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#YouTubeRewind: Celebrating what India watched & shared

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MUMBAI: 2016 was the year when sidekick became the superhero – yes you guessed it right – Kabali ruled the charts to become top trending movie trailer. Kapil Sharma show featuring Salman Khan got company from our very own YouTube stars of The Viral Fever playing truth or dare with dad and All India Bakchod’s honest portrayal of bars and restaurants as the top trending video’s of the year. Entertainment aside, we were also most curious to know about the GPS chip in the new 2000 rupees note.

As 2016 is coming to an end, and you know what that means….it’s time for #YouTubeRewind.

This year, more than 200 YouTube stars from 18 countries accepted our Ultimate 2016 Rewind Challenge to pay homage to the biggest videos, memes, channels, songs, and pop culture moments of the year. Keep an eye out for some pretty epic surprise guests. Oh, and we got Major Lazer to help us out with an original mix too.

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We’re excited to announce the top trending videos, music videos and bollywood trailers from 2016, according to time spent watching, sharing, commenting, liking and more. From Kapil Sharma, TVF, AIB and behind the scene video of Shah Rukh Khan becoming the FAN, this year’s top trending videos represent the amazing variety of creativity shared on YouTube every day.

Collectively, the top 10 videos have 70 million views and the channels who make them have more than 45 million subscribers who tune in regularly to  watch the funny, insightful, entertaining content they create/ upload, a blog posted by YouTube head of entertainment partnerships Satya Raghavan, stated.

Top trending videos:

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The Kapil Sharma Show: Sultan

The Voice India Kids: Ayat Shaikh

Crime Patrol Dial 100: Andhkaar

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Complete truth of Rs 2000 notes with a chip embedded in it

TVF: Truth or Dare with Dad

TVF’s Permanent Roommates: The Parents

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AIB : Honest Bars & Restaurants

Life Sahi Hai:  The Maid

How Shah Rukh Khan Became The FAN – Gaurav

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AIB Diwas:  Zakir Khan

In Music, 2016 seemed to be all about Kala Chashma with 45 million views, and ‘kar gayi chull’ and baby ‘ko base pasand hai’ taking the next slots. 

Top music videos:

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Kala Chashma:  Baar Baar Dekho

Kar Gayi Chull: Kapoor & Sons

Baby Ko Bass Pasand Hai:  Sultan

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Bulleya: Ae Dil Hai Mushkil

Cham Cham: Baaghi

GF BF: T-Series

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Hua hain Aaj Pehli Baar: Sanam Re

Ae Dil Hai Mushkil

Jabra:Fan

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The Breakup Song: Ae Dil Hai Mushkil

In movies, Rajinikanth as Kabali went viral with Aamir Khan’s Dangal and Salman Khan’s Sultan following closely behind. The biopic of MS Dhoni featuring Sushant Singh Rajput was also a huge hit.

Top movie trailers:

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Kabali Tamil Movie

Dangal

Sultan

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M.S.Dhoni – The Untold Story

Shivaay

Befikre

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Ae Dil Hai Mushkil

Fan

Baaghi

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Dishoom

From an ads perspective, it is quite evident from the YouTube Leaderboard 2016 that several brands chose to create long format ads for a primarily digital-first audience. In fact, seven out of top 10 most watched ads in 2016 were over 90 seconds long. And audiences too were willing to invest their time and attention on ads that are narrative-driven and take a storytelling approach. #Dettolsheronkepanje was the most viewed ads for 2016 with close to 13 million views, and #Ranveerchingreturns and Amazon’s#ApniDukaan taking the next spots.

Most viewed ads:

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Dettol Sheron ke Panje – #MaaMaane Dettol Ka Dhula

Ranveer Ching Returns

Amazon #ApniDukaan

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Doublemint #StartSomethingFresh

Ola Micro Stories

Bajaj V – The Invincible

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Makemytrip #BefikarBookKar – Taxi

#NothingDirty Anthem ft. Badshah

Amazon#MomBeAGirlAgain

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Samsung Galaxy S7 and S7 Edge

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iWorld

Meta plans 8,000 layoffs in new AI-led restructuring wave

First phase from May 20 may cut 10 per cent workforce amid AI pivot.

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MUMBAI: At Meta, the future may be artificial but the cuts are very real. The social media giant is reportedly preparing a fresh round of layoffs, with an initial wave expected to impact around 8,000 employees as it doubles down on its artificial intelligence ambitions. According to a Reuters report, the first phase of job cuts is slated to begin on May 20, targeting roughly 10 per cent of Meta’s global workforce. With nearly 79,000 employees on its rolls as of December 31, the move marks one of the company’s most significant workforce reductions in recent years.

And this may only be the beginning. Sources indicate that additional layoffs are being planned for the second half of the year, although the scale and timing remain fluid, likely to be shaped by how Meta’s AI capabilities evolve in the coming months. Earlier reports had suggested that total cuts in 2026 could reach 20 per cent or more of its workforce.

The restructuring comes as chief executive Mark Zuckerberg continues to steer the company towards an AI-first operating model, committing hundreds of billions of dollars to the transition. Internally, this shift is already visible: teams within Reality Labs have been reorganised, engineers have been moved into a newly formed Applied AI unit, and a Meta Small Business division has been created to align with broader structural changes.

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The trend is hardly isolated. Across the tech sector, companies are trimming headcount while investing aggressively in automation. Amazon, for instance, has reportedly cut around 30,000 corporate roles nearly 10 per cent of its white-collar workforce citing efficiency gains driven by AI. Data from Layoffs.fyi shows over 73,000 tech employees have already lost jobs this year, compared with 153,000 in all of 2024.

For Meta, the move echoes its earlier “year of efficiency” in 2022–23, when about 21,000 roles were eliminated amid slowing growth and market pressures. This time, however, the backdrop is different. The company is financially stronger, generating over $200 billion in revenue and $60 billion in profit last year, with shares up 3.68 per cent year-to-date though still below last summer’s peak.

That contrast underlines the shift underway. These layoffs are less about survival and more about reinvention. As Meta restructures itself around AI from autonomous coding agents to advanced machine learning systems, the question is no longer whether the company will change, but how many roles will be left unchanged when it does.

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