MIT News December 6, 2024 Researchers at MIT evaluated claims about the large macroeconomic implications of new advances in AI. So long as AI’s microeconomic effects are driven by cost savings/productivity improvements at the task level, its macroeconomic consequences will be given by Gross Domestic Product (GDP) and aggregate productivity gains can be estimated by what fraction of tasks are impacted and average task-level cost savings. Predicted TFP gains over the next 10 years could be modest. They showed theoretically that even when AI improves the productivity of low-skill workers in certain tasks it may increase rather than reduce inequality. Empirically, […]
Category Archives: AI
AI fact checks can increase belief in false headlines, study finds
Phys.org December 4, 2024 Recent AI language models have shown impressive ability in fact-checking tasks, but how humans interact with fact-checking information provided by these models is unclear. Researchers at Indiana University investigated the impact of fact-checking information generated by a popular large language model (LLM) on belief in and sharing intent of political news headlines in a preregistered randomized control experiment. Although the LLM accurately identified most false headlines (90%), they found that the information did not significantly improve participants’ ability to discern headline accuracy or share accurate news. In contrast, viewing human-generated fact checks enhanced discernment in both […]
Invisible touch: Researchers give AI the ability to feel and measure surfaces
Phys.org November 18, 2024 Researchers at Stevens Institute explored a novel approach to surface roughness metrology utilizing a single pixel, raster scanning single photon counting LiDAR system. It used a collimated laser beam in picosecond pulses to probe a surface, capturing the changes of back-scattered photons from different points on the surface into a single mode fiber, and counted them using a single photon detector. The back-scattered photons carried speckle noise produced by the rough surface, and the variation in photon counts over different illumination points across the surface becoming a good measure of its roughness. By analyzing the variation […]
Novel AI algorithm captures photons in motion
Phys.org November 19, 2024 An international team of researchers (Canada, USA – Stanford University) presented an imaging and neural rendering technique that seeks to synthesize videos of light propagating through a scene from novel, moving camera viewpoints. They used a new ultrafast imaging setup to capture a first-of-its kind, multi-viewpoint video dataset with picosecond-level temporal resolution. Combined with this dataset, they introduced an efficient neural volume rendering framework based on the transient field defined as a mapping from a 3D point and 2D direction to a high-dimensional, discrete-time signal that represented time-varying radiance at ultrafast timescales. They rendered a range […]
Despite its impressive output, generative AI doesn’t have a coherent understanding of the world
MIT News November 5, 2024 A team of researchers in the US (Harvard University, MIT, Cornell University, University of Chicago) used a case where the underlying reality was governed by deterministic finite automaton to test the possibility of large language models implicitly learning world models. They proposed new evaluation metrics for world model recovery inspired by the classic Myhill-Nerode theorem from language theory and illustrated their utility in three domains: game playing, logic puzzles, and navigation. In all domains, the generative models they considered did well on existing diagnostics for assessing world models, but their evaluation metrics revealed their world […]
Analysis of approximately 75 million publications finds those employing AI are more likely to be a ‘hit paper’
Phys.org October 11, 2024 Despite enormous efforts devoted to understanding AI’s economic impacts, we lack a systematic understanding of the benefits to scientific research associated with the use of AI. Researchers at the Northwestern University developed a measurement framework found that the use and benefits of AI appeared widespread throughout the sciences, growing especially rapidly since 2015. However, there is a substantial gap between AI education and its application in research, highlighting a misalignment between AI expertise supply and demand. Their analysis revealed demographic disparities, with disciplines with higher proportions of women or Black scientists reaping fewer benefits from AI, […]
Method prevents an AI model from being overconfident about wrong answers
MIT News July 31, 2024 Recent studies have found that common interventions such as instruction tuning often result in poorly calibrated large language models (LLMs). Although calibration is well-explored in traditional applications, calibrating LLMs is uniquely challenging. The challenges stem as much from the severe computational requirements of LLMs as from their versatility, which allows them to be applied to diverse tasks. To address these challenges, researchers at MIT proposed THERMOMETER, a calibration approach tailored to LLMs. For calibrating the LLMTHERMOMETER learned an auxiliary model, using the data given from multiple tasks. According to the researchers it was computationally efficient, […]
Doing more but learning less: Addressing the risks of AI in research
Phys.org March 8, 2024 Scientists are enthusiastically imagining ways in which artificial intelligence (AI) tools might improve research. A team of researchers in the US (Yale University, Princeton University) developed a taxonomy of scientists’ visions for AI, observing that their appeal comes from promises to improve productivity and objectivity by overcoming human shortcomings. But proposed AI solutions can also exploit our cognitive limitations, making us vulnerable to illusions of understanding in which we believe we understand more about the world than we actually do. Such illusions obscure the scientific community’s ability to see the formation of scientific monocultures, in which […]
AI just got 100-fold more energy efficient
Science Daily October 12, 2023 Although support vector machine algorithms for electrocardiogram classification show high classification accuracy, hardware implementations for edge applications are impractical due to the complexity and substantial power consumption needed for kernel optimization when using conventional CMOS circuits. A team of researchers in the US (Northwestern University, University of Southern California) has shown that reconfigurable mixed-kernel transistors based on dual-gated van der Waals heterojunctions could generate fully tunable individual and mixed Gaussian and sigmoid functions for analogue support vector machine kernel applications. The heterojunction-generated kernels can be used for arrhythmia detection from electrocardiogram signals with high classification […]
AI models struggle to identify nonsense, says study
Phys.org September 14, 2023 Neural network language models appear to be increasingly aligned with how humans process and generate language, but identifying their weaknesses through adversarial examples is challenging due to the discrete nature of language and the complexity of human language perception. An international team of researchers (USA – Columbia University, Israel) turned the models against each other by generating controversial sentence pairs where two language models disagreed about which sentence is more likely to occur. Considering nine language models (including n-gram, recurrent neural networks, and transformers), they created hundreds of controversial sentence pairs through synthetic optimization or by […]