Pooja Pillai is an entertainment journalist with Asian Media Group, where she covers cinema, pop culture, internet trends, and the politics of representation. Her work spans interviews, cultural features, and social commentary across digital platforms.
She began her reporting career as a news anchor, scripting and presenting stories for a regional newsroom. With a background in journalism and media studies, she has since built a body of work exploring how entertainment intersects with social and cultural shifts, particularly through a South Indian lens.
She brings both newsroom rigour and narrative curiosity to her work, and believes the best stories don’t just inform — they reveal what we didn’t know we needed to hear.
Fifty years have passed since that dusty road in Ramgarh first brought us Jai, Veeru, Basanti, Thakur, and a villain whose name still sends a shiver. It’s a film you don’t just watch, you inherit. Parents pass it to kids like a family heirloom. Every rewatch is a homecoming, yet it still surprises you.
And now, as 15 August 2025 marks its golden jubilee, Sholay is not just being remembered, it’s being reborn. Here’s how its fire still crackles, half a century on.
Sholay turns 50 with global 4K comeback and untold stories Instagram/rameshsippy47
1. Global 4K debut in Toronto
The Film Heritage Foundation’s painstakingly restored 4K version will premiere at the Toronto International Film Festival on 6 September 2025. A packed 1,800-seat Roy Thomson Hall will watch it in never-before clarity. The question on every Indian fan’s lips: “When’s it hitting home screens here?”
2. “Yeh Dosti” hits the UK stage
A full-scale musical and dance tour by LuvEntertainment is bringing Sholay’s beats to life across Hayes, Leicester, Coventry, and beyond. Think “Mehbooba Mehbooba” with blazing lights and live choreography. Like nostalgia, but with stage pyrotechnics.
3. The ending we were never meant to see
For decades, the true climax, Thakur kicking Gabbar to death, was a whisper among film buffs. Censors chopped it out in 1975. In June 2025, the Bologna festival unveiled it to a stunned audience.
4. Casting “what-ifs” and wild sets
Danny Denzongpa was first choice for Gabbar before schedules clashed. Amitabh Bachchan was billed fourth. Dharmendra allegedly bribed lighting crew to prolong romantic takes with Hema Malini. Meanwhile, Jaya Bachchan quietly shot her scenes while pregnant.
5. The jaw-dropping pay scale
Bachchan got £9,400 (₹1,00,000). Dharmendra, the top earner, got £14,100 (₹1,50,000). British stuntmen made £470 (₹50,000) each for the train heist scene, a sum that, at the time, could buy a small flat in Mumbai.
6. From flop to phenomenon
When it released, Sholay had slow ticket sales and mixed reviews. Javed Akhtar admitted he kept watching it himself, worried. Then word-of-mouth turned it into India’s highest-grossing film for nearly 20 years.
7. The records that won’t die
Five years straight at Mumbai’s Minerva Theatre. Over 25 crore footfalls worldwide. Proof that sometimes, the audience just needs time to catch up to genius.
8. Blood, sweat, and real bullets
Basanti’s tanga chase? Twelve days in scorching heat. Some action scenes used actual bullets for “authenticity”, Dharmendra’s idea. The first cut ran over four hours before it was trimmed for release.
9. Gabbar’s roots in reality
Amjad Khan modelled him on 1950s Chambal Valley dacoits. His gravelly “Kitney aadmi the?” didn’t just enter pop culture, it became shorthand for suspicion in Indian households.
10. Writers who never looked back
Javed Akhtar hasn’t rewatched Sholay since its 70mm re-release. His reasoning: “Those lost in their history have no hope for their future.” It’s a sentiment that keeps the film alive, we remember, even if its creators have moved on.
You don’t talk about Sholay like any other film. You talk about where you first saw it. You talk about watching it with people who aren’t here anymore. You talk about quoting its lines at weddings, in classrooms, in WhatsApp groups.
Fifty years later, it’s still more than cinema. It’s part of our vocabulary, our memory, our muscle. And as its 4K rebirth travels the world, Sholay reminds us: some friendships, some enemies, and some stories never fade.
AI can make thousands of podcast episodes every week with very few people.
Making an AI podcast episode costs almost nothing and can make money fast.
Small podcasters cannot get noticed. It is hard for them to earn.
Advertisements go to AI shows. Human shows get ignored.
Listeners do not mind AI. Some like it.
A company can now publish thousands of podcasts a week with almost no people. That fact alone should wake up anyone who makes money from talking into a mic.
The company now turns out roughly 3,000 episodes a week with a team of eight. Each episode costs about £0.75 (₹88.64) to make. With as few as 20 listens, an episode can cover its cost. That single line explains why the rest of this story is happening.
When AI takes over podcasts human creators are struggling to keep up iStock
The math that changes the game
Podcasting used to be slow and hands-on. Hosts booked guests, edited interviews, and hunted sponsors. Now, the fixed costs, including writing, voice, and editing, can be automated. Once that system is running, adding another episode barely costs anything; it is just another file pushed through the same machine.
To see how that changes the landscape, look at the scale we are talking about. By September 2025, there were already well over 4.52 million podcasts worldwide. In just three months, close to half a million new shows joined the pile. It has become a crowded marketplace worth roughly £32 billion (₹3.74 trillion), most of it fuelled by advertising money.
That combination of a huge market plus near-zero marginal costs creates a simple incentive: flood the directories with niche shows. Even tiny audiences become profitable.
What mass production looks like
These AI shows are not replacements for every human program. They are different products. Producers use generative models to write scripts, synthesise voice tracks, add music, and publish automatically. Topics are hyper-niche: pollen counts in a mid-sized city, daily stock micro-summaries, or a five-minute briefing on a single plant species. The episodes are short, frequent, and tailored to narrow advertiser categories.
That model works because advertisers can target tiny audiences. If an antihistamine maker can reach fifty people looking up pollen data in one town, that can still be worth paying for. Multiply that by thousands of micro-topics, and the revenue math stacks up.
How mass-produced AI podcasts are drowning out real human voicesiStock
Where human creators lose
Podcasting has always been fragile for independent creators. Most shows never break even. Discoverability is hard. Promotion costs money. Now, add AI fleets pushing volume, and the problem worsens.
Platforms surface content through algorithms. If those algorithms reward frequency, freshness, or sheer inventory, AI producers gain an advantage. Human shows that take weeks to produce with high-quality narrative, interviews, or even investigative pieces get buried.
Advertisers chasing cheap reach will be tempted by mass AI networks. That will push down the effective CPMs (cost per thousand listens) for many categories. Small hosts who relied on a few branded reads or listener donations will see the pool shrink.
What listeners get and what they lose
Not every listener cares if a host is synthetic. Some care only about the utility: a quick sports update, a commute briefing, or a how-to snippet. For those use cases, AI can be fine, or even better, because it is faster, cheaper, and always on.
But the thing is, a lot of podcast value comes from human quirks. The long-form interview, the offbeat joke, the voice that makes you feel known—those are hard to fake. Studies and industry voices already show 52% of consumers feel less engaged with content. The result is a split audience: one side tolerates or prefers automated, functional audio; the other side pays to keep human voices alive.
When cheap AI shows flood the market small creators lose their edgeiStock
Legal and ethical damage control
Mass AI podcasting raises immediate legal and ethical questions.
Copyright — Models trained on protected audio and text can reproduce or riff on copyrighted works.
Impersonation — Synthetic voices can mirror public figures, which risks deception.
Misinformation — Automated scripts without fact-checking can spread errors at scale.
Transparency — Few platforms force disclosure that an episode is AI-generated.
If regulators force tighter rules, the tiny profit margin on each episode could disappear. That would make the mass-production model unprofitable overnight. Alternatively, platforms could impose labelling and remove low-quality feeds. Either outcome would reshape the calculus.
How the industry can respond through practical moves
The ecosystem will not collapse overnight.
Label AI episodes clearly.
Use discovery algorithms that reward engagement, not volume.
Create paywalls, memberships, or time-listened metrics.
Use AI tools to help humans, not replace them.
Industry standards on IP and voice consent are needed to reduce legal exposure. Platforms and advertisers hold most of the cards here. They can choose to favour volume or to protect quality. Their choice will decide many creators’ fates.
Three short scenarios, then the point
Flooded and cheap — Platforms favour volume. Ads chase cheap reach. Many independent shows vanish, and audio becomes a sea of similar, useful, but forgettable feeds.
Regulated and curated — Disclosure rules and smarter discovery reward listener engagement. Human shows survive, and AI fills utility roles.
Hybrid balance — Creators use AI tools to speed up workflows while keeping control over voice and facts. New business models emerge that pay for depth.
All three are plausible. The industry will move towards the one that matches where platforms and advertisers put their money.
Can human podcasters survive the flood of robot-made showsiStock
New rules, old craft
Machines can mass-produce audio faster and cheaper than people. That does not make them better storytellers. It makes them efficient at delivering information. If you are a creator, your defence is simple: make content machines cannot copy easily. Tell stories that require curiosity, risk, restraint, and relationships. Build listeners who will pay for that difference.
If you are a platform or advertiser, your choice is also simple: do you reward noise or signal? Reward signal, and you keep what made podcasting special. Reward noise, and you get scale and a thinner, cheaper industry in return. Either way, the next few years will decide whether podcasting stays a human medium with tools or becomes a tool-driven medium with a few human highlights. The soundscape is changing. If human creators want to survive, they need to focus on the one thing machines do not buy: trust.
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