Unite.AI

MAY 8, 2024

In parallel, Large Language Models (LLMs) like GPT-4, and LLaMA have taken the world by storm with their incredible natural language understanding and generation capabilities. In this article, we will delve into the latest research at the intersection of graph machine learning and large language models.

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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 Also,feel free to follow us on Twitter and dont forget to join our 80k+ ML SubReddit.

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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. Also,feel free to follow us on Twitter and dont forget to join our 80k+ ML SubReddit.

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Unite.AI

JANUARY 22, 2025

MLOps is a set of practices designed to streamline the machine learning (ML) lifecyclehelping data scientists, IT teams, business stakeholders, and domain experts collaborate to build, deploy, and manage ML models consistently and reliably. With the rise of large language models (LLMs), however, new challenges have surfaced.

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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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Flipboard

MARCH 21, 2025

AI for IT operations (AIOps) is the application of AI and machine learning (ML) technologies to automate and enhance IT operations. AIOps helps IT teams manage and monitor large-scale systems by automatically detecting, diagnosing, and resolving incidents in real time.

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Marktechpost

APRIL 9, 2025

While these sinks were previously seen as artifacts of large key and query activations, this work argues that they are vital in maintaining stable representations, especially in long sequences. By concentrating attention, sinks prevent excessive mixing of information across layers, helping to preserve the uniqueness of token representations.

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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

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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AWS Machine Learning Blog

NOVEMBER 19, 2024

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services. Visit the session catalog to learn about all our generative AI and ML sessions.

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Marktechpost

APRIL 11, 2025

Notably, some problems are designed to have no solution or feature unrelated information, testing LLMs ability to recognize illogical conditions and resist recitation-based answers. Overall, these findings highlight the limitations of current models in adaptive reasoning. Annotators ensured minimal wording changes and no ambiguity.

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Marktechpost

JULY 16, 2024

Telecommunications involves the transmission of information over distances to communicate. Mainstream Large Language Models (LLMs) lack specialized knowledge in telecommunications, making them unsuitable for specific tasks in this field. Join our Telegram Channel and LinkedIn Gr oup.

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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

MARCH 15, 2025

Large Language Models (LLMs) have become crucial in customer support, automated content creation, and data retrieval. Also, they generate misleading or incorrect information, commonly called hallucination, making their deployment challenging in scenarios requiring precise, context-aware decision-making.

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Marktechpost

APRIL 2, 2025

Research on LLM applications in gaming has taken multiple directions, including evaluating model competency in simple deterministic games like Tic-Tac-Toe and assessing their strategic reasoning in more complex environments. Also,feel free to follow us on Twitter and dont forget to join our 85k+ ML SubReddit.

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Large Language Models Prompt Engineer Prompt Engineering LLM 48

Flipboard

JANUARY 24, 2025

In this post, we show you an example of a generative AI assistant application and demonstrate how to assess its security posture using the OWASP Top 10 for Large Language Model Applications , as well as how to apply mitigations for common threats.

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Marktechpost

NOVEMBER 6, 2024

With a growing dependence on technology, the need to protect sensitive information and secure communication channels is more pressing than ever. Until recently, existing large language models (LLMs) have lacked the precision, reliability, and domain-specific knowledge required to effectively support defense and security operations.

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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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Flipboard

DECEMBER 3, 2024

This conversational agent offers a new intuitive way to access the extensive quantity of seed product information to enable seed recommendations, providing farmers and sales representatives with an additional tool to quickly retrieve relevant seed information, complementing their expertise and supporting collaborative, informed decision-making.

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AWS Machine Learning Blog

DECEMBER 16, 2024

70B marks an exciting advancement in large language model (LLM) development, offering comparable performance to larger Llama versions with fewer computational resources. This performance profile makes it an ideal candidate for organizations seeking to balance model capabilities with operational efficiency. Deploy Llama 3.3

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Flipboard

FEBRUARY 10, 2025

Multimodal Capabilities in Detail Configuring Your Development Environment Project Structure Implementing the Multimodal Chatbot Setting Up the Utilities (utils.py) Designing the Chatbot Logic (chatbot.py) Building the Interface (app.py) Summary Citation Information Building a Multimodal Gradio Chatbot with Llama 3.2 Introducing Llama 3.2

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Marktechpost

SEPTEMBER 20, 2024

As datasets grow, existing models struggle to maintain scalability and efficiency, especially when real-time predictions are required. Traditional methods in the field, such as ID-based embeddings, use simple encoding techniques to convert user and item information into vectors that the system can process.

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Unite.AI

FEBRUARY 7, 2024

Machine learning (ML) is a powerful technology that can solve complex problems and deliver customer value. However, ML models are challenging to develop and deploy. MLOps are practices that automate and simplify ML workflows and deployments. MLOps make ML models faster, safer, and more reliable in production.

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Unite.AI

APRIL 25, 2024

Recent innovations include the integration and deployment of Large Language Models (LLMs), which have revolutionized various industries by unlocking new possibilities. More recently, LLM-based intelligent agents have shown remarkable capabilities, achieving human-like performance on a broad range of tasks.

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Marktechpost

MARCH 1, 2025

Current memory systems for large language model (LLM) agents often struggle with rigidity and a lack of dynamic organization. Traditional approaches rely on fixed memory structurespredefined storage points and retrieval patterns that do not easily adapt to new or unexpected information.

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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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BAIR

MARCH 11, 2024

Here, you’ll find detailed profiles, research interests, and contact information for each of our graduates. Currently, I am working on Large Language Model (LLM) based autonomous agents. human player's racing trajectories) to inform better, more sample efficient control algorithms.

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Marktechpost

JANUARY 30, 2025

Contrastingly, agentic systems incorporate machine learning (ML) and artificial intelligence (AI) methodologies that allow them to adapt, learn from experience, and navigate uncertain environments. Embeddings like word2vec, GloVe , or contextual embeddings from large language models (e.g.,

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AWS Machine Learning Blog

JANUARY 28, 2025

Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Regular interval evaluation also allows organizations to stay informed about the latest advancements, making informed decisions about upgrading or switching models.

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Marktechpost

NOVEMBER 30, 2024

Among these features, “Product Cards” stand out for their ability to display detailed product information, including images, pricing, and AI-generated summaries of reviews and features. The tool is particularly useful for companies seeking to enhance productivity by leveraging AI to unify diverse information sources.

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AWS Machine Learning Blog

MARCH 17, 2025

Large language models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like text with remarkable accuracy. However, despite their impressive language capabilities, LLMs are inherently limited by the data they were trained on.

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AI Weekly

DECEMBER 19, 2024

In the News Perplexitys Erroneous AI Election Info On the heels of the 2024 US presidential election, AI search startup Perplexity launched a new platform that aims to keep track of election results and offer information about candidates, their policies and endorsements in the form of AI-generated summaries. Lets simplify it.

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Flipboard

DECEMBER 2, 2024

This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in the cloud. The scale down to zero feature presents new opportunities for how businesses can approach their cloud-based ML operations. However, it’s possible to forget to delete these endpoints when you’re done.

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Flipboard

MARCH 4, 2025

Integration with the AWS Well-Architected Tool pre-populates workload information and initial assessment responses. The WAFR Accelerator application retrieves the review status from the DynamoDB table to keep the user informed. Brijesh specializes in AI/ML solutions and has experience with serverless architectures.

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Unite.AI

MARCH 3, 2025

Statistical AI is incredible at identifying patterns and doing translation using information it learned from the data it was trained on. At Deutsche Bank we dealt with a lot of very complex code that made automated trading decisions based on various ML inputs, risk indicators, etc. The field of AI has (very roughly!)

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Flipboard

FEBRUARY 10, 2025

Organizations can build agentic applications using these reasoning models to execute complex tasks with advanced decision-making capabilities, enhancing efficiency and adaptability. For more information, refer to Deploy models for inference.

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Marktechpost

OCTOBER 31, 2024

In the vast world of AI tools, a key challenge remains: delivering accurate, real-time information. Large language models like OpenAI’s ChatGPT transformed how we interact with information, but they were limited by outdated training data, reducing their utility in dynamic, real-time situations.

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