International
John Calley expires
MUMBAI: Producer of The Da Vinci Code John Calley died on Tuesday. He was 81. His death was announced by Sony Pictures Entertainment.
Calley – three-time studio chief, confidant of Stanley Kubrick rose to Hollywood‘s highest ranks by making gut-level bets on directors and writers and by gently and quietly steering them.
Stints at leading studios like Warner Brothers, United Artists and Sony gave Calley his A-list status in Hollywood‘s executive ranks, but it was his approach to those jobs that made him stand out.
Like any studio boss, he had his share of failures and purely commercial hits. While The Towering Inferno was a hit, he also directed films like Clockwork Orange (1971), The Exorcist (1973), Chariots of Fire (1981) and As Good as It Gets.
“When he believed in someone, he trusted and supported him,” Mike Nichols, who collaborated with Calley in films like Catch-22 to Closer, said in a statement.
John Calley was born on 8 July, 1930, in Jersey City, the son of a car salesman, and, after serving in the Army, worked at 21 as a mail clerk for NBC in New York. After climbing a few rungs on the network‘s ladder, he left to join an advertising firm before giving film producing a try at Filmways, a production company mostly known for TV comedies like The Beverly Hillbillies.
In 1996, Calley took the reins of Sony‘s movie operation and delivered hits like Jerry Maguire with Tom Cruise, but his biggest contribution to the studio involved restoring stability: Columbia, Sony‘s major arm, had four presidents come and go from 1991 to 1996.
He stepped down in 2003 but kept producing films for Sony that included The Da Vinci Code.
Calley‘s survivors include his daughter, Sabrina Calley, and three stepchildren, Emily Zinnemann, David Zinnemann and Will Firth, from his marriage to the actress Meg Tilly that ended in 2002.
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.
