Towards AI

OCTOBER 10, 2024

The evolution of Large Language Models (LLMs) allowed for the next level of understanding and information extraction that classical NLP algorithms struggle with. The data span a period of 18 years, including ~35 million reviews up to March 2013. But often, these methods fail on more complex tasks.

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Unite.AI

NOVEMBER 30, 2023

By 2013, I began wondering if I could do something bigger. Randy and I both come from finance and algorithmic trading backgrounds, which led us to take the concept of matching requests with answers to build our own NLP for hyper-specific inquiries that would get asked at locations. By 25, I was running my own department.

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Unite.AI

OCTOBER 20, 2023

I had a casual conversation with some software developers who had done some rudimentary experiments with audio and text (not transcription) in 2013. NLP and speech processing algorithms are part of our day-to-day, but we will investigate any creative ways to use AI to help journalists extract information from videos, audios and images.

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Towards AI

APRIL 8, 2024

While numerous techniques have been explored, methods harnessing natural language processing (NLP) have demonstrated strong performance. Word2Vec, a widely-adopted NLP algorithm has proven to be an efficient and valuable tool that is now applied across multiple domains, including recommendation systems.

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Hal Daumé III

MARCH 14, 2017

I had the pleasure of writing a mini-bio for Kathy for NAACL 2013 when I got to introduce her as one of the two invited speakers, and learned during that time that she was the first woman chair of computer science at Columbia and also the first woman to get tenure in the entirety of Columbia's School of Engineering and Applied Science.

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Sebastian Ruder

JANUARY 19, 2021

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP). This is less of a problem in NLP where unsupervised pre-training involves classification over thousands of word types.

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Marek Rei

APRIL 28, 2022

I am sharing here the yearly paper analysis for 2021, containing statistics about ML and NLP publications from the past year. Microsoft, CAS, Amazon, Tencent, Cambridge, Washington and Alibaba stand out as having quite a large proportion of papers at NLP conferences, whereas the other top organizations seem to focus mostly on ML venues.

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AWS Machine Learning Blog

FEBRUARY 2, 2024

Embeddings capture the information content in bodies of text, allowing natural language processing (NLP) models to work with language in a numeric form. In entered the Big Data space in 2013 and continues to explore that area. He also holds an MBA from Colorado State University.

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Hal Daumé III

JULY 16, 2018

You should also read these sources (which mostly focus on panels, not invited speakers, and also mostly focus on gender): Four steps to put an end to all-male panels at conferences , Bronwen Clune, The Guardian, 2013 Stop Agreeing To Be On All-Male Panels Just Stop , Emily Peck, Huffington Post, 2016 How to avoid an all-male panel?

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Sebastian Ruder

AUGUST 18, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP. In the span of little more than a year, transfer learning in the form of pretrained language models has become ubiquitous in NLP and has contributed to the state of the art on a wide range of tasks. However, transfer learning is not a recent phenomenon in NLP.

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Hal Daumé III

AUGUST 14, 2016

P16-1152 : Artem Sokolov; Julia Kreutzer; Christopher Lo; Stefan Riezler Learning Structured Predictors from Bandit Feedback for Interactive NLP This was perhaps my favorite paper of the conference because it's trying to do something new and hard and takes a nice approach. P16-2096 : Dirk Hovy; Shannon L.

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ML Review

FEBRUARY 26, 2018

Following its successful adoption in computer vision and voice recognition, DL will continue to be applied in the domain of natural language processing (NLP). ACM, 2013: 2333–2338. [2] 2] Minghui Qiu and Feng-Lin Li. MeChat: A Sequence to Sequence and Rerank based Chatbot Engine.

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Unite.AI

JULY 28, 2023

MarketMuse, founded by Aki Balogh and Jeff Coyle in 2013, is a content marketing and keyword planner tool that utilizes artificial intelligence and machine learning. Conducts real-time research with NLP, semantic analysis, and the best SEO practices to write an entire article. MarketMuse Key Features: Competitive content analysis.

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Snorkel AI

FEBRUARY 6, 2024

The first DARPA funding that Snorkel ever had back in 2012, 2013 was a wonderful project called SIMPLEX. Then, once they have the information, they have to understand and be tuned how to make the right decision for their domain, their company, their objectives. This segues into another topic that I’m always a broken record about.

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ODSC - Open Data Science

FEBRUARY 28, 2023

Narrowing the communications gap between humans and machines is one of SAS’s leading projects in their work with NLP. Plotly In the time since it was founded in 2013, Plotly has released a variety of products including Plotly.py, which, along with Plotly.r, became one of “the most downloaded interactive graphing libraries in the world.”

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AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. In entered the Big Data space in 2013 and continues to explore that area. He also holds an MBA from Colorado State University. Nitin Eusebius is a Sr.

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Sebastian Ruder

OCTOBER 26, 2019

Cross-lingual learning might be useful—but why should we care about applying NLP to other languages in the first place? The NLP Resource Hierarchy In current machine learning, the amount of available training data is the main factor that influences an algorithm's performance. 2015 , Artetxe et al.,

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Topbots

JUNE 15, 2023

Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. 2 ] Multilingual models perform worse on several NLP tasks on low resource languages than on high resource languages such as English.[ Common Crawl makes up 60% of GPT-3 training data.[ OpenAI API.

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Topbots

SEPTEMBER 11, 2023

3] Don Norman (2013). 4] Google, Gartner and Motista (2013). Continuous Discovery Habits: Discover Products that Create Customer Value and Business Value. [2] 2] Orbit Media (2022). New Blogging Statistics: What Content Strategies Work in 2022? We asked 1016 Bloggers. [3] The Design of Everyday Things. [4]

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The Stanford AI Lab Blog

MAY 31, 2022

Language Model Pretraining Language models (LMs), like BERT 1 and the GPT series 2 , achieve remarkable performance on many natural language processing (NLP) tasks. They are now the foundation of today’s NLP systems. 2013. ↩ Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing.

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Artificial Corner

JUNE 6, 2023

Natural Language Processing (NLP) techniques can be applied to analyze and understand unstructured text data. The integration of AI and ML into data engineering pipelines enables a wide range of applications. For example, predictive analytics models can be trained on historical data to make accurate forecasts. Zaharia, M., Morgan Kaufmann.

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Probably Approximately a Scientific Blog

AUGUST 30, 2019

This has caused some fear among the general population; some criticism among other NLP people; and many questions from their relatives ("hey, look at this article I've found - did they just solve NLP? The effect is similar to the effect that pre-trained word embeddings had on NLP in 2013.

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Sebastian Ruder

DECEMBER 6, 2021

2013 ), MCScript ( Modi et al., Among current key applications of NLP, QA has the lowest linguistic global utility, i.e. performance averaged across the world's languages ( Blasi et al., Linguistic and demographic utility of different NLP applications ( Blasi et al., 2018 ), Children's Book Test ( Hill et al.,

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Explosion

DECEMBER 13, 2021

This new experimental tokenizer uses spaCy’s built-in NER component under the hood to segment on the character level, following the idea behind the Elephant tokenizer (Evang et al. If you haven’t already installed transformers , you might want to have a look at our recommended installation steps.

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Lexalytics

APRIL 5, 2021

Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. As with ULMFiT and ELMo, these contextual word vectors could be incorporated into any NLP application. I was out of the neural net biz. and BERT. Socher, L.-J.

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Explosion

DECEMBER 17, 2013

I wrote this blog post in 2013, describing an exciting advance in natural language understanding technology. You should probably at least skim that post before reading this one, unless you’re very familiar with NLP research. The derivation for the transition system we’re using, Arc Hybrid, is in Goldberg and Nivre (2013).

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Probably Approximately a Scientific Blog

JANUARY 3, 2016

2] , but gained extreme popularity with word2vec [3] in 2013. Suggested Reading: Deep Learning, NLP, and Representations , from Christopher Olah's blog (more technical and advanced). CoRR, 2013. This approach was first presented in 2003 by Bengio et al. [2] There are also some other variants of word embeddings, like GloVe [4].

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NLP People

JULY 24, 2019

We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. The article is backed by a statistical and – guess what – NLP-based analysis of ACL papers from the last 20 years. But what is the substance behind the buzz?

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ML Review

MARCH 5, 2019

Star our repo: ai-distillery And clap your little hearts out for MTank ! References Harris, Z. Distributional structure. Word, 10(2–3), 146–162. Mikolov, T., Sutskever, I., Corrado, G. S., & Dean, J. Distributed Representations of Words and Phrases and their Compositionality. In NIPS (pp. 3111–3119). Bojanowski, P.,

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ODSC - Open Data Science

FEBRUARY 29, 2024

The Facebook AI Research Lab (FAIR) Established in 2013, FAIR has quickly become one of the most influential AI research labs in the world, partially when it comes to open-source technology and models such as Llama 2. Another project, SynthID , helps to identify and watermark AI-generated images.

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ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Attention and Memory in Deep Learning and NLP. In: Daniilidis K., Paragios N.

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ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

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Viso.ai

DECEMBER 21, 2023

His contributions to ML, deep learning , computer vision, and NLP underscore his influence in the rapidly evolving AI landscape. Transitioning to Facebook (now Meta) in 2013, LeCun served as the first Director of AI Research. Thus, positioning him as one of the top AI influencers in the world.

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Probably Approximately a Scientific Blog

NOVEMBER 12, 2016

In the my introductory post about NLP I introduced the following survey question: when you search something in Google (or any other search engine of your preference), is your query: (1) a full question, such as "What is the height of Mount Everest?" (2) In EMNLP 2013. [3] Question answering systems have been around since the 1960s.

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Probably Approximately a Scientific Blog

NOVEMBER 23, 2016

Antonymy in NLP While there is a vast linguistics literature about antonyms, I'm less familiar with it, and I'm going to focus on some observations and interesting points about antonymy that appear in NLP papers that I read. ACL 2015. [3] 3] Computing Word-Pair Antonymy. Saif Mohammad, Bonnie Dorr and Graeme Hirst. EMNLP 2008. [4]

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