Aporia’s Post

Here at Aporia, while we all come from different backgrounds and have different personalities, We all have a passion for AI. And we want to share the knowledge and talent we have gained with others. So join us for our next webinar: Niv, our Director of AI, is going to show you how to get started with RAG chatbots. ✅ You'll understand about the basic architecture of RAGs, ✅ Learn about Langchain, Llamalndex and Vector DB for prototyping RAG systems, ✅ And gain tips for fine-tuning and mitigating hallucinations. Join us online, on the 18th July, 2pm EST https://lnkd.in/dxpus2wx

THE INVERSE RELATIONSHIP BETWEEN PROMPT LENGTH AND LLM ACCURACY 🔙 The research, detailed in the paper, “Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models,” highlights that LLMs quickly degrade in their reasoning capabilities even with input lengths of 3,000 tokens, much shorter than their technical maximum. 🤔So, once you've found your optimal prompt length, how can you safeguard AI without needing to touch your prompt? Find out here on Grit Daily News → https://lnkd.in/drzezYpT #AIprompt #AIaccuracy #AIhallucinations

What makes Aporia's platform so unique? After all, we aren't just another platform offering standard AI guardrails... Introducing...our signature Custom Policy 🤔 Allowing you to create completely customizable policies from scratch, without needing to lift a finger. ➡ All you need to fill in is the behavior you want to detect and whether or not it should be considered a violation or a legitimate answer. ✅ You can even test it out to check the policy is behaving as it should in real-time. See how it works here⬇

It was great meeting everyone at the AIQCon on Tuesday in #sanfrancisco. We got to speak to many AI practitioners and engineers and had insightful conversations about the importance and challenges of shipping truly reliable AI agents - a problem we all know will only get worse as AI gets more 'intelligent'. #aiqcon #aihallucinations #ai

Aporia’s response to Thomson Reuters on safeguarding customers’ data privacy: Indeed, earning public trust in AI requires a strong ethical foundation. Maintaining client privilege and ensuring the confidentiality of sensitive information is critical. While Thomson Reuters has measures in place to safeguard user data, robust guardrails are necessary to ensure AI security. Rather than simply pledging not to share PII with third parties, why not take it a step further? We can prevent the accidental sharing of PII by intercepting and managing it in real-time before it reaches the LLM. Users need to trust AI. Enhancing protections not only boosts safety but also promotes wider AI adoption among businesses. Article reference: https://lnkd.in/eavxc_FW

Behind the scenes of our last webinar 🎬 (Yes, the red ears were essential for a successful event 👏 kudos to Gadi Bessudo)

AI Engineers, last chance to sign up ⤵️ You really don't want to miss this one!

Are RAGs the solution to AI hallucinations⁉ While RAGs do hold promise for mitigating #AI hallucinations, industries and businesses turning to these solutions must also understand their inherent limitations. When used in tandem with RAGs, there are complementary methodologies that should be used when addressing #LLM hallucinations. For example, businesses can employ real-time AI guardrails to secure #LLM responses and mitigate AI hallucinations. #Guardrails act as a net that vets all LLM outputs for fabricated, profane, or off-topic content before it reaches users. This proactive middleware approach ensures the reliability and relevance of retrieval in #RAG systems, ultimately boosting trust amongst users, and ensuring safe interactions that align with a company’s brand. Read the full article on Unite.AI here ➡️https://lnkd.in/dAyY7as6

Who else is excited for Alon Gubkin to be speaking next Tuesday on 'Mitigating Hallucinations and Inappropriate Reponses in RAG Hallucinations?' We know we are 🙋♀️ 🙋