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 Researcher AI Research Natural Language Processing Neural Network 111

Marktechpost

JANUARY 17, 2024

The field of natural language processing has been transformed by the advent of Large Language Models (LLMs), which provide a wide range of capabilities, from simple text generation to sophisticated problem-solving and conversational AI. All credit for this research goes to the researchers of this project.

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LLM Algorithm AI Researcher AI Research 93

ODSC - Open Data Science

FEBRUARY 14, 2023

It is the latest in the research lab’s lineage of large language models using Generative Pre-trained Transformer (GPT) technology. Trained with 570 GB of data from books and all the written text on the internet, ChatGPT is an impressive example of the training that goes into the creation of conversational AI.

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ChatGPT Large Language Models OpenAI Conversational AI 124

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.

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Large Language Models Natural Language Processing AI Researcher AI Research 110

Topbots

DECEMBER 19, 2023

The NeurIPS 2023 conference, held in the vibrant city of New Orleans from December 10th to 16th, had a particular emphasis on generative AI and large language models (LLMs). One of the core themes of this year’s conference was the quest for more efficient AI systems. Sign up for more AI research updates.

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Computer Vision Natural Language Processing AI Researcher AI Research 52

NVIDIA

AUGUST 10, 2023

“AI Village draws the community concerned about the implications of AI systems – both malicious use and impact on society,” said Sven Cattell founder of AI Village and co-organizer of the Generative Red Team Challenge. “At This marked the first time a company had allowed public access to their model for scrutiny.”

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Generative AI Large Language Models LLM OpenAI 85

Topbots

SEPTEMBER 11, 2023

Often, companies assume that all they need to include AI in their offering is to hire AI experts and let them play the technical magic. Over the years, I have seen a great deal of frustration from data scientists and engineers whose technically outstanding AI implementations did not find their way into user-facing products.

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UX Design AI AI Automation 59

Topbots

JUNE 15, 2023

Large language models such as ChatGPT process and generate text sequences by first splitting the text into smaller units called tokens. Over a hundred years ago, telegraphy, a revolutionary technology of its time (“the internet of its era”), faced language inequities similar to those we see in today’s large language models.

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Natural Language Processing Computational Linguistics NLP ChatGPT 59

Marktechpost

MAY 1, 2024

Free LLM Playgrounds and Their Comparative Analysis As the landscape of AI technology advances, the proliferation of free platforms to test large language models (LLMs) online has greatly increased. Its extensive offerings support a broad spectrum of AI research and development activities. Image Source 3.

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LLM Large Language Models Data Scientist Artificial Intelligence 101

Topbots

JUNE 29, 2023

This vision is embraced by conversational interfaces which allow humans to interact with data using language, our most intuitive and universal channel of communication. After parsing a question, an algorithm encodes it into a structured logical form in the query language of choice, such as SQL. in the data.

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Auto-complete Algorithm Data Scientist Auto-classification 52

Topbots

JUNE 6, 2023

There are three principal dimensions along which LLMs can become more efficient: Less compute and memory : for example, FlashAttention [4] allows to reduce number of reads and writes on GPU as compared to standard attention algorithms, thus leading to faster and memory-efficient fine-tuning. Scaling Laws for Neural Language Models. [7]

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