For years, the conventional wisdom among Silicon Valley futurists was that artificial intelligence and automation spelled doom for blue-collar workers whose jobs involved repetitive manual labor. Truck drivers, retail cashiers and warehouse workers would all lose their jobs to robots, they said, while workers in creative fields like art, entertainment and media would be safe. Well, an unexpected thing happened recently: A.I. entered the creative class. In the past few months, A.I.-based image generators like DALL-E 2, Midjourney and Stable Diffusion have made it possible for anyone to create unique, hyper-realistic images just by typing a few words into a text box. These apps, though new, are already astoundingly popular.

A lack of balance between those poles (in whichever direction) produces different kinds of issues in adults. I have written extensively about those matters, but that is not the topic of this article. Let's get back to the artists. Many great artists have the following thing in common. They are able to navigate this depth elevator in an agile and flexible way.

In Silicon Valley, crypto and the metaverse are out. That much became clear Monday night at the San Francisco Exploratorium, where Stability AI, the start-up behind the popular Stable Diffusion image-generating algorithm, gave a party that felt a lot like a return to prepandemic exuberance. The event -- which lured tech luminaries including the Google co-founder Sergey Brin, the AngelList founder Naval Ravikant and the venture capitalist Ron Conway out of their Zoom rooms -- was billed as a launch party for Stability AI and a celebration of the company's recent $101 million fund-raising round, which reportedly valued the company at $1 billion. But it doubled as a coming-out bash for the entire field of generative A.I. -- the wonky umbrella term for A.I. that doesn't just analyze existing data but creates new text, images, videos, code snippets and more. It's been a banner year, in particular, for generative A.I. apps that turn text prompts into images -- which, unlike NFTs or virtual reality metaverses, actually have the numbers to justify the hype they've received.

It's been two years since OpenAI announced the arrival of GPT-3, its seminal natural language processing (NLP) application. Users were blown away by the AI language tool's uncanny ability to generate insightful, considered and colorful prose -- including poems, essays, song lyrics and even detailed manifestos -- using the briefest of prompts. Known as a "foundation model," OpenAI's GPT-3 was trained by feeding it practically the entire internet, from Wikipedia to Reddit to the New York Times and everything in between. It uses this vast dataset to predict what words are the most plausible given any prompt. Given the scale of such a vast research undertaking, there are only a handful of these foundation models.

Today, the technology most commonly used to achieve AI is machine learning – advanced software algorithms designed to carry out one specific task, such as answering questions, translating languages or navigating a journey – and become increasingly good at it as they are exposed to more and more data. Worldwide, spending by governments and business on AI technology will top $500 billion in 2023, according to IDC research. But how will it be used, and what impact will it have? Here, I outline what I believe will be the most important trends around the use of AI in business and society over the next 12 months. AI will only achieve its full potential if it's available to everyone and every company and organization is able to benefit.

If you're like most people, you've probably never heard of generative AI. But even though it's still in its infancy, generative AI is starting to make waves in a variety of industries. Here's a closer look at what this promising technology is all about and why you should care. In a nutshell, generative AI refers to AI systems that are capable of creating new data based on what they have learned. That might sound confusing, so let's break it down with an example.

OpenAI, whose text- and image-generating artificial intelligence has become a mainstream hit, is in advanced talks to raise more funding from Microsoft, which previously backed the startup with capital that includes credits to use Microsoft's Azure cloud computing services to develop its technology, according to a person with knowledge of the discussions. A new deal could help Microsoft grow Azure usage, one of its top priorities, while keeping OpenAI's business away from rivals including Amazon Web Services and Google Cloud. The talks follow a previously undisclosed sale of OpenAI stock by existing shareholders last year to investors including Sequoia Capital, Tiger Global Management, Bedrock Capital and Andreessen Horowitz. In that deal, the price of the shares implied a valuation of nearly $20 billion for the seven-year-old startup, said several people with knowledge of the deal.

Microsoft is in advanced talks for a new round of funding in OpenAI, according to a person familiar with the matter, as the software giant seeks to further incorporate artificial intelligence into its products. No deal has been reached between the two sides and the funding amount could vary as negotiations evolve, the person said. The companies have held talks in recent weeks, according to people familiar with the matter. Microsoft invested $1 billion in OpenAI in 2019. The new cash could help bankroll the tremendous computing power OpenAI needs to run its various artificial intelligence products on Azure, Microsoft's cloud computing service.

Microsoft has begun rolling out Image Creator from Microsoft Bing in a preview to select markets, preparing the AI art generator for a wider rollout to Microsoft Edge later this month. In a blog post and related video, the company showed off how Image Creator will work and explained in more detail what limitations it will place upon prompts that users generate. Microsoft said last week that it would be bringing AI art to both Bing and Edge, using the more advanced DALL-E 2 algorithm to generate the art. It appears that Image Creator will be accessible from Bing.com and a related version will be available from Edge soon after. The company showed off Image Creator working within the Edge sidebar, which can carve out a small vertical column to display search results and other information as well as some useful utilities.

By August, it had been cloned in the open by two master's students as OpenGPT-2 By November, OpenAI released their 1.5B parameter model, after a cautious staged release process May 2020: OpenAI released GPT-3 as a paper and a closed beta API in June 2020. Mar 2021: EleutherAI released their open GPT-Neo 1.3B and 2.7B models May 2022: Meta released OPT-175B for researchers (with logbook! and an open license) The Text-to-Image cycle took 4? months: Apr 2022: OpenAI announces DALL-E 2 with a limited "research preview" The timelines above are highly cherrypicked of course; the story is much longer if you take into account the longer development history starting from the academic papers for diffusion (2015) and transformer models (2017) and older work on GANs. But what is more interesting is what has happened since: OpenAI's audio-to-text model, Whisper, was released under MIT license in September with no API paywall. Of course, there is less scope for abuse in the audio-to-text domain, but more than a few people have speculated that the reception to Stable Diffusion's release influenced the open sourcing decision. Sufficiently advanced community is indistinguishable from magic.