@h2oai and NVIDIA are working together to provide an end-to-end workflow for financial institutions, using NVIDIA AI Enterprise. Companies can develop and deploy their own #LLMs to power #generativeAI use cases in #financialservices. Read the blog here.
LLMS
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H2O and NVIDIA Enable LLM Deployment for Financial Services
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@h2oai and NVIDIA are working together to provide an end-to-end workflow for financial institutions, using NVIDIA AI Enterprise. Companies can develop and deploy their own #LLMs to power #generativeAI use cases in #financialservices. Read the blog here.
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H2O and NVIDIA Enable Enterprise LLM Deployment for Financial Services
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@h2oai and NVIDIA are working together to provide an end-to-end workflow for financial institutions, using NVIDIA AI Enterprise. Companies can develop and deploy their own #LLMs to power #generativeAI use cases in #financialservices. Read the blog here.
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Inflection AI celebrates innovation year with Pi capabilities
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🥂 Cheers to a year of innovation.🚀 Check out the game-changing capabilities of Pi – and try it out for yourself: https://t.co/e1SMbsqDUo pic.twitter.com/ib9Q45INil
— Inflection AI (@inflectionAI) 4 janvier 2024🥂 Cheers to a year of innovation.🚀 Check out the game-changing capabilities of Pi – and try it out for yourself: Pi.ai
→ View original post on X — @inflectionai, 2024-01-04 17:15 UTC
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Challenges of Deploying RAG Applications in Enterprise Environments
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The most common use of LLMs in enterprise is building RAG (retrieval augmented generation) applications on a custom knowledge base, which are difficult to put in production. Some of the challenges are: •Parsing docs and PDFs (most open-source libraries struggle with this)
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Information Extraction from Files Using LLMs
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Information Extraction using LLMs This great blog walks through how to create an app that allows you to: Upload a file of your choice
Specify the schema you want to extract And then it pulls out all that info! Blog: https://
pub.towardsai.net/demystifying-i
nformation-extraction-using-llm-f1a551f01f66
… Full code links in blog! -
Advanced Retrieval for RAG with Chroma Course
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New short course on advanced retrieval for RAG (retrieval augmented generation)!
— Andrew Ng (@AndrewYNg) 4 janvier 2024
RAG fetches relevant documents to give context to an LLM. In Advanced Retrieval for AI with Chroma, taught by @trychroma founder @atroyn, you’ll learn:
(i) Query expansion using an LLM to rewrite… pic.twitter.com/7MHX4HT09VNew short course on advanced retrieval for RAG (retrieval augmented generation)! RAG fetches relevant documents to give context to an LLM. In Advanced Retrieval for AI with Chroma, taught by @trychroma founder @atroyn
, you’ll learn:
(i) Query expansion using an LLM to rewrite -
LLMs Not Responsible for Amazon Content Scams
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People have run such scams on Amazon since before LLMs. The generated content is irrelevant, it's only there for SEO purposes
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ChatGPT Struggles with Negation Prompts in Image Generation
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Anyone notice ChatGPT seems to underperform on negation prompts?
— Allie K. Miller (@alliekmiller) 4 janvier 2024
One viral example: the man asking Dall-E to remove the chopsticks from the image of the ramen, but they just keep moving around the bowl. https://t.co/w6anLdV8hiAnyone notice ChatGPT seems to underperform on negation prompts? One viral example: the man asking Dall-E to remove the chopsticks from the image of the ramen, but they just keep moving around the bowl.
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Behind the Scenes: GPT Builder Feature in ChatGPT
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Excited to share a little behind the scenes of the GPT Builder feature available inside the @ChatGPTapp GPT Builder is actually itself a GPT using instructions and a custom action. This is useful to read if you are building GPTs: