Dataconomy

MARCH 17, 2025

Timeline of key milestones Launch of Siri with the iPhone 4S in 2011 Expansion to iPads and Macs in 2013 Introduction of Siri to Apple TV and the HomePod in 2018 The anticipated Apple Intelligence update in 2024, enhancing existing features How does Siri work?

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Data Science Dojo

MAY 27, 2024

Duplex leverages sophisticated machine learning algorithms to understand natural language, navigate complex conversations, and perform tasks autonomously, mimicking human-like interactions seamlessly.

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Dataconomy

DECEMBER 15, 2023

History of GPTs so far Here’s a concise chronology of the GPT (Generative Pre-trained Transformer) series: GPT-1 (June 2018) : OpenAI introduced the first iteration of the Generative Pre-trained Transformer. It marked a significant advancement in natural language processing and understanding. billion parameters.

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ODSC - Open Data Science

JUNE 9, 2023

Once a set of word vectors has been learned, they can be used in various natural language processing (NLP) tasks such as text classification, language translation, and question answering. GPT-1 (2018) This was the first GPT model and was trained on a large corpus of text data from the internet.

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Towards AI

APRIL 5, 2023

Picture created with Dall-E-2 Yoshua Bengio, Geoffrey Hinton, and Yann LeCun, three computer scientists and artificial intelligence (AI) researchers, were jointly awarded the 2018 Turing Prize for their contributions to deep learning, a subfield of AI.

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Towards AI

DECEMBER 28, 2023

Later, Python gained momentum and surpassed all programming languages, including Java, in popularity around 2018–19. The introduction of attention mechanisms has notably altered our approach to working with deep learning algorithms, leading to a revolution in the realms of computer vision and natural language processing (NLP).

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Data Science Dojo

SEPTEMBER 13, 2023

Deep learning And NLP Deep Learning and Natural Language Processing (NLP) are like best friends in the world of computers and language. Building Chatbots involves creating AI systems that employ deep learning techniques and natural language processing to simulate natural conversational behavior.

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Dataconomy

OCTOBER 2, 2024

He played a pivotal role in the creation of influential AI systems such as DALL-E and ChatGPT , which have helped revolutionize text-to-image generation and natural language processing. However, in 2018, he transitioned to being a part-time angel investor and advisor to AI startups, and later rejoined Google Brain.

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Depends on the Definition

DECEMBER 9, 2018

In 2018 we saw the rise of pretraining and finetuning in natural language processing. Large neural networks have been trained on general tasks like language modeling and then fine-tuned for classification tasks. One of the latest milestones in this development is the release of BERT.

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Data Science Dojo

SEPTEMBER 8, 2023

However, with the introduction of Deep Learning in 2018, predictive analytics in engineering underwent a transformative revolution. It replaces complex algorithms with neural networks, streamlining and accelerating the predictive process. Uses deep learning, natural language processing, and computer vision.

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Towards AI

JULY 20, 2023

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

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Towards AI

JULY 23, 2023

In the first part of the series, we talked about how Transformer ended the sequence-to-sequence modeling era of Natural Language Processing and understanding. The authors introduced the idea of transfer learning in the natural language processing, understanding, and inference world.

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Towards AI

JUNE 12, 2024

Photo by david clarke on Unsplash The most recent breakthroughs in language models have been the use of neural network architectures to represent text. There is very little contention that large language models have evolved very rapidly since 2018. RNNs and LSTMs came later in 2014. The story starts with word embedding.

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Dataconomy

APRIL 3, 2023

A generative pre-trained transformer (GPT) is a large language model (LLM) neural network that can generate code, answer questions, and summarize text, among other natural language processing tasks. GPT GPT1 : OpenAI released GPT-1 in 2018. But to understand the future, one must first understand the past.

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Mlearning.ai

MAY 5, 2023

However, these early systems were limited in their ability to handle complex language structures and nuances, and they quickly fell out of favor. In the 1980s and 1990s, the field of natural language processing (NLP) began to emerge as a distinct area of research within AI.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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ODSC - Open Data Science

AUGUST 31, 2023

A Mongolian pharmaceutical company engaged in a pilot study in 2018 to detect fake drugs, an initiative with the potential to save hundreds of thousands of lives. The Role of AI in Counterfeit Detection Experts must bolster AI tools to be more proficient at being an anti-counterfeit technology than one to make illegal products.

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Towards AI

JULY 19, 2023

John on Patmos | Correggio NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER The NLP Cypher | 02.14.21 mlpen/Nystromformer Transformers have emerged as a powerful workhorse for a broad range of natural language processing tasks. The Vision of St. Heartbreaker Hey Welcome back! Connected Papers ?

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Dataconomy

JULY 29, 2024

From GPT-1 (introduced in 2018) to GPT-4o (launched in May 2024), ChatGPT has made great strides in understanding and generating natural language. It can now process a diverse mix of inputs, including text, audio, images, and video, and produce output in several forms. million paid subscribers as of March 2024.

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Towards AI

FEBRUARY 10, 2023

Building natural language processing and computer vision models that run on the computational infrastructures of Amazon Web Services or Microsoft’s Azure is energy-intensive. China’s data center industry gets 73% of its power from coal, emitting roughly 99 million tons of CO2 in 2018 [4].

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Dataconomy

AUGUST 10, 2023

With the application of natural language processing (NLP) and machine learning algorithms, AI systems can understand and translate spoken language into written notes. Founded in 2018, Mutuo Health Solutions has ushered in an inventive solution to the often cumbersome task of manual medical documentation.

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AWS Machine Learning Blog

JULY 9, 2024

of its consolidated revenues during the years ended December 31, 2019, 2018 and 2017, respectively. Sonnet made key improvements in visual processing and understanding, writing and content generation, natural language processing, coding, and generating insights. As pointed out in Anthropic’s Claude 3.5

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Dataconomy

FEBRUARY 19, 2025

BERT is an open source machine learning framework for natural language processing (NLP) that helps computers understand ambiguous language by using context from surrounding text. The model was pretrained on text from English Wikipedia and the Brown Corpus, and it can be fine-tuned with question-and-answer datasets.

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Dataconomy

SEPTEMBER 4, 2023

It uses natural language processing (NLP) techniques to extract valuable insights from textual data. For instance, British Airways faced a fine of £183 million ($230 million) for a GDPR breach in 2018. Text analytics is crucial for sentiment analysis, content categorization, and identifying emerging trends.

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Mlearning.ai

FEBRUARY 19, 2023

You don’t need to have a PhD to understand the billion parameter language model GPT is a general-purpose natural language processing model that revolutionized the landscape of AI. GPT-3 is a autoregressive language model created by OpenAI, released in 2020 . What is GPT-3?

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Alation

FEBRUARY 20, 2020

While this requires technology – AI, machine learning, log parsing, natural language processing,metadata management, this technology must be surfaced in a form accessible to business users – the data catalog. The Forrester Wave : Machine Learning Data Catalogs, Q2 2018. Subscribe to Alation's Blog.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

The financial analyst asks the following question: “ What are the closing prices of stocks AAAA, WWW, DDD in year 2018? Prompt the LangChain agent to build an optimal portfolio using the collected data What are the closing prices of stocks AAAA, WWW, DDD in year 2018? Can you build an optimized portfolio using these three stocks? ”

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Smart Data Collective

FEBRUARY 24, 2021

Tomorrow Sleep was launched in 2017 as a sleep system startup and ventured on to create online content in 2018. In order to achieve this, Grammarly’s technology combines machine learning with natural language processing approaches. Tomorrow Sleep Achieved 10,000% Increase in Web Traffic.

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Towards AI

JANUARY 7, 2025

Well do so in three levels: first, by manually adding a classification head in PyTorch* and training the model so you can see the full process; second, by using the Hugging Face* Transformers library to streamline the process; and third, by leveraging PyTorch Lightning* and accelerators to optimize training performance.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Her research interests lie in Natural Language Processing, AI4Code and generative AI. He joined Amazon in 2016 as an Applied Scientist within SCOT organization and then later AWS AI Labs in 2018 working on Amazon Kendra. His research interests lie in the area of AI4Code and Natural Language Processing.

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AWS Machine Learning Blog

JUNE 26, 2024

Technical architecture and key steps The multi-modal agent orchestrates various steps based on natural language prompts from business users to generate insights. For unstructured data, the agent uses AWS Lambda functions with AI services such as Amazon Comprehend for natural language processing (NLP).

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AWS Machine Learning Blog

OCTOBER 5, 2023

His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering. From 2015–2018, he worked as a program director at the US NSF in charge of its big data program. He founded StylingAI Inc.,

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AWS Machine Learning Blog

FEBRUARY 6, 2024

Transformers, BERT, and GPT The transformer architecture is a neural network architecture that is used for natural language processing (NLP) tasks. BERT can be fine-tuned for a variety of NLP tasks, including question answering, natural language inference, and sentiment analysis.

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Pickl AI

JULY 24, 2024

” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. Notable achievements included the development of ELIZA, an early natural language processing program created by Joseph Weizenbaum, which simulated human conversation.

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Towards AI

JULY 21, 2023

Photo by Will Truettner on Unsplash NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER NLP News Cypher | 07.26.20 Last Updated on July 21, 2023 by Editorial Team Author(s): Ricky Costa Originally published on Towards AI. Primus The Liber Primus is unsolved to this day. It contains 3,654 question answer pairs.

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Chatbots Life

MAY 16, 2023

Data Monsters can help companies deploy, train and test machine learning pipelines for natural language processing and computer vision. Data Monsters, a Palo Alto-based R&D lab and consulting company, provides professional services in the AI space. Elite Service Delivery partner of NVIDIA.

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ODSC - Open Data Science

MARCH 6, 2024

REGISTER NOW Building upon the exponential advancements in Deep Learning, Generative AI has attained mastery in Natural Language Processing. The driving force behind Generative AI and Large Language Models (LLMs) is Language Modeling, a Natural Language Processing technique that predicts the next word in a sequence of words.

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