ODSC - Open Data Science

JANUARY 10, 2024

Takeaways include: The dangers of using post-hoc explainability methods as tools for decision-making, and where traditional ML falls short. In this talk, You’ll explore how these foundation models are trained. Get practical experience and return to work ready to start implementing these concepts in your daily work.

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Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

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Machine Learning BERT Deep Learning ML Engineer 94

TheSequence

JANUARY 19, 2024

Generative AI and Large Language Models (LLMs) are new to most companies. If you are an engineering leader building Gen AI applications, it can be hard to know what skills and types of people are needed. At the same time, the capabilities of AI models have grown. Much less sophistication is needed to use them.

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Prompt Engineer Prompt Engineering Generative AI Large Language Models 59

Marktechpost

OCTOBER 11, 2023

The team started with a collection of 15 ML engineering projects spanning various fields, with experiments that are quick and cheap to run. percent over baseline prediction on well-established tasks like developing a better model over the ogbn-arxiv dataset (Hu et al., It achieves an average improvement of 48.18

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Heartbeat

OCTOBER 5, 2023

Unsurprisingly, Machine Learning (ML) has seen remarkable progress, revolutionizing industries and how we interact with technology. The emergence of Large Language Models (LLMs) like OpenAI's GPT , Meta's Llama , and Google's BERT has ushered in a new era in this field. Their mission?

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Large Language Models DevOps Prompt Engineer Prompt Engineering 52

deepsense.ai

APRIL 18, 2023

experts will share insights on various areas of machine learning latest developments: April 20, 2023: workshop “Large language models in limited hardware environments” conducted by Adam Maciaszek, Senior Data Scientist, and Szymon Janowski, ML Engineer April 21, 2023: presentation “What do we learn by fooling GPT?”

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Machine Learning Data Scientist Large Language Models ML Engineer 52

TensorFlow

MAY 11, 2023

Posted by Thad Starner (Professor, Georgia Tech and Staff Research Scientist, Google), Sam Sepah (ML Research Program Manager), Manfred Georg (Software Engineer, Google), Mark Sherwood (Senior Product Manager, Google), Glenn Cameron (Product Marketing Manager, Google) Over 70 million deaf people around the world use sign language to communicate.

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Software Engineer Large Language Models ML Engineer ML 98

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. The input to the training pipeline is the features dataset.

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ML Machine Learning ETL Data Scientist 98

Towards AI

SEPTEMBER 22, 2023

There were significant distinctions between academic researchers, ML practitioners, and their clients. However, emerging large language models have significantly changed the world. Some people foresaw the emergence of prompt engineer as a new title. Is this the future of the ML engineer?

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Prompt Engineer Prompt Engineering LLM ML 57

Snorkel AI

JUNE 9, 2023

Snorkel Co-Founder and CEO Alex Ratner kicked off the day’s events by giving attendees a peek into Snorkel’s new Foundation Model Data Platform, which includes solutions to develop and adapt large language models and foundation models. This approach, Zhang said, yields several advantages.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Snorkel Co-Founder and CEO Alex Ratner kicked off the day’s events by giving attendees a peek into Snorkel’s new Foundation Model Data Platform, which includes solutions to develop and adapt large language models and foundation models. This approach, Zhang said, yields several advantages.

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Large Language Models Data Scientist Machine Learning Computer Vision 52

AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. These five risks are insecure output handling, supply chain vulnerabilities, sensitive information disclosure, excessive agency, and overreliance.

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AWS Machine Learning Blog

JUNE 23, 2023

For data scientists, moving machine learning (ML) models from proof of concept to production often presents a significant challenge. One of the main challenges can be deploying a well-performing, locally trained model to the cloud for inference and use in other applications.

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Large Language Models ML Python Machine Learning 87

Snorkel AI

MAY 1, 2024

phData Senior ML Engineer Ryan Gooch recently evaluated options to accelerate ML model deployment with Snorkel Flow and AWS SageMaker. If a new modeling approach or new category of service needs is proposed, everything goes back to the drawing board.

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AI Developer AI Development Machine Learning AI 52

AWS Machine Learning Blog

AUGUST 4, 2023

The following is an example of how to operationalize a SageMaker model using Salesforce Flow. SageMaker integration SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.

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Data Scientist ML ETL AI 73

Snorkel AI

MAY 4, 2023

In the era of large language models (LLMs), your data is the difference maker. Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation.

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Computer Vision Large Language Models AI AI 52

Snorkel AI

MAY 4, 2023

In the era of large language models (LLMs), your data is the difference maker. Large Language Models (LLMs) such as GPT-4 and LLaMA have revolutionized natural language processing and understanding, enabling a wide range of applications, from conversational AI to advanced text generation.

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Computer Vision Large Language Models AI AI 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

It also integrates with Machine Learning and Operation (MLOps) workflows in Amazon SageMaker to automate and scale the ML lifecycle. About the authors Ram Vegiraju is a ML Architect with the SageMaker Service team. He focuses on helping customers build and optimize their AI/ML solutions on Amazon SageMaker. What is FMEval?

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Large Language Models LLM Algorithm Responsible AI 87

AWS Machine Learning Blog

DECEMBER 13, 2023

Machine learning (ML) models do not operate in isolation. To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. The SageMaker Model Registry centralizes model tracking, simplifying model deployment.

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ML Automation Metadata Software Development 100

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. However, bringing such solutions and models to the business-as-usual operations is not an easy task. Our approach applies to both open-source and proprietary models equally.

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Generative AI Prompt Engineer Prompt Engineering AI 102

AWS Machine Learning Blog

AUGUST 16, 2023

Thomson Reuters (TR), a global content and technology-driven company, has been using artificial intelligence (AI) and machine learning (ML) in its professional information products for decades. Thomson Reuters Labs, the company’s dedicated innovation team, has been integral to its pioneering work in AI and natural language processing (NLP).

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AWS Machine Learning Blog

JUNE 8, 2023

However, businesses can meet this challenge while providing personalized and efficient customer service with the advancements in generative artificial intelligence (generative AI) powered by large language models (LLMs). This enables you to begin machine learning (ML) quickly. Choose Delete.

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Generative AI LLM Large Language Models Machine Learning 73

Chatbots Life

MAY 16, 2023

10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland. Deeper Insights has six years of experience in building AI solutions for large enterprise and scale-up clients, a suite of AI models, and data visualization dashboards that enable them to quickly analyze and share insights.

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AWS Machine Learning Blog

AUGUST 1, 2023

Artificial intelligence (AI) and machine learning (ML) models have shown great promise in addressing these challenges. Models can be trained to analyze and interpret large volumes of text data, effectively condensing information into concise summaries. No ML engineering experience required.

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ML Large Language Models NLP Natural Language Processing 74

Flipboard

JULY 17, 2023

The practical implementation of a Large Language Model (LLM) for a bespoke application is currently difficult for the majority of individuals. Stochastic has a team of bright ML engineers, postdocs, and Harvard grad students focusing on optimizing and speeding up AI for LLMs.

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Large Language Models LLM ML Engineer ML 65

AWS Machine Learning Blog

APRIL 29, 2024

In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows. Metaflow’s coherent APIs simplify the process of building real-world ML/AI systems in teams.

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ML Python Data Scientist Deep Learning 98

Viso.ai

FEBRUARY 11, 2024

To learn more about computer vision and more AI tools and frameworks from Meta, check out our other articles: The complete guide to Meta’s Segment Anything Model (SAM) Understanding Semantic vs Instance Segmentation The most popular object detection algorithms and AI software every ML engineer should know LLAMA2: an open-source large language (..)

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Computer Vision Robotics Deep Learning Large Language Models 52

BAIR

MARCH 11, 2024

Currently, I am working on Large Language Model (LLM) based autonomous agents. More recently, I am excited about emerging security and privacy risks on large language models. I work on improving protein property classification and protein design, as well as understanding what different protein models learn.

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Robotics Natural Language Processing Machine Learning Computer Vision 344

AWS Machine Learning Blog

MAY 15, 2024

Next, we present the solution architecture and process flows for machine learning (ML) model building, deployment, and inferencing. Acting as a model hub, JumpStart provided a large selection of foundation models and the team quickly ran their benchmarks on candidate models. We end with lessons learned.

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The MLOps Blog

NOVEMBER 14, 2023

While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The large language model GPT-4 that OpenAI released in the spring of 2023 is rumored to have nearly 2 trillion parameters.

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Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

AWS Machine Learning Blog

FEBRUARY 28, 2024

The solution in this post aims to bring enterprise analytics operations to the next level by shortening the path to your data using natural language. With the emergence of large language models (LLMs), NLP-based SQL generation has undergone a significant transformation.

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Metadata LLM Generative AI NLP 111

AWS Machine Learning Blog

MARCH 13, 2024

By orchestrating toxicity classification with large language models (LLMs) using generative AI, we offer a solution that balances simplicity, latency, cost, and flexibility to satisfy various requirements. Latency and cost are also critical factors that must be taken into account.

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LLM Natural Language Processing Prompt Engineer Prompt Engineering 107

AWS Machine Learning Blog

NOVEMBER 30, 2023

Code Editor is based on Code-OSS , Visual Studio Code Open Source, and provides access to the familiar environment and tools of the popular IDE that machine learning (ML) developers know and love, fully integrated with the broader SageMaker Studio feature set. Choose Open CodeEditor to launch the IDE.

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Machine Learning ML LLM Software Engineer 101

AWS Machine Learning Blog

MARCH 14, 2024

Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. Grace Lang is an Associate Data & ML engineer with AWS Professional Services. This is a guest post co-written with Scott Gutterman from the PGA TOUR.

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AWS Machine Learning Blog

MAY 13, 2024

In part 1 of this blog series, we discussed how a large language model (LLM) available on Amazon SageMaker JumpStart can be fine-tuned for the task of radiology report impression generation. We also explore the utility of the RAG prompt engineering technique as it applies to the task of summarization.

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Allen AI

NOVEMBER 8, 2023

Patrick Beukema is the Lead ML Engineer for Skylight Patrick Beukema is the Lead ML Engineer for Skylight. Our ( Skylight ) team’s work and that of our sister teams ( Wildlands , Climate Modeling , and EarthRanger ) are AI2’s effort to create a more sustainable future and a healthier planet.

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Computer Vision ML Engineer ML Neural Network 52

Snorkel AI

OCTOBER 12, 2023

Closing Keynote: LLMOps: Making LLM Applications Production-Grade Large language models are fluent text generators, but they struggle at generating factual, correct content. In this presentation, center NLP Engineer James Dunham shares takeaways from the half-dozen project teams who used Snorkel in the past year.

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