International
Oscar-winning producer Richard Zanuck dies at 77
MUMBAI: Oscar-Winning producer Richard D. Zanuck, whose distinguished career as a producer included The Sting and Driving Miss Daisy, Jaws and other well-received films as The Verdict and Cocoon, died on Friday of a heart attack at his home in Beverly Hills. He was 77.
In recent times , Zanuck produced Tim Burton’s Alice in Wonderland and Dark Shadows. He worked on six films with the director.
Regarded as one of the more progressive producers in Hollywood, Zanuck was partnered by his wife, Lili Fini Zanuck, in their company called Zanuck Co. Their first production was Driving Miss Daisy(1992). Winner of four Oscars, the film captured several other top honors: a Golden Globe award, the National Board of Review Award and Producer of the Year honours from the Producers Guild of America.
In 1999, Zanuck and his partner, David Brown, received the Irving G. Thalberg award from the Academy of Motion Picture Arts and Sciences.The occasion marked the first time that an honoree was a second-generation recipient – Zanuck’s father, former 20th Century Fox head of production, and chairman Darryl F. Zanuck, were given the award in 1938, 1945 and 1951. They also happen to be the only father and son producers to be nominated for best picture at the Oscars.
In 1962, Zanuck became the youngest studio chief in history in1965 when he was appointed by his father as head of Fox at the age of 28. During his five years at the helm, the studio earned an impressive 159 Oscar nominations. Three of the films — The Sound of Music (1965), Patton (1970) and The French Connection (1971) — won best picture.
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.
