Artificial Intelligence used to be a Google thing. The company has developed a reputation for making long-term bets on all kinds of far-fetched technologies, and much of the research underpinning the current wave of AI-powered chatbots has taken place in its labs. Yet a startup called OpenAI has emerged as an early leader in so-called generative AI—software that can generate its own text, images or videos—by launching ChatGPT in November. Its sudden success has left Google parent company Alphabet scrambling in a key subsector of technology that Chief Executive Officer Sundar Pichai has said will be “deeper than fire or lightning”.
ChatGPT, which some see as an eventual challenger to Google’s traditional search engine, seems a double threat given OpenAI’s close ties to Microsoft. According to current and former employees as well as others close to the company, the feeling that Google is lagging behind in an area that it has considered a major strength is no small measure of concern in Mountain View, Calif. asked to remain anonymous because he was not allowed to speak publicly. As one current employee puts it: “There is an unhealthy combination of unusually high expectations and great insecurity about any AI-related initiative.”
According to a former employee, the effort has made Pichai relive his days as a product manager, as he is moved to directly weigh in on the details of product features, a task that typically Their pay falls well below the grade. Google co-founders Larry Page and Sergey Brin have also become more involved in the company over the years, with Brin even submitting code changes to Bard, Google’s ChatGPT-esque chatbot. Senior management has declared a “code red” that comes with instructions that all of its most important products—which have more than a billion users—be incorporated generative AI within months, according to a person with knowledge of the matter. Have to do In an early example, the company announced in March that creators on its YouTube video platform would soon be able to use the technology to virtually swap outfits.
Some Google alumni are reminded of a past time the company enforced an internal mandate to introduce every major product with a new idea: an effort beginning in 2011 to promote the ill-fated social network Google+. . It’s not an accurate comparison—Google has never been seen as a leader in social networking, while its expertise in AI is undeniable. Still it has the same feeling. Employee bonuses were once tied to the success of Google+. Current and former employees say that at least some Googlers’ ratings and reviews will be influenced by their ability to integrate generative AI into their work. Code Red has already resulted in dozens of planned generative AI integrations. “We’re throwing spaghetti at the wall,” says a Google employee. “But it’s not even close to what’s needed for a company to transform and be competitive.”
Ultimately, the mobilization around Google+ failed. The social network struggled to find traction with users, and Google eventually said in 2018 that it would be discontinuing the product for consumers. A former Google executive sees the flop as a cautionary tale. “Larry’s mandate was that every product must have a social component,” this person says. “It ended pretty bad.”
A Google spokesperson pushes back against the comparison between Code Red and the Google+ campaign. While the Google+ mandate has touched all products, the current AI push encourages Googlers to test the company’s AI tools internally, the spokesperson says: a common practice in tech nicknamed “dogfooding.” The spokesperson says most Googlers aren’t pivoting to spend extra time on AI, working only on relevant projects.
Google isn’t alone in its firm belief that AI is everything now. Silicon Valley has entered a full-hype cycle, with venture capitalists and entrepreneurs suddenly declaring themselves AI visionaries, shying away from recent fixations like blockchain, and companies seeing their stock prices jump after announcing AI integrations. seeing an increase in In recent weeks, Meta Platforms CEO Mark Zuckerberg has been focused on AI rather than the Metaverse — a technology he recently declared so fundamental to the company that he was forced to change its name, according to two people familiar with the matter. was needed.
The new marching orders are welcome news for some at Google, which is well aware of its history of diving into speculative research when it comes to commercializing it. Members of some teams that are already working on generative AI projects expect that they will now “be able to ship more and speak more product, as opposed to just being a matter of some research,” according to Case. According to one of the people with knowledge.
In the long run, it may not matter much that OpenAI took all the air out of the public conversation for a few months, given how much work Google has already done. Pichai began referring to Google as an “AI-first” company in 2016. It’s been using machine learning to drive its advertising business for years, weaving AI into key consumer products like Gmail and Google Photos, where it uses the technology to help users. Compose emails and organize images. In a recent analysis, research company Zeta Alpha examined the top 100 most cited AI research papers from 2020 to 2022 and found that Google dominates the field. “The way it is starting to appear is that Google was a kind of sleeping giant that is now behind and playing catch-up. I think the reality is actually not quite that much,” says Amin Ahmed, a former Google AI researcher who co-founded Vectara, a startup that provides conversational search tools to businesses. “Google was really good, I think, at implementing this technology in some of its core products years and years ahead of the rest of the industry.”
Google has also struggled with the tension between its business priorities and the need to responsibly handle emerging technology. There is a well-documented tendency for automated tools to reflect biases present in the data sets they are trained on, as well as concerns about the implications of testing tools on the public before they are ready. Generative AI in particular comes with risks that have kept Google from getting into the market. For example, in search, a chatbot can give a single answer that comes directly from the company that built it, in the same way that ChatGPT appears to be the voice of OpenAI. This is a fundamentally riskier proposition than simply providing a list of links to other websites.
Google’s Code Red seems to have broken its risk-reward calculations in ways that worry some experts in the field. Emily Bender, a professor of computational linguistics at the University of Washington, says that Google and other companies bucking the generative AI trend may not be able to steer their AI products away from “the most egregious examples of bias, let alone the broader ones.” But little nuance matters. The spokesperson says Google’s efforts are governed by its AI Principles, a set of guidelines announced in 2018 for developing the technology responsibly, adding that the company is still taking a cautious approach.
Other organizations have already shown they are willing to move forward, whether Google does so or not. One of the most important contributions Google researchers made in this area was a landmark paper titled “Attention is All You Need,” in which the authors introduced transformers: systems that allow AI models to zero in on the most important pieces of information in data. help to do. They are analyzing. Transformers are now the key building block for the larger language model, the technology powering the current crop of chatbots—the “T” in ChatGPT stands for “transformer.” Five years after the paper’s publication, all but one of the authors have left Google, some citing a desire to break free from the rigors of a large, slow-moving company.
They are among dozens of AI researchers who have made the jump to OpenAI as well as several smaller startups including Character.ai, Anthropic and Adept. A handful of startups founded by Google alumni—including Neeva, Perplexity AI, Tonita, and Vectara—are looking to re-imagine search using the big language model. The fact that only a few key locations have the knowledge and ability to build them means that competition for talent is “much more intense than in other areas where the training model’s methods are not as specialized,” Google Brain alumna, Sarah Hooker It is said that now AI startups are working in the fog.
It is not unheard of for people or organizations to make significant contributions to the development of one or another breakthrough technology, only to see someone else realize stupid financial gains without them. Kewal Desai, a former Googler who is now managing director of venture capital firm Shakti, cites the example of Xerox Parc, the research lab that laid the groundwork for the personal computing era, only to see Apple Inc. And Microsoft came along and built their trillion dollar empire behind it. “Google wants to make sure it’s not the Xerox Parse of its era,” says Desai. “All the innovation happened there, but none of the execution.”
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