Can work through imagine a machine automating your things reducing your workload or something in that grey area - just an idea
Human Machine Collaboration 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
Don’t fear AI - Explore AI Try the Tools pair with others
The future’s so bright. is it?
The Deep Learning Revolution [The Big Bang of AI]
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
ANI – Artificial Narrow Intelligence
AI specialized in a single task (e.g., Siri, ChatGPT, Google Maps). Most current AI systems fall under this category.
AGI – Artificial General Intelligence
A human-level AI that can understand, learn, and apply intelligence across a wide range of tasks — like a real person.
ASI – Artificial 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 AI
By 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
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