Топ-10 конкурентов lethain.com

staffeng.com

March, 2021 blog, twitter, linkedin Disclaimer: I’m an employee of IBM. The views expressed in this article are mine and don’t necessarily reflect the positions, strategies, or opinions of the company. Tell us a little about your current role: where do you work, your title and generally the sort of work that you and your team do. I work at IBM on the Cognos Analytics (CA) for Mobile team. CA is a suite of business intelligence tools that provides powerful cognitive capabilities. It uses AI and machine learning to help prep data and suggest ways to manage and visualize data. For example, it can suggest visualization types based on the type of data provided. It features best-in-class analytics capabilities, such as reporting, dashboards, data modelling, and data exploration. CA also takes analytics further and uses AI to generate insights and predictions. Since it’s true enterprise software, it runs in on-prem environments as well as the hybrid cloud on IBM Cloud Pak™ for Data.

medium.engineering

Stories from the team building Medium.

simonwillison.net

Today I wanted to understand the performance difference between two Python implementations of a mechanism to detect changes to a SQLite database schema. I rendered the difference between the two …

addyosmani.com

Addy Osmani is a Software Engineer at Google working on Google Cloud and Gemini.

substack.com

Substack is a media platform for video, writing, podcasts, and creator-centered communities, all powered by subscriptions.

arxiv.org

A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory. In this study, we test karma in an online experiment in which human subjects repeatedly compete for a resource with time-varying and stochastic individual preferences or urgency to acquire the resource. We confirm that karma has significant and sustained welfare benefits even in a population with no prior training. We identify mechanism usage in contexts with sporadic high urgency, more so than with frequent moderate urgency, and implemented as a simple (binary) karma bidding scheme as particularly effective for welfare improvements: relatively larger aggregate efficiency gains are realized that are (almost) Pareto superior. These findings provide guidance for further testing and for future implementation plans of such mechanisms in the real world.

openai.com

We believe our research will eventually lead to artificial general intelligence, a system that can solve human-level problems. Building safe and beneficial AGI is our mission.

medium.com

Read stories about Support on Medium. Discover smart, unique perspectives on Support and the topics that matter most to you like Mental Health, Love, Community, Relationships, Friendship, Life, Tech, Writing, Family, and more.

anthropic.com

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.