Marktechpost

FEBRUARY 26, 2024

Recent solutions often focus on sophisticated ensemble methods or frameworks where multiple LLM agents collaborate. This work investigates a fascinating phenomenon: the potential to improve LLM performance simply by scaling up the number of agents used. These approaches certainly improve performance, but they add layers of complexity.

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LLM Large Language Models Prompt Engineer Prompt Engineering 125

Unite.AI

MARCH 15, 2024

Nevertheless, addressing the cost-effectiveness of ML models for business is something companies have to do now. For businesses beyond the realms of big tech, developing cost-efficient ML models is more than just a business process — it's a vital survival strategy. Challenging Nvidia, with its nearly $1.5

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TheSequence

MARCH 19, 2024

Created Using DALL-E 💡 ML Concept of the Day: A Summary Of Our Series About LLM Reasoning Today, we are concluding our series about reasoning in LLMs with a summary of the different topics covered. Here is our summary: Edge 253 : Provides an introduction to LLM reasoning and its relevance.

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LLM Explainability ML AI 105

Marktechpost

APRIL 15, 2024

It is no longer science fiction to imagine that many interactions on the internet will be between LLM-powered systems. Currently, humans verify LLM-generated outputs for correctness before implementation due to the complexity of code comprehension.

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LLM ML Large Language Models AI 139

Marktechpost

MARCH 11, 2024

This not only enhances throughput but also allows for the serving of larger models under fixed hardware constraints, a significant leap forward in LLM serving technology. This approach dramatically reduces the redundancy and latency typically associated with recovery processes in traditional LLM serving systems.

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LLM Machine Learning Large Language Models Chatbots 132

TheSequence

APRIL 30, 2024

Created Using DALL-E In this Issue: An overview of function calling in LLMs and its role in autonomous agnets. A review of UC Berkeley’s LLM Compiler to execute parallel functions in LLMs. An introduction to the Phidata framework for building autonomous agents.

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Marktechpost

FEBRUARY 28, 2024

In recent research, a team of researchers from Meta has presented TestGen-LLM, a unique tool that uses Large Language Models (LLMs) to improve pre-existing human-written test suites automatically. This verification procedure is crucial to solve issues with LLM hallucinations, where produced content may differ from the intended quality.

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Large Language Models LLM Automation Software Engineer 129

Marktechpost

FEBRUARY 14, 2024

Addressing this challenge, a groundbreaking framework developed at Microsoft Research, TAG-LLM, emerges. It is designed to harness LLMs’ general capabilities while tailoring their prowess to specialized domains. The ingenuity of TAG-LLM unfolds through a meticulously structured methodology comprising three stages.

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LLM Natural Language Processing Large Language Models AI 129

AWS Machine Learning Blog

APRIL 24, 2024

To increase training samples for better learning, we also used another LLM to generate feedback scores. We present the reinforcement learning process and the benchmarking results to demonstrate the LLM performance improvement. They can also provide a better answer to the question or comment on why the LLM response is not satisfactory.

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Marktechpost

MARCH 24, 2024

However, complexities are involved in developing and evaluating new reasoning strategies and agent architectures for LLM agents due to the intricacy of existing frameworks. A research team from Salesforce AI Research presents AgentLite , an open-source AI Agent library that simplifies the design and deployment of LLM agents.

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LLM AI Researcher AI Research Large Language Models 140

Marktechpost

MARCH 2, 2024

From each cluster, a representative ad is chosen for detailed LLM review. This step is pivotal, as it dramatically reduces the content volume that requires LLMs’ comprehensive analysis capabilities, thereby optimizing resource utilization. Also, don’t forget to follow us on Twitter and Google News.

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LLM Large Language Models ML AI 106

Marktechpost

APRIL 25, 2024

The method’s capacity to generalize the LLM to non-domain contexts is a great benefit. The team was also able to show that the accompanying model may be efficiently shrunk without compromising performance by utilizing a small, well-trained retriever in conjunction with the LLM. If you like our work, you will love our newsletter.

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LLM Machine Learning Large Language Models Artificial Intelligence 124

Marktechpost

FEBRUARY 29, 2024

The researchers from Google research have proposed USER-LLM , a framework integrating user embeddings with LLMs to adapt dynamically to user context. The USER-LLM framework involves two stages: embedding generation and LLM contextualization. Also, don’t forget to follow us on Twitter and Google News.

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Artificial Intelligence Artificial Intelligence LLM Large Language Models 127

Marktechpost

MARCH 21, 2024

By harmonizing dynamic planning, tool integration, and logical error detection, the Data Interpreter addresses the quintessential challenges in data science, offering a robust and versatile solution that stands out in the landscape of LLM-based tools. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

Data Science 140

Data Science LLM Large Language Models Machine Learning 140

Marktechpost

DECEMBER 24, 2023

Additionally, LLM hallucination is an infamous issue that causes LLMs to generate unreliable content. To tackle the shortcomings of existing models, researchers at Microsoft have released InsightPilot, a system that automates the process of data exploration using LLMs. If you like our work, you will love our newsletter.

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LLM Automation Insight Engine Data Analysis 133

Marktechpost

MARCH 28, 2024

Within this evolving landscape, a major hurdle has been the efficient management of LLM-based agents. A research team from Rutgers University has developed the AIOS (Agent-Integrated Operating System) , a pioneering LLM agent operating system designed to streamline the deployment and operation of LLM-based agents.

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Large Language Models LLM Artificial Intelligence Artificial Intelligence 141

Marktechpost

MARCH 1, 2024

In recent research, the concept of radioactivity in the context of Large Language Models (LLMs) has been discussed, with particular attention to the detectability of texts created by LLMs. Here, radioactivity refers to the detectable residues left in a model that has been refined using information produced by an additional LLM.

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LLM Large Language Models AI AI 112

Marktechpost

JANUARY 30, 2024

For instance, in functions like generating personalized content based on user data, LLMs might perform highly in a few cases but also risk causing incorrect or inappropriate content. This inconsistency can lead to significant issues, particularly when LLM outputs are used in sensitive or critical applications.

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LLM Large Language Models Artificial Intelligence Artificial Intelligence 124

John Snow Labs

OCTOBER 10, 2023

Join us for a talk on the journey of scaling ads ranking at Pinterest using innovative machine learning algorithms and innovation in ML platform. The post LLM and Foundational Models in Ads Ranking appeared first on John Snow Labs. Throughout the process, we encountered various challenges and gained valuable lessons.

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LLM Deep Learning NLP Machine Learning 98

Marktechpost

APRIL 4, 2024

Challenge 3: They lack the ability to effectively present a large-scale item corpus to LLMs in a natural language format. A key advantage of UniLLMRec lies in its utilization of the inherent zero-shot capabilities of LLMs, which eliminates the need for training or fine-tuning. recall, ranking, re-ranking) by chain of recommendation.

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LLM Large Language Models ChatGPT ML 131

AWS Machine Learning Blog

DECEMBER 5, 2023

New and powerful large language models (LLMs) are changing businesses rapidly, improving efficiency and effectiveness for a variety of enterprise use cases. Speed is of the essence, and adoption of LLM technologies can make or break a business’s competitive advantage. This optimization pass is delivered through an extension to PyTorch.

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LLM AI AI Generative AI 100

Marktechpost

FEBRUARY 27, 2024

A team of researchers at Google Research has introduced the LLM Comparator tool, which facilitates the side-by-side comparison of LLM outputs, enabling an in-depth analysis of their performance. The LLM Comparator integrates visual analytics, allowing users to delve into the specifics of model performance across different scenarios.

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Large Language Models LLM AI AI 108

Marktechpost

APRIL 8, 2024

Innovations in Arithmetic Coding, adjusted for better LLM compatibility, and exploring “token-free” language modeling through convolutional downsampling offer alternative paths for neural tokenization. The results show that models trained using “Equal-Info Windows” significantly outperform traditional methods.

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LLM Large Language Models AI AI 132

Unite.AI

MAY 8, 2024

We will explore how LLMs can be used to enhance various aspects of graph ML, review approaches to incorporate graph knowledge into LLMs, and discuss emerging applications and future directions for this exciting field.

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Neural Network Large Language Models LLM BERT 147

Marktechpost

MARCH 3, 2024

This finding underscores the gap between the current capabilities of LLM-based discriminators and the demands of more sophisticated planning methods. Join our 38k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup. At least 90% accuracy is required to realize significant improvements over re-ranking.

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LLM Large Language Models Algorithm ML 131

Marktechpost

FEBRUARY 5, 2024

In the rapidly evolving data analysis landscape, the quest for robust time series forecasting models has taken a novel turn with the introduction of TIME-LLM, a pioneering framework developed by a collaboration between esteemed institutions, including Monash University and Ant Group.

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LLM Machine Learning Data Analysis Natural Language Processing 137

Topbots

FEBRUARY 19, 2024

However, building a successful LLM application involves much more than just leveraging advanced technology. When embarking on the journey of building an LLM application, one of the first and most crucial decisions is choosing the foundation model. Create Targeted Evaluation Sets for Comparing LLM Performance in Your Specific Use Case.

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LLM Natural Language Processing Automation Data Ingestion 64

Marktechpost

MARCH 6, 2024

These models have become essential tools for various tasks, prompting a growing need for proprietary LLMs among individuals and organizations. However, the resource-intensive nature of LLM development remains a challenge for many. This methodology enables the fusion of pre-trained LLMs with diverse architectures into a cohesive model.

LLM 107

LLM Large Language Models Neural Network Natural Language Processing 107

Marktechpost

APRIL 6, 2024

Researchers from Microsoft Research, UT Austin, and Peking University introduced LLM-ABR, the first system that utilizes the generative capabilities of LLMs to autonomously design adaptive bitrate (ABR) algorithms tailored for diverse network characteristics. In this paper, network architecture design is limited to GPT-3.5

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Machine Learning Algorithm LLM Neural Network 116

Unite.AI

FEBRUARY 10, 2024

This English dominance also prevails in LLM development and has resulted in a digital language gap, potentially excluding most people from the benefits of LLMs. To solve this problem for LLMs, an LLM that can be trained in different languages and perform tasks in different languages is needed. Enter Multilingual LLMs!

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LLM Large Language Models Data Quality ML 317

Towards AI

APRIL 1, 2024

TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. A few days ago, Databricks open sourced DBRX, a massive general-purpose LLM that show incredible performance across different benchmarks. Join thousands of data leaders on the AI newsletter.

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LLM Machine Learning Large Language Models Generative AI 85

Marktechpost

MARCH 22, 2024

Yet, comparing these attacks proves challenging due to variations in evaluation criteria and the absence of readily available source code, exacerbating efforts to identify and counter LLM vulnerabilities. Human design involves manually crafting prompts to exploit model weaknesses, such as role-playing or scenario crafting.

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LLM Machine Learning Natural Language Processing Categorization 132

Marktechpost

SEPTEMBER 16, 2023

Recent studies show that handling an LLM request can be expensive, up to ten times higher than a traditional keyword search. So, there is a growing need to boost the throughput of LLM serving systems to minimize the per-request expenses. To further reduce memory utilization, the researchers have also deployed vLLM.

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LLM Machine Learning Large Language Models Algorithm 143

Marktechpost

MARCH 5, 2024

The findings reveal that increasing the LLM model size has a more pronounced effect on fine-tuning performance than expanding the pretraining data or scaling up the PET parameters. In conclusion, the comprehensive study conducted by the Google DeepMind and Google Research team sheds light on the nuanced dynamics of LLM fine-tuning.

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LLM Large Language Models ML AI 112

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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Machine Learning Large Language Models LLM BERT 294

TheSequence

FEBRUARY 27, 2024

Created Using DALL-E In this Issue: An overview of ReWOO as an LLM reasoning method. An introduction to LLMFlows, a framework for building LLM applications. Often overlooked is the impact that RAG-type techniques have on the reasoning abilities of LLMs. Typically, a RAG system needs to coordinate reasoning and action with LLMs.

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LLM Generative AI ML AI 59

Marktechpost

MARCH 8, 2024

Large language models (LLMs) trained on vast amounts of text data show remarkable abilities in diverse tasks via next-token prediction and fine-tuning. While traditional benchmarks become obsolete due to LLM advancements, distinguishing between deep understanding and shallow memorization poses a challenge. Check out the Paper.

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LLM Large Language Models OpenAI ML 104