I turned myself into an AI-generated deathbot - here's what I found If a loved-one died tomorrow, would you want to keep talking to them? Not through memories or saved messages, but through artificial intelligence - a chatbot that uses their texts, emails and voice notes, to reply in their tone and style. A growing number of technology companies now offer such services as part of the digital afterlife industry, which is worth more than £100bn, with some people using it as a way to deal with their grief. Cardiff University's Dr Jenny Kidd has led research on so-called deathbots, published in the Cambridge University Press journal Memory, Mind and Media, and described the results as both fascinating and unsettling. Attempts to communicate with the dead are not new.

Thecomputation ofthecompetitiveequilibrium isknownasthemarketequilibrium computation problem, whose unique solution was shown to exist under a general model of the economics in the seminal work of Arrow and Debreu[3].

Thepresented equations can be efficiently solved using well-known numerical methods.

While some biological neural networks are well known, we expect that the vast majority remain undiscovered due to the enormous variety of tasks the brain performs. Many methods have been developed to help discover latent networks of neural populations (i.e.

Although there are many commonalities between the various DICE estimators, their derivations are distinct and seemingly incompatible.

Transformer's runtime is quadratic with respect to the input sequence length, which makes training

In practical settings, the reinforcement learning (RL) algorithms are faced with a challenge of maximizing the cumulative reward given a finite sample of environment transitions and inexact representation ofpolicyandvaluefunction. This givesrisetoerrors thatpropagateacross learning iterations and, combined, can result in divergence. Recently, state-of-the-art RL algorithms have been successful in solving complex environments and, hence, overcoming inaccuracies and their accumulation.

Forthemulti-armed bandit problem, we also provide a nearly-tight lower bound up to a logarithmic factor.

Forthemulti-armed bandit problem, we also provide a nearly-tight lower bound up to a logarithmic factor.