The following is a partially redacted and lightly edited transcript of a chat conversation about AGI between Eliezer Yudkowsky and a set of invitees in early September 2021. By default, all other participants are anonymized as "Anonymous". I think this Nate Soares quote (excerpted from Nate's response to a report by Joe Carlsmith) is a useful context-setting preface regarding timelines, which weren't discussed as much in the transcript: The gap between AI systems then and AI systems now seems pretty plausibly greater than the remaining gap, even before accounting the recent dramatic increase in the rate of progress, and potential future increases in rate-of-progress as it starts to feel within-grasp. But basically all that has fallen. The gap between us and AGI is made mostly of intangibles. Sure, but on my model, "good" versions of those are a hair's breadth away from full AGI already. And the fact that I need to clarify that "bad" versions don't count, speaks to my point that the only barriers people can name right now are intangibles.) That's a very uncomfortable place to be! But I'm in the second-to-last epistemic state, where I wouldn't feel all that shocked to learn that some group has reached the brink. Maybe I won't get that call for 10 years! But it could also be 2, and I wouldn't get to be indignant with reality. I wouldn't get to say "but all the following things should have happened first, before I made that observation". I have made those observations. For one thing, I don't expect to need human-level compute to get human-level intelligence, and for another I think there's a decent chance that insight and innovation have a big role to play, especially on 50 year timescales. There has been a lot of AI progress recently.
Steep sections on slippery ground, high steps, scree and forest trails full of roots: the path up the 1,098-metre-high Mount Etzel at the southern end of Lake Zurich is peppered with numerous obstacles. But ANYmal, the quadrupedal robot from the Robotic Systems Lab at ETH Zurich, overcomes the 120 vertical metres effortlessly in a 31-minute hike. That's 4 minutes faster than the estimated duration for human hikers -- and with no falls or missteps. This is made possible by a new control technology, which researchers at ETH Zurich led by robotics professor Marco Hutter recently presented in the journal Science Robotics. "The robot has learned to combine visual perception of its environment with proprioception -- its sense of touch -- based on direct leg contact. This allows it to tackle rough terrain faster, more efficiently and, above all, more robustly," Hutter says.
ETH Zurich researchers led by Marco Hutter developed a new control approach that enables a legged robot, called ANYmal, to move quickly and robustly over difficult terrain. Thanks to machine learning, the robot can combine its visual perception of the environment with its sense of touch for the first time. Steep sections on slippery ground, high steps, scree and forest trails full of roots: the path up the 1,098-meter-high Mount Etzel at the southern end of Lake Zurich is peppered with numerous obstacles. But ANYmal, the quadrupedal robot from the Robotic Systems Lab at ETH Zurich, overcomes the 120 vertical meters effortlessly in a 31-minute hike. That's 4 minutes faster than the estimated duration for human hikers--and with no falls or missteps.
The U.S. federal government is the most prepared among 160 nations to use artificial intelligence in the public services they provide, according to a report released this week by London-based consultancy Oxford Insights. The annual report, called the 2021 Government AI Readiness Index, rates countries based on 42 indicators--including software spending and industry investment in emerging technologies--across three pillars: government, technology sector, and data and infrastructure. Buoyed by the unrivaled maturity of its technology sector, the U.S. topped the rankings, followed by Singapore, which topped the government pillar due to its digital capacity. The United Kingdom, Finland and the Netherlands finished third, fourth and fifth, respectively. "Governments stand to gain from the vast applications of recent developments in AI," said Richard Stirling, CEO and co-founder of Oxford Insights. "Those governments who take a strategic approach to harnessing AI within government and promoting their national AI sector are likely to see the greatest benefits.
The Royal Surrey Foundation Trust treated Emma McCormick, 44, using adaptive radiotherapy after she was diagnosed with the cancer last April and was referred to St Luke's Cancer Centre. The treatment, called Ethos, involves a machine, created by healthcare company Varian, which uses artificial intelligence to deliver a prescription dose to tumours. The AI technology uses daily CT scans to target the specific areas that need radiotherapy, which helps avoid damage to healthy tissue and limit side-effects. Patients are required only to lay still on a flat surface inside the machine for the duration of the treatment. There is a screen above the machine which shows different images, and medical staff can play music to make the treatment more comfortable.
DeepMind co-founder Mustafa Suleyman has departed Google after an eight-year stint at the company. Suleyman co-founded AI giant DeepMind alongside Demis Hassabis and Shane Legg in 2010 before it was acquired by Google in 2014 for $500 million. DeepMind has become somewhat of an AI darling and has repeatedly made headlines for creating neural networks that have beat human capabilities in a range of games. DeepMind's AlphaGo even beat Go world champion Lee Sedol in a five-game match. He left for Google in 2019 and was most recently the company's vice president of AI product management and policy.
The manufacturing industry is the backbone of the European economy, accounting for around 20 % of the EU's GDP. AI and advanced robotics are opening new horizons in all sectors of industry, developing novel manufacturing techniques as well as reimagining the interaction between human workers and automated tools. This new Results Pack presents the results of 14 innovative Horizon 2020 projects that are reshaping AI and industry. As economies aim for sustained post-COVID recoveries, industry needs to innovate in a way that is in line with the priorities of the European Commission, in particular those laid out by the European Green Deal, a Europe Fit for the Digital Age and an Economy that Works for People. Industry 5.0 provides a coherent vision for such a future industry, focused on human centricity, sustainability and resilience.
In an effort to serve its consumers more directly, Nike has released a plan of action that details an innovative approach to transforming its supply chain. The company issued a statement listing four key components to help make its goal successful. First, Nike intends to open several regional distribution centers across the US and Europe, in addition to having its own dedicated train – the Nike "Sole Train" – to increase capacity and speed, and help power long term growth. This step would transform the brand's central distribution centers in Memphis, TN, into omni-channel facilities. Second, the brand will leverage technology by using AI and machine learning to deliver products faster and more precisely.