International
Die Hard sequel collects $10.1 million in first weekend
MUMBAI: Box-office receipts of 20th Century Fox‘s release of A Good Day To Die Hard, that was released in limited outlets, was the highlight of a sluggish session on the foreign theatrical circuit despite Sony‘s Django Unchained remaining No. 1 overseas for the fourth consecutive weekend.
Springing a jump on its US and Canada bow this week, the fifth installment of the action franchise starring Bruce Willis opened over the weekend in just seven Asian markets and managed to draw in $10.1 million at 1,102 locations for a per-screen average of over $9,000.
In South Korea, the opening take including previews was $4.2 million from 459 sites. The film set a Fox record in Indonesia and set a franchise record in Hong Kong ($1.2 million at 87 spots).
Over a 25-year span the four prior Die Hard titles all starring Willis have made money overseas grossing $694.6 million, while the second sequel of the franchise, 1995‘s Die Hard With A Vengeance roped in $264.5 million.
The 1988 original Die Hard drew $57.8 million in offshore box office, with the first sequel, 1990‘s Die Hard 2, grossing $122.5 million. The last sequel, 2007‘s Live Free or Die Hard, completed its foreign run with box office of $249.7 million.
Meanwhile, director Quentin Tarantino‘s Unchained collected $18.7 million from 5,280 locations in 65 markets. The action westerner co starring Jamie Foxx, Christoph Waltz and Leonardo Di Caprio that has acquired as many as five Oscar nominations, has grossed a total of $187.1 million since its opening.
In Germany, its best market, Unchained drew $3.9 million in its fourth round at 843 sites for a market total of $35.6 million while in France, the film has been at the No. 1 spot for four consecutive weeks with the latest weekend tally ($3.3 million) down around 33 per cent from that of the last weekend.
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 Sofía 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. Sofía 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.
