Federico Kamelhar

27 posts

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Federico Kamelhar

Federico Kamelhar

@FedeKamelhar

Building agentic AI on OCI for practical, real-world workflows.

New York, NY Katılım Nisan 2019
50 Takip Edilen11 Takipçiler
Federico Kamelhar
Federico Kamelhar@FedeKamelhar·
so excited to see this out in the wild! 🎉 got to team up with @LiteLLM to make OCI Generative AI a first-class provider — Llama, Grok, Cohere, Gemini & gpt-5 through one OpenAI-compatible gateway, signing handled for you 🚀 #LiteLLM #OCI #GenAI x.com/OracleCloud/st…
Oracle Cloud@OracleCloud

LiteLLM now supports Oracle Generative AI Infrastructure as a first-class provider. social.ora.cl/6012BDuEx6 You can route requests to models hosted on Oracle Generative AI Infrastructure, while LiteLLM handles OCI Signature v1 request signing and centralizes production controls.

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Oracle Cloud
Oracle Cloud@OracleCloud·
LiteLLM now supports Oracle Generative AI Infrastructure as a first-class provider. social.ora.cl/6012BDuEx6 You can route requests to models hosted on Oracle Generative AI Infrastructure, while LiteLLM handles OCI Signature v1 request signing and centralizes production controls.
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Federico Kamelhar
Federico Kamelhar@FedeKamelhar·
New Haystack integration: Oracle AI Vector Search. Use Oracle Database 26ai as your vector store in any Haystack pipeline — native VECTOR type, HNSW + IVF indexing, hybrid search (vector + keyword), and metadata filtering. Ships with OracleDocumentStore, OracleEmbeddingRetriever, and OracleBM25Retriever — drop them into your indexing and query pipelines. Haystack for the RAG pipeline. Oracle for the vectors. Big thanks to David Batista (@davidsbatista on GH), @Julian_Risch, and @LukawskiKacper for the collaboration. haystack.deepset.ai/integrations/o… #Haystack #RAG #VectorSearch #OracleDatabase #Oracle26ai #GenAI #LLM #AI
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Federico Kamelhar
Federico Kamelhar@FedeKamelhar·
@DarshanSays What that typing buys: in n=200 adversarial across 4 judges, removing the four-way partition drops proceed by up to −49; ρ=0 inflates score on every judge. GSAR decides ship/rewrite/replan; the action layer reads the partition. (2/2)
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Federico Kamelhar
Federico Kamelhar@FedeKamelhar·
@DarshanSays @DarshanSays Appreciate the safety lens. Quick reframe: GSAR isn't gating tool calls — it evaluates *claims in the produced summary*. §1 example: "CPU >95% at t" → tool_match (w≈1); "likely caused the spike" → inference (lower w). Same sentence, different evidence type. (1/2)
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Federico Kamelhar
Federico Kamelhar@FedeKamelhar·
I’ve just shared a new paper on arXiv: arxiv.org/abs/2604.23366 GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMs As more teams build multi-agent systems for enterprise AI, a practical question arises: How do you know the system is actually pointing you in the right direction? Most current approaches reduce this to a single score or pass/fail signal. However, what’s missing is a method to turn that signal into actionable insights for the system. This paper aims to make that shift by treating grounding not just as evaluation, but as a control layer for agentic systems, which includes: - Proceed - Regenerate (a cost-effective fix) - Replan (more costly, but sometimes necessary) The goal is to advance from simply asking “is this grounded?” to understanding what kind of grounding signal we have and determining the appropriate actions to take. Key insights from this work include: - Not all evidence is equal; tool outputs versus model inference are more significant than expected. - Small design choices, such as how contradictions are handled, can greatly impact outcomes. - Different models exhibit varied behaviors when tasked with judging grounding. If you’re working on or deploying agentic systems, I’d be interested in your perspective — and feel free to take a guess at which model “wins” before reviewing the results. #AI #LLM #Agents #EnterpriseAI #MachineLearning #OracleCloud #Anthropic #OpenAI
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Oracle Cloud
Oracle Cloud@OracleCloud·
Any developers building AI applications on OCI Generative AI? We’ve got good news! social.ora.cl/6015BBMROc You can run the same Cohere code on OCI Generative AI—including Command A, Command A Vision, Command A Reasoning, Embed v4, and Rerank 3.5—while keeping authentication, compartment governance, and inference within your OCI tenancy.
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Oracle
Oracle@Oracle·
We’re incredibly excited about our partnership with OpenAI and remain focused on building and delivering the capacity they need to support rapidly growing demand. We’re seeing firsthand how quickly adoption of their technology is accelerating, driven by the strength of their latest models. OpenAI’s new 5.5 model is a significant step forward, and we expect continued momentum as access to their technology expands across cloud providers. Together, we’re enabling customers to bring powerful AI capabilities into production at scale.
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Oracle Developers
Oracle Developers@OracleDevs·
This tutorial walks you through deploying the vLLM Production Stack on OKE—from infrastructure provisioning to running your first inference request. social.ora.cl/6012hNgEp
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