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Exploring Open-Source Alternatives to OpenAI Models

Analytics Vidhya

But this begs an important question: how trustworthy are closed models and the people behind them? It will not be a pleasant experience when the model you use in […] The post Exploring Open-Source Alternatives to OpenAI Models appeared first on Analytics Vidhya.

Modeling 250
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Amazon launches Bedrock: AI Model Evaluation with Human Benchmarking

Analytics Vidhya

In a development, Amazon Bedrock introduces the ability to assess, compare, and choose the optimal foundation models (FMs) tailored to your specific need. The Model Evaluation feature, now in preview, empowers developers with a range of evaluation tools, offering both automatic and human benchmarking options.

Modeling 237
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KOSMOS-2: A Multimodal Large Language Model by Microsoft

Analytics Vidhya

Introduction 2023 has been an AI year, from language models to stable diffusion models. It is a multimodal large language model (MLLM) making waves with groundbreaking capabilities in understanding text and images. One of the new players that has taken center stage is the KOSMOS-2, developed by Microsoft.

Modeling 270
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Explainable AI: Demystifying the Black Box Models

Analytics Vidhya

Explainable AI aims to make machine learning models more transparent to clients, patients, or loan applicants, helping build trust and social acceptance of these systems. Now, different models require different explanation methods, depending on the audience.

Modeling 263
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Democratizing AI for All: Transforming Your Operating Model to Support AI Adoption

It may require changing your operation models and finding the right guidance to realize the full breadth of capabilities. But in order to reap the rewards that AI offers, it is essential that businesses first address how their organizations are set up, from their people to their processes. Aligning AI to your business objectives.

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A Deep Dive into Model Quantization for Large-Scale Deployment

Analytics Vidhya

Introduction In AI, two distinct challenges have surfaced: deploying large models in cloud environments, incurring formidable compute costs that impede scalability and profitability, and accommodating resource-constrained edge devices struggling to support complex models.

Modeling 255
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DeepSeek: China’s Latest Language Model

Analytics Vidhya

In a recent development, the DeepSeek LLM has emerged as a formidable force in the realm of language models, boasting an impressive 67 billion parameters.

Modeling 169
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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionzing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

How to choose the appropriate fairness and bias metrics to prioritize for your machine learning models. How to successfully navigate the bias versus accuracy trade-off for final model selection and much more. Download this guide to find out: How to build an end-to-end process of identifying, investigating, and mitigating bias in AI.

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Getting Started With Scenario Modeling in Supply Chain Network Design

Let’s explore how you can apply scenario modeling in supply chain network design. To build your supply chain’s agility and responsiveness, you need to look at scenarios more frequently instead of relying on a single plan.

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Best Practices to Model Carbon Costs in Supply Chain Network Design

In this article, we share best practices about modeling carbon costs in network design. Do you want to know the environmental impact of your supply chain and make sustainable decisions?

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Addressing Top Enterprise Challenges in Generative AI with DataRobot

Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments.

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Resilient Machine Learning with MLOps

To prevent deployment delays and deliver resilient, accountable, and trusted AI systems, many organizations invest in MLOps to monitor and manage models while ensuring appropriate governance. Download today to find out more!

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Easily Build an Optimization App and Empower Your Data

Speaker: Gertjan de Lange

If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. Experience how efficient you can be when you fit your model with actionable data. Don't let uncertainty drive your business.