The document discusses various AI models and tools developed by H2O.ai, including their focus on enterprise applications that emphasize security, scalability, and customization. Key offerings include integrations with popular LLMs, support for RAG frameworks, and a fully containerized, customizable platform for enterprise use. It highlights benchmarks for open-source LLMs and emphasizes ensuring data ownership and adaptability across different cloud environments.

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Arno Candel
Chief Technology Officer, H2O.ai
Jon McKinney
Director of Research, H2O.ai
S P E A K E R S

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github.com/h2oai/h2ogpt
gpt.h2o.ai

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RAG
PrivateGPT, Quiver, h2oGPT
Agency
AutoGPT, AutoGen, BabyAGI,
ChatDev, GPT-Engineer
Inference + Data
vLLM, Semantic Kernel, DSPy,
Langchain, LlamaIndex, MemGPT
H2O Data Studio, H2O LLM Eval
(Pre-) Training
OpenAI, Meta, Google, Mistral
Torch, DeepSpeed
Fine-Tuning
LLM Studio, Transformers
LORA, RLHF, DPO
Hardware
AI Clouds
NVIDIA GPUs
AI Stack

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RAG

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Application:
❏ Multi-Chat
❏ RAG w/HYDE
❏ Query w/Web
❏ Map & Map Reduce
❏ Python & Search Agents
Focus:
❏ KGM Models
❏ Parallelism
❏ Instruct LLMs
❏ Prompt Engineering
❏ Testing new LLMs
Goal:
❏ OSS RAG with API
❏ Backend for Enterprise
h2oGPT

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What LLM saw Where was the answer?

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Claude2 OpenAI

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Bard

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ChatPDF

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KGM Image-OCR Models

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Challenges
Context Size:
❏ 100k - Claude2
❏ 128k - OpenAI GPT-4
❏ 32k - LongAlpaca 70B LLaMa-2
❏ 128k - Yarn - Mistral 7B
❏ 192k - Baichuan2
Other Challenges:
❏ Vague or Meta questions
❏ Critique, Verification
❏ Lexical + Semantic
❏ Retrieval vs. Summarization and Extraction
❏ Time-Aware RAG
❏ Multi-Modal Agency
Meta Queries
Retrieval
Understanding

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Enterprise h2oGPTe

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Enterprise h2oGPTe
h2oGPTe = h2oGPT + focus on
Enterprise Requirements
< Security, Scalability, GUI,
Collaboration, APIs, Airgapped,
Multi-Cloud, HA, K8s />
AI includes:
HyDE, ReRanker, Self-reflection,
Prompt Engineering, etc.

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Enterprise h2oGPTe
Fully customizable APIs!

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h2oGPTe RAG Benchmarks Key Take-Aways for h2oGPTe:
● open-source LLMs are good enough
● built on top of h2oGPT for latest AI
● designed for airgapped environments
● runs on any cloud/VPC, K8s
● Python/JS client API + GUI
● fully containerized and scalable
● customizable, any LLM, any language
● guard rails, agents, tools on road map
● own your data and models!
https://h2o.ai/platform/enterprise-h2ogpt/ https://pypi.org/project/h2ogpte/
< DEMO BOOTH!
See live demos! />

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