8 years later: A world Go champion’s reflections on AlphaGo
World-famous Go champion Lee Sae Dol reflects on his match against our AI system AlphaGo eight years ago.
Unlock the potential of generative AI in industrial operations
In the evolving landscape of manufacturing, the transformative power of AI and machine learning (ML) is evident, driving a digital revolution that streamlines operations and boosts productivity. However, this progress introduces unique challenges for enterprises navigating data-driven solutions. Industrial facilities grapple with vast volumes of unstructured data, sourced from sensors, telemetry systems, and equipment dispersed …
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Enhance performance of generative language models with self-consistency prompting on Amazon Bedrock
Generative language models have proven remarkably skillful at solving logical and analytical natural language processing (NLP) tasks. Furthermore, the use of prompt engineering can notably enhance their performance. For example, chain-of-thought (CoT) is known to improve a model’s capacity for complex multi-step problems. To additionally boost accuracy on tasks that involve reasoning, a self-consistency prompting …
What’s cooking: How Hellmann’s is using Google Cloud AI to turn leftovers into meals
Hellmann’s introduces Meal Reveal, a new tool powered by Google Cloud AI that analyses fridge contents and suggests matching recipes.
Optimize price-performance of LLM inference on NVIDIA GPUs using the Amazon SageMaker integration with NVIDIA NIM Microservices
NVIDIA NIM microservices now integrate with Amazon SageMaker, allowing you to deploy industry-leading large language models (LLMs) and optimize model performance and cost. You can deploy state-of-the-art LLMs in minutes instead of days using technologies such as NVIDIA TensorRT, NVIDIA TensorRT-LLM, and NVIDIA Triton Inference Server on NVIDIA accelerated instances hosted by SageMaker. NIM, part …
Fine-tune Code Llama on Amazon SageMaker JumpStart
Today, we are excited to announce the capability to fine-tune Code Llama models by Meta using Amazon SageMaker JumpStart. The Code Llama family of large language models (LLMs) is a collection of pre-trained and fine-tuned code generation models ranging in scale from 7 billion to 70 billion parameters. Fine-tuned Code Llama models provide better accuracy …
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Transform one-on-one customer interactions: Build speech-capable order processing agents with AWS and generative AI
In today’s landscape of one-on-one customer interactions for placing orders, the prevailing practice continues to rely on human attendants, even in settings like drive-thru coffee shops and fast-food establishments. This traditional approach poses several challenges: it heavily depends on manual processes, struggles to efficiently scale with increasing customer demands, introduces the potential for human errors, …
Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker
This post is co-written with Chaoyang He, Al Nevarez and Salman Avestimehr from FedML. Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities. However, the sharing of …
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Enable data sharing through federated learning: A policy approach for chief digital officers
This is a guest blog post written by Nitin Kumar, a Lead Data Scientist at T and T Consulting Services, Inc. In this post, we discuss the value and potential impact of federated learning in the healthcare field. This approach can help heart stroke patients, doctors, and researchers with faster diagnosis, enriched decision-making, and more …
The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype
This is a guest post co-written with Scott Gutterman from the PGA TOUR. Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. Given the data sources, LLMs provided tools …