vidhya
FEBRUARY 16, 2024
Introduction In Natural Language Processing (NLP), developing Large Language Models (LLMs) has proven to be a transformative and revolutionary endeavor. These models, equipped with massive parameters and trained on extensive datasets, have demonstrated unprecedented proficiency across many NLP tasks.
From a School Talk to an AI Internship: My Journey into the World of Machine Learning and NLP
Mlearning.ai
SEPTEMBER 2, 2023
AI | MACHINE LEARNING | START-UP This is the story of how my interest in AI takes me to give a talk about AI, train my first machine-learning model, and get my internship at an AI research start-up. This is my very first time having to really read research papers and it is tough.
Are Pre-Trained Foundation Models the Future of Molecular Machine Learning? Introducing Unprecedented Datasets and the Graphium Machine Learning Library
Marktechpost
OCTOBER 18, 2023
The recent results of machine learning in drug discovery have been largely attributed to graph and geometric deep learning models. Like other deep learning techniques, they need a lot of training data to provide excellent modeling accuracy. Join our AI Channel on Whatsapp. We are also on WhatsApp.
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This Machine Learning Research Opens up a Mathematical Perspective on the Transformers
Marktechpost
DECEMBER 24, 2023
Self-attention greatly enhances the performance of transformers in real-world applications, including computer vision and Natural Language Processing (NLP). In a recent study , researchers have provided a mathematical model that can be used to perceive Transformers as particle systems in interaction.
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Meet PowerInfer: A Fast Large Language Model (LLM) on a Single Consumer-Grade GPU that Speeds up Machine Learning Model Inference By 11 Times
Marktechpost
DECEMBER 23, 2023
Generative Large Language Models (LLMs) are well known for their remarkable performance in a variety of tasks, including complex Natural Language Processing (NLP), creative writing, question answering, and code generation. If you like our work, you will love our newsletter.
This Paper from MIT and Microsoft Introduces ‘LASER’: A Novel Machine Learning Approach that can Simultaneously Enhance an LLM’s Task Performance and Reduce its Size with no Additional Training
Marktechpost
JANUARY 2, 2024
Transformer-based LLMs have significantly advanced machine learning capabilities, showcasing remarkable proficiency in domains like natural language processing, computer vision, and reinforcement learning. The method has shown significant gains in accuracy across various reasoning benchmarks in NLP.
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AI News Weekly - Issue #383: New York Daily News, Chicago Tribune, and others sue OpenAI and Microsoft - May 2nd 2024
AI Weekly
MAY 2, 2024
Ethics Understanding The Layers Of Trustworthy AI In the push to make AI systems more ethical and trustworthy, organizations are realizing the broad scope and set of things to consider under the umbrella of the term “Trustworthy AI.” Whether or not consumers are convinced it's the right idea is another matter entirely.
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Google AI Researchers Introduce MADLAD-400: A 2.8T Token Web-Domain Dataset that Covers 419 Languages
Marktechpost
SEPTEMBER 14, 2023
In the ever-evolving field of Natural Language Processing (NLP), the development of machine translation and language models has been primarily driven by the availability of vast training datasets in languages like English. What sets this dataset apart is the rigorous auditing process it underwent.
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This AI Paper from Alibaba Introduces EE-Tuning: A Lightweight Machine Learning Approach to Training/Tuning Early-Exit Large Language Models (LLMs)
Marktechpost
FEBRUARY 7, 2024
Large language models (LLMs) have profoundly transformed the landscape of artificial intelligence (AI) in natural language processing (NLP). These models can understand and generate human-like text, representing a pinnacle of current AI research.
This AI Research Introduces Owl: A New Large Language Model for IT Operations
Marktechpost
SEPTEMBER 21, 2023
In the ever-evolving landscape of Natural Language Processing (NLP) and Artificial Intelligence (AI), Large Language Models (LLMs) have emerged as powerful tools, demonstrating remarkable capabilities in various NLP tasks. If you like our work, you will love our newsletter.
A New AI Research Introduces Recognize Anything Model (RAM): A Robust Base Model For Image Tagging
JUNE 10, 2023
When it comes to natural language processing (NLP) tasks, large language models (LLM) trained on massive online datasets perform exceptionally well. …
Can Synthetic Clinical Text Generation Revolutionize Clinical NLP Tasks? Meet ClinGen: An AI Model that Involves Clinical Knowledge Extraction and Context-Informed LLM Prompting
Marktechpost
NOVEMBER 14, 2023
Medical data extraction, analysis, and interpretation from unstructured clinical literature are included in the emerging discipline of clinical natural language processing (NLP). Even with its importance, particular difficulties arise while developing methodologies for clinical NLP.
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Researchers from the University of Washington and Google have Developed Distilling Step-by-Step Technology to Train a Dedicated Small Machine Learning Model with Less Data
Marktechpost
SEPTEMBER 29, 2023
In recent years, large language models (LLMs) have revolutionized the field of natural language processing, enabling unprecedented zero-shot and few-shot learning capabilities. Similar reductions in dataset size were observed across various NLP tasks, including ANLI, CQA, and SVAMP. of the full dataset.
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This AI Research Shares a Comprehensive Overview of Large Language Models (LLMs) on Graphs
Marktechpost
DECEMBER 13, 2023
The well-known Large Language Models (LLMs) like GPT, BERT, PaLM, and LLaMA have brought in some great advancements in Natural Language Processing (NLP) and Natural Language Generation (NLG). If you like our work, you will love our newsletter.
Top 6 NLP Language Models Transforming AI In 2023
Topbots
APRIL 11, 2023
In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. The Most Important Large Language Models (LLMs) in 2023 1. This model marked a new era in NLP with pre-training of language models becoming a new standard.
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Can ChatGPT Compete with Domain-Specific Sentiment Analysis Machine Learning Models?
Topbots
JUNE 22, 2023
ChatGPT is a GPT ( G enerative P re-trained T ransformer) machine learning (ML) tool that has surprised the world. Its breathtaking capabilities impress casual users, professionals, researchers, and even its own creators. SA is a very widespread Natural Language Processing (NLP). Felizardo, L.
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Can Large Language Models Really Do Math? This Artificial Intelligence AI Research Introduce MathGLM: A Robust Model To Solve Mathematical Problems Without a Calculator
Marktechpost
SEPTEMBER 12, 2023
When it comes to downstream natural language processing (NLP) tasks, large language models (LLMs) have proven to be exceptionally effective. Their text comprehension and generation abilities make them extremely flexible for use in a wide range of NLP applications.
Complete Beginner’s Guide to Hugging Face LLM Tools
Unite.AI
SEPTEMBER 20, 2023
Hugging Face is an AI research lab and hub that has built a community of scholars, researchers, and enthusiasts. In a short span of time, Hugging Face has garnered a substantial presence in the AI space. Transformers in NLP In 2017, Cornell University published an influential paper that introduced transformers.
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8 AI Research Labs Pushing the Boundaries of Artificial Intelligence
ODSC - Open Data Science
FEBRUARY 29, 2024
If you’re curious, here are eight AI research labs that are leading the way in AI research that you’d want to keep an eye on. From responsible AI to protein discovery and more, The MIT Media Lab aims to drive AI research to create a “transformative future” while working toward the social good.
Commonsense Reasoning for Natural Language Processing
Probably Approximately a Scientific Blog
JANUARY 12, 2021
Image captioning models often learn to recognize objects based solely on their typical environment , and fail to recognize them outside their typical environment. In NLP, dialogue systems generate highly generic responses such as “I don’t know” even for simple questions. In the last 3 years, language models have been ubiquitous in NLP.
NLP in Legal Discovery: Unleashing Language Processing for Faster Case Analysis
Heartbeat
AUGUST 23, 2023
But what if there was a technique to quickly and accurately solve this language puzzle? Enter Natural Language Processing (NLP) and its transformational power. This is the promise of NLP: to transform the way we approach legal discovery. But exactly what is NLP , and how can it facilitate legal discovery?
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7 Sessions at ODSC East 2023 to Help You Perform NLP Better
ODSC - Open Data Science
APRIL 11, 2023
A lot goes into NLP. Languages, dialects, unstructured data, and unique business needs all contribute to requiring constant innovation from the field. Going beyond NLP platforms and skills alone, having expertise in novel processes, and staying afoot in the latest research are becoming pivotal for effective NLP implementation.
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Hypernetworks and Long-Form AI: Jason Phang’s Transformative Research in NLP
NYU Center for Data Science
DECEMBER 1, 2023
The quest to refine AI’s understanding of extensive textual data has recently been advanced due to two recent papers by CDS PhD student Jason Phang , who is the first author of two recent NLP papers that secured “best paper” accolades at ICML 2023 and EMNLP 2023. By Stephen Thomas
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Do Language Models Know When They Are Hallucinating? This AI Research from Microsoft and Columbia University Explores Detecting Hallucinations with the Creation of Probes
Marktechpost
DECEMBER 31, 2023
Large Language Models (LLMs), the latest innovation of Artificial Intelligence (AI), use deep learning techniques to produce human-like text and perform various Natural Language Processing (NLP) and Natural Language Generation (NLG) tasks.
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A New AI Research from Apple and Equall AI Uncovers Redundancies in Transformer Architecture: How Streamlining the Feed Forward Network Boosts Efficiency and Accuracy
Marktechpost
SEPTEMBER 10, 2023
Transformer design that has recently become popular has taken over as the standard method for Natural Language Processing (NLP) activities, particularly Machine Translation (MT). All Credit For This Research Goes To the Researchers on This Project. Check out the Paper.
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Top 10 Influential AI Research Papers in 2023 from Google, Meta, Microsoft, and More
Topbots
DECEMBER 5, 2023
Top 10 AI Research Papers 2023 1. Sparks of AGI by Microsoft Summary In this research paper, a team from Microsoft Research analyzes an early version of OpenAI’s GPT-4, which was still under active development at the time. Sign up for more AI research updates. Enjoy this article?
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AI News Weekly - Issue #345: Hollywood’s Major Crew Union Debates How to Use AI as Contract Talks Loom - Aug 10th 2023
AI Weekly
AUGUST 10, 2023
Powered by clkmg.com In the News Deepset nabs $30M to speed up natural language processing projects Deepset GmbH today announced that it has raised $30 million to enhance its open-source Haystack framework, which helps developers build natural language processing applications. 1.41%) (BRK.B
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Meet InternLM-20B: An Open-Sourced 20B Parameter Pretrained Artificial Intelligence AI Framework
Marktechpost
SEPTEMBER 30, 2023
Researchers continually strive to build models that can understand, reason, and generate text like humans in the rapidly evolving field of natural language processing. These models must grapple with complex linguistic nuances, bridge language gaps, and adapt to diverse tasks.
Meet Pretzel: An AI Dev Startup with an Open-Source, Offline Browser-based Tool and AI-Native Alternative to Jupyter Notebooks
Marktechpost
MARCH 24, 2024
Artificial intelligence’s application is revolutionizing technology in fields like NLP (Natural Language Processing) and ML (Machine Learning). The learning curve for artificial intelligence is steep, too, for those who aren’t enthusiastic about diving in.
Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations
Topbots
DECEMBER 19, 2023
Generated with Midjourney The NeurIPS 2023 conference showcased a range of significant advancements in AI, with a particular focus on large language models (LLMs), reflecting current trends in AI research. These awards highlight the latest achievements and novel approaches in AI research. Enjoy this article?
This AI Research Evaluates the Correctness and Faithfulness of Instruction-Following Models For Their Ability To Perform Question-Answering
Marktechpost
AUGUST 5, 2023
Recently introduced Large Language Models (LLMs) have taken the Artificial Intelligence (AI) community by storm. These models have been able to successfully imitate human beings by using super-good Natural Language Processing (NLP), Natural Language Generation (NLG) and Natural Language Understanding (NLU).
AI News Weekly - Issue #380: 63% of IT and security pros believe AI will improve corporate cybersecurity - Apr 11th 2024
AI Weekly
APRIL 11, 2024
No legacy process is safe. And this is particularly true for accounts payable (AP) programs, where AI, coupled with advancements in deep learning, computer vision and natural language processing (NLP), is helping drive increased efficiency, accuracy and cost savings for businesses.
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What is Machine Learning as a Service? Benefits And Top MLaaS Platforms
Marktechpost
JUNE 27, 2023
Machine learning uses statistical analysis to generate prediction output without requiring explicit programming. It employs a chain of algorithms that learn to interpret the relationship between datasets to achieve its goal. Data scientists can easily handle these complications thanks to Machine Learning as a Service (MLaaS).
A Research Group From CMU, AI2 and University of Washington Introduces NLPositionality: An AI Framework for Characterizing Design Biases and Quantifying the Positionality of NLP Datasets and Models
Marktechpost
JULY 14, 2023
Researchers’ positionality—their perspectives formed by their own experience, identity, culture, and background—influences their design decisions while developing NLP datasets and models. Latent design choices and the researcher’s positionality are two sources of design bias in producing datasets and models.
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Top AI Email Assistants (November 2023)
Marktechpost
NOVEMBER 3, 2023
AI Mailer AI Mailer makes sending high-quality, tailored emails easy for companies and professionals. It employs GPT and NLP tech to generate customized, timely replies to consumer emails and develop content aware of its context. Crystal Crystal is an AI-driven writing helper that uses NLP to produce engaging email messages.
A New AI Research Introduces AttrPrompt: A LLM-as-Training-Data-Generator for a New Paradigm in Zero-Shot Learning
Marktechpost
JULY 2, 2023
The performance of large language models (LLMs) has been impressive across many different natural language processing (NLP) applications. Don’t forget to join our 25k+ ML SubReddit , Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.
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This AI Research from DeepMind Aims at Reducing Sycophancy in Large Language Models (LLMs) Using Simple Synthetic Data
Marktechpost
AUGUST 13, 2023
A number of researches, including those by OpenAI and Google, have emphasized a lot on these developments. LLMs have revolutionized the way humans interact with machines and is one of the greatest advancements in the field of Artificial Intelligence (AI).
Understanding the Dark Side of Large Language Models: A Comprehensive Guide to Security Threats and Vulnerabilities
Marktechpost
SEPTEMBER 1, 2023
LLMs have become increasingly popular in the NLP (natural language processing) community in recent years. Scaling neural network-based machine learning models has led to recent advances, resulting in models that can generate natural language nearly indistinguishable from that produced by humans.
Your Roadmap to Learn AI from Scratch 2024
Pickl AI
APRIL 19, 2024
Continuous learning is critical to becoming an AI expert, so stay updated with online courses, research papers, and workshops. Specialise in domains like machine learning or natural language processing to deepen expertise.
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