AI/ML H&H PPT

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Can work through imagine a machine automating your things reducing your workload or something in that grey area - just an idea

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Human Machine Collaboration
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Goal is saving time. Machine Learning creates more highly trained specialists not an all knowing being.
Purpose - Aid Humans & Not Replace them
Humans Remain in Control of the system
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Don’t fear AI - Explore AI Try the Tools pair with others

The future’s so bright. is it?
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The Deep Learning Revolution [The Big Bang of AI]
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The future of work and the work of the future.
We are living in very exciting times. This is your present, not your children’s, not your children’s children’s.
Awareness is the best antidote for ignorance.
We are entering the next way of tech change.
Pointers:
90+ Languages Online Today
1,000,000,000 Daily Transactions | 200’000,000 Daily Users
4,000,000,000 People Coming Online by 2025

DATA AND MODELS ARE GREAT. YOU KNOW WHAT’S EVEN BETTER? THE RIGHT EVALUATION APPROACH
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ANIArtificial Narrow Intelligence
AI specialized in a single task (e.g., Siri, ChatGPT, Google Maps). Most current AI systems fall under this category.
AGIArtificial General Intelligence
A human-level AI that can understand, learn, and apply intelligence across a wide range of tasks — like a real person.
ASIArtificial Superintelligence
A hypothetical AI that surpasses human intelligence in all aspects — reasoning, creativity, emotional intelligence, etc.


PITCH VERSION

Strategic Slide Flow:

Title: The Future of Work in Pharma: From Intelligence to Agentic AIBy NITI AI | Powered by Pucho.ai

Section 1: The Age of Intelligence

Slide 1: Welcome & Hook

“Is knowledge still power — or is it action?”
Visual: Francis Bacon “Is Knowledge Still Power?” quote
Set the tone: We’re in a shift from knowledge → intelligent action

Slide 2: What is Intelligence?

Definitions of natural intelligence (adaptation, creativity, decision-making)
Examples: Crossing roads, drawing, composing

Slide 3: From Natural to Artificial Intelligence

Can machines… make discoveries? Decide to wait or pivot? Compose?
Introduce grey area → Machines that act intelligently

Section 2: Understanding AI & Its Evolution

Slide 4: What is AI (Foundations)

Overview of ML, ANN, Deep Learning, NLP, Speech Recognition

Slide 5: Intelligence Spectrum

ANI vs AGI vs ASI
Show where we are, and where we’re headed

Slide 6: Deep Research is No Magic

It’s pattern recognition, not thinking — but it’s powerful
Highlight learning from data + black box limitation

Section 3: AI’s Impact on Work & Pharma

Slide 7: The Automation Shift

Hook: “It’s not a field force, it’s the formula”
Talk about disappearing tasks, not jobs
Introduce: "Massive transformation coming for regulated industries like pharma"

Slide 8: Ride the Train – Don't Jump in Front of It

A motivational slide: adapt early, don’t resist
Transition into how AI impacts regulated, data-heavy industries

Slide 9: Why Pharma Needs AI Urgently

90+ languages online, 4B users by 2025
Clinical ops, compliance, field force, research, inventory — all data-rich
But today: fragmented, slow, manual

Section 4: Enter Agentic AI

Slide 10: Current Digital Workers Aren’t Intelligent

Show contrast: Chatbots vs RPAs (they respond or automate, but not both)
Chatbots Can Talk. RPAs Can Click. Neither Can Think.

Slide 11: Agentic AI Evolution

Visual: Process Automation → Supervised → Gen AI → Agentic AI
Define agents: goal-oriented, memory-enabled, act-reflect-learn systems

Slide 12: How Agents Learn Over Time

Individual adaptation + systemwide upgrades
Pucho.ai brings agents into your daily workflows

Slide 13: Agentic AI in the News

Microsoft, Nvidia, Salesforce, McKinsey — credibility + market validation

Section 5: Pucho.ai for Pharma

Slide 14: Introducing Pucho.ai

The no-code, agentic AI platform built for Indian enterprises
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