This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Both the missing sales data and the limited length of historical sales data pose significant challenges in terms of model accuracy for long-term sales prediction into 2026. However, the maximum length of historical sales data (maximum length of 140 months) still posed significant challenges in terms of model accuracy.
They are followed by marketing and sales (42%), and customer service (40%); 64% expect it to confer a competitive advantage; By 2026, companies focusing on responsibleAI could enhance business goal achievement and user acceptance by 50% ; Artificial intelligence disruption may increase global labor productivity by 1.5%-3.0%
Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in DataAnalysis and intelligent decision-making. DataAnalysisDataAnalysis involves cleaning, processing, and analysing data to uncover patterns, trends, and relationships.
For GPAI systems, including large language models or generative AI , there are particular demands on transparency and safety. 2 August 2026: Full implementation of GPAI commitments begins. Post-Market Surveillance Companies will be required to maintain post-market monitoring programs for as long as the AI system is in use.
We organize all of the trending information in your field so you don't have to. Join 15,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content