Unite.AI

OCTOBER 18, 2023

Large Language Models (LLMs) are currently one of the most discussed topics in mainstream AI. These models are AI algorithms that utilize deep learning techniques and vast amounts of training data to understand, summarize, predict, and generate a wide range of content, including text, audio, images, videos, and more.

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Marktechpost

MARCH 29, 2025

Large language models struggle to process and reason over lengthy, complex texts without losing essential context. Traditional models often suffer from context loss, inefficient handling of long-range dependencies, and difficulties aligning with human preferences, affecting the accuracy and efficiency of their responses.

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Unite.AI

MARCH 22, 2024

Since OpenAI unveiled ChatGPT in late 2022, the role of foundational large language models (LLMs) has become increasingly prominent in artificial intelligence (AI), particularly in natural language processing (NLP). It offers a more hands-on and communal way for AI to pick up new skills.

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Unite.AI

MARCH 19, 2025

While no AI today is definitively conscious, some researchers believe that advanced neural networks , neuromorphic computing , deep reinforcement learning (DRL), and large language models (LLMs) could lead to AI systems that at least simulate self-awareness.

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Marktechpost

MARCH 1, 2025

Large Language Models (LLMs) have advanced significantly, but a key limitation remains their inability to process long-context sequences effectively. While models like GPT-4o and LLaMA3.1 Longer context windows are essential for AI applications such as multi-turn conversations, document analysis, and long-form reasoning.

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Marktechpost

MARCH 5, 2025

Prior research has explored strategies to integrate LLMs into feature selection, including fine-tuning models on task descriptions and feature names, prompting-based selection methods, and direct filtering based on test scores. A built-in validation step ensures reliability, mitigating potential LLM inaccuracies.

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Unite.AI

MARCH 31, 2025

This method has been celebrated for helping large language models (LLMs) stay factual and reduce hallucinations by grounding their responses in real data. Intuitively, one might think that the more documents an AI retrieves, the better informed its answer will be. Source: Levy et al. Why is this such a surprise?

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Unite.AI

DECEMBER 8, 2023

The integration and application of large language models (LLMs) in medicine and healthcare has been a topic of significant interest and development. The research discussed above delves into the intricacies of enhancing Large Language Models (LLMs) for medical applications.

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Unite.AI

APRIL 5, 2025

NotebookLM is Google's AI research and note-taking tool that understands source materials. While most AI tools draw from their general training data, NotebookLM focuses on understanding and working with your documents. It's like having a research assistant who's read all your materials thoroughly. What is NotebookLM?

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Marktechpost

DECEMBER 13, 2023

The well-known Large Language Models (LLMs) like GPT, BERT, PaLM, and LLaMA have brought in some great advancements in Natural Language Processing (NLP) and Natural Language Generation (NLG). If you like our work, you will love our newsletter.

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Flipboard

MAY 16, 2023

.” The tranche, co-led by General Catalyst and Andreessen Horowitz, is a big vote of confidence in Hippocratic’s technology, a text-generating model tuned specifically for healthcare applications. ” AI in healthcare, historically, has been met with mixed success.

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Marktechpost

MARCH 22, 2025

Large language models (LLMs) are rapidly transforming into autonomous agents capable of performing complex tasks that require reasoning, decision-making, and adaptability. FAIR at Meta and UC Berkeley researchers proposed a new reinforcement learning method called SWEET-RL (Step-WisE Evaluation from Training-time Information).

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Marktechpost

JANUARY 14, 2024

Their aptitude to process and generate language has far-reaching consequences in multiple fields, from automated chatbots to advanced data analysis. Grasping the internal workings of these models is critical to improving their efficacy and aligning them with human values and ethics. If you like our work, you will love our newsletter.

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Marktechpost

JANUARY 5, 2024

While Document AI (DocAI) has made significant strides in areas such as question answering, categorization, and extraction, real-world applications continue to face persistent hurdles related to accuracy, reliability, contextual understanding, and generalization to new domains. If you like our work, you will love our newsletter.

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Marktechpost

JANUARY 15, 2024

LLMs are trained on vast amounts of web data, which can lead to unintentional memorization and reproduction of sensitive or private information. This approach involves modifying models after training to deliberately ‘forget’ certain elements of their training data. Check out the Paper and Project.

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Unite.AI

FEBRUARY 26, 2025

A standout feature of Bridgetowns AI suite is its voice botssophisticated AI agents trained to recruit and interview industry experts. By collecting primary datadirect insights from seasoned professionalsthese agents provide businesses with proprietary intelligence that goes beyond publicly available information.

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Unite.AI

JANUARY 6, 2025

Training large language models (LLMs) has become out of reach for most organizations. With costs running into millions and compute requirements that would make a supercomputer sweat, AI development has remained locked behind the doors of tech giants.

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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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AI News

JANUARY 9, 2025

In the suit, the Times alleges that OpenAI committed copyright infringement when it ingested thousands of articles to train its large language models. Balaji said he initially bought OpenAI’s argument that if the information was posted online and freely available, scraping constituted fair use.

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John Snow Labs

NOVEMBER 8, 2024

Our results indicate that, for specialized healthcare tasks like answering clinical questions or summarizing medical research, these smaller models offer both efficiency and high relevance, positioning them as an effective alternative to larger counterparts within a RAG setup. What is Retrieval-Augmented Generation?

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Towards AI

NOVEMBER 11, 2024

This issue is especially common in large language models (LLMs), the neural networks that drive these AI tools. They produce sentences that flow well and seem human, but without truly “understanding” the information they’re presenting. Today, AI researchers face this same kind of limitation.

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Unite.AI

MARCH 19, 2025

In recent years, large language models (LLMs) have made significant progress in generating human-like text, translating languages, and answering complex queries. In this article, well explore the transition from LLMs to LCMs and how these new models are transforming the way AI understands and generates language.

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Marktechpost

DECEMBER 27, 2023

In the evolving landscape of artificial intelligence and machine learning, the integration of visual perception with language processing has become a frontier of innovation. This integration is epitomized in the development of Multimodal Large Language Models (MLLMs), which have shown remarkable prowess in a range of vision-language tasks.

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Marktechpost

JULY 8, 2024

Large language models (LLMs) have demonstrated remarkable performance across various tasks, with reasoning capabilities being a crucial aspect of their development. The last layers’ intrinsic dimension proves highly informative about response correctness across model sizes.

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Unite.AI

FEBRUARY 19, 2025

Large language models (LLMs) like OpenAIs o3 , Googles Gemini 2.0 , and DeepSeeks R1 have shown remarkable progress in tackling complex problems, generating human-like text, and even writing code with precision. But do these models actually reason , or are they just exceptionally good at planning ?

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Marktechpost

JANUARY 2, 2024

The development of multimodal large language models (MLLMs) represents a significant leap forward. These advanced systems, which integrate language and visual processing, have broad applications, from image captioning to visible question answering. If you like our work, you will love our newsletter.

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Marktechpost

JANUARY 12, 2024

[link] Enter ‘DiarizationLM,’ a groundbreaking framework developed by researchers at Google that promises to revolutionize speaker diarization by harnessing the power of large language models (LLMs). The inner workings of DiarizationLM are as intriguing as its premise.

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Flipboard

APRIL 2, 2025

Large language models think in ways that dont look very human. Their outputs are formed from billions of mathematical signals bouncing through layers of neural networks powered by computers of unprecedented power and speed, and most of that activity remains invisible or inscrutable to AI researchers.

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Flipboard

MARCH 21, 2025

Its not a new feature to the AI worldbut the companys approach stands as one the most thoughtful to date. Much like Perplexity , Anthropics Claude works relevant information from the web into a conversational answer, and includes clickable source citations. but let me search for more precise information since this could have changed.

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Marktechpost

NOVEMBER 16, 2023

Large language models, like GPT-3, learn from vast data, including examples of correct and incorrect language usage. These models are trained on diverse datasets containing a wide range of text from the internet, books, articles, and more. It understands grammar, syntax, semantics, and even nuances of language use.

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Marktechpost

FEBRUARY 13, 2024

A groundbreaking study unveils an approach to peering into the minds of Large Language Models (LLMs), particularly focusing on GPT-4’s understanding of color. The challenge of interpreting AI models lies in their complexity and the opaque nature of their internal workings.

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Marktechpost

SEPTEMBER 1, 2023

Therefore, researchers from Tilburg University and University College London survey the state of safety and security research on LLMs and provide a taxonomy of existing techniques by classifying them according to dangers, preventative measures, and security holes. If you like our work, you will love our newsletter.

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Marktechpost

OCTOBER 4, 2024

Multimodal large language models (MLLMs) represent a cutting-edge area in artificial intelligence, combining diverse data modalities like text, images, and even video to build a unified understanding across domains. is poised to address key challenges in multimodal AI. The post Apple AI Research Introduces MM1.5:

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Marktechpost

DECEMBER 30, 2023

The recent advancements in Artificial Intelligence have enabled the development of Large Language Models (LLMs) with a significantly large number of parameters, with some of them reaching into billions (for example, LLaMA-2 that comes in sizes of 7B, 13B, and even 70B parameters).

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Marktechpost

DECEMBER 14, 2023

The advancement of technology has ushered in a digital age where language models play an increasingly important role in information processing, communication, and problem-solving. Recently, Deci has introduced DeciLM-7B, an innovative model with high precision and speed available in the 7-billion-parameter class.

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Unite.AI

MARCH 2, 2025

Artificial Intelligence (AI) is evolving at an unprecedented pace, with large-scale models reaching new levels of intelligence and capability. From early neural networks to todays advanced architectures like GPT-4 , LLaMA , and other Large Language Models (LLMs) , AI is transforming our interaction with technology.

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Marktechpost

DECEMBER 13, 2023

Large Language Models (LLMs), due to their strong generalization and reasoning powers, have significantly uplifted the Artificial Intelligence (AI) community. This function guarantees recoverability and retains crucial information even after translation, adding to LLMLingua’s overall impressiveness.

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