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Open Source & AI: Shaping the Future

Varun Pandya, CTO – Weamai

"Collaborative Innovation for the AI Era"

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About Me

Chief Technology Officer

At Weam.ai, I leads the technological vision and strategy, driving the company's innovation forward.

Tech Solutions Builder

With a versatile background in both service and product domains, I focuses on building and scaling technology solutions that address real business challenges.

Innovation Driver

Passionate about fostering innovation, cultivating high-performing teams, and translating complex ideas into impactful products across diverse industries.

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Agenda

What is Open Source & Why it matters

Evolution of AI

How Open Source drives AI innovation

Benefits & Challenges

Case Studies & Ecosystem

Trending GitHub Projects

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Open Source in a Nutshell

63%

Companies using OSS AI

Organizations leveraging open-source AI technologies in 2024

96%

Developer adoption

Developers actively using open-source software components

$84B

Market projection

Open-source services market value by 2030 (~17% CAGR)

80%

Cloud infrastructure

Cloud systems running on open-source software foundations

Iconic Open Source Projects

Linux

Apache

Kubernetes

WordPress

Sources: Stack Overflow Developer Survey 2024, McKinsey Global Survey 2024

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AI in a Nutshell

78%

AI business adoption

Organizations using AI in at least one business function

71%

Generative AI usage

Organizations actively adopting generative AI technologies

AI Market Growth Trajectory

The AI market is experiencing unprecedented expansion: $233B in 2024 projected to reach $1.77T by 2032, representing a robust 29% compound annual growth rate.

Key AI Use Cases

Healthcare

Finance

Marketing

Education

Logistics

Sources: McKinsey Global Survey 2024, Gartner AI Market Forecast 2024

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Why Open Source + AI?

Open Source + AI: Better Together

Open Source

AI

Networked AI

Innovation & Scale

Puts Advanced AI in the hands of the broader community

Transparency builds trust in models & decisions

Community pace → faster innovation cycles

Lower implementation costs vs proprietary alternatives

Global access → diverse contributions & rapid iteration

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Open Source AI Ecosystem

Frameworks

PyTorch, TensorFlow

Communities

Hugging Face, LangChain

Models

LLaMA, Qwen, Deepseek

Databases/Tools

Qdrant, Weaviate, Haystack

UI & Apps

Gradio, ComfyUI

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Trending Open Source AI Projects

Real-Voice Cloning

These tools let you create a believable copy of someone’s voice from a short sample. Real‑Time Voice Cloning uses a three‑step process to learn a speaker’s sound and then convert text into speech Project Link: https://github.com/CorentinJ/Real-Time-Voice-Cloning

Perplexcia

This open‑source search engine combines results from many sources and uses AI to understand your question and find up‑to‑date answers. �Project Link: https://github.com/ItzCrazyKns/Perplexica

AutoAgent

This framework lets you build powerful language‑model agents without writing code. �Project Link: https://github.com/HKUDS/AutoAgent

N8n-Workflows

This is a huge collection of ready‑made automation templates for the n8n platform�over 2,000 workflows �Project Link: https://github.com/Zie619/n8n-workflows

RAG -Anything

RAG‑Anything is an open‑source toolkit that lets you upload a document—whether it’s a PDF, slide deck, spreadsheet or even images and equations—and ask questions about it.�Project Link: https://github.com/HKUDS/RAG-Anything

Source: GitHub trends and AI community activity as of 2024

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Benefits of Open Source AI

Flexibility & Customization

Complete control without vendor lock-in constraints

Cost Efficiency

Reduces infrastructure and tooling costs by 30–50%

Enhanced Security

Transparency and community code review strengthen protection

Rapid Deployment

Faster prototyping and deployment for quicker time-to-market

Client Trust

Builds confidence through auditability and control

Key Value Drivers

  • Lower Total Cost of Ownership
  • Tailored Solutions
  • Security Visibility
  • Rapid Delivery
  • Stakeholder Trust

Source: Industry analysis of enterprise OSS adoption, 2024

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Challenges of Open Source AI

1

Security & Compliance

Organizations struggle with governance frameworks and regulatory compliance in open-source environments

2

Long-term Support

Uncertainty around maintenance commitments and project sustainability over time

3

Licensing Complexity

Navigating diverse license types: Apache, GPL, Elastic 2.0, and custom licensing models

4

Ethical Risks

Potential misuse of powerful open models without proper safeguards and oversight

5

Project Sustainability

Funding and stewardship challenges for critical open-source AI infrastructure

Sources: Open Source Security Foundation, Linux Foundation, MITRE AI Risk Framework

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Case Studies / Ecosystem Impact

Hugging Face

200K+ models, standardized sharing

Meta LLaMA

Open weights → 1,000+ research projects

Stable Diffusion

10M+ downloads in <1 year

LangChain

100K projects in <2 years

Copilot Studies

+6.5% productivity uplift in OSS teams

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Industry Impact

Driving Transformation Across Key Sectors

Agencies & Startups

Achieve 40% faster prototyping cycles with OSS AI stacks.

Enterprises

Realize significant TCO reductions through self-hosted open models.

Developers

Gain democratized access, accelerating global innovation and skill development.

Education & Research

Enable large-scale experimentation at affordable costs.

Sources: McKinsey Global Survey 2024, Stack Overflow Developer Survey 2024

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Thank You!

Let's shape the future of Open Source & AI together

varun@weam.ai

linkedin.com/in/varun-pandya-1676a0103

Collaborative Innovation for the AI Era