ODSC - Open Data Science

JUNE 27, 2023

Who Are AI Builders, AI Users, and Other Key Players? AI Builders AI builders are the data scientists, data engineers, and developers who design AI models. The goals and priorities of responsible AI builders are to design trustworthy, explainable, and human-centered AI.

Data Scientist 98

Data Scientist AI AI Responsible AI 98

ODSC - Open Data Science

DECEMBER 1, 2023

Work with Generative Artificial Intelligence (AI) Models in Azure Machine Learning The purpose of this course is to give you hands-on practice with Generative AI models. You’ll explore the use of generative artificial intelligence (AI) models for natural language processing (NLP) in Azure Machine Learning.

Data Science 52

Data Science Large Language Models DevOps Machine Learning 52

AWS Machine Learning Blog

MAY 9, 2024

Governance Establish governance that enables the organization to scale value delivery from AI/ML initiatives while managing risk, compliance, and security. Additionally, pay special attention to the changing nature of the risk and cost that is associated with the development as well as the scaling of AI.

ML 105

ML Generative AI AI AI 105

ODSC - Open Data Science

JANUARY 10, 2024

Deploying Trustworthy Generative AI Krishnaram Kenthapadi | Chief AI Officer & Chief Scientist | Fiddler AI Generative AI models have engendered several ethical and social considerations that need to be addressed.

Large Language Models 52

Large Language Models LLM Deep Learning ML 52

ODSC - Open Data Science

FEBRUARY 6, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

Large Language Models 52

Large Language Models LLM Big Data NLP 52

ODSC - Open Data Science

AUGUST 3, 2023

ODSC Keynote — Infuse Generative AI in your apps using Azure OpenAI Service Eve Psalti | Principal Group Program Manager | Microsoft Join this session to learn how Azure OpenAI Service can help your business integrate large language models to help create innovative applications.

Large Language Models 52

Large Language Models Data Science Data Scientist Prompt Engineer 52

ODSC - Open Data Science

APRIL 21, 2023

Well, during the hackathon you’ll have access to cutting-edge tools and platforms, including Weaviate and OpenAI API & ChatGPT plugins, to work on projects such as generative search and prompt engineering. Present your innovative solution to both a live audience and a panel of judges.

Generative AI 52

Generative AI Large Language Models Prompt Engineer Prompt Engineering 52

ODSC - Open Data Science

FEBRUARY 8, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI. Register soon!

Large Language Models 52

Large Language Models Big Data Deep Learning Data Science 52

ODSC - Open Data Science

SEPTEMBER 26, 2023

At ODSC West 2023 , you’ll find an unprecedented breadth and depth of content, with hands-on training sessions on the latest advances in Generative AI, LLMs, Prompt Engineering, Machine Learning, Deep Learning, MLOps, Data Engineering, and much, much more.

Data Science 52

Data Science Data Scientist Continuous Learning Deep Learning 52

Pickl AI

AUGUST 2, 2023

Its responses are based on patterns observed in the training data, which can sometimes lead to biased or untruthful outputs. Efforts are continually being made to improve AI models’ safety, robustness, and ethical usage. Overreliance on AI models may have long-term consequences for the human brain.

ChatGPT 52

ChatGPT Neural Network Prompt Engineer Prompt Engineering 52

Snorkel AI

JUNE 7, 2023

Mann touched on many details of the project—from the mix of the data Bloomberg used to their training sequence to the impact of the numerical precision of gradient estimates to the challenge in evaluating the performance of generative AI models. The output of generative models defies simple comparisons to test sets.

Data Scientist 52

Data Scientist Large Language Models Machine Learning AI 52

Snorkel AI

JUNE 7, 2023

Mann touched on many details of the project—from the mix of the data Bloomberg used to their training sequence to the impact of the numerical precision of gradient estimates to the challenge in evaluating the performance of generative AI models. The output of generative models defies simple comparisons to test sets.

Data Scientist 52

Data Scientist Large Language Models Machine Learning AI 52

AWS Machine Learning Blog

APRIL 22, 2024

Set the right data foundations As a CEO aiming to use generative AI to achieve sustainability goals, remember that data is your differentiator. Figure 5 offers an overview on generative AI modalities and optimization strategies, including prompt engineering , Retrieval Augmented Generation , and fine-tuning or continued pre-training.

Generative AI 111

Generative AI ESG AI AI 111

AWS Machine Learning Blog

MAY 13, 2024

Amazon Bedrock also comes with a broad set of capabilities required to build generative AI applications with security, privacy, and responsible AI. You can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.

Generative AI 105

Generative AI Prompt Engineer Prompt Engineering LLM 105

AWS Machine Learning Blog

JANUARY 26, 2024

As part of quality assurance tests, introduce synthetic security threats (such as attempting to poison training data, or attempting to extract sensitive data through malicious prompt engineering) to test out your defenses and security posture on a regular basis.

Generative AI 122

Generative AI LLM ML AI 122

AWS Machine Learning Blog

FEBRUARY 1, 2024

Make sure to validate prompt input data and prompt input size for allocated character limits that are defined by your model. If you’re performing prompt engineering, you should persist your prompts to a reliable data store.

Generative AI 111

Generative AI Prompt Engineer Prompt Engineering AI 111

AWS Machine Learning Blog

NOVEMBER 22, 2023

Third, a number of sessions will be of interest to ML practitioners who build, deploy, and operationalize both traditional and generative AI models. Then, as we started doing last re:Invent, we’ll be offering several sessions on how to build AI responsibly. This year, learn about LLMOps, not just MLOps!

ML 109

ML Generative AI Prompt Engineer Prompt Engineering 109

AWS Machine Learning Blog

MARCH 15, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Generative AI 119

Generative AI Prompt Engineer Prompt Engineering LLM 119

Snorkel AI

MARCH 2, 2023

I am Ali Arsanjani, and I lead partner engineering for Google Cloud, specializing in the area of AI-ML, and I’m very happy to be here today with everyone. Similar to when you train a model, it has a certain degree of, let’s say, an F1 score or accuracy or what. Number two is the model transparency and reproducibility.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

I am Ali Arsanjani, and I lead partner engineering for Google Cloud, specializing in the area of AI-ML, and I’m very happy to be here today with everyone. Similar to when you train a model, it has a certain degree of, let’s say, an F1 score or accuracy or what. Number two is the model transparency and reproducibility.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

The MLOps Blog

JUNE 27, 2023

W&B (Weights & Biases) W&B is a machine learning platform for your data science teams to track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results, spot regressions, and share findings with colleagues.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134