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AlphaGo brought the era of classical board-game benchmarks to a close when Artificial Intelligence proved their competitive edge over humans in 2016.
Games provide a high-profile benchmark for assessing rates of progress many games have a large professional player base and a well-established competitive rating system. Researcher Andrew Ng has suggested, as a "highly imperfect rule of thumb", that "almost anything a typical human can do with less than one second of mental thought, we can probably now or in the near future automate using AI." While projects such as AlphaZero have succeeded in generating their own knowledge from scratch, many other machine learning projects require large training datasets. Some versions of Moravec's paradox observe that humans are more likely to outperform machines in areas such as physical dexterity that have been the direct target of natural selection. There is no consensus on how to characterize which tasks AI tends to excel at. This gives better insight into the comparative success of artificial intelligence in different areas.ĪI, like electricity or the steam engine, is a general purpose technology. There are many useful abilities that can be described as showing some form of intelligence.
4.3 Human-level artificial general intelligence (AGI). 2 Proposed tests of artificial intelligence. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results. Such tests have been termed subject matter expert Turing tests. To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Kaplan and Haenlein structure artificial intelligence along three evolutionary stages: 1) artificial narrow intelligence – applying AI only to specific tasks 2) artificial general intelligence – applying AI to several areas and able to autonomously solve problems they were never even designed for and 3) artificial super intelligence – applying AI to any area capable of scientific creativity, social skills, and general wisdom. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore." "Many thousands of AI applications are deeply embedded in the infrastructure of every industry." In the late 1990s and early 21st century, AI technology became widely used as elements of larger systems, but the field was rarely credited for these successes at the time. Red line - the error rate of a trained human on a particular task.Īrtificial intelligence applications have been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery, video games, and toys. That's crazy.Progress in machine classification of images In DX12 mode, ~14% utilized and 6.3 GB of memory in use. In DX11 mode, my GPU was reading ~65% utilized with 4.4 GB of memory in use. GPU utilization is different and almost unbelievable, though. About 13 cores running at half capacity, 4 cores oscillating from full utilization to almost nothing and then back again, and another core that's about 20% utilized. I see the same CPU core utilization in both modes, though. So, DirectX 12 is a win for my computer and it's really not even close. Gathering Storm Graphics Benchmark: 9.766ms (Average Frame Time), 13.266ms (99th Percentile) Vanilla Graphics Benchmark: 7.614ms (Average Frame Time), 10.263ms (99th Percentile) Gathering Storm Graphics Benchmark: 13.252ms (Average Frame Time), 18.152ms (99th Percentile)
Vanilla Graphics Benchmark: 9.884ms (Average Frame Time), 13.076ms (99th Percentile) GPU: nVidia RTX 2070 SUPER Founders Edition