Modeling Related Topics 
Analytics Vidhya
APRIL 13, 2024
Introduction Machine learning models hold immense potential, but they need to be effectively integrated into real-world applications to unlock their true value. This is where model deployment and serving tools come into play. By […] The post Top 11 Model Deployment and Serving Tools appeared first on Analytics Vidhya.
Analytics Vidhya
APRIL 14, 2024
French startup, Mistral AI, has launched its latest large language model (LLM), Mixtral 8x22B, into the artificial intelligence (AI) landscape. Similar to its previous models, this too aligns with Mistral’s commitment to open-source development.
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Analytics Vidhya
APRIL 15, 2024
Elon Musk’s xAI recently showcased a preview of its multimodal AI model Grok-1.5V, which looks quite promising. This innovative new AI model bridges the gap between textual and visual understanding, marking a significant milestone in artificial intelligence (AI). Multimodal Model appeared first on Analytics Vidhya.
Analytics Vidhya
APRIL 16, 2024
This innovative multimodal language model performs remarkably well across a range of assessment parameters. It is placed on par with top industry models like GPT-4V and Claude-3 Opus.
Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase
Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing 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.
Analytics Vidhya
MARCH 14, 2024
Anthropic, a San Francisco-based startup, has recently launched Claude 3 Haiku, the latest addition to its Claude 3 family of AI models. Positioned as the fastest and most cost-effective model in its class, Haiku offers advanced vision capabilities and robust performance on industry benchmarks.
Analytics Vidhya
MARCH 27, 2024
Vision Language models are the models that can process and understand both visual and language(textual input) data simultaneously. These models combine techniques from Computer Vision and Natural Language Processing to understand and generate text based on the image content and language instruction.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial.
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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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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?
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.
Advertiser: Data Robot
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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Modeling your base case. Modeling carbon costs. Scenario analysis and optimization defined. Creating a strategic digital twin (digital representation) of your supply chain network. Optimizing your supply chain based on costs and service levels. Dealing with multiple capacity constraints. Network design for risk and resilience.
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This report explores how the state of supply chain network design has changed – including how the tools, maturity models, and market demands are transforming the network design practice. Advanced analytics & Scenario Modeling. This report is useful if you are interested in: Exploring new network design insights and capabilities.
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The guide includes a checklist, an assessment, industry-specific use cases, and a data & analytics maturity model and roadmap. Download this guide for practical advice on using a semantic layer to improve data literacy and scale self-service analytics.
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