Lamini

Lamini AI

Lamini AI

Lamini AI

Lamini AI

Lamini AI

Lamini AI

Lamini AI

Lamini AI

Lamini AI

Lamini AI

🎯 Aiming for 90%+ accuracy on your Text-to-SQL agent, but can't get past 50%? With our proven methodology, our customers have cracked the code and hit 9s of accuracy! We're spilling the tea 🍵 in ou

🎯 Aiming for 90%+ accuracy on your Text-to-SQL agent, but can't get past 50%? With our proven methodology, our customers have cracked the code and hit 9s of accuracy! We're spilling the tea 🍵 in our upcoming webinar. Bring your toughest Text-to-SQL questions—we’ve got answers! 💪 🎯 Build high-accuracy Text-to-SQL BI agents 📅 March 20, 2025 🕘 10:00 - 10:45 AM PT 🔗 Register here today: https://t.co/BhQbxOtIcf

Join us for a webinar on building Text-to-SQL BI agents. We’ll show how to finetune any open LLM to reach 90%+ accuracy. Register now https://t.co/0B73RnZWWI 🎯 Build high-accuracy Text-to-SQL BI age

Join us for a webinar on building Text-to-SQL BI agents. We’ll show how to finetune any open LLM to reach 90%+ accuracy. Register now https://t.co/0B73RnZWWI 🎯 Build high-accuracy Text-to-SQL BI agents 📅 March 20, 2025 🕘 10:00 - 10:45 AM PT

🙌Introducing Memory RAG—a simpler approach to RAG that leverages embed-time compute to create more intelligent, validated data representations. Build mini-agents with a simple prompt. Get the paper:

🙌Introducing Memory RAG—a simpler approach to RAG that leverages embed-time compute to create more intelligent, validated data representations. Build mini-agents with a simple prompt. Get the paper: https://t.co/X0sdzAuX2m https://t.co/N4dAqUIncF

Thanks @DeepLearningAI for featuring us in The Batch! https://t.co/oQVE0GSNYz

Thanks @DeepLearningAI for featuring us in The Batch! https://t.co/oQVE0GSNYz

@nooriefyi Couldn't agree more!

@nooriefyi Couldn't agree more!

Have you seen our Classifier Agent Toolkit 😺 demo yet? Learn how to use our SDK to build a highly accurate Classifier Agent for a customer service chatbot. The agent categorizes customer interactio

Have you seen our Classifier Agent Toolkit 😺 demo yet? Learn how to use our SDK to build a highly accurate Classifier Agent for a customer service chatbot. The agent categorizes customer interactions by intent so it can respond appropriately. You can run multiple evaluations until you reach your desired level of accuracy. https://t.co/ogIpBKFguR

@realSharonZhou 😻😻😻😻😻😻😻😻😻

@realSharonZhou 😻😻😻😻😻😻😻😻😻

🎁 Our new Classifier Agent Toolkit (CAT 🐱) is here! No more extensive manual data labeling or heavy ML systems. 😻 Build classifier agents that can quickly categorize large volumes of data at 95%+

🎁 Our new Classifier Agent Toolkit (CAT 🐱) is here! No more extensive manual data labeling or heavy ML systems. 😻 Build classifier agents that can quickly categorize large volumes of data at 95%+ accuracy / 400k token throughput in under 2 seconds. Watch the demo and get the link to the docs and repo here: https://t.co/1u1SpHrgRJ

🙌 Our new Enterprise Guide to Fine-Tuning is out! If you can't get above 40-50% accuracy with RAG, fine-tuning might be the answer. Learn the basics of fine-tuning and specific applications and use c

🙌 Our new Enterprise Guide to Fine-Tuning is out! If you can't get above 40-50% accuracy with RAG, fine-tuning might be the answer. Learn the basics of fine-tuning and specific applications and use cases. https://t.co/lAMmspVaD2 https://t.co/RyCgzRohgw

.@realSharonZhou recently spoke at @Aurecon's #ExemplarForum2024 on high-ROI use cases for LLMs and overcoming key challenges in AI deployment, including poor model quality, hallucinations, costs, and

.@realSharonZhou recently spoke at @Aurecon's #ExemplarForum2024 on high-ROI use cases for LLMs and overcoming key challenges in AI deployment, including poor model quality, hallucinations, costs, and security. Watch the video here: https://t.co/N24bfOyJGb

🎉🎉🎉 Excited to announce our new pay-as-you-go offering, Lamini On-Demand. Get $300 in free credit to run your tuning and inference jobs on our high-performance GPU cluster. Happy tuning! https://t.

🎉🎉🎉 Excited to announce our new pay-as-you-go offering, Lamini On-Demand. Get $300 in free credit to run your tuning and inference jobs on our high-performance GPU cluster. Happy tuning! https://t.co/77M1tMpS6U

@StanTechAddict @GregoryDiamos Great idea @StanTechAddict!

@StanTechAddict @GregoryDiamos Great idea @StanTechAddict!

LLM inference frameworks have hit the “memory wall”, which is a hardware imposed speed limit on memory bound code. Is it possible to tear down the memory wall? @GregoryDiamos explains how it works in

LLM inference frameworks have hit the “memory wall”, which is a hardware imposed speed limit on memory bound code. Is it possible to tear down the memory wall? @GregoryDiamos explains how it works in his new technical blog post. https://t.co/hAgiZmYaQb

Go from AI novice to fine-tuning wiz with our Improving Accuracy of LLM Applications course with @DeepLearningAI + @asangani7. Here's one student's experience getting to 96% accuracy on factual data i

Go from AI novice to fine-tuning wiz with our Improving Accuracy of LLM Applications course with @DeepLearningAI + @asangani7. Here's one student's experience getting to 96% accuracy on factual data in just 3 iterations. https://t.co/jgA0F2OsBP

Vertical vs. horizontal AI use cases? GitHub Copilot started vertical and crossed over into horizontal applications. Low latency + accuracy were key! Thanks for the great discussion @gajenkandiah and

Vertical vs. horizontal AI use cases? GitHub Copilot started vertical and crossed over into horizontal applications. Low latency + accuracy were key! Thanks for the great discussion @gajenkandiah and @Hitachi! https://t.co/eGNB0AohJ3