Anniversary special in memory of acting icon and her breakthrough film Himmatwala
By ASJAD NAZIRFeb 23, 2023
THIS week marks the anniversary of legendary actress Sridevi’s death on February 24, 2018, at the age of 54.
It is also the week when her movie Himmatwala was released in 1983. The masala entertainer, which hit cinemas on February 25, became a blockbuster success and propelled Sridevi towards becoming the biggest pan-Indian film icon.
Eastern Eye decided to mark both occasions by finding 20 facts about the superstar-making Hindi film classic that gave rise to an unforgettable cinema giant who has left her mark on Bollywood.
1.Himmatwala was a remake of Telugu-language comedy Ooruki Monagadu (1981), and had the same director – K Raghavendra Rao.
2. The filmmaker had become successful in Telugu cinema during the 1970s and made his Bollywood debut with Jeetendra starrers Nishana (1981) and blockbuster hit Farz Aur Kanoon (1982). He would work with that actor and Sridevi in subsequent films including Justice Chaudhury (1983) and Tohfa (1984).
Sridevi with Jeetendra in Himmatwala
3. The film’s original title was Zabardasti when it was launched, but it was changed later on.
4. Rekha was the first choice to play the lead in Himmatwala and the character was even named after her. Jaya Prada, who had starred in the original Telugu version, was also considered. Sridevi eventually landed the role and took her first big step towards superstardom.
5. The actress had originally been signed by the same production house, Padmalaya, for a Telugu film that got shelved. The producers decided to use her dates for Himmatwala instead and it turned out to be a masterstroke.
6. After becoming a big name in Tamil and Telugu cinema, Sridevi had made an unsuccessful Bollywood debut with Solva Saawan (1979). She returned to Hindi cinema with Himmatwala four years later, and it turned her into an overnight super star. She immediately became the most in-demand leading lady.
7. Waheeda Rehman played Jeetendra’s mother despite only being four years older than him. In stark contrast, his love interest in the movie, Sridevi, was 21 years younger than him.
8. The superhit film started a successful partnership between the lead stars Jeetendra and Sridevi, which included a further three successful releases in 1983 – Jaani Dost, JusticeChaudhary and Mawaali. They would act opposite one another in 15 films within a few years.
The earthern pots featured in hit song Naino Mein Sapna
9. The stand-out moment in the movie was the song Naino Mein Sapna, which became a rage. It was so popular that earthen pots similar to those featured in the song were placed outside cinema halls showing the film, while sales of similar colourfully designed pots rocketed. The late great Kishore Kumar had sung the song originally, and in the 2013 remake, those duties were given to his son Amit Kumar.
10. Despite being an accomplished dancer, Jeetendra admitted to being nervous performing songs with Sridevi. He said she got the dance steps straight away and helped him in rehearsals to get them right.
11. Sridevi had her dialogues dubbed by former child star Naaz because Hindi wasn’t her first language. It worked so well in Himmatwala that Naaz would become the voice of Sridevi throughout the 1980s in the star’s biggest blockbusters.
12. The eye-catching action scenes were choreographed by Veeru Devgan. Interestingly, his son Ajay Devgn would play the lead role in the 2013 remake.
13. Kader Khan had become a Bollywood villain but started a new phase as a massively successful comedy actor with Himmatwala because his negative roles would result in his son getting into fights. The multi-talented star also wrote unforgettable dialogues for the film.
14. Legendary Bollywood comedian Asrani acted in Himmatwala and then in the Hindi remake 30 years later.
15. Actress Swaroop Sampat played the hero’s sister in Himmatwala. Coincidentally, her actor husband Paresh Rawal took on the role originally played by Kader Khan in the unsuccessful 2013 remake.
Jeetendra and Sridevi
16. There is a small supporting role by Arun Govil when he was a relatively unknown actor in the film. He would go onto become a huge TV icon with his role of Lord Rama in classic drama series Ramayana in the 80s.
17. The film was so popular that it successfully ran in some cinemas across India for nearly two years.
18. Years later, Sridevi admitted that she didn’t like Himmatwala being her big breakthrough movie because it typecast her into glamorous roles. She preferred more performance-driven projects like Sadma, which was released in the same year, but she was pushed towards being a pin-up, which didn’t allow her to fully showcase her acting talent.
19. A big reason why Sridevi became a sex symbol were her figure-hugging clothes and extreme close-ups of her body. One particularly tiny one-piece outfit showing her legs earned her the nickname ‘thunder thighs’. Many people flocked to cinemas just to get a glimpse of her legs.
20.Himmatwala is available to watch for free on YouTube. It has been viewed over six million times.
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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