AI’s sudden big leap into use | Tech Rasta

For all the huge potential of artificial intelligence, it remains a backwater in the investment world. There are companies that have ridden the AI ​​wave in significant ways: Google claims to have improved many of its services with the help of AI, machine learning has boosted sales of Nvidia’s graphics processing units, and TikTok’s algorithm is a big part of what keeps users engaged. Coming back to its short videos.

But it’s hard to find a pure AI company that has grown behind the technology or identified a large new market that has been created. That picture can change and change a lot.

According to Pat Grady, a partner at Sequoia Capital, something significant has happened in AI in recent weeks. Generative systems — those that automatically generate text and images from simple text prompts — have evolved to the point where they have broad business uses. A partner at another prominent Silicon Valley venture capital firm described AI’s recent history as a graveyard for start-up investors, also reporting that the race is on to find breakthrough applications for this new technology.

Since the launch of OpenAI’s GPT3 text-writing system two years ago, generative models like this have been gaining traction in AI. The ethical issues they raise are profound, from any biases they might perceive from the data they’re trained on, to the risk that they could be used to spread misinformation. But that did not prevent hunting for practical uses.

Three things changed to transform these systems from clever party tricks to potentially useful tools.

For one, AI systems have moved beyond text. Last week, Meta unveiled the first system that can generate a video from a text or image prompt. That breakthrough is thought to be two years or more away. Not to be outdone, Google responded with not one but two AI video systems of its own.

This year’s biggest AI breakthrough came in image generation, thanks to systems like OpenAI’s Doll-E 2, Google’s Imagen and start-up Midjourney. Imad Mostak, the London hedge fund manager behind Stable Diffusion, the latest image-generating system taking the AI ​​world by storm, called images the “killer app” for this new form of AI. For a generation that grew up with TikTok and Snapchat, this new creative tool will be profound, he says. It also presents a clear threat to anyone whose livelihood depends on making images in other ways.

The second big change comes from the rapidly falling cost of the training giant’s AI models. Microsoft’s $1bn support of OpenAI three years ago highlighted its prohibitive cost for ever-larger models. New techniques that make it possible to achieve high-quality results by training neural networks with fewer layers of artificial neurons are changing the picture. The computing resources used to train the stable spread cost only $600,000 at market prices, According to Mostak.

A third change is the availability of technology. Google and OpenAI have been wary of making their technology widely available, partly out of concern that it could be misused. In contrast, Midjourney’s image system is available to all users through a freemium pricing model. Stable Diffusion went further, open sourcing its software and releasing details of how it trained its system. This makes it possible for other organizations to train the image model on their own data sets.

Hazards arising from such manufacturing systems have received much attention. They pull out fresh images or text based on millions of learned examples, without understanding the underlying material. That leads to meaningless results, as well as deliberate misinformation.

But in a business setting, at least some of these errors can be controlled. Finding ways to incorporate technology into existing work processes, creating tools that suggest new ideas or accelerate creative production, filter the output of human workers. This idea is already being used to generate computer code.

The big question now, says one investor: Will existing giants in industries like marketing, media and entertainment take advantage of these powerful new creative tools? Or will they be disrupted by a new generation of upstarts with their roots in AI?

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