From Search Ads to Chat Ads: Will LLMs Carry Ads? (Deep Dive + Forecast) From Search Ads to Chat Ads: Will LLMs Carry Ads? (Deep Dive + Forecast)

16th August 2025 - Raviteja Gullapalli

From Search Ads to Chat Ads: Will LLMs Carry Ads? (Deep Dive + Forecast)

TL;DR: Search monetized intent, YouTube monetized attention, and ChatGPT could monetize trust. The likely future: sponsored recommendations embedded into conversations. Here’s how it compares with Google Ads and YouTube, with some real-world examples i foresee from my experience.

Looking Back: The Evolution of Digital Ads

2000s – Intent Monetization (Google Search)

Google revolutionized ads by targeting explicit intent. If you searched “buy shoes,” advertisers bid for that keyword. High commercial intent meant high ROI, fueling Google’s ad empire.

2010s – Attention Monetization (YouTube & Social Media)

YouTube, Facebook, and Instagram shifted the model: instead of intent, they sold attention. Algorithms maximized watch time, and ads were inserted into streams — pre-rolls, mid-rolls, and influencer shoutouts.

2020s – Commerce Everywhere

Shopping surfaces integrated into almost every platform. Ads weren’t just banners; they became shoppable listings, video integrations, and dynamic recommendations.

Today: The Rise of Chat-first Interfaces

Users now ask ChatGPT or Bing Copilot for answers instead of searching Google. Instead of 10 blue links and ad slots, they get a synthesized conversational answer. This disrupts the traditional ad inventory model.

Current Footprint: Google Ads, YouTube, and ChatGPT

Google & YouTube

• Google Search Ads: Still the largest driver of digital ad revenue ($198B+ in 2024).
• YouTube Ads: ~$36B annually, monetizing user attention with video placements.

AI Answers with Ads

• Google AI Overviews: Ads are now shown inside AI-generated answers.
• Microsoft Bing/Copilot: Extends search ads into conversational chat answers.

ChatGPT (OpenAI)

• No ads in answers today — monetization is via subscriptions (Plus, Pro), enterprise licenses, and API usage.
• Leadership hasn’t ruled out ads in the future; experiments with “commerce in chat” are possible.

What “Chat Ads” Might Look Like

• Sponsored picks inside answers: A laptop query could include one promoted model with a discount.
• Shoppable snippets: Price + availability + quick buy link embedded in the response.
• Local services: “Dentist near me” returns one sponsored local clinic alongside recommendations.
• Cross-category nudges: Health, travel, or automotive assistants could suggest sponsored alternatives.

🚗 Example: Automotive Diagnostics in Chat

Today: If you type “My Tata Nexon engine is misfiring, what could be wrong?” into ChatGPT, it may guide you through checks like:

• Step 1: Inspect spark plugs.
• Step 2: Check ignition coils.
• Step 3: Verify fuel quality (E10 vs E20 compatibility).
• Step 4: Run OBD diagnostics.

Future (with ads): After giving you the diagnostic flow, the chat could add:

• “Sponsored: Visit Tata Motors Authorised Service Center – Bellandur for a same-day diagnostic and fix.”
• “Sponsored: Considering recurring ignition issues? Explore an upgrade to the Honda Elevate, designed for better ethanol compatibility.”

Just as Google search ads once linked you to car dealers, ChatGPT could directly influence your decision to book a service — or even switch manufacturers — inside the troubleshooting conversation.

Why Chat Ads Could Be More Influential

• Trust: Chat feels like a personal advisor, making sponsored nudges more persuasive.
• Scarcity: Only 1–2 ad slots per conversation flow, increasing value per placement.
• Contextual Fit: Answers can adapt to your specific problem, location, or budget.

Challenges & Regulations

Embedding ads inside advice raises ethical and legal concerns:

• FTC (US): Requires clear “Sponsored” labels for native ads.
• EU DSA: Requires transparency in targeting and political ad restrictions.
• Trust Risk: If ads blend too seamlessly, users may feel manipulated.

Comparison Table

Dimension	Google Search Ads	YouTube Ads	ChatGPT Ads (Future)
Unit	Keyword slot	Video pre/mid-roll	Sponsored recommendation
User State	Explicit intent	Passive attention	Active problem-solving
Inventory	Many per page	Several per video	1–2 per chat flow
Influence	High	Moderate	Very high (trusted advice)

Forecast: 2025 → 2030

1. Standardized ad formats: “Sponsored pick,” “Shoppable card,” “Local slot.”
2. High-value verticals first: Travel, healthcare, automotive, electronics.
3. Hybrid monetization: Subscriptions + ads + revenue share from transactions.
4. Regulation hardens: Assistant-specific rules on labeling and disclosure.

Final Take

Google Ads monetized intent, YouTube monetized attention, but ChatGPT is positioned to monetize trust. If ads arrive, they won’t be banners or pop-ups — they’ll be embedded recommendations inside conversations. That shift could make them the most influential ads yet, especially when users are troubleshooting real-world problems like their car, health, or travel plans.

Let me know your thoughts ;)

There’s More to Life Than Money, Position, and Talent There’s More to Life Than Money, Position, and Talent

10th July 2025 - Raviteja Gullapalli

There’s More to Life Than Money, Position, and Talent

In our fast-paced, hyper-connected world, it's easy to get caught in the never-ending race for titles, promotions, and recognition. You may feel anxious and uneasy today, wrestling with challenges you never expected—navigating office politics, chasing deadlines, or constantly trying to prove your worth in a system that rarely pauses for breath.

It’s natural to want to climb higher. To grow. To shine. But sometimes, in the process, we forget the simple truth: life is more than just achievements, designations, or how many skills you can stack on your résumé.

Years from now, when the hustle softens and the noise dims, you’ll realize that what mattered most was not your LinkedIn title, but the peace in your heart and the gratitude in your soul.

There will always be another challenge, another corporate summit, another goal to chase. But what gives your journey depth isn't just what you accomplish—it's how deeply you appreciate the foundation you're standing on. Your health, your family, the people who love you for who you are—not what you do. These are the quiet anchors of a life well lived.

Look beyond the metrics of success. Look at the moments you laughed without reason, the times you helped someone without expecting anything in return, the evenings where you watched the sunset in silence and just felt… grateful.

The brave new world around us glorifies growth. But real fulfillment doesn’t come from upward motion—it comes from inward reflection.

So pause. Breathe. Remind yourself today that you are more than your KPIs. More than your career graph. More than your so-called potential.

In the end, what truly matters is not how high you’ve climbed, but how deeply you've lived, loved, and appreciated the life you’ve been given.

When Curiosity Meets Its Limits – AI’s Plateau? When Curiosity Meets Its Limits – AI’s Plateau?

22nd June 2025 - Raviteja Gullapalli

Human curiosity has always sought to replicate the mysteries of the mind. From early childhood questions to breakthrough innovations, our fascination with intelligence has been relentless. The story of artificial intelligence mirrors this very journey—rising, evolving, and now perhaps, showing signs of stagnation.

From Human Brain to Accidental AI

The ambition to model the human brain started with neural networks—simple, almost childlike attempts to learn from patterns. Over decades, those systems matured. Their learning grew layer by layer, until they began outperforming us in tasks like image recognition, language translation, and game playing. With only a fraction of the brain's neural connections, they still managed feats that stunned even their creators.

To put it in perspective: modern large language models like GPT operate using around 1 trillion parameters. The human brain, in contrast, has roughly 100 trillion synapses. That’s a hundredfold difference—yet AI models already show capabilities that feel intuitive, articulate, even creative. It's a humbling realization of what curated data and structured architecture can accomplish.

What powered them wasn't just computation, but the same force behind all human achievement: curiosity, now supercharged by data.

A Learning Curve—And a Plateau

But like humans, AI too appears to be hitting limits. While early training shows rapid progress, complexity soon piles on, and learning slows. Modern AI—especially large neural networks—begins making decisions no one fully understands. It's not unlike a human learner growing in ways even their teachers can’t predict.

And with that unpredictability comes risk. When AI systems evolve beyond our transparency and control, their usefulness may be outpaced by their unknowability.

The Mirror of Human Plateau

Humans naturally plateau. We learn, we specialize, and then we struggle with diminishing returns. The same could be true for AI: the more complex it becomes, the harder it is to guide, the more uncertain its trajectory. Are we watching a superintelligence take form, or just another system bound by its own design?

The Curiosity Twist

The paradox lies in the very force that created it—curiosity. It built the machines. It trained the models. And now it questions the outcome. We are simultaneously the parents and the puzzled observers of AI’s next chapter. Some outcomes are profound—drug discovery, medical imaging, climate modeling. Others are more troubling—bias amplification, misinformation, surveillance, and autonomous weaponry.

The Uncertain Future

What happens when AI begins modifying itself? Or when its logic becomes inscrutable? Regulation is vital, but how do we govern a system we can’t fully decode? These aren't just technical puzzles—they're philosophical dilemmas about intelligence, agency, and our place in the future.

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Closing Thought
Just as human curiosity leads to breakthroughs—and eventual stagnation—so too does AI. Its learning curves rise, flatten, and now raise questions of what lies beyond. Will AI leap ahead, stall, or evolve in ways we can’t yet grasp? The answer remains unclear.

So we wait. We observe. We stay curious.
Because the story of intelligence—natural or artificial—is far from over.

It’s All My Fault… But There’s Something I Can Do It’s All My Fault… But There’s Something I Can Do

22nd May 2025 - Raviteja Gullapalli

It’s All My Fault… But There’s Something I Can Do

A story of love, sacrifice, and the healing that comes with understanding.

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Chapter 1: Threads of Two Worlds

Arjun was born into a traditional Telugu Brahmin family in Vijayawada — a home built on discipline, rituals, and quiet reverence. His mother, Padmavathi, was deeply religious, waking at 4 AM every day, reciting scriptures while making strong filter coffee. His father, Srinivasa Rao, was a retired Sanskrit professor who held pride in values, caste, and legacy.

Sana came from Delhi. A half-Punjabi, half-Muslim woman, raised in a home of shared festivals, noisy dinners, and open windows. She was bold, warm, and carried the scent of Delhi winters with her — strong, sharp, yet comforting.

They met during their MBA in Pune. What started as a group project bloomed into late-night study sessions, long train rides, and finally, love. But they both knew — the real test would not be between them. It would be with the world around them.

Chapter 2: The First No

When Arjun told his parents about Sana, silence fell like a stone.

“She’s not Brahmin,” his father said quietly.
“She’s not Telugu,” his mother added, her voice trembling.
“She eats meat.”
“She won't know our ways.”

They didn’t yell. That wasn’t their style. But their disappointment was louder than anger.

Arjun stayed back a few days to talk. To explain that Sana was willing to learn. That she respected their values. But Padmavathi, usually so composed, cried silently one night and clutched her chest.

Her blood pressure had spiked. She was hospitalized for two days.

“See what you’ve done?” his father said.

Arjun stood by her bed, eyes red. “It’s all my fault,” he whispered to himself, again and again.

Chapter 3: Distance

Back in Hyderabad, Sana noticed his growing silence. He smiled less, held her hand less often, and stared at his phone too long after every call.

“I don’t want to hurt her,” he confessed one night. “She’s not just my mother. She raised me when Appa was busy at work for months. She had compromised on everything for us. I can’t be the reason she suffers now.”

Sana nodded, quietly. Her heart broke, but she didn’t fight. She stopped sending wedding decor ideas. She started taking evening walks alone.

One day, she packed a small bag. “I’m going to stay with a friend for a while. You need to be with your family now.”

Chapter 4: The Wait

Weeks passed. Padmavathi recovered physically, but emotionally, she could sense something inside Arjun was… lost. He was at home, but distant. She noticed how he no longer smiled at his favorite rasam. How he stared blankly when she played his childhood songs.

One afternoon, she found a note tucked into the Bhagavad Gita he had once gifted her.

“Amma, I didn’t choose between you and her. I chose you… hoping you would one day choose me — all of me. Including the woman who makes me whole.”

That evening, she turned to Srinivasa Rao and said, “We are holding his body, but his soul… it’s elsewhere.”

Chapter 5: The Return

Sana was back in Delhi, working quietly. She had stopped replying to Arjun’s messages. She didn’t want to make it harder for him.

Until one morning, her doorbell rang. And there stood Padmavathi, with folded hands and tearful eyes.

“I came alone. Not as his mother… but as a woman who once gave up everything for love. I see now… you’re not taking our son away. You’re giving him back to us.”

Sana broke down. That night, Padmavathi stayed with her, and they talked — about rituals, about compromise, about boundaries.

Chapter 6: A Different Kind of Wedding

They didn’t have a lavish wedding. There was no band, no paparazzi, no endless rituals. Instead, it was held at a small venue in Vijayawada. A limited guest list. Simple attire.

Sana had spent months learning Telugu. She kept her promise, and she celebrated every festival with Padmavathi, even learning how to light the lamp just right.

Arjun, in turn, visited Delhi every few months. He learned to cook chole for her father.

They had both let go of something — parts of their habits, their timelines, their pride — but in return, they got something stronger: belonging.

Final Note

Love didn’t win through rebellion. It won through empathy. Through slow healing, awkward first steps, honest apologies, and everyday patience.

Sana and Arjun didn’t just marry. They taught two families to unlearn fear.

And in the quiet corners of their small Hyderabad apartment, where the tulsi plant sways next to fairy lights, where ghee sizzles next to Delhi spices… they found peace.

“It’s all my fault... that I loved her. But there was something I could do. I waited. I understood. And I chose her, every single day.”

– The End –

Learn Like a GenAI: Podcasting Your Way to Machine-Level Mastery Learn Like a GenAI: Podcasting Your Way to Machine-Level Mastery

20th May 2025 - Raviteja Gullapalli

🧠 Learn Like a GenAI: Podcasting Your Way to Machine-Level Mastery

Ever wonder how a GenAI model like ChatGPT, Gemini, or Claude learns so fast? Like, blazingly fast, absorbing entire Wikipedia dumps, arXiv preprints, Reddit rants, and 90s fanfiction with equal appetite?

Now imagine this: what if you could learn like that—while brushing your teeth, walking your dog, or pretending to listen on Zoom calls?

🎙️ Enter: Google’s NotebookLM + Podcasts = Human Learning 2.0.

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🤖 The GenAI Way of Learning (a TL;DR)

Let’s break down how GenAI models learn:

1. Ingest tons of data.
2. Build connections.
3. Update based on feedback.
4. Repeat until... superintelligence?

Sounds mechanical? Well yeah—it is. But here’s the thing: you can steal their method. All you need is a way to turn your info diet into a constant stream of contextual, connected, and convenient knowledge.

And that’s where Google NotebookLM’s podcast-generation comes in.

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🧩 What's NotebookLM Anyway?

Imagine if Google Docs had a baby with a research assistant and that baby could talk.

NotebookLM lets you drop in your notes, docs, links, and more—and it then auto-summarizes, highlights insights, and (here’s the juicy bit) generates podcasts you can listen to.

Yes, you heard that right. It takes your messy research notes and turns them into a podcast episode hosted by a friendly AI voice that sounds like your favorite NPR narrator on too much coffee.

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🔄 How to Learn Like a GenAI (but fun and caffeinated)

Here’s your 5-step playbook to go full synthetic-brain-mode:

1. Pick a Topic You’d Like to Know Cold

Could be anything—LLMs, quantum computing, policy shifts in Web3, or why raccoons look like tiny burglars. Gather links, notes, articles, and even your half-written rants in a doc.

2. Feed It to NotebookLM

Drag and drop. Paste. Upload. Sacrifice a PDF. Whatever works. The model chews through your info like a machine with no concept of sleep.

3. Generate the Podcast

Now for the magic: ask NotebookLM to turn your notes into a podcast-style summary. Customize the tone (casual, formal, Joe Rogan-esque?). Press go.

4. Listen on the Go

• Morning walks? ✅
• Stuck in traffic? ✅
• Pretending to work while secretly spiraling? ✅

You’re now learning like a model—absorbing info on loop, context-rich, and bite-sized.

5. Ask Questions & Iterate

Just like a model fine-tunes weights, you adjust your mental model. Ask NotebookLM for clarifications. Add new content. Generate new podcasts. Repeat.

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🌟 Why This Works

Unlike doomscrolling or binge-watching “explainer videos” at 2x speed:

• You’re learning passively and actively.
• It’s your content—tailored to what you care about.
• Repetition locks in long-term memory (same way LLMs reinforce weights).
• And bonus: you feel like Iron Man with JARVIS in your ears.

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🧪 Bonus Hack: Layer It with Spaced Repetition

Want to go beast mode? Take insights from the podcast and feed them into an app like RemNote or Anki. Boom—now you’ve got GenAI + Human Brain + Flashcards. Resistance is futile.

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🏁 Final Thought

Learning like a GenAI isn’t about speed. It’s about consistency, context, and curiosity.

So the next time you're sipping coffee and feeling like you’re not “learning fast enough”—just remember: even transformers start with token by token. You just happen to listen to yours on Spotify now. 😉

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Try it. Make your brain a podcast junkie. And tell me what weird rabbit holes you fell into.

Until next time,
Stay curious, stay caffeinated.


—Ravi 🤖☕
www.ravitejagullapalli.com

Sanskrit Poetry Verses : Childhood memories Sanskrit Poetry Verses : Childhood memories

20th April 2025 - Raviteja Gullapalli

Radiance and Serenity

Original Sanskrit Verse

दशायमान सुमहास कदम्बवनवास कुसुम्भ सुमनो
वास विपञ्ची कृतरस विदूय मधु मसरविन्द मधुर
कासरसून तटिभासा अभिराम तनुर असर शीत करुण
नासमणि प्रवरभासा शिव तिमिरमसादयेदुपरति।

(daśāyamāna sumahāsa kadambavanavāsa kuśumbha sumanovāsa vipañcī kṛtarasa vidūya madhu masaravinda madhura kāsarasūna ṭaṭibhāsā abhirāma tanur asara śīta karuṇa nāsamaṇi pravarabhāsā śiva timiramasādayed uparati।)

 

English Translation and Explanation

Beaming with a radiant smile, dwelling in the kadamba groves,
adorned with kusumbha and sumana flowers,
her fragrance surpassing the sweetness of spring blossoms,
as though the music of the vipañcī (a string instrument) has come alive in her aura.

She washes away the fatigue of summer with the charm of blooming lotuses,
her glow like the banks of a moonlit pond,
her graceful body exudes a gentle, selfless coolness like moonlight,
and the brightness of the gem on her nose
may dispel the darkness of sorrow and lead us to inner peace.

Poetic Beauty and Meaning

This verse is a perfect blend of śṛṅgāra (aesthetic of beauty and love) and śānta (serenity). The poet paints a portrait of a serene, luminous maiden whose mere presence brings emotional and spiritual calm. The metaphors move from nature to emotion, from external beauty to internal tranquility.

Elements like the kadamba forest, kusumbha flowers, lotus ponds, and moonlight are rich in classical Indian symbolism. The reference to the nose gem dispelling darkness is metaphorical for inner transformation — beauty that leads to liberation. The syntax flows like music, echoing the effect of a vipañcī being played in the background of a moonlit lotus grove.

Closing Reflection

This poem offers more than just a description of beauty — it is an invitation to calm, to reflection, and to recognizing the harmony of the natural and emotional world. It reminds us that poetry, especially in Sanskrit, was not just art — it was a path to inner stillness.

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— Curated for the love of languages