A senior Google employee has claimed she was made redundant after reporting a manager who told clients stories about his swinger lifestyle and showed a nude of his wife. Victoria Woodall told an employment tribunal she was subjected to a campaign of retaliation by the company after whistleblowing on the man who was later sacked. Google UK's internal investigation found the manager had touched two female colleagues without their consent, and his behaviour amounted to sexual harassment, documents seen by the BBC in court show. The tech giant denies retaliating against Woodall and argues she became paranoid after whistleblowing and began to view normal business activities as sinister. In her claim, Woodall says her own boss subjected her to a relentless campaign of retaliation after her complaint also implicated his close friends who were later disciplined for witnessing the manager's behaviour and failing to challenge it.

Biological machine learning is often bottlenecked by a lack of scaled data. One promising route to relieving data bottlenecks is through high throughput screens, which can experimentally test the activity of $10^6-10^{12}$ protein sequences in parallel. In this article, we introduce algorithms to optimize high throughput screens for data creation and model training. We focus on the large scale regime, where dataset sizes are limited by the cost of measurement and sequencing. We show that when active sequences are rare, we maximize information gain if we only collect positive examples of active sequences, i.e. $x$ with $y>0$. We can correct for the missing negative examples using a generative model of the library, producing a consistent and efficient estimate of the true $p(y | x)$. We demonstrate this approach in simulation and on a large scale screen of antibodies. Overall, co-design of experiments and inference lets us accelerate learning dramatically.

Google's central London office cost as much as a tech unicorn and the company's UK boss, Debbie Weinstein, says it pulses with a similar spirit. "It feels like a startup energy," she says. However, we are meeting on a morning when Google has been threatened with a reckoning reserved for members of the corporate establishment, not tech ingenues: a breakup. Hours earlier, the US Department of Justice had asked a federal judge to order the sale of Google's Chrome browser, along with a host of other actions including making its search index – a database of all the webpages it has crawled – available to competitors. It follows a ruling by the same judge in August that the 2tn company has built an illegal monopoly in the search market.

Debbie Weinstein, Google's UK managing director, says'proactive action' is needed to keep the country at the forefront of new tech. Debbie Weinstein, Google's UK managing director, says'proactive action' is needed to keep the country at the forefront of new tech. Google says UK risks being'left behind' in AI race without more data centres Thu 19 Sep 2024 14.08 EDTFirst published on Thu 19 Sep 2024 11.00 EDT The company pointed to research showing that the UK is ranked seventh on a global AI readiness index for data and infrastructure, and called for a number of policy changes. Google's UK managing director, Debbie Weinstein, said that the government "sees the opportunity" in AI but needs to introduce more policies boosting its deployment. "We have a lot of advantages and a lot of history of leadership in this space, but if we do not take proactive action, there is a risk that we will be left behind," she said.

What if you build it and they don't come? The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. It's fair to say the shine is coming off the AI boom. Soaring valuations are starting to look unstable next to the sky-high spending required to sustain them.

Almost two-thirds of British jobs could be "enhanced" with AI, Google has claimed, with only a tiny proportion at risk of being "phased out" entirely. Instead of worrying about job losses caused by AI, the focus needed to be on making sure the millions of Britons who could work in smarter and faster ways with AI tech got the support to use it, the company said. "Fewer than 50% of people are actually taking advantage of these tools in their working life on a day to day basis," said Debbie Weinstein, managing director of Google UK. "The uptake of these tools is very low, and I think the only way we're going to unlock the potential of what AI can do is actually by getting people to use them, and to feel confident and capable about them." According to research from the thinktank Public First, commissioned by Google, 61% of British jobs will be "radically" transformed by AI, with just 31% "insulated" from the technology – defined as having fewer than a quarter of their workplace tasks with the potential to be automated. Those insulated jobs would overwhelmingly be in social care, transport, accommodation and food services, where complex and varied physical tasks were achievable only by human workers, Public First said.

For decades, the Department of Commerce has maintained a little-known list of technologies that, on grounds of national security, are prohibited from being sold freely to foreign countries. Any company that wants to sell such a technology overseas must apply for permission, giving the department oversight and control over what is being exported and to whom. These export controls are now inflaming tensions between the United States and China. They have become the primary way for the U.S. to throttle China's development of artificial intelligence: The department last year limited China's access to the computer chips needed to power AI and is in discussions now to expand them. A semiconductor analyst told The New York Times that the strategy amounts to a kind of economic warfare.

From TikTok to Huawei routers to DJI drones, rising tensions between China and the US have made Americans--and the US government--increasingly wary of Chinese-owned technologies. But thanks to the complexity of the hardware supply chain, encryption chips sold by the subsidiary of a company specifically flagged in warnings from the US Department of Commerce for its ties to the Chinese military have found their way into the storage hardware of military and intelligence networks across the West. In July of 2021, the Commerce Department's Bureau of Industry and Security added the Hangzhou, China-based encryption chip manufacturer Hualan Microelectronics, also known as Sage Microelectronics, to its so-called "Entity List," a vaguely named trade restrictions list that highlights companies "acting contrary to the foreign policy interests of the United States." Specifically, the bureau noted that Hualan had been added to the list for "acquiring and ... attempting to acquire US-origin items in support of military modernization for [China's] People's Liberation Army." Yet nearly two years later, Hualan--and in particular its subsidiary known as Initio, a company originally headquartered in Taiwan that it acquired in 2016--still supplies encryption microcontroller chips to Western manufacturers of encrypted hard drives, including several that list as customers on their websites Western governments' aerospace, military, and intelligence agencies: NASA, NATO, and the US and UK militaries.

The power consumed by machine learning is exploding, and while advances are being made in reducing the power consumed by them, model sizes and training sets are increasing even faster. Even with the introduction of fabrication technology advances, specialized architectures, and the application of optimization techniques, the trend is disturbing. Couple that with the explosion in edge devices that are adding increasing amounts of intelligence and it becomes clear that something dramatic has to happen. The right answer is not to increase the world's energy production. It is to use what we have more wisely. The industry has to start taking total energy consumed by a machine learning application seriously, and that must include asking the question, 'Is the result worth the power expenditure?'

In the fall of 2015, Rob Reich, a philosopher and a political scientist at Stanford, was chatting with a freshman during office hours. "I asked him what he planned to study," Reich recalled recently. "He said, 'Definitely computer science. I have some ideas for startups.' " In the spirit of small talk, Reich asked, What kind? "He looked at me with total earnestness and said, 'To tell you that, I'd have to ask you to sign a nondisclosure agreement.'