Latest news with #TheImitationGame
Metro
3 days ago
- Entertainment
- Metro
Period drama hailed the 'best movie of the last 20 years' arrives on Prime Video
To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video A stirring World War II period drama has officially landed on Prime Video – and viewers are already flocking to revisit its emotional depth and historical impact. The Imitation Game (2014), starring Benedict Cumberbatch in one of his most acclaimed performances, is now streaming for subscribers. Based on the extraordinary true story of Alan Turing – the mathematician and cryptanalyst who helped crack Nazi Germany's Enigma code – the film blends historical gravitas with emotional intensity, making it a must-watch for fans of prestige cinema. Directed by Morten Tyldum and written by Graham Moore (who won the Oscar for Best Adapted Screenplay), the film also stars Keira Knightley, Matthew Goode, Rory Kinnear and Mark Strong. Upon release, The Imitation Game was nominated for eight Academy Awards, including Best Picture and Best Actor for Cumberbatch, and took home the Oscar for its script. Cumberbatch delivers a quietly devastating performance as Turing, a brilliant, socially awkward man whose groundbreaking contributions to modern computing were overshadowed by the tragic consequences of being prosecuted for homosexuality in 1950s Britain. The film balances the high-stakes drama of wartime codebreaking with intimate portrayals of isolation, injustice, and genius misunderstood. Viewers on social media continue to hail the film as a masterpiece, with one recent Letterboxd reviewer writing: 'WOW. Not sure why it's taken me 11 years to watch this film but an incredible story about an incredible man.' Another wrote: 'This movie is honestly one of my favorites. The soundtrack is beautiful, the cast is great, and the story is a devastating yet necessary one to tell.' Many viewers have noted the emotional impact of the film, with one posting: 'There are few movies I have sobbed this violently at…god it wrecked me.' One Reddit user said: 'Phenomenal. I don't hear it mentioned enough. I think it's the best movie of the last 20 years.' More Trending With a Rotten Tomatoes score of 90%, it isn't only beloved by viewers but also by critics. The film's arrival on Prime Video has reignited interest in both the real-life legacy of Turing – who received a posthumous royal pardon in 2013 – and the film's gripping portrayal of unsung heroism. Alongside its dramatic tension, The Imitation Game offers a thoughtful meditation on identity, secrecy and sacrifice, earning it a special place among the most powerful biopics of the last decade. Whether you're watching for the first time or returning for a rewatch, it's a poignant reminder of how one man's intellect and perseverance helped shorten the war – and changed the course of history. Got a story? If you've got a celebrity story, video or pictures get in touch with the entertainment team by emailing us celebtips@ calling 020 3615 2145 or by visiting our Submit Stuff page – we'd love to hear from you. MORE: All Neighbours spoilers for next week as fan-favourite leaves amid affair drama MORE: Every episode of 'masterpiece' TV series now streaming on Amazon Prime MORE: Jeremy Clarkson reveals extent of 'enormous disruption' caused at farm by TB outbreak
Chicago Tribune
18-07-2025
- Entertainment
- Chicago Tribune
What if you could see inside machines? ‘Art of X-rays' opens at the Griffin MSI
The Griffin Museum of Science and Industry recently unveiled a new interactive 'Beyond the Surface: The Art of X-rays' exhibit by photographer Andrei Duman, allowing museum guests to examine the interior of everyday objects. The exhibit takes up four rooms in the Kenneth C. Griffin Studio. Entering the studio, guests walk past an introduction of Duman and the show, then are introduced to the history of X-rays. Multiple posters give a more detailed description of Duman's process while creating the exhibit. Other rooms display Duman's photographs from his six-year project, as well as X-rays of artifacts from the museum. Images show X-rays of common everyday items like toys, a coffee maker, alarm clocks and more. Voula Saridakis, head curator of collections and archives at the museum, said Duman's work balances art and science. '(He's a) photographer who's walking into science,' she said. Historical artifacts include an Enigma coding machine from the museum's U-505 submarine. Saridakis referenced the movie 'The Imitation Game' as a way to better understand the history of the device. She said the X-ray showed the complexities of the Enigma machine from the inside. Creating that image in particular was challenging, Duman said. Due to how much metal there was in the machine, he wasn't able to capture the X-ray in one shot. Instead, he took around 10 photos with different exposures. He then 'flattened' the images together in post-production and chose bits from each photo to make one composite picture. Other historical artifacts from the museum were light bulbs from a Thomas Edison patent trial. A clear glass case contains two lightbulbs from Edison's patent infringement trial. Saridakis said Edison frosted the bulbs so no one could see what the filaments looked like inside. While in court, he was forced to break open one of the bulbs, leaving one of them cracked. When Duman X-rayed the other bulb, he noticed that one was cracked as well, which was news to museum officials. Another artifact is a camera box from the 1933 Century of Progress World's Fair. 'You kind of marvel at that level of detail,' Saridakis said while looking at the X-ray. A final room displays six scaled models of Bugatti automobiles. Duman teamed up with Amalgam, a scale model car company, to create 1:8 scale models of different vehicles. Bugatti was chosen 'because of the prestige of the brand, obviously the legacy that they have, and also just a variety of the models,' Duman said. Whenever one of the cars is displayed on the floor, it's also displayed on the wall. Using tracking technology, when guests walk across the car projection on the floor, the X-ray display moves with them. Molly Powers, 42, said she and her children enjoyed the museum during their visit from Dubuque, Iowa. Reed, 10, said his favorite part of the museum was the fourth room because of how the cars moved when he did. 'It was really cool getting to see all things inside and knowing what's inside,' said Reed. Cate, 8, said she chased the cars when she saw the X-rays move. Dan Powers, 43, said some parts of the exhibit gave him motion sickness. Duman said he's worked on the project for years. 'The whole project was really driven by that concept of 'What happens if I X-rayed this?'' Duman said his interest in X-rays came from his infatuation with design. 'There's so much amazing stuff in there that they crammed into that space, I found it fascinating to expose that,' he said. He said he photographed a lot of artifacts from the museum, but only chose the ones that looked the most interesting to show in the exhibit. His form of X-raying is different from more typical forms of X-raying, he said 'There were many times when I thought 'Oh, this is going to be really great,' and you put it on an X-ray and it's just not, there's nothing really that interesting,' he said. 'And vice versa too, there's something that I left at the very last minute I'm like 'Ugh, this is probably going to look like crap,' and actually it turned out to be actually really interesting stuff in there,' Duman said.
Daily Record
25-06-2025
- Entertainment
- Daily Record
Netflix fans 'in tears' over 'haunting' war film about unsung heroes
The movie tells the real-life story of Alan Turing, who played a pivotal role in cracking the German Enigma code during World War II An A-list ensemble has come together to recreate the momentous tale of the Enigma code's decryption, hailed as a 'masterpiece' by enthusiasts and set against the backdrop of the Second World War. The Imitation Game, inspired by the true story of the esteemed mathematician Alan Turing, features Benedict Cumberbatch in the lead role as the computer scientist whose contributions were crucial to the war effort. Drawing from the accounts in his biography, the film portrays Alan Turing's success in cracking the codes used by German intelligence, significantly aiding the British government's wartime triumphs. Upon its release in 2014, The Imitation Game enjoyed a box office surge, amassing over $233 million globally, making it the most successful independent film of the year. Its critical acclaim was reflected in numerous nominations across prestigious award ceremonies. A Rotten Tomatoes critique reads: "I really enjoyed this movie. "What could have been a tedious subject - codebreaking - was dramatic and suspenseful. All of the actors were terrific, and you really care about them, especially Benedict Cumberbatch's character. "You admire his brilliance but sympathise with his difficulties relating to people. And the relationship between him and Keira Knightley is poignant. "I really think this is an excellent film." The film's enigmatic allure is further amplified by Kiera Knightley, who portrays Alan Turing's close friend and brief fiancée, Joan Clarke. Audiences have praised the "superb acting" for truly "bring it to life", and it's these stellar performances that earned both actors nominations for best actor and best supporting actress at the Academy Awards and Golden Globes that year, reports the Express. When Britain declared war on Germany in 1939, the brilliant Alan Turing joined the cryptography team to decipher the Enigma machine, which the Nazis were utilising for coded communications. The film captures the tense moment when Alan uncovers an imminent attack on a convoy, but any hasty reaction could expose their operation and alert the Germans to their decoded messages. Consequently, the computer scientist is faced with a tough choice to minimise the risk of detection. Above all, it's these authentic narratives of unsung wartime heroes that deeply resonate with viewers. One viewer commented: "The Imitation Game is a masterpiece that left me in tears. Alan Turing's brilliance and sacrifice are beautifully portrayed, reminding us of the unsung heroes who change history. It's a powerful story of genius and courage, and the actors did a fantastic job." Another review described the film as "haunting". They added: "A brilliant performance by Cumberbatch to honour a brilliant mathematician. "The film is so encapsulating that by the time the screen darkens, you will want to reach through it and hug Turing tight and tell him his work is worthy of the highest appreciation." For those in search of a poignant cinematic journey or eager to delve into the intellect that contributed to the defeat of the Nazis, 'The Imitation Game' on Netflix is not to be missed.
Yahoo
05-06-2025
- Business
- Yahoo
FTX Limited Series a Go at Netflix With Julia Garner, Anthony Boyle Starring
Netflix has greenlit a series about the rise and fall of cryptocurrency exchange FTX and the two central figures involved — Sam Bankman-Fried and Caroline Ellison. The streamer has formally ordered The Altruists, which will chronicle how Bankman-Fried and Ellison 'two hyper-smart, ambitious young idealists tried to remake the global financial system in the blink of an eye — and then seduced, coaxed, and teased each other into stealing $8 billion.' Julia Garner, who had been in talks to star in the drama, and Anthony Boyle will play Ellison and Bankman-Fried, respectively. More from The Hollywood Reporter 'The Thursday Murder Club' Is on the Case in Teaser for Chris Columbus Netflix Movie John Mulaney's Fight With Three 14-Year-Olds Was a Bit of a Letdown - Because It Had to Be Netflix, BBC Studios Team on Comedy Podcast 'The Big Pitch With Jimmy Carr' Graham Moore (The Imitation Game, The Outfit) and Jacqueline Hoyt (The Leftovers, The Underground Railroad) will serve as co-showrunners on the series. James Ponsoldt (Shrinking) is set to direct. The Altruists comes from Barack and Michelle Obama's Higher Ground Productions, which has an overall deal at Netflix. 'For nearly three years now, Sam and Caroline's story has been my daily obsession,' said Moore. 'I'm so grateful to my friends at Netflix and Higher Ground for loving this story not only as much as I do, but in the same way that I do. And we can't wait to show all of you why.' FTX went under in late 2022 after a run on customer withdrawals at the crypto exchange brought to light an $8 billion imbalance in its books. Bankman-Fried was convicted in November 2023 on seven charges of fraud and conspiracy; Ellison, who was co-CEO of a related hedge fund, Alameda Research — and Bankman-Fried's former girlfriend — testified against him after pleading guilty to other charges. The Altruists brings Garner back to Netflix, where she won three Emmys for her role on Ozark and also was nominated for Inventing Anna. She'll next be seen in The Fantastic Four: First Steps, where she plays the Silver Surfer, when the Marvel movie hits theaters in July. Boyle's credits include FX's Say Nothing and Apple's Masters of the Air and Manhunt. Moore, Hoyt and Ponsoldt will executive produce the series with Vinnie Malhotra and Jessie Dicovitsky for Higher Ground, Scoop Wasserstein for New York Magazine/Vox Media Studios, Tonia Davis, Lauren Morelli and Garner. The Altruists is one of several TV and film projects delving into Bankman-Fried and FTX. Lena Dunham is writing a feature film for Apple and A24, and Amazon's Prime Video ordered a limited series from Joe and Anthony Russo's AGBO and writer David Weil shortly after FTX imploded. On the nonfiction side, Mark Wahlberg's Unrealistic Ideas and Fortune magazine are teaming on a documentary, and Bloomberg has also produced a doc about the company's collapse. Best of The Hollywood Reporter 'The Studio': 30 Famous Faces Who Play (a Version of) Themselves in the Hollywood-Based Series 22 of the Most Shocking Character Deaths in Television History A 'Star Wars' Timeline: All the Movies and TV Shows in the Franchise
Campaign ME
26-05-2025
- Campaign ME
The illusion of control: How prompting Gen AI reroutes you to 'average'
After speaking on a recent AI panel and hearing the same questions come up again and again, I realised something simple but important: most people don't actually understand the difference between artificial intelligence and the kind of AI we interact with every day. The tools we use, ChatGPT, image generators, and writing assistants, aren't just 'AI'. They're generative AI (GenAI), a very specific category of machine learning built to generate content by predicting what comes next. As someone who moves between research and creative work, I don't see GenAI as a magic tool. I see it more like a navigation system. Every time we prompt it, we're giving it directions, but not on an open map. We're working with routes that have already been traveled, mapped, and optimised by everyone who came before us. The more people follow those routes, the more paved and permanent they become. So while it may feel like you're exploring something new, most of the time you're being rerouted through the most popular path. Unless you understand how the model was trained, how it predicts, and what its limitations are, you'll keep circling familiar ground. That's why I believe we need to stop treating Gen AI like cruise control and start learning how it actually works. If your prompts have ever felt like they're taking you in loops, you're not imagining it, you're just following a road that was already laid. Let's look at where it came from, how GenAI works, and what it means when most of our roads lead to the same place. History: From logic machines to language models The term artificial intelligence was coined in 1956 at the Dartmouth Summer Research Project. Early AI systems focused on symbolic reasoning and logical problem-solving but were constrained by limited computing power. Think of the cryptography machine in Morten Tyldum's 2014 movie, The Imitation Game. These limitations contributed to the first AI winter in the 1970s, when interest and funding declined sharply. By the early 2000s, advances in computing power, algorithm development, and data availability ushered in the big data era. AI transitioned from theoretical models to practical applications, automating structured data tasks such as recommendation engines like Amazon's e-commerce and that of Netflix, early social media ranking algorithms, and predictive text tools like Google's autocomplete. A transformative milestone came in 2017 when Google researchers introduced the Transformer architecture in the seminal paper Attention Is All You Need. This innovation led to the development of large language models (LLMs) and foundational structures of today's generative AI systems. Functionality: How Gen AI thinks in averages Everything begins with the training data: massive amounts of text, cleaned, filtered, and then broken down into small parts called tokens. A token might be a whole word, a piece of a word, or even punctuation. Each token is assigned a numerical ID, which means the model doesn't actually read language, it processes streams of numbers that stand in for language. Once tokenised, the model learns by predicting the next token in a sequence, over and over, across billions of examples. But not all data is treated equally. Higher-quality sources, like curated books or peer-reviewed articles, are weighted more heavily than casual internet text. This influences how often certain token patterns are reinforced. So, if a phrase shows up repeatedly in high-quality contexts, the model is more likely to internalise that phrasing as a reliable pattern. Basically, it learns what an 'average' response looks like, not the mathematical average, but by converging on the most statistically stable continuation. This averaging process isn't limited to training. It shows up again when you use the model. Every prompt you enter is converted into tokens, passed through layers of the model where each token is compared with every other using what's called self-attention, a kind of real-time weighted averaging of context. These weightings are not revealed to the user prompting. The model then outputs the token it deems most probable, based on all the patterns it has seen. This makes the system lean heavily toward the median, the safe middle of the distribution. It's why answers often feel polished but cautious, they're optimised to avoid being wrong by aiming for what is most likely to be right. You can change the 'averaging' with a setting called temperature, which controls how sharply the model focuses on the median results. At low temperature, the model stays close to the statistical center: safe, predictable, and a bit dull. As you raise the temperature, the model starts scattering probabilities away from the median, allowing less common, more surprising tokens to slip in. But with that variation comes volatility. When the model output moves away from the centre of the distribution, you get randomness, not necessarily creativity. So whether in training or in real-time generation, Gen AI is built to replicate the middle. Its intelligence, if we can call it that, lies in its ability to distill billions of possibilities into one standardised output. And while that's incredibly powerful, it also reveals the system's fundamental limit: it doesn't invent meaning, it averages it. Gen AI prompting: Steering the system without seeing the road Prompting isn't just about asking a question, it's about narrowing in on the exact statistical terrain the model has mapped during training. When we write a prompt, we are navigating through token space, triggering patterns the model has seen before, and pulling from averages baked into the system. The more specific the prompt, the tighter the clustering around certain tokens and their learned probabilities. But we often forget that the user interface is smoothing over layers of complexity. We don't see the weighted influences of our word choices or the invisible temperature settings shaping the randomness of the response. These models are built to serve a general audience, another kind of average, and that makes it even harder to steer them with precision. So while it may feel like prompting is open-ended, it's really about negotiating with invisible distributions and system defaults that are doing a lot more deciding than we think. Prompt frameworks like PICO (persona, instructions, context, output) or RTF (role, task, format) can help shape structure, but it's worth remembering, they, too, are built around assumptions of what works most of the time for most people. That's still an average. Sometimes you'll get lucky and the model's output will land above your own knowledge, it will sound brilliant, insightful, maybe even novel. But the moment you hand it to someone deep in the subject, it becomes obvious: it sounds like AI. That's the trick, understanding the average you're triggering and knowing whether it serves your purpose. Who will read this? What will they expect? What level of depth or originality do they need? That's what should shape your prompt. Whether you use a structured framework, or just write freely, what matters is clarity about the target and awareness of the terrain you're pulling from. And sometimes, the best move is tactical: close the chat, open a fresh window. The weight of previous tokens, cached paths, and context history might be skewing everything. It's not your fault. The averages just got noisy. Start again, recalibrate, and aim for a better median. Conclusion: When the average becomes the interface One of the things that worries me is how the companies behind GenAI are learning to optimise for the average. The more people use these tools with prompt engineering templates and frameworks, the more the system starts shaping itself around those patterns. These models are trained to adapt, and what they're adapting to is us, our habits, our shortcuts, our structured formats. So what happens when the interface itself starts reinforcing those same averages? It becomes harder to reach anything outside the probable, the expected, the familiar. The weird, the original, the statistically unlikely, those start to fade into the background. This becomes even more complicated when we look at agentic AI, the kind that seems to make decisions or deliver strong outputs on its own. It can be very convincing. But here's the issue: it's still built on averages. We risk handing over not just the task of writing or researching, but the act of thinking itself. And when the machine is tuned to reflect what's most common, we're not just outsourcing intelligence, we're outsourcing our sense of nuance, our ability to hold an opinion that doesn't sit neatly in the middle. So the next time an AI gives you something that feels weirdly brilliant or frustratingly obvious, stop and consider what's really happening. It's not inventive. It's navigating, pulling from the most common, most accepted, most repeated paths it's seen before. Your prompt triggered that route, and that route reflects the prompts of thousands of others like you. Once you understand that, you can start steering more intentionally. You can recognise when your directions are being rerouted through popular lanes and when it's time to get off the highway. And sometimes, when the output is so average it feels broken, the smartest move is simple: close the window, reset the route, and start over. Because every now and then, the only way to find something new is to stop following the crowd. By Hiba Hassan, Head of the Design and Visual Communications Department, SAE Dubai
