AWS Machine Learning Blog

FEBRUARY 21, 2025

Fine-tuning a pre-trained large language model (LLM) allows users to customize the model to perform better on domain-specific tasks or align more closely with human preferences. You can use supervised fine-tuning (SFT) and instruction tuning to train the LLM to perform better on specific tasks using human-annotated datasets and instructions.

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AI News

OCTOBER 7, 2024

Perhaps more strikingly, almost a quarter (22%) of respondents reported using GenAI or LLM tools such as ChatGPT and Claude for at least half of their idea submissions, with 8% employing these technologies for every single submission. Recently, Wazoku launched its own conversational AI to aid innovation.

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Marktechpost

MARCH 23, 2025

Traditional approaches to developing conversational LLM applications often fail in real-world use cases. Flowchart-based processing , which sacrifices the real magic of LLM-powered interactions: dynamic, free-flowing, human-like interactions. However, their reliability as autonomous customer-facing agents remains a challenge.

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Flipboard

JANUARY 22, 2025

For general travel inquiries, users receive instant responses powered by an LLM. Make sure the role includes the permissions for using Flows, as explained in Prerequisites for Amazon Bedrock Flows , and the permissions for using Agents, as explained in Prerequisites for creating Amazon Bedrock Agents.

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AWS Machine Learning Blog

DECEMBER 5, 2024

For use cases where accuracy is critical, customers need the use of mathematically sound techniques and explainable reasoning to help generate accurate FM responses. Encoding your domain knowledge into structured policies helps your conversational AI applications provide reliable and trustworthy information to your users.

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Chatbots Life

AUGUST 23, 2024

Large Language Models have emerged as the central component of modern chatbots and conversational AI in the fast-paced world of technology. Just imagine conversing with a machine that is as intelligent as a human. Conversational AI chatbots have been completely transformed by the advances made by LLMs in language production.

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AWS Machine Learning Blog

FEBRUARY 20, 2025

In this post, we describe the development of the customer support process in PAAS, incorporating generative AI, the data, the architecture, and the evaluation of the results. Conversational AI assistants are rapidly transforming customer and employee support. Verisk developed an evaluation tool to enhance response quality.

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AWS Machine Learning Blog

MARCH 19, 2025

They use a highly optimized inference stack built with NVIDIA TensorRT-LLM and NVIDIA Triton Inference Server to serve both their search application and pplx-api, their public API service that gives developers access to their proprietary models. ServiceNows innovative AI solutions showcase their vision for enterprise-specific AI optimization.

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Unite.AI

JULY 22, 2024

His latest venture, OpenFi , equips large companies with conversational AI on WhatsApp to onboard and nurture customer relationships. Can you explain why you believe the term “chatbot” is inadequate for describing modern conversational AI tools like OpenFi? They’re just not even in the same category.

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Topbots

OCTOBER 10, 2023

Source: rawpixel.com Conversational AI is an application of LLMs that has triggered a lot of buzz and attention due to its scalability across many industries and use cases. While conversational systems have existed for decades, LLMs have brought the quality push that was needed for their large-scale adoption.

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Marktechpost

JANUARY 30, 2025

To mitigate these limitations, the LLM-as-a-Judge paradigm has emerged, leveraging LLMs themselves to act as evaluators. To overcome these issues, Meta AI has introduced EvalPlanner, a novel approach designed to improve the reasoning and decision-making capabilities of LLM-based judges through an optimized planning-execution strategy.

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Marktechpost

MARCH 10, 2025

A researcher from New York University presents soft inductive biases as a key unifying principle in explaining these phenomena: rather than restricting hypothesis space, this approach embraces flexibility while maintaining a preference for simpler solutions consistent with data.

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AWS Machine Learning Blog

OCTOBER 31, 2024

The solution integrates large language models (LLMs) with your organization’s data and provides an intelligent chat assistant that understands conversation context and provides relevant, interactive responses directly within the Google Chat interface. In the following sections, we explain how to deploy this architecture.

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Marktechpost

MAY 28, 2024

Retrieval-Augmented Generation (RAG) Retrieval-augmented generation (RAG) is an architectural strategy that enhances the effectiveness of Large Language Model (LLM) applications by utilizing custom data. Conventional RAG refers to external authoritative knowledge bases before response generation to improve the output of LLMs.

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Heartbeat

FEBRUARY 8, 2024

This evolution paved the way for the development of conversational AI. The recent rise of Large Language Models (LLMs) has been a game changer for the ChatBot industry. These models are trained on extensive data and have been the driving force behind conversational tools like BARD and ChatGPT. Run the following command:

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Towards AI

MARCH 6, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Ever since we launched our From Beginner to Advanced LLM Developer course, many of you have asked for a solid Python foundation to get started. Well, its here! Join the Course and start coding today!

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Unite.AI

APRIL 8, 2025

Can you explain how your approach to retrieval differs from other AI-powered search and knowledge management systems? The art and science of RAG is about maximizing signal (truth) and minimizing noise (irrelevant context that often confuses the LLM). Pryon focuses on Retrieval-Augmented Generation (RAG).

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AWS Machine Learning Blog

DECEMBER 6, 2023

Conversational AI has come a long way in recent years thanks to the rapid developments in generative AI, especially the performance improvements of large language models (LLMs) introduced by training techniques such as instruction fine-tuning and reinforcement learning from human feedback.

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Marktechpost

DECEMBER 19, 2024

Large Language Models (LLMs) play a vital role in many AI applications, ranging from text summarization to conversational AI. Many such tools also struggle with explainability, leaving users uncertain about how to address identified issues. Its design emphasizes reliability, generalizability, and clarity.

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AWS Machine Learning Blog

JUNE 25, 2024

However, the implementation of LLMs without proper caution can lead to the dissemination of misinformation , manipulation of individuals, and the generation of undesirable outputs such as harmful slurs or biased content. Introduction to guardrails for LLMs The following figure shows an example of a dialogue between a user and an LLM.

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IBM Journey to AI blog

JULY 17, 2023

Transforming the contact center with AI With a suite of AI solutions powered by IBM Consulting™ , your enterprise can harness the power of generative AI for customer care. is a studio to train, validate, tune and deploy machine learning (ML) and foundation models for Generative AI. Watsonx.ai

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John Snow Labs

APRIL 3, 2025

Introducing Healthcare NLP & LLM The Healthcare NLP Library is a powerful component of John Snow Labs Healthcare NLP platform , designed to streamline natural language processing (NLP) tasks in the healthcare domain.

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Flipboard

JUNE 13, 2023

Redfin Photo) “We’ve already found a number of places where AI tools are making our engineers more efficient. .” Bridget Frey , CTO at Redfin , a Seattle-based real estate company Bridget Frey, CTO at Redfin. ” Jonathan Wiggs.

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Unite.AI

APRIL 12, 2024

By training LLMs to seamlessly resolve references across three key domains – conversational, on-screen, and background – ReALM aims to create a truly intelligent digital companion that feels less like a robotic voice assistant and more like an extension of your own thought processes.

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Chatbots Life

MARCH 17, 2023

As pioneers in adopting ChatGPT technology in Malaysia, XIMNET dives in to take a look how far back does Conversational AI go? Photo by Milad Fakurian on Unsplash Conversational AI has been around for some time, and one of the noteworthy early breakthroughs was when ELIZA , the first chatbot, was constructed in 1966.

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ODSC - Open Data Science

FEBRUARY 14, 2023

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. and is trained in a manner similar to OpenAI’s earlier InstructGPT, but on conversations.

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Towards AI

MARCH 28, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, I’m super excited to announce that we are finally releasing our book, ‘Building AI for Production; Enhancing LLM Abilities and Reliability with Fine-Tuning and RAG,’ where we gathered all our learnings.

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Topbots

MARCH 21, 2025

Chain-of-Thought Prompting: Teaching LLMs to Think Step by Step One of the earliest and most enduring techniques to improve reasoning in LLMs is surprisingly simple: ask the model to explain itself. Offloading these subtasks lets the LLM focus on higher-order logic, dramatically improving accuracy and reliability.

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AWS Machine Learning Blog

DECEMBER 6, 2023

Despite the seemingly unstoppable adoption of LLMs across industries, they are one component of a broader technology ecosystem that is powering the new AI wave. Many conversational AI use cases require LLMs like Llama 2, Flan T5, and Bloom to respond to user queries. pip install -qU sagemaker pinecone-client==2.2.1

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AWS Machine Learning Blog

JULY 31, 2024

The source field should be set to INPUT when the content to evaluated is from a user, typically the LLM prompt. The source should be set to OUTPUT when the model output guardrails should be enforced, typically an LLM response. In the following example, we ask the LLM to generate three names and tell us what is a bank.

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AWS Machine Learning Blog

DECEMBER 12, 2023

This post shows you how you can create a web UI, which we call Chat Studio, to start a conversation and interact with foundation models available in Amazon SageMaker JumpStart such as Llama 2, Stable Diffusion, and other models available on Amazon SageMaker. Navigate to the GitHub repository and download the react-llm-chat-studio code.

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AWS Machine Learning Blog

MAY 9, 2024

In this post, we describe the development of the customer support process in FAST incorporating generative AI, the data, the architecture, and the evaluation of the results. Conversational AI assistants are rapidly transforming customer and employee support.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

For example, a chatbot could suggest products that match a shopper’s preferences and past purchases, explain details in language adapted to the user’s level of expertise, or provide account support by accessing the customer’s specific records. It augments prompts with these relevant chunks to generate an answer using the LLM.

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TheSequence

SEPTEMBER 17, 2023

Technical Report Microsoft Research published a paper explaining the groundbreaking techniques behind their phi-1.5 Language Agents Architectures Researchers from Princeton University published a paper proposing Cognitive Architectures for Language Agents(CoALA), a systhematic framework for creating LLM-based agents.

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Marktechpost

MARCH 12, 2025

Many existing systems also lack the capability to explain their decision-making process, which makes it hard to understand how a specific emotion is detected. The method begins with a cold start phase, where the model is pre-trained using a combined dataset from Explainable Multimodal Emotion Reasoning (EMER) and a manually annotated dataset.

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ODSC - Open Data Science

FEBRUARY 5, 2025

A key focus was on the paradigm shift from traditional conversational AI to agentic applications capable of orchestrating complex tasks autonomously. The session included a hands-on demonstration of building an AI agent from scratch, using blockchain for orchestration.

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Topbots

JULY 2, 2024

The demo showcased Astra’s impressive capabilities: it could explain the functionality of a piece of code simply by observing someone’s screen through a smartphone camera, recognize a neighborhood by viewing the scenery from a window, and even “remember” the location of an object shown earlier in the video stream.

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