A16Z's recent GenAI report breaks down the challenges of putting enterprise AI into production, read more: https://
buff.ly/4a4Y5SL Snorkel Custom was designed to help enterprises overcome those challenges, and accelerate delivery of production ready AI.
@snorkelai
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Enterprise GenAI Production Challenges and Snorkel Solutions
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Proprietary Data as Secret Sauce in Enterprise AI
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More of Paroma! Paroma and Ali Arsenjani, Google's director of AI/ML partner engineering discuss the "secret sauce" that proprietary data plays in enterprise AI Watch it here: https://
buff.ly/4cZg5Q3 -
AI in Banking: Opportunities and Unstructured Data Challenges
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Looking to deepen your understanding of AI in the banking sector? Industry leaders delve into the opportunities and challenges of unstructured data as AI for the financial sector continues to evolve. Check it out:
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Wayfair Improves Model Accuracy with Data-Centric AI
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See how Wayfair improved model accuracy by adopting data-centric AI to curate high-quality training data: Label millions of images in months vs. years Improve F1 scores by 20+ percentage points Deliver production models 10x faster Register: https://
buff.ly/4aXqt9w -
Dataset Cartography: Managing Training Data in AI
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A year ago, William Huang of Capital One explored ""dataset cartography"" and its value in training data management. Check out this must-watch video to stay updated on the latest trends in the field:
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Foundation Models Shaping AI Future Applications
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Have you ever wondered how foundation models are shaping the future of AI? If you're keen on understanding how these large models trained on enormous datasets are used in downstream applications, this is a must-watch. Watch the full video here: https://
youtube.com/watch?v=9s7- -
Snorkel Custom: Enterprise AI Model Deployment Accelerator
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Deliver production AI models within weeks. Introducing Snorkel Custom, an accelerator for enterprises to deliver production AI. Snorkel experts work with you to rapidly evaluate, select, tune, and optimize LLMs for your unique use cases.
Learn more: https://
snkl.ai/custom -
Distilling Step-by-Step: Training Smaller LLMs with Reasoning
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Jason Fries discusses "distilling step-by-step." This method prompts an LLM to provide not just an answer, but also the reasoning behind it. This information is then used to train a smaller, model with similar performance. Watch here: https://
youtube.com/watch?v=TIqf4L
MNCjU
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Snorkel Tops AlpacaEval: Training Approach and Metrics Changes
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Hoang Tran, one of the researchers behind Snorkel's AlpacaEval Leaderboard-topping model, explains his training approach and why he asked for the leaderboard to change its metrics.https://t.co/xXve73ofo2 pic.twitter.com/YnSsbvZrfo
— Snorkel AI (@SnorkelAI) 11 avril 2024Hoang Tran, one of the researchers behind Snorkel's AlpacaEval Leaderboard-topping model, explains his training approach and why he asked for the leaderboard to change its metrics. https://
snorkel.ai/how-snorkel-to
pped-the-alpacaeval-leaderboard-and-why-we-re-not-there-anymore/
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Snorkel Custom: Enterprise LLM Application Accelerator Announced
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Today we're excited to announce Snorkel Custom, a hands-on accelerator for enterprises using LLMs to build AI applications. It pairs Snorkel Flow, an AI data development platform, with Snorkel AI researchers and ML practitioners.
Learn more: https://
snkl.ai/custom