Latest news with #Pythia
Forbes
a day ago
- Entertainment
- Forbes
Charles Sandison Illuminates The Oracle With AI
Charles Sandison, The Garden of Pythia, 2025, PCAI artwork commission in Delphi, Greece Photo Maria Toultsa. Courtesy of PCAI Finland-based British artist Charles Sandison doesn't just work with light and language – he composes with code. Long before digital art became fashionable, he was programming a Sinclair ZX81 computer in the remote north of Scotland in the early '80s, teaching himself to code at age 12, while drawing and painting as his primary way of expressing himself. At a time when computers were alien to most households and new media was scarcely taught in art schools, Sandison forged his own hybrid language of software and symbolism. His breakthrough came in 2001 at the Venice Biennale, and since then, his computer-generated video projections have illuminated the Catacombs of Paris, the facade of the Oslo Opera House and museums across the world. Sandison's latest – and perhaps most profound – work, 'The Garden of Pythia', is nestled on the ancient slopes of Delphi, Greece, at Pi, Global Center for Circular Economy and Culture. Commissioned by the Polygreen Culture & Art Initiative (PCAI), an organization merging culture and ecology founded by Greek entrepreneur Athanasios Polychronopoulos, the installation draws a poetic parallel between today's artificial intelligence and the 8th-century B.C. Oracle of Delphi known as Pythia. Powered by AI-driven code and projected onto the hillside, the work pulses with ancient texts, fragments of Delphic statues, digital symbols and environmental data. For Sandison, it marks his deepest engagement yet with AI, blending myth, code and memory into a living landscape. Kika Kyriakakou, PCAI Artistic Director, says, 'Sandison's new work echoes in the most refined manner PCAI's environmental mission and our dedication to contemporary art. We are pleased to have commissioned this immersive, real-time computer-generated installation that exemplifies Sandison's sculptural approach towards moving image and information technology, along with his deep concern for nature protection, human and non-human communication and cultural heritage.' Sandison speaks about growing up in the Scottish Highlands, coding as a creative language and his latest project, 'The Garden of Pythia'. Installation view of PCAI's newly commissioned work The Garden of Pythia by Charles Sandison, at Pi, Global Center for Circular Economy and Culture in Delphi, Greece Photo Maria Toultsa. Courtesy of PCAI You originally planned to move to Berlin. How did you end up in Finland instead? I studied at the Glasgow School of Art in the late '80s and early '90s, and even taught there briefly. In 1995, I was planning to move to Berlin to set up a studio. I felt I'd been in Glasgow long enough and wanted to see what life in Berlin might offer. On the way, I had a short detour for an exhibition in Finland – just two weeks, I thought. That was 30 years ago. I'm still there. I guess I'm someone drawn to northern places. Wherever you find a 'north', give a shout – Charles will probably be up a mountain somewhere, messing about with projectors and code. That's my thing. What was your early relationship with technology like? I grew up in a remote part of northern Scotland. My parents were a bit hippie-ish and believed isolation was good for the soul. If it doesn't drive you mad, you find ways to occupy yourself. In the early '80s, home microcomputers – 8-bit machines – started appearing. My best friend from age 12 until I left for art school was a little Sinclair ZX81. I taught myself to code. At the same time, I was always drawing and painting. Those were my first ways of speaking to the world. How did you connect art and code as one language? It was around that time a light bulb went off in my head: painting, drawing and writing computer code – they're the same thing to me. That realization shaped my artistic practice for years. What made you shift from museum installations to more site-specific, outdoor work? My early installations were mostly in 'white cube' galleries. But after years of traveling and installing work in the same kind of museum spaces, I realized I wasn't that interested in those interiors. I began making peripheral works – sketches of a kind, using light and code – in sites around the world. In Rome, for example, while installing work at the MAXXI Museum, I asked to access the Farnese Gardens by night so I could experiment with projections. If you work with digital art, you can't just pull out a sketchbook. You have to invent new ways to sketch using light and code. I've done that in the Catacombs of Paris, on the mountainside outside Seoul, and very quickly, those peripheral works became more interesting to me than the museum shows. Charles Sandison, Opera of the Sea, 2019, Oslo Opera House, 6 projectors, 6 computers, C++ code, variable dimensions Photo courtesy of the artist, Kulturbyrået Mesén, Finsk-norsk kulturinstitutt, Den Norske Opera & Ballett How did 'The Garden of Pythia' come about? The project really began in 2020 with a show at Bernier/Eliades in Athens – right in a small window between lockdowns. One of the very few people who saw it was Athanasios Polychronopoulos. He came up to me and said, 'I've got a place I think you'd be interested in.' And that was the beginning. We kept talking over the years, ping-ponging ideas, until we finally got to the business of installing the work here. Being in Delphi feels natural to me. It reminds me of the small, remote communities I grew up in – places where the past and present collide, where survival is pragmatic, but history lives in the landscape. What was it like working on-site at Delphi? I can only work at night. My installations don't come alive until the sun goes down. So over the last few visits, I've spent my nights up on the hillside, just me, computers, code and light. My wife said it looked like Frankenstein's mountain lab – sparks flashing in the dark. But it's in those moments, alone in the landscape, that everything connects. That's when the work really happens. You've spoken about using AI in your work. How do you see your role as an artist engaging with such advanced technologies? I'm not evangelistic about AI. I don't think every artist needs to use it. But I happen to have been born at a time with a certain skill set that lets me dive deep into the mechanics of AI and computer code. If you have that ability as an artist, I think it's important to engage with it, understand it and even shape it. I've visited places like Google Labs in London and spoken with engineers – people building this landscape. Most of the public doesn't really know what AI is or how it works. I feel like my role isn't to explain it technically, but to act as an intermediary. I'm not giving an education – I'm offering an experience. For me, it's like a transfer of experience, similar to how a painting silently communicates in a museum. That's what I try to do with AI in my work. And really, the model of AI is much older than we think. It began in places like the Temple of Apollo with the Oracle of Delphi. Pilgrims would come from all over the known world, bringing questions: Should we marry? Go to war? They'd climb the hill, present their offerings and receive a cryptic answer from behind a screen. That was a kind of machine intelligence too – a biomythic one, but artificial nonetheless. It's fascinating how that structure echoes in the way we interact with AI today.
Hindustan Times
16-05-2025
- Science
- Hindustan Times
Spin cycle: Inside the world of trendspotting and fashion forecasting
'It's tough to make predictions, especially about the future.' That's a quote attributed to Yogi Berra, the American baseball catcher, manager and coach. Others, including physicist Niels Bohr and filmmaker Samuel Goldwyn, have made similar observations. Predicting future trends has long been an obsession with humans. One of the earliest future-trend predictors was the priestess Pythia at Delphi, in Ancient Greece. She was revered for her prescience on war and other matters of state. Pythia actually lives on, in modern boardrooms, as the much-revered Delphi Technique, in which a team is made to predict future outcomes, individually, and through repeated rounds arrive at a 'most probable' future prediction. Jump forward about 2,000 years and there was the Nostradamus (Michel de Nostredame), the 16th-century French astrologer, perhaps the most famous historical figure associated with future predictions. In India, meanwhile, one of the seven Vedic sages, Bhrigu, is seen as the father of Indian astrology (or future predictions). Predicting the future used to be about the security of a kingdom or a throne: What plagues or enemy action might be coming? Was a drought, or some form of pestilence, imminent? These were the things the people in power were most eager to prepare for. Today, in addition to governments, businesses need to be better prepared to face the future. This is part of what drove sales of futurist Alvin Toffler's 1970 bestseller Future Shock, which has sold over 6 million copies around the world. The book traces the impact of rapid social and technological change on individuals and society. It highlights the psychological distress and disorientation caused by too much change in a short period. Toffler coined the term 'future shock', and defined it as a state of anxiety and disorientation resulting from an accelerating rate of change. And he was writing more than two decades before the first glimmers of the internet appeared. The way technology has continued to change our lives would make Toffler a modern-day Nostradamus indeed. While he dealt with what the future had in store, in broad terms, John Naisbitt, through his 1982 book Megatrends: Ten New Directions Transforming Our Lives, made trendspotting a public obsession. Naisbitt identified 10 major trends that he believed would reshape society, business and culture, as the world transitioned from the industrial era to the information age. Some of these — a shift from an industrial society to an information society; forced technology to high-tech / high-touch; national economies to a world economy; hierarchies to networking — hold true, more than 40 years on. We'd gone from predicting the future to predicting trends. We were starting to let technology guide the way. It was game on for trendspotting. *** Part of the credit for this goes to Faith Popcorn, author of the 1992 bestseller Popcorn Report: Revolutionary Trend Predictions for Marketing in the 1990s. She used consumer analysis and cultural-trend analysis to predict long-lasting societal shifts, clearly distinguishing them from fleeting fads. Some of the trends she spotted were cocooning (retreating into home for safety and comfort), cashing out (leaving high-pressure jobs for simpler, more meaningful lives), clanning (seeking out a community of like-minded individuals), and small indulgences (splurging on select premium products). Many of these have remained relevant, through downturns and tech bubbles bursting, through boom times and a pandemic. Today, most market researchers, consultancies and marketing agencies have dedicated trendspotting teams. Seeing into the future remains the holy grail, except now what most people really want to know is: What could the next bestseller be? Exercises in this direction are more or less what annual trend reports are about. It's still very much a game of chance and circumstance. So many annual reports are irrelevant even before the proverbial ink has dried. The better future predictors are able to look beyond the obvious and examine adjacencies. *** I remember analysing the future of the Indian engine-oil market, in the late 1990s. The large brand we were working with was focussed on the commercial-vehicles segment. This brand was the leading provider of engine oil to truck operators. Business was growing, in the wake of liberalisation. But there were several storm clouds visible. For one thing, engine and engine-oil technology was changing, increasing the gap between required oil changes from one month to sometimes several. This was a variable visible to the company. In our conversations, they often spoke of how they hoped to counter it. Then our research team sat down to do a little research of our own, and that's when we realised no one was looking at the data on trains. The growth of the Indian Railways was about to cut into the transit of goods by road. Even a rise of a few percentage points in the share of goods transported by rail would change the math entirely for trucks, and for our client, who was hoping to sell them tonnes of engine oil. We presented our data to the client, who had not considered goods trains part of their competition until then. It was an interesting reversal of the case study in Theodore Levitt's seminal Harvard Business Review article, Marketing Myopia. There, he pointed out how American railroad companies saw businesses decline — not because fewer goods or people needed to be moved from place to place; those numbers grew. They lost business because they remained confined to their pre-existing ideas of where a railroad should go, who it should serve, and how. The roads became the primary mode of transportation because they evolved to go anywhere the consumer needed them to go. *** If a product as fundamental as engine oil, in a segment not exactly bustling with competitors, can be affected by future trends, it's easy to see why prediction is such a core piece of the puzzle, in industries defined by flux: such as fashion (and personal technology, for that matter). Predicting the future of fashion — and being able to shape what people will choose — is, in many ways, the only way this industry has ever been a sustainable one. Because each of us may, of course, wear whatever we please. We may make our own clothes, barter and swap (as indeed we should, at this point in our carbon-emissions struggles). Fashion isn't like food or pharmaceuticals, education or indeed most consumer goods (cars, toys, furniture, engine oil). In all these cases, it is relatively easy to herd the consumer. Offer them a range of colours, styles and price bands, and they will feel sufficiently pandered to. Fashion is different. What we wear must reflect who we are; and each of us prefers to think we are unique. Who is to say what we will piece together, or how long a given preference will hold? Trend-forecasting, in fashion, is not for the faint-hearted. Which is why the effort is an aggressively ongoing one. It starts with colours (of the season, the year, the moment). Colour-trend 'forecasting' can be traced to at least the 1800s, and the creation of swatch books for use by French textile mills. With the development of synthetic dyes in the mid-19th century, the need for such forecasting grew, as the range of available colours boomed. Now, as you are likely thinking to yourself, who buys anything in a shade of peach fuzz (the 2024 colour) or mocha mousse (the colour for this year)? I asked this question of a leading menswear brand that makes most of its revenue from formal shirts in plain blue or plain white. Why bother with the colour of the year, every year, I asked? Clients want to see a colourful new collection; it reassures them that their brand is in step with the times, I was told. In other words, in order to sell blue, or white, sometimes you have to make a little peach fuzz. *** How much of it is really prediction? Well, it's not just someone throwing darts at a shade card. Market researchers talk to consumers, by the thousands. They talk to domain experts, opinion leaders and influencers. They use ethnographic studies and observational studies. They hit the roads to see what's popular within different segments of a market, and why. Modern trend predictors use a plethora of digital tools. They scrape images from social media and analyse them at scale using AI programs. What do pictures shared on certain kinds of social-media handles have in common? What's the demographic? The geography? Global companies like WGSN, Mintel and Heuritech have built an impressive track record of spotting trends by using a mix of qualitative research (cultural observation, expert interviews, scenario planning) and quantitative analysis (data mining, social listening, consumer analytics) to detect both strong and weak signals of change. Time series analysis is used to spot if a trend is growing, how fast will it grow, when will it peak. AI algorithms help through it all. Read the story alongside for more on how this works (and the corresponding dangers of it). How often do they get it right? Let me end with a little story. When Segway PT, the self-balancing transportation device, was launched in December 2001, it was hailed as a revolution in personal transportation. Steve Jobs, who we know saw the future better than most mortals, wanted to invest in Segway, and offered them $60 million. Dean Kamen, the inventor, turned him down. Kamen didn't want to relinquish that much control. Then, Segway slowly tottered, it was blamed for being too highly priced, too heavy, for having 'unclear practical utility'. It faced regulatory challenges too. Learning from the mistakes made, the company's new owner, the Chinese firm Ninebot, pivoted. The original Segway PT sold an estimated 100,000 units between 2002 and 2018. Its successor the Segway-Ninebot eKickScooter, more stable, more solid and easier to maneouvre, shipped one million units in its launch year, 2018, alone. Often, spotting a trend is just the start. A lot depends on what we do next: how well we listen as new cues pour in; how agilely we pivot to what a customer will actually buy. It's true of almost any sphere of life. Seeing into the future is just half the spell. The other half is scrambling fast enough to meet it, and being agile enough to correct course midway. (Ambi Parameswaran is an independent brand coach and author of 11 best-selling books on branding, advertising and consumer behaviour)
