International
Hunger Games grosses $250 mn in 10 days
MUMBAI: New releases Wrath of the Titans and Mirror Mirror could not survive the wrath of Hunger Games. The Lionsgate film, in its second weekend, grossed $61.1 million crossed $250 million in only 10 days-the fastest ever for a non-sequel.
Hunger Games grossed $34.8 million in its second weekend of play at the foreign box office, putting its cume at $113.9 million and global total at $364.9 million.
Wrath of the Titans grossed $34.2 million, compared to the $61.2 opening of Clash of the Titans two years ago. Warner‘s knew the sequel wouldn‘t match that number since Clash of the Titans opened on Good Friday, a holiday.
“We made the decision to open even with Hunger Games and the NCAA Final Four baskeball games so that we could play through the heart of the holidays,” said Warner Bros. president of domestic distribution Dan Fellman.
Fellman pointed out that Sherlock Holmes: A Game of Shadows also opened to substantially less than the first Sherlock Holmes, or $39.6 million versus $62.3 million, but that the sequel eventually caught up and has now surpassed the first film.
Wrath of the Titans did far better overseas over the weekend, opening to $78 million and beating Hunger Games, which has been a softer play internationally outside of English-speaking territories. Wrath‘s global opening is $112.2 million.
Wrath of the Titans, playing in a total of 4,127 locations, drew 65 per cent of its revenues from 3D runs. That included including more than 290 IMAX theatres, which generated $4.7 million in ticket sales, or 14 per cent of the total gross. Domestically, Wrath received a B+ CinemaScore, compared with a B for Titans.
On the other hand, Mirror Mirror succeeded in luring families, who made up 60 per cent of the audience. While kids under the age of 12 made up 37 per cent of the audience, their parents made up 23 per cent.
Mirror… is the first of two Snow White movies opening this year, though Universal‘s Snow White and the Huntsman, which bows in the summer, isn‘t a family film.
LOS ANGELES: Acting has never been an easy profession, but in recent years, it has acquired a new existential anxiety. Artificial intelligence can now mimic faces, clone voices and, in theory at least, speak any language it is fed. The fear that actors may soon be replaced by algorithms no longer belongs exclusively to science fiction. And yet, despite the rise of digital inauthenticity, some performers remain stubbornly resistant to replacement. The reason is not celebrity, nor even talent. It is language.
On paper, this should not be a problem. AI can translate. It can imitate accents. It can string together grammatically correct sentences in dozens of languages. But acting, inconveniently, is not about grammatical correctness. It is about meaning, and meaning is where AI still falters.
Machine translation offers a cautionary tale. Google Translate, now powered by neural AI, has improved markedly since its debut in 2006. It can manage menus, emails and airport signage with impressive efficiency. What it struggles with, however, are the moments that matter most: idioms, metaphors, irony, and cultural shorthand. Ask it to translate a joke, a threat disguised as politeness, or a line heavy with emotional subtext, and it begins to unravel. Acting lives precisely in those gaps.
This matters because film language is rarely literal. Scripts, particularly in independent cinema, rely on figurative speech and symbolism to convey what characters cannot say outright. Pedro Almodóvar’s Volver is a useful example. The film’s recurring use of red operates on multiple levels: grief, desire, repression, liberation, and memory. These meanings are inseparable from the Spanish cultural context and emotional cadence. A translation may convey the words, but not the weight they carry. An AI-generated performance might replicate the sound, but not the sense.
This is where multilingual actors gain their edge. Performers such as Penélope Cruz and SofÃa Vergara do not simply switch between languages; they move between cultural logics. Their fluency allows them to inhabit characters without flattening them for international consumption. Language, for them, is not an accessory but a structuring force.
Beyond European cinema, this becomes even more pronounced. Languages such as Hindi, Arabic and Mandarin are spoken by hundreds of millions of people and underpin vast cinematic traditions. As global audiences grow more interconnected, the demand for authenticity increases rather than diminishes. Viewers can tell when a performance has been filtered through approximation. Subtle errors, misplaced emphasis, and an unnatural rhythm break the illusion.
There is also a practical dimension. Multilingualism expands opportunity. SofÃa Vergara has spoken openly about how learning English enabled her to work beyond Colombia and access Hollywood roles. But this movement is not a one-way export of talent into English-speaking cinema. Multilingual actors carry stories, styles and sensibilities back with them, enriching multiple industries at once.
Cinema has always thrived on such hybridity. Denzel Washington’s performances, for instance, draw on the cultural realities of growing up African American in the United States, while also reflecting stylistic influences from classic Hollywood and Westerns. His work demonstrates how identity and influence intersect on screen. Multilingual actors extend this intersection further, embodying multiple cultural frameworks simultaneously.
At times, linguistic authenticity is not merely artistic but ethical. Films that confront historical trauma, such as Schindler’s List, rely on language to anchor their moral seriousness. When Jewish actors perform in German, the choice is not incidental. Language becomes a site of memory and confrontation. It is difficult to imagine an automated voice carrying that responsibility without hollowing it out.
This is why claims that AI heralds the death of language miss the point. Language is not just a delivery system for information. It is a repository of history, humour, power and pain. Fluency is not only about knowing what to say, but when to hesitate, when to understate, and when to let silence do the work. These are not technical problems waiting to be solved; they are human instincts shaped by lived experience.
AI may one day improve its grasp of metaphor and nuance. It may even learn to sound convincing. But acting is not about sounding convincing; it is about being convincing. Until algorithms can acquire memory, cultural inheritance and emotional intuition, multilingual actors will remain irreplaceable. AI may learn to speak. But it cannot yet learn to mean.
In an industry increasingly tempted by shortcuts, language remains stubbornly resistant to automation. And for actors who can move between worlds, linguistic, cultural, and emotional, that resistance is not a weakness, but a quiet, enduring advantage.
