Join Okareo and AICamp for a night out where we'll be digging into the best practices of making AI agents behave even better. Get ready to see what your agents are really capable of when we unleash their full potential. Register today: https://lnkd.in/gJ2Hg54p #AI #agentics #inpersonevents
Okareo
软件开发
San Francisco，CA 489 位关注者
LLM Evaluation and Fine-Tuning to Help You Build Smarter AI Apps
关于我们
Okareo offers the most comprehensive LLM evaluation and fine-tuning platform to ensure AI application developers can deliver high-quality LLM-powered applications fast.
- 网站
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https://okareo.com/
Okareo的外部链接
- 所属行业
- 软件开发
- 规模
- 2-10 人
- 总部
- San Francisco，CA
- 类型
- 私人持股
- 创立
- 2023
- 领域
- Model Evaluation、ML Evaluation Framework、Natural Language Processing、Natural Language Understanding、Large Language Models、Neural Information Retrieval、RAG、Retrieval Augmented Generation、Semantic Analysis 、Model Performance、Grounded Generation、ML Testing Automation、 Model Benchmarks、GenAI、Generative AI、NLP、LLM和Machine Learning
地点
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主要
获取路线
US，CA，San Francisco
Okareo员工
动态
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Yesterday's "DevGuild AI Summit III: Code Generation" was fantastic. One of the best parts of an intense meet-up with brilliant folks is the next day brainstorming with the team. Well ideas were flowing today at Okareo. More cool capabilities coming and a definite doubling down on multi-model/agent evaluation. The agents are coming. It was also nice to hear that areas we've put a lot of investment into, like challenger AI Judges and simulation with use-case specific scenarios (generated synthetically) are gaining traction even outside of our conversational bubble. I did promise at the end of the DevGuild meetup that I would post some content on agent patterns and what agents are and aren't. So, stay alert. That will be coming soon. But most of all, if you are building multi-model products with LLMs, get vocal! We builders have a lot of ground to cover to reach what's possible. Thank you #Heavybit and #Stifel for making the DevGuild event possible. You rock! #AI, #LLM, #RAG, #Agentic #AgentEvaluation
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Matthew Wyman, Co-Founder/CEO at Okareo, joined Tatyana Mamut ????????????, Co-Founder/CEO at Wayfound, and Scott Jorgensen, Co-Founder/CPO, for a lively conversation on the ROIs of AI agents at the Bee Partners' office as part of #SFTechWeek on Tuesday. At Okareo, we are building the most comprehensive LLM evaluation and fine-tuning platform to ensure our customers can deliver high-quality agent, RAG, and LLM applications fast. Learn more at https://okareo.com/. #AI #LLM #RAG #Agentic #SFTechWeek
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Research Scientist, PhD, and PE with industry expertise in applied machine learning
?? Want to see how Okareo can help you bootstrap and evaluate your LLM fine-tuning experiments? Check out this demo! https://lnkd.in/gQWRnv9B This video is a companion piece to my recent blog on fine-tuning intent detection models for RAG agents. ?? Read the original post here: https://lnkd.in/gUgPwUw5 Want to dive deeper into LLM evaluations and synthetic data? ??Try Okareo for yourself (free!): https://lnkd.in/gFT37B3e #MachineLearning #AI #LLM #FineTuning #Okareo #SyntheticData
Okareo fine-tuning demo with Mason del Rosario
https://www.youtube.com/
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Ok, so I built a bot (see prior post) and then I wanted to improve it. The bot was doing a great job filtering out English spam. But it was worthless when the message was in Icelandic, Hungarian, and other languages. I'm sharing this because it is a essential experience with prompts. After dozens of reasonable prompt iterations where I added phrases like “Ignore non-english comments” or “Accept only english comments”, the solution was: ? indent the spam rules ? add a title “Spam Rules” ? add an extra line before and after the spam rule block Yeah. That is some silly, illogical, [stuff].? Thank goodness for baselines, incremental measurement and the ability to synthetically create non-english scenarios to evaluate against. Because without that, it would have been hours not minutes to solve. So, it turns out Prompt Debugging is a thing. Thank goodness I have one. ;)