IBM Journey to AI blog

JANUARY 9, 2024

Scaling AI for better business outcomes and impact AI has transitioned from peripheral to core business driver, demanding optimized infrastructure for high-performance AI workloads.

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Data Ingestion Automation Data Platform AI Modeling 212

Unite.AI

MARCH 14, 2024

In collaboration with partners CoreWeave and NVIDIA, Inflection AI is building the largest AI cluster in the world, comprising an unprecedented 22,000 NVIDIA H100 Tensor Core GPUs. The post Inflection-2.5: The Powerhouse LLM Rivaling GPT-4 and Gemini appeared first on Unite.AI.

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LLM Large Language Models Data Ingestion AI 274

Marktechpost

JUNE 16, 2024

The feature eliminates the need for data teams to manually manage maintenance operations, such as scheduling jobs, diagnosing failures, and managing infrastructure. Anker: The data engineering team at Anker reported a 2x improvement in query performance and 50% savings in storage costs after enabling Predictive Optimization.

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Data Ingestion Python Automation Data Scientist 116

Marktechpost

SEPTEMBER 26, 2023

AI Copilots are often updated regularly to incorporate new programming languages, frameworks, and best practices, ensuring they remain valuable to developers as technology evolves. It is a user’s own AI copilot, trained specifically for their product and their requirement. Now, a team of researchers design OpenCopilot.

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Data Ingestion Natural Language Processing Artificial Intelligence Artificial Intelligence 128

Towards AI

JULY 24, 2024

Each stage of the pipeline can perform structured extraction using any AI model or transform ingested data. The pipelines start working immediately upon data ingestion into Indexify, making them ideal for interactive applications and low-latency use cases. pip install dspy-ai==2.0.8

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Data Ingestion OpenAI Natural Language Processing Chatbots 105

Towards AI

JULY 24, 2024

Each stage of the pipeline can perform structured extraction using any AI model or transform ingested data. The pipelines start working immediately upon data ingestion into Indexify, making them ideal for interactive applications and low-latency use cases. pip install dspy-ai==2.0.8

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Data Ingestion OpenAI Natural Language Processing Chatbots 98

AWS Machine Learning Blog

OCTOBER 2, 2024

This allows enterprises to track key performance indicators (KPIs) for their generative AI models, such as I/O volumes, latency, and error rates. Opensearch Dashboards provides powerful search and analytical capabilities, allowing teams to dive deeper into generative AI model behavior, user interactions, and system-wide metrics.

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Generative AI Data Ingestion AI AI 113

ODSC - Open Data Science

MARCH 27, 2023

ML Governance: A Lean Approach Ryan Dawson | Principal Data Engineer | Thoughtworks Meissane Chami | Senior ML Engineer | Thoughtworks During this session, you’ll discuss the day-to-day realities of ML Governance.

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Machine Learning Data Science Deep Learning Data Ingestion 98

Marktechpost

DECEMBER 3, 2024

In a world where AI models depend on the quality of the data they receive, having a tool that minimizes data loss is crucial. Parsing documents manually is not only inefficient but also prone to errors and data omissions. Check out the GitHub Page.

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LLM AI Tools Large Language Models Data Ingestion 102

Unite.AI

JUNE 4, 2024

Google Cloud’s AI and machine learning services, including the new generative AI models, empower businesses to harness advanced analytics, automate complex processes, and enhance customer experiences. This step unified their data landscape, making it easier and more efficient for them to access and analyze their data.

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Data Ingestion Data Platform Machine Learning Generative AI 130

AWS Machine Learning Blog

NOVEMBER 15, 2023

The teams built a new data ingestion mechanism, allowing the CTR files to be jointly delivered with the audio file to an S3 bucket. Principal and AWS collaborated on a new AWS Lambda function that was added to the Step Functions workflow.

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Data Ingestion Metadata NLP Data Scientist 117

ODSC - Open Data Science

OCTOBER 7, 2024

It isn’t just about writing code or creating algorithms — it requires robust pipelines that handle data, model training, deployment, and maintenance. One of the key challenges in AI development is building scalable pipelines that can handle the complexities of modern data systems and models.

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Software Engineer Data Ingestion Machine Learning Data Scientist 52

Towards AI

MARCH 28, 2024

Pre-ordering your copy now and take the first step towards your AI journey! Learn AI Together Community section! It offers free API service to access AI models like Gemma, GPT-4, GPT-4–1106-PREVIEW, GPT-3.5-turbo, Building an Enterprise Data Lake with Snowflake Data Cloud & Azure using the SDLS Framework.

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Large Language Models Prompt Engineering Prompt Engineer LLM 97

Snorkel AI

DECEMBER 2, 2024

At its core, Snorkel Flow empowers data scientists and domain experts to encode their knowledge into labeling functions, which are then used to generate high-quality training datasets. This approach not only enhances the efficiency of data preparation but also improves the accuracy and relevance of AI models.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Rather than requiring your data science and IT teams to build and maintain AI models, you can use pre-trained AI services that can automate tasks for you. IaC architectures – When running an IDP solution, the solution includes multiple AI services to perform the end-to-end workflow chronologically.

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IDP ML Machine Learning Automation 109

ODSC - Open Data Science

FEBRUARY 25, 2025

Generative AI TrackBuild the Future with GenAI Generative AI has captured the worlds attention with tools like ChatGPT, DALL-E, and Stable Diffusion revolutionizing how we create content and automate tasks. This track will cover the latest best practices for managing AI models from development to deployment.

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Data Scientist Machine Learning Large Language Models ML Engineer 52

DataRobot Blog

SEPTEMBER 13, 2022

Automation also makes AI-driven forecast models possible at scale, which further minimizes your costs by accurately forecasting demand. At the operational level, organizations have deployed several AI models serving different business needs into production. Operationalization.

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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. Sign me up!

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Large Language Models Deep Learning Data Science LLM 52

Pickl AI

AUGUST 28, 2024

Unified ML Workflow: Vertex AI provides a simplified ML workflow, encompassing data ingestion, analysis, transformation, model training, evaluation, and deployment. This unified approach enables seamless collaboration among data scientists, data engineers, and ML engineers.

Machine Learning 52

Machine Learning ML Engineer ML Automation 52

ODSC - Open Data Science

FEBRUARY 22, 2024

Stripling, PhD | Lead AI & ML Content Developer | Google Cloud In a no-code or low-code world you don’t have to have mastered coding to deploy machine learning models. In particular, you’ll explore Google’s Vertex AI for both no-code and low-code ML model training, and Google’s Colab, a free Jupyter Notebook service.

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Machine Learning Data Science Python ML 52

The MLOps Blog

FEBRUARY 5, 2023

It provides a web-based interface for building data pipelines and can be used to process both batch and streaming data. Azure Stream Analytics : A cloud-based service that can be used to process streaming data in real-time. It provides a variety of features, such as data ingestion, data transformation, and real-time processing.

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Machine Learning Big Data Auto-complete Data Ingestion 72

The MLOps Blog

JUNE 27, 2023

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

SEPTEMBER 11, 2024

For example, over 90% of the top 100 Hugging Face models (now over 100,000 AI models) now run on AWS using Optimum Neuron, enabling the Hugging Face transformer natively supported for Neuron. This usability, tooling, and integrations of the Neuron SDK has made Amazon PBAs extremely popular with users.

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ODSC - Open Data Science

JULY 11, 2023

A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. Data lakes are designed to handle large volumes of data and can store data in its raw format, without enforcing any structure. ChatGPT: Optimizing language models for dialogue, on [link] 3.

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The MLOps Blog

AUGUST 11, 2023

1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., Scikit-learn, Feature Tools) 4 Model Training (e.g., TensorFlow, PyTorch) 5 Model Evaluation (e.g., Scikit-learn, MLflow) 6 Model Deployment (e.g., pandas, NumPy) 3 Feature Engineering and Selection (e.g.,

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ML Machine Learning Data Ingestion Deep Learning 52

AWS Machine Learning Blog

OCTOBER 23, 2024

This intuitive platform enables the rapid development of AI-powered solutions such as conversational interfaces, document summarization tools, and content generation apps through a drag-and-drop interface. This integrated architecture not only supports advanced AI functionalities but also makes it easy to use.

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Generative AI IDP LLM Automation 73

Unite.AI

JANUARY 13, 2025

Real-Time and Offline Processing : Our dual-track system supports low-latency real-time writes and high-throughput offline imports, ensuring data freshness. Embedded AI Models : By integrating multimodal embedding and ranking models, weve lowered the barrier to implementing complex search applications.

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Data Scarcity ETL Data Ingestion Software Engineer 144

AWS Machine Learning Blog

SEPTEMBER 19, 2024

You could further optimize the time for training in the following graph by using a SageMaker managed warm pool and accessing pre-downloaded models using Amazon Elastic File System (Amazon EFS). Challenges with fine-tuning LLMs Generative AI models offer many promising business use cases.

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ML Large Language Models Machine Learning Data Ingestion 91

NVIDIA

MARCH 18, 2025

While a traditional data center typically handles diverse workloads and is built for general-purpose computing, AI factories are optimized to create value from AI. They orchestrate the entire AI lifecycle from data ingestion to training, fine-tuning and, most critically, high-volume inference.

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AI AI Data Platform Data Ingestion 64

The MLOps Blog

MARCH 21, 2023

An end-to-end enterprise-grade platform for data scientists, data engineers, DevOps, and managers to manage the entire machine learning & deep learning product life-cycle. An end-to-end machine learning platform to build and deploy AI models at scale. Allegro.io

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

AWS Machine Learning Blog

NOVEMBER 14, 2024

It contains two flows: Data ingestion – The data ingestion flow converts the damage datasets (images and metadata) into vector embeddings and stores them in the OpenSearch vector store. We need to initially invoke this flow to load all the historic data into OpenSearch.

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