Algorithmscouldsoon—iftheydon'talready—haveabetterideaaboutwhichshowyou'dliketowatchnextandwhichjobcandidateyoushouldhirethanyoudo.Oneday,humansmayevenfindawayformachinestomakethesedecisionswithoutsomeofthebiasesthathumanstypicallydisplay. Buttotheextentthatunpredictabilityispartofhowpeopleunderstandthemselvesand...
P2P payment platforms employ various strategies to protect users from scams. Many services provide guidelines on common scam tactics and how to avoid them. Some may also use algorithms and AI to identify and block suspicious activity, as well as dedicated security teams to investigate potential frau...
Inpredictive analytics, a machine learning algorithm is typically part of a predictive modeling that uses previous insights and observations to predict the probability of future events. Logistic regressions are also supervised algorithms that focus on binary classifications as outcomes, such as "yes" or...
Large language models (LLMs) are deep learning algorithms that can recognize, summarize, translate, predict, and generate content using very large datasets.
It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear behaviours. Here we challenge this assumption by leveraging mathematical models derived from measurements of local field potentials via intracranial electroenc
programs are typically executed by a processor, or a specialized hardware device called an application specific integrated circuit (asic). the program is converted into machine-readable code which instructs the processor how to execute the desired operations. in some cases, the program may also ...
However, learning analytics research tends to ignore the issue of the reliability of results that are based on MOOCs data, which is typically noisy and generated by a largely anonymous crowd of learners. This paper provides evidence that learning analytics in MOOCs can be significantly biased by ...
Generally, if a user makes a request of a generative AI tool, they desire an output that appropriately addresses the prompt (that is, a correct answer to a question). However, sometimesAIalgorithms produce outputs that are not based on training data, are incorrectly decoded by the transformer...
Sentiment analysis is one of the more impressive applications. A combination of unsupervised and supervised learning allows LLMs to identify intent, attitudes, and emotions in text. Some algorithms can even pick up specific feelings such as sadness, while others can determine the difference between ...
Options pricing models distill complex market dynamics into actionable information. However, it's crucial to remember that these models are merely prediction algorithms. They provide estimates based on present information, but the market often has its own surprises in store. ...