![]() The takeaway for me is that perhaps we need newer and more comprehensive benchmarks to evaluate against. This year, the top performing model hit 84.3% accuracy. For example, the Visual Question Answering Challenge tests AI systems with open-ended textual questions about images. So we’re seeing a saturation among these benchmarks – there just isn’t really any improvement to be made.Īdditionally, while some benchmarks are not hitting the 90% accuracy range, they are beating the human baseline. ![]() For example, the best image classification system on ImageNet in 2021 had an accuracy rate of 91% 2022 saw only a 0.1 percentage point improvement. This year across the majority of the benchmarks, we saw minimal progress to the point we decided not to include some in the report. In earlier years, people were improving significantly on the past year’s state of the art or best performance. So, for each benchmark, were researchers able to beat the score from last year? Did they meet it? Or was there no progress at all? We looked at ImageNet, a language benchmark called SUPERGlue, a hardware benchmark called MLPerf, and more some 50 were analyzed and over 20 made it into the report. – and evaluated the state-of-the-art result in each benchmark year over a year. We looked across multiple technical benchmarks that have been created over the past dozen years – around vision, around language, etc. What did the AI Index study find regarding these benchmarks? The goal is to correctly identify as many of the images as possible. Researchers run their image classification algorithms on ImageNet as a way to test their system. One example is HAI Co-Director Fei-Fei Li’s ImageNet, a dataset of over 14 million images. It’s a way of defining what you want your tool to do, and then working toward that goal. In this conversation, Parli explains more about the benchmarking trends she sees from the AI Index.Ī benchmark is essentially a goal for the AI system to hit. “We really need to be thinking about how we, as humans and society, want to interact with AI, and develop new benchmarks from there.” “Most of the benchmarks are hitting a point where we cannot do much better, 80-90% accuracy, ” she said. In the newest AI Index, published on April 3, a team of independent researchers analyzed over 50 benchmarks in vision, language, speech, and more to find out that AI tools are able to score extremely high on many of these evaluations. "But when you actually use the tool, it gives incorrect answers, says thing we don’t want it to say, and is still difficult to interact with. “There’s been a lot of excitement, and it meets some of these benchmarks quite well," she said. She cites the current popular example of ChatGPT. But that doesn’t mean most artificial intelligence tools work the way we want them to, says Vanessa Parli, associate director of research programs at the Stanford Institute for Human-Centered AI and a member of the AI Index steering committee. We welcome your feedback on the Digital Economy and Society Index.How good is AI? According to most of the technical performance benchmarks we have today, it’s nearly perfect. The scoreboard assesses Member States' performance in the areas of Internet use, Internet user skills as well as specialist skills and employment based on 12 indicators.ĭownload WiD Country Profiles 2022 (.pdf) The WiD scoreboard is one of the actions put in place to assess women's inclusion in digital jobs, careers and entrepreneurship. Member States that chose to invest more than 30% of their RRF allocation to digital are Austria, Germany, Luxembourg, Ireland and Lithuania DESI 2022 Member States dedicated on average 26% of their Recovery and Resilience Facility (RRF) allocation to the digital transformation, above the compulsory 20% threshold. This an unprecedented opportunity to accelerate digitalisation, increase the Union’s resilience and reduce external dependencies with both reforms and investments. EUR 127 billion are dedicated to digital related reforms and investments in the national Recovery and Resilience Plans. The EU has put on the table significant resources to support the digital transformation. During the COVID-19 pandemic, Member States have been advancing in their digitalisation efforts but still struggle to close the gaps in digital skills, the digital transformation of SMEs, and the roll-out of advanced 5G networks. The DESI 2022 reports are based mainly on 2021 data and tracks the progress made in EU Member States in digital. ![]() Each year, DESI includes country profiles which support Member States in identifying areas requiring priority action as well as thematic chapters offering a European-level analysis across key digital areas, essential for underpinning policy decisions. The European Commission has been monitoring Member States’ digital progress through the Digital Economy and Society Index (DESI) reports since 2014. ![]()
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