Pacing the Frontier Between Our Ears

Much of the noise about AI is people shouting one true thing at people shouting another true thing. These times demand that we hold several truths in our heads at once. Those who learn to do so will build AI's future, and with it, better futures for all of us. I want to share my thoughts stemming from being in and around AI since I was a teenager.

AI in the right hands is already delivering extraordinary improvements. I was recently shocked by a piece of software I built. Years ago I led the development of a software platform that large enterprises rely on. It carried extreme reliability requirements. Building it took a large team several years of hard work. This time, with a frontier coding model, I rebuilt a rough, simplified version of it in a day. When I think about it, I still cannot believe it. AlphaFold predicted the structure of 200 million proteins, work that would have taken hundreds of millions of years at the bench, and earned Demis and colleagues a Nobel Prize. Don Knuth learned that a colleague used a model to find a beautiful solution to a problem he had identified years ago, and publicly softened his doubts about AI. OpenAI announced a team’s breakthrough with the Navier Stokes equations, a seminal mathematical challenge that was open for a century+. Successes like this and more are popping up across all walks of life.

AI in the wrong hands can do catastrophic damage. In 2017, long before ChatGPT, hackers leaked EternalBlue, a cyberweapon stolen from the US National Security Agency. Within weeks it powered the WannaCry and NotPetya attacks, crippling hospitals, ports and factories worldwide and causing billions in damage. Soon ordinary criminals were using it. Today's AI models encode much of humanity's knowledge, and social media carries their output to billions of people worldwide. Deepfakes, automated fraud and knowledge repurposed for harm can now spread further and faster than ever.

AI by itself does nothing. As Alan Kay says, "the music is not in the piano." In July, AI agents from OpenAI broke out of their sandbox and into Hugging Face's servers and more. What happened was no mystery, and certainly no miracle. It was large model(s) trained on details of exactly such attacks, and a piece of code running over it, let loose onto the world without adequate safeguards. These systems amplify whatever we bring to them: our ingenuity, and equally our negligence. We failed to contain EternalBlue. If we don’t learn from Hugging Face, we will have failed again. To make matters worse, the doomsday talk and the sales talk often come from the same people, because describing AI as godlike raises fear and valuations together.

AI is deeply disruptive to India's $300-billion IT services industry, which was built on the coding, testing and support work AI now automates. Yet every enterprise on earth needs help to use AI well: to understand its own business, to transform decades old systems, and take responsibility when things go wrong. That is a massive opportunity for the industry.

AI urgently needs regulatory oversight. Our modern world runs because of commonsense safeguards and regulations, from our barbers operating scissors on our heads to our buildings and bridges, automobiles and airplanes, what we eat and what we entertain ourselves with, our medicines and our machines, all built with guardrails often put together by organizations of peers.

And yes, AI needs a lot more innovation, fast. AI development has a long way to go. From overcoming hallucinations, which are at the heart of how current LLMs work (as my son Varin and I showed recently), and improving AI’s ability to understand the physical world around us, to significantly improving AI’s power and computing footprint. We are still in the early innings of AI development.

So our times increasingly are times to understand things more deeply, and to apply our own minds. Humanity has achieved billion-fold improvements before: in my lifetime, computing has become more than a billion times cheaper. Building bridges, skyscrapers, agriculture and more are unimaginably more productive than just a century ago. We can grow our understanding of AI with the same ambition.

AI today has a dangerous concentration of power. A handful of companies control the AI frontier, with barely a few thousand experts building frontier models. With all the talk about pacing the AI frontier, I believe the real frontier is teaching millions how to build this piano and billions how to make music with it.

In the time ahead, perhaps in my lifetime, likely in my children’s lifetime, we will see AI systems that can build and do anything we ask. John McCarthy, another great teacher of my life, saw this decades ago. In one of the defining moments of my life, he said that at a time when we can ask a machine to build us anything, what we ask it to build becomes the frontier. A billion curious minds, fully conversant in what AI is and how it works, making magic with it, magic that may be incomprehensible to us, is what the real frontier is. Yes we must accelerate the frontier, the one between our ears.

- Vishal Sikka