As nouns the difference between car and train is that car is (dated) a wheeled vehicle, drawn by a horse or other animal or car can be (computing) the first part of a cons in lisp the first element of a list while train is elongated portion or train can be (obsolete) treachery; deceit.
Schlagwort: KI
Elongated nons.
Dissident uit Roermond, 1298 - 1353.
"Heigh Jah van daar moeder en waarom de komiteaal honden kjat naam andertaar te geldert aanwezig" I said to my boyfriend as I picked up my phone and called my dad
Who are the users, and who gets used?
Right now, as we’re anticipating the creation of AIs to serve our intimate needs, organise our diaries and care for us, and to do it all for free and without complaint, it’s easy to see how many designers might be more comfortable with those entities having the voices and faces of women. If they were designed male, users might be tempted to treat them as equals, to acknowledge them as human in some way, perhaps even offer them an entry-level salary and a cheeky drink after work.
Grün(schnabel) KI.
This position paper advocates a practical solution by making efficiency an evaluation criterion for research alongside accuracy and related measures. In addition, we propose reporting the financial cost or "price tag" of developing, training, and running models to provide baselines for the investigation of increasingly efficient methods. Our goal is to make AI both greener and more inclusive — enabling any inspired undergraduate with a laptop to write high-quality research papers.
Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni: Green AI.
Wronderstanding.
When patterns in the dataset are aligned with the goal of the task at hand, a strong learner being able to recognize, remember, and generalize these patterns is desirable. But if the patterns are not what we're actually interested in, then they become cues and shortcuts that allow the model to perform well without understanding the task.
To prevent the Clever Hans effect, we hence need to aim for datasets without spurious patterns, and we need to assume that a well-performing model didn't learn anything useful until proven otherwise.