If there was any doubt, AI mania was on full display at Google Cloud Next in Las Vegas this week, but history shows us that when humans start getting manic about things, it doesn’t always work out great.
Lately, I’ve seen a few commentators bringing up the horrible story of the radium girls to try to make this point. Have you ever heard of them? They were factory workers of the 1920s hired to paint watch faces with newfangled luminous paint containing deadly radium.
The camel hair paintbrushes the workers used lost their shape after a few brush strokes so they were encouraged to reshape the brushes by licking the tips. Many of the workers also used the paint as lipstick or nail polish, because why not?
This did not go well for anybody involved. Many radium girls experienced dental issues, lost teeth, and suffered oral lesions and ulcers. Others developed anaemia and necrosis of the jaw. Some experienced disruption to their menstrual cycles or were even rendered sterile.
At least 50 women died prematurely as a result.
This wasn’t the only misuse of radium. In a short-lived mania for the radioactive metal – first discovered by Marie and Pierre Curie in 1898 – humans also put it in toothpaste, hair cream, and a medicinal tonic drink called Radithor. Doctors even used it to try to treat cancer.
AI is manifestly not a radioactive element but there are clear parallels between its widespread application and the reckless use of radium a century ago. And I believe there is a warning here for us, or a lesson if we care to hear it; we need to figure AI out before we do something really dumb.
Put your hands in the air, the use cases aren’t there
Just look at the application of AI to the ‘creation’ of art and music and other forms of self-expression. Here, take-up has become so pervasive that the well of human creativity, perhaps our most awesome trait, is rapidly being poisoned with utter slop.
As a case in point, ahead of the opening keynote at Google Cloud Next, 32,000 humans and a handful of AIs were treated to a Google Gemini-enhanced DJ set accompanied by AI-generated visuals created by the complex ‘art’ of waving your hands about in midair.
To be fair to the performers, the results were quite impressive and the audience was bopping along.
But it’s worth a sidenote that Italian DJ Robert Miles created his breakthrough 1995 track Children using nothing more than a Korg 01/W FD synthesiser, its 16’ Piano patch, and his own skill.
My point is that Children remains an iconic piece of genre-defining ‘90s dance music, but nobody in the Google audience will be able to hum today’s set in 30 years’ time.
Next, in a demonstration of the power of Google’s Gemini Agent Platform – officially unveiled at the show – Google Cloud’s Erica Chuong, manager for applied AI forward deployed engineering, designed a ground-up interior design campaign for a fictional furniture company that had found itself lumbered with dead stock that nobody wants.
Analysing current ‘modern organic’ interior design trends the agent designed a campaign for Chuong where relevant dead stock was repriced to undercut the competition and created a series of videos showing off its flair for interior design.
Unfortunately for the agent the result was a banal and unimaginative sofa and coffee table combo dominated by dull neutral tones and devoid of personality. It would have looked okay in a Travelodge lobby.
In a world where interior design trends are being dictated by consumers asking their AI assistants about the latest interior design trends while interior designers ask their AI agents what interior design trends consumers are into, you may be wondering how any new information about interior design trends gets into this loop. If you find out how, please let someone at Computer Weekly know.
But at this point, the AI cat is not only out of the bag, it’s on top of your living room shelves knocking over your good wine glasses. Three quarters of Google Cloud customers already leverage Google’s AI, says CEO Thomas Kurian. “You have moved beyond the pilot, the experimental phase is behind us and now the real challenge begins,” he told the audience.
Moving AI into production of course needs a unified stack and happily for Google Cloud, right on cue, here comes a Google-branded one. As Google iterates its tensor processing units (TPUs) at an ever-increasing pace, it also comes with a whole new chipset, TPU 8i to support inference and TPU 8t to run training.
Lest his existence be forgot during the love-in, Kurian’s boss, Google and Alphabet CEO Sundar Pichai, appeared on a big screen to tell everyone how glad he was that they were in Las Vegas even though he hadn’t made the trip himself, and revealed just how much money – almost two hundred billion dollars – Google will spend on capex investment in innovation this year, a good portion of it to the cloud unit and much of it supporting AI.
“We are more on the front foot than ever before,” remarked Pichai. “We are moving in a bold and responsible way.”
So if that’s true, where are the bold and responsible use cases? Do they even exist? Or are they just the usual conference waffle? I went looking.
Resident agents
Resident Evil developer Capcom says it is using Google Cloud to enhance its videogame development processes, not by taking over the creativity but by enabling creatives to be creative.
A big challenge for videogame developers is playtesting their products prior to release, and as their properties grow in scale – many now encompass vast digital worlds with unthinkable numbers of permutations – the strain on developers has ramped up, big time, leading to a phenomena known as defensive development.
Defensive development is a situation where the cost of making technical changes to an in-progress project gets so high that the human engineers feel pressurised to prioritise maintenance over innovation. In gaming this often occurs late in the production cycle, leading to problems with titles being released that seem, well, unfinished in some way.
It’s not an issue that’s unique to companies like Capcom, though. Take the manufacturing sector, where facility managers might see similar challenges when trying to simulate how a hardware update will work within their current procedures, or in retail, where logistics experts must navigate dynamic data reserves when trying to optimise supply chains without disrupting their current inventory systems.
Working with Google Cloud, Capcom has now launched an in-house agentic platform that not only relieves some of this burden but also serves as a blueprint for where AI might be used better in the creative sector, and others.
It describes its approach as a multimodal workbench, and at its core, it comprises a small group of distinct agents that optimise the playtesting process using vision and reasoning to understand the intent of a system.
The first of these, the visual inspection agent, uses Gemini Vision to look at the screen through near-human eyes, working out what is an intentional design choice and what is a technical failure.
The second, the predictive agent, pores over historical data to work out where a system might break next and directs a mini army of test bots to ‘swarm’ high-risk areas, rather than testing randomly.
The third, the institutional knowledge agent, enables new team members, human ones, to learn how their colleagues or predecessors worked similar problems before, preserving decades of expertise – three of them in the case of the Resident Evil franchise.
The fourth, the data inefficiency agent, spots inefficiencies within datasets to optimise overall game performance. Developers can query it to help summarise complex technical logs and make more advanced data more widely available to their teams.
Data inefficiency agents: These agents identify inefficiencies within massive datasets to optimize game performance. Developers can query their AI teammates to receive summaries of complex technical logs, making advanced development data accessible to all team members.
Collectively, Capcom’s agents are now running for 30,000 human hours every month and the firm’s developers say they now feel empowered to focus on higher value creative tasks, while Google Cloud, for its part, says that many of the tasks the agents are performing have applications in many other industries.
Citi Sky lines up
Elsewhere, Citi Wealth, the wealth management arm of Citibank parent Citigroup, unveiled an AI team member called Citi Sky, which it says will help reshape how its clients access market insights, act on potential opportunities, and work with their human financial advisors. Bilingual in English and Spanish, in time it will be integrated into Citi Wealth’s platforms – although in the US only for now.
Citi head of wealth, Andy Sieg, said that for decades, managing your financial life has meant navigating calls, meetings, and more recently apps. With the new agentic service, you simply ask and then act. It’s a shift from interface to intelligence and transactions to outcomes, he says, with a universal question at the centre: am I financially okay?
Citi Sky will answer this question in real time, marrying insight and execution simply and clearly – not replacing human advisors, but extending their reach and deepening their impact. In fact, Citi Wealth plans to hire advisors in the years ahead.
For Citi Wealth as a business, Sieg says the goal is to unlock massive scale and apply basically unlimited cognitive resources to its clients. “And the real need that we’ve met … is creating a relationship that can evoke the same kind of trust, we believe, that clients have with their human financial advisors,” he says.
Citi Wealth invoked Google’s full AI stack to build Sky, from Google Cloud infrastructure to Google DeepMind and, of course, Gemini models running on Gemini Enterprise Agent Platform. It worked closely with both teams to incorporate DeepMind’s real-time avatar technology and Gemini’s live application programming interface (API) to solve challenges around providing low-latency audio and video conversations.
A plea for rational thinking
I must acknowledge that Google Cloud’s customer stories are carefully curated by its communications teams – not every customer wants to talk, some will be forbidden from doing so, even more are still shivering on the edge of the pool with their inflatable armbands on, too scared to jump in.
And to be blunt, some customers will be at the deep end doing really stupid things with AI that will blow up in their faces.
But in the examples of Capcom and Citi Wealth – and others that would have pushed the word count unreasonably high – I think there is some hope.
With forethought – not even very much of it – and a rational head, we can turn AI loose on both the small challenges we face in our daily lives, and the grand challenges we face collectively.
But to do this we need to resist the advances of the snake oil salesmen, the charmers and grifters, and especially the tech bros who want to disrupt something that doesn’t need disrupting, like the habit of art, for the sake of making themselves richer.
And I fear we may be running out of time to do so.