Unite.AI

FEBRUARY 28, 2024

Large language models (LLMs) like GPT-4, DALL-E have captivated the public imagination and demonstrated immense potential across a variety of applications. Question answering: They can provide informative answers to natural language questions across a wide range of topics.

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Unite.AI

FEBRUARY 23, 2024

However, instruction-based methods often provide brief directions that may be challenging for existing models to fully capture and execute. Additionally, diffusion models, known for their ability to create realistic images, are in high demand within the image editing sector.

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Marktechpost

OCTOBER 23, 2024

Utilizing Large Language Models (LLMs) through different prompting strategies has become popular in recent years. Differentiating prompts in multi-turn interactions, which involve several exchanges between the user and model, is a crucial problem that remains mostly unresolved. LLMs can be promoted in various ways.

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Marktechpost

OCTOBER 27, 2024

Formal theorem proving has emerged as a critical benchmark for assessing the reasoning capabilities of large language models (LLMs), with significant implications for mathematical automation. The earliest breakthrough came with next tactic prediction, where models generate the next proof step based on the current proof state.

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Marktechpost

JANUARY 2, 2024

Recent advances in the field of Artificial Intelligence (AI) and Natural Language Processing (NLP) have led to the introduction of Large Language Models (LLMs). and Harbin Institute of Technology has introduced KwaiAgents, an information-seeking agent system based on LLMs.

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Marktechpost

JANUARY 30, 2024

One of the most exciting advancements in AI and machine learning has been speech generation using Large Language Models (LLMs). While effective in various applications, the traditional methods face a significant challenge: the integration of semantic and perceptual information, often resulting in inefficiencies and redundancies.

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Marktechpost

JANUARY 12, 2024

One of the most important areas of NLP is information extraction (IE), which takes unstructured text and turns it into structured knowledge. At the same time, Llama and other large language models have emerged and are revolutionizing NLP with their exceptional text understanding, generation, and generalization capabilities.

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Marktechpost

SEPTEMBER 29, 2024

Large Language Models (LLMs) are vulnerable to jailbreak attacks, which can generate offensive, immoral, or otherwise improper information. Don’t Forget to join our 50k+ ML SubReddit. The post JailbreakBench: An Open Sourced Benchmark for Jailbreaking Large Language Models (LLMs) appeared first on MarkTechPost.

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Marktechpost

FEBRUARY 13, 2024

The quest to enhance Large Language Models (LLMs) has led to a groundbreaking innovation by a team from the Beijing Academy of Artificial Intelligence and Gaoling School of Artificial Intelligence at Renmin University. Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup.

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Large Language Models Artificial Intelligence Artificial Intelligence Data Analysis 133

Marktechpost

NOVEMBER 11, 2024

While Large Language Models (LLMs) have revolutionized various AI domains and shown potential as sources of structured knowledge, extracting and materializing their complete knowledge remains a significant challenge. Don’t Forget to join our 55k+ ML SubReddit. [ The most common properties are patentCitation (3.15

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Large Language Models Natural Language Processing LLM ML 80

Marktechpost

NOVEMBER 16, 2024

Large language models (LLMs) have revolutionized natural language processing by offering sophisticated abilities for a range of applications. However, these models face significant challenges. Don’t Forget to join our 55k+ ML SubReddit. If you like our work, you will love our newsletter.

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Marktechpost

JANUARY 21, 2024

Large Language Models (LLMs) have exhibited remarkable prowess across various natural language processing tasks. However, applying them to Information Retrieval (IR) tasks remains a challenge due to the scarcity of IR-specific concepts in natural language. Also, don’t forget to follow us on Twitter.

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Towards AI

MAY 3, 2023

Solving Machine Learning Tasks with MLCoPilot: Harnessing Human Expertise for Success Many of us have made use of large language models (LLMs) like ChatGPT to generate not only text and images but also code, including machine learning code. This is where ML CoPilot enters the scene.

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Marktechpost

JULY 22, 2024

Large Language Models (LLMs) have revolutionized natural language processing, demonstrating remarkable capabilities in various applications. The architecture processes tokenized input through embedding layers, applies multi-headed self-attention, and incorporates positional encoding to retain sequence order information.

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Large Language Models Neural Network Natural Language Processing LLM 128

Marktechpost

MAY 7, 2024

The emergence of large language models (LLMs) has profoundly influenced the field of biomedicine, providing critical support for synthesizing vast data. These models are instrumental in distilling complex information into understandable and actionable insights. on the GIT and ChemProt datasets, respectively.

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Flipboard

NOVEMBER 26, 2023

Amazon Redshift ML empowers data analysts and database developers to integrate the capabilities of machine learning and artificial intelligence into …

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Marktechpost

OCTOBER 2, 2024

Large Language Models (LLMs) have made significant strides in various Natural Language Processing tasks, yet they still struggle with mathematics and complex logical reasoning. Some limitations are observed in the RuleTaker and ProofWriter datasets with GPT-4, attributed to information extraction issues.

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Marktechpost

MAY 4, 2024

Large Language Models (LLMs) represent a significant leap in artificial intelligence, offering robust natural language understanding and generation capabilities. These advanced models can perform various tasks, from aiding virtual assistants to generating comprehensive content and conducting in-depth data analysis.

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Marktechpost

SEPTEMBER 2, 2024

Information retrieval (IR) is a fundamental aspect of computer science, focusing on efficiently locating relevant information within large datasets. Recent developments in machine learning, particularly in natural language processing (NLP), have significantly enhanced the capabilities of IR systems.

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Marktechpost

OCTOBER 30, 2024

Theory of Mind (ToM) capabilities – the ability to attribute mental states and predict behaviors of others – have become increasingly critical as Large Language Models (LLMs) become more integrated into human interactions and decision-making processes.

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Marktechpost

OCTOBER 13, 2024

One of the key findings was that the softmax-then-topK routing consistently outperformed other approaches, such as topK-then-softmax, which is often used in dense models. This new approach allowed the upcycled MoE models to better utilize the information contained in the expert layers, leading to improved performance.

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Marktechpost

MAY 7, 2024

The burgeoning expansion of the data landscape, propelled by the Internet of Things (IoT), presents a pressing challenge: ensuring data quality amidst the deluge of information. With IoT devices increasingly interconnected and data acquisition costs declining, enterprises are capitalizing on this wealth of data to inform strategic decisions.

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Marktechpost

SEPTEMBER 22, 2024

In artificial intelligence and natural language processing, long-context reasoning has emerged as a crucial area of research. As the volume of information that needs to be processed grows, machines must be able to synthesize and extract relevant data from massive datasets efficiently.

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Large Language Models Artificial Intelligence Artificial Intelligence Natural Language Processing 124

Marktechpost

FEBRUARY 3, 2024

A significant challenge is the models’ tendency to produce “hallucinations” or factual errors due to their reliance on internal knowledge bases. The pivotal question arises: what happens when the retrieval process fails, introducing inaccuracies or irrelevant information into the generative process?

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Marktechpost

SEPTEMBER 17, 2024

Prior research on Large Language Models (LLMs) demonstrated significant advancements in fluency and accuracy across various tasks, influencing sectors like healthcare and education. This progress sparked investigations into LLMs’ language understanding capabilities and associated risks.

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Marktechpost

SEPTEMBER 23, 2024

Large language models (LLMs) have gained significant attention due to their potential to enhance various artificial intelligence applications, particularly in natural language processing. Currently, approaches like prompting techniques align the models’ responses with document-grounded information.

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Large Language Models Natural Language Processing LLM AI 117

Marktechpost

MARCH 1, 2024

The quest for clean, usable data for pretraining Large Language Models (LLMs) resembles searching for treasure amidst chaos. While rich with information, the digital realm is cluttered with extraneous content that complicates the extraction of valuable data. Also, don’t forget to follow us on Twitter and Google News.

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Large Language Models Data Extraction Neural Network LLM 134

Marktechpost

JULY 25, 2024

Large Language Models (LLMs) excel in generating human-like text, offering a plethora of applications from customer service automation to content creation. This method leverages human conversation strategies to extract harmful information from LLMs. However, this immense potential comes with significant risks.

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Marktechpost

OCTOBER 12, 2024

Multimodal Large Language Models (MLLMs) have made significant progress in various applications using the power of Transformer models and their attention mechanisms. The attention mechanism, which determines how input information is weighted to generate outputs, is especially prone to these biases.

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Marktechpost

JULY 13, 2024

Large language models (LLMs) have been crucial for driving artificial intelligence and natural language processing to new heights. First, demonstration examples are processed to generate an in-context vector that captures essential task information. Check out the Paper and GitHub.

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Large Language Models Natural Language Processing LLM Artificial Intelligence 126

Marktechpost

OCTOBER 18, 2024

Recent advancements in Large Language Models (LLMs) have reshaped the Artificial intelligence (AI)landscape, paving the way for the creation of Multimodal Large Language Models (MLLMs). This step helps the model understand and work with both visuals and sounds.

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Marktechpost

SEPTEMBER 27, 2024

When asked to produce fallacious content, these models often “leak” truthful information instead, making it difficult to prevent them from offering accurate yet potentially harmful outputs. The researchers developed FFA to bypass existing safeguards by leveraging the models’ inherent weakness in fallacious reasoning.

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Marktechpost

AUGUST 24, 2024

Retrieval Augmented Generation (RAG) represents a cutting-edge advancement in Artificial Intelligence, particularly in NLP and Information Retrieval (IR). This integration allows LLMs to perform more accurately and effectively in knowledge-intensive tasks, especially where proprietary or up-to-date information is crucial.

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Marktechpost

OCTOBER 6, 2024

A popular method when employing Large Language Models (LLMs) for complicated analytical tasks, such as code generation, is to attempt to solve the full problem within the model’s context window. The informational segment that the LLM is capable of processing concurrently is referred to as the context window.

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Marktechpost

SEPTEMBER 17, 2024

Generative Large Language Models (LLMs) are capable of in-context learning (ICL), which is the process of learning from examples given within a prompt. However, research on the precise principles underlying these models’ ICL performance is still underway. If you like our work, you will love our newsletter.

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Large Language Models Prompt Engineering Prompt Engineer LLM 111

Flipboard

NOVEMBER 21, 2024

We use the open source library fmeval to evaluate the model and register it in the Amazon SageMaker Model Registry based on its performance. Solution overview The following architecture diagram shows the various steps involved to create an automated and scalable process to fine-tune large language models (LLMs) using AutoMLV2.

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Marktechpost

OCTOBER 27, 2024

Large Language Models (LLMs) have lately demonstrated potential in expediting scientific discovery by generating research ideas due to their extensive text-processing capabilities. Don’t Forget to join our 55k+ ML SubReddit. LLMs become more useful instruments for scientific discovery because of this organized framework.

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