Searching the Web is, according to Microsoft’s chief executive Satya Nadella, “the most profitable category on planet Earth”. For decades, one company has reaped the benefits: Google.
The head-spinning explosion in recent months of new artificial intelligence (AI) tools such as ChatGPT, however, has blown open the market. And Nadella reckons he can finally give the Google leviathan a run for its money. Last week, he unveiled a new version of Microsoft’s long-mocked Bing search engine paired with ChatGPT, the conversational chatbot that can answer questions directly rather than producing a list of links. “It’s a new day in search. It’s a new paradigm,” he announced. “A race starts today.”
After a fumbled response last week, including a lackluster AI demo, shares in Google parent Alphabet plunged nearly 12 percent, vaporizing $150 billion (£125 billion) of market value in two days.
The most profitable business on the planet, however, is the tip of the iceberg. Technology insiders claim that a transformative moment has arrived, akin to the invention of the Internet. At the core of this is “generative AI” — a new generation of software tools that, with simple prompts, can compose original text, have conversations, generate art and music, write code, and even invent drugs. In short, software appears to be taking a giant leap up the ladder of jobs that one would have thought, until just a few months ago, could be done only by humans.
Matt Bornstein of Andreessen Horowitz, the renowned Silicon Valley venture capital firm, wrote last week: “The potential size of this market is hard to grasp — somewhere between all software and all human endeavors. Generative AI changes the game.”
He can finally give the Google leviathan a run for its money.
So how might this technology be deployed? What industries will be upended? How will it change our lives? Below is a glimpse of what may await:
1. Your AI clone is here
Chat GPT and a rapidly growing set of rivals — including Anthropic, Cohere and Google’s Bard — have proven capable of holding human-level conversations. How long before one of these companies — or someone else — launches a bot concierge, to which you can outsource the banalities of life, from arguing with British Gas over your bill to booking restaurants? Indeed, Microsoft researchers this month revealed a text-to-audio tool that, after hearing just three seconds of audio, can replicate your voice. Pair that with a chatbot able to respond to queries on the fly, and hey presto: an AI clone that can fight the council over that parking ticket while you are down at the pub.
Such capabilities also have implications for corporations, which often devote huge swathes of their budgets to customer service. Highly capable bot armies could empty out call centers, leading to a world where corporate and personal butler bots battle over bills, bookings and overcharging. You thought it was hard to get hold of a human now? Just wait.
2. The end of sex
Young people are having less sex than previous generations. They also have fewer friendships, and report higher rates of loneliness. A principal reason, many have theorized, is the rise of the smartphone and the attendant hours on social media that have come with it. AI may be about to make all this worse.
This month Italy’s privacy watchdog ordered Replika, a San Francisco company that generates “AI friends”, to stop processing user data in the country. Why? Because the AI friend, which the company claims is “always ready to chat”, has shown a proclivity for sending users explicit messages. Some have even admitted to have fallen in love with their Replikas.
At the same time, generative AI tools have come on leaps and bounds in their ability to create realistic photos and videos of fictitious people. The ability to entwine a chatty, randy bot with the image or video of a “person” made-to-order to meet a user’s physical preferences is here. What that means for society, let alone the Internet’s oldest industry — pornography — is anyone’s guess.
3. You won’t need a lawyer ever again
February 22 was the day that the first AI lawyer was set to argue in court. Josh Browder, the British founder of “robot lawyer” start-up DoNotPay, planned to equip a person with smartglasses that would record proceedings over a disputed speeding ticket. The defendant would then be fed legal arguments into an earpiece by a bot his company had created. Threatened with jail time by multiple authorities, Browder backed off from the stunt.
But the day when lawyers become an “obscure profession” is closer than one thinks, due to the leap in AI capabilities, Browder predicted. “The average person won’t need a lawyer ever. We won’t even know what a lawyer is,” he said.
The large language models (LLMs) at the heart of this new generation of chatbots are trained on incalculable reams of data — the entire written Internet, for example. They then draw out patterns based on that data, and use those patterns as a framework for the answers they give.
It is not foolproof — ChatGPT and its ilk will often fabricate facts or get tripped up by simple prompts. But they can be honed with training data concentrated in certain areas — such as consumer protection law — and are useful enough that Browder is building a suite of services on top of ChatGPT and other chatbots. Until now, his company has been largely confined to generating templates.
Once a company or government responded, it would struggle. “We can now have conversations with companies and governments in real time. So instead of appealing a $100 parking tickets, the bots can appeal a [much more complex] $20,000 medical bill,” he said.
4. Drugs that are programmed, not discovered
Generate Biomedicines is at the forefront of a wave of drug developers that have pointed generative AI at biology. Mike Nally, Generate’s chief executive and a Big Pharma veteran, believes the approach will spark a revolution.
Today, drug discovery is, Nally said, “artisanal” — a trial-and-error method that relies on building molecules that manipulate natural biological processes to create new treatments. More than 90 percent of drug candidates created this way fail.
The Massachusetts start-up has trained its AI models on experiment results and then uses algorithms to infer the rules governing proteins and how they function. It then generates novel molecules programmed against therapeutic targets inside the body, synthesizes those proteins in its lab, and starts testing them.
Rather than trying to “discover” drugs, its AI is inventing them from scratch. By the end of the year, the 250-person company expects to have at least 25 drugs in development, including a novel Covid vaccine. That number of candidates is comparable to a Big Pharma rival with tens of thousands of workers.
Nally said: “If you go back over the arc of history, when you look at complex fields, whenever they become engineerable, industrial revolutions occur. When biology becomes engineerable, it’s going to be a really big deal for humanity.”
5. The inevitable, almighty bust
Cast your mind back 18 months, and the tech industry was in love with crypto. Start-ups with the sketchiest of ideas raised vast sums of money at ten-figure valuations. The world, we were told, was about to change. Well, it didn’t. Rather, investors lost their shirts. An astounding $2 trillion of value was vaporized as the dream died.
It is worth keeping that in mind as this AI bubble inflates. Paul Graham, co-founder of the famed start-up boot camp Y Combinator, last week predicted a bloodbath for investors who are falling over each other to invest in new firms with even a whiff of AI. “Founders respond quickly to changes in investor fashion. The number of ‘AI’ start-ups will increase to match the size of the giant seed funds blindly investing in such companies,” he wrote. “What happens then, I can’t say for sure, except that the investors’ returns will suck.”
Unlike crypto, there are already a number of very obvious uses for artificial intelligence. The question is whether AI will indeed become a platform upon which a new generation of companies is built, or instead generate a litany of add-on features to existing services and industries.
One investor made the comparison to self-driving cars — another fad that attracted countless billions but has fallen far short of expectations.
What it has produced is the Roomba, a “self-driving” vacuum cleaner, which is a reasonable use of a technology that remains far from the capabilities required to pilot cars in the real world.
Danny Fortson is the West Coast correspondent for The Sunday Times of London and the host of the weekly podcast Danny in the Valley