Heartbeat

JANUARY 15, 2024

However, researchers have devised various solutions to address this issue. CNN for Deep Learning U-Net: Embracing Semantic Segmentation One of the most enchanting acts in deep learning is U-Net. With its encoder-decoder design, U-Net architecture gracefully navigates through the complexities of semantic segmentation.

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Dataconomy

JULY 18, 2023

Its tendency to hallucinate results in the frequent propagation of incorrect information, making it less suitable for serious research work. Although the model is released for academic research purposes, it highlights the necessity of further evaluation and reporting on any troubling behaviors. does exhibit some shortcomings.

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IBM Journey to AI blog

AUGUST 28, 2023

Part-of-speech (POS) tagging: POS tagging facilitates semantic analysis by assigning grammatical tags to words (e.g., Syntax parsing: Parsing involves analyzing the structure of sentences and phrases to determine the role of different words in the text. noun, verb, adjective, etc.),

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Mlearning.ai

DECEMBER 21, 2023

In May 2020, researchers in their paper “ Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks ” explored models which combine pre-trained parametric and non-parametric memory for language generation. The official paper —  [link] Facebook’s AI research, fastText builds embeddings composed of characters instead of words.

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Google Research AI blog

OCTOBER 26, 2022

Posted by Kedem Snir, Software Engineer, and Gal Elidan, Senior Staff Research Scientist, Google Research Whether it's a professional honing their skills or a child learning to read, coaches and educators play a key role in assessing the learner's answer to a question in a given context and guiding them towards a goal.

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ODSC - Open Data Science

FEBRUARY 15, 2024

Anthropic HH Golden The Anthropic HH Golden dataset is a collection of high-quality human-human conversations. It is a curated collection of high-quality human-human conversations, capturing the essence of natural, spontaneous dialogue. It can be valuable for fine-tuning LLMs to generate more natural and engaging responses.

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Flipboard

APRIL 13, 2023

We take the same democratizing approach to generative AI: we work to take these technologies out of the realm of research and experiments and extend their availability far beyond a handful of startups and large, well-funded tech companies.

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Google Research AI blog

JULY 23, 2023

Posted by Cat Armato, Program Manager, Google Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. As a leader in ML research, Google has a strong presence at this year’s conference with over 120 accepted papers and active involvement in a number of workshops and tutorials.

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Google Research AI blog

DECEMBER 7, 2022

We are proud to be a Diamond Sponsor of EMNLP 2022, with Google researchers contributing at all levels. Take a look below to learn more about the Google research being presented at EMNLP 2022 (Google affiliations in bold ). This year we are presenting over 50 papers and are actively involved in 10 different workshops and tutorials.

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Chatbots Life

SEPTEMBER 11, 2023

From casual online conversations to professional correspondence, our ability to express ourselves effectively is deeply connected to the precision of our language. No Semantic Understanding: Spell checkers generally do not understand the semantics of the text, so they may suggest incorrect corrections that don’t make sense in the context.

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ML Review

DECEMBER 16, 2019

The main venue alone had more than 100 graph-related publications, and even more were available at three workshops: Graph Representation Learning (about 100 more papers), Knowledge Representation & Reasoning Meets Machine Learning (KR2ML) (about 50 papers), Conversational AI. So we’ll consider all events jointly. Great work! ?

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The MLOps Blog

MARCH 12, 2024

Recommended LLM Fine-Tuning and Model Selection Using Neptune and Transformers Read more Training and serving LLMs For larger organizations or dedicated research teams, the journey may involve training LLMs from scratch—a path taken when existing models fail to meet an application’s unique demands or when pushing the envelope of innovation.

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AWS Machine Learning Blog

AUGUST 14, 2023

Researchers can download, run, and study BLOOM to investigate the performance and behavior of recently developed LLMs down to their deepest internal operations. LLMs have demonstrated remarkable capabilities in learning the semantics of natural language and producing human-like responses. The [robot] is very nice and empathetic.

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phData

JUNE 7, 2023

Early AI research focused on rule-based systems, known as expert systems, which mimicked human decision-making in specific domains. Research in artificial neural networks – now the foundation of modern AI – began around 1950, but progress stalled for decades due to challenges in training them to solve meaningful problems.

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