What marketers really want to know about GenAI

Generative AI has produced a lot of hype, but has the hype translated into application among marketing leaders and practitioners? Most agree that generative AI brings equal parts opportunity and apprehension, but very few answers when it comes to the practice of marketing and the impact it will have on customer experiences. Join experts as…

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Researchers from the University of Oxford and Xi’an Jiaotong University Introduce an Innovative Machine-Learning Model for Simulating Phase-Change Materials in Advanced Memory Technologies

  Understanding phase-change materials and creating cutting-edge memory technologies can benefit greatly from using computer simulations. However, direct quantum-mechanical simulations can only handle relatively simple models with hundreds or thousands of atoms at most. Recently, researchers at the University of Oxford and the Xi’an Jiaotong University in China developed a machine learning model that might…

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Meet LocoMuJoCo: A Novel Machine Learning Benchmark Designed to Facilitate Rigorous Evaluation and Comparison of Imitation Learning Algorithms

  Researchers from the Intelligent Autonomous Systems Group, Locomotion Laboratory, German Research Center for AI, Centre for Cognitive Science, and Hessian.AI introduced a benchmark to advance research in Imitation Learning (IL) for locomotion, addressing the limitations of existing measures that often focus on simplified tasks. This new benchmark comprises diverse environments, including quadrupeds, bipeds, and…

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Microsoft updates notification process for ad disapprovals

Microsoft has updated its email notification process to promptly inform marketers about disapprovals in their ads, keywords, and product offers. These changes include: More frequent alerts. Enhanced insights. Technical error notifications. Why we care. The enhanced notification process is designed to give marketers quicker and more detailed information about ad disapprovals. This grants you additional…

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A New Research Paper Introduces a Machine-Learning Tool that can Easily Spot when Chemistry Papers are Written Using the Chatbot ChatGPT

  In an era dominated by AI advancements, distinguishing between human and machine-generated content, especially in scientific publications, has become increasingly pressing. This paper addresses this concern head-on, proposing a robust solution to identify and differentiate between human and AI-generated writing accurately for chemistry papers. Current AI text detectors, including the latest OpenAI classifier and…

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5 behavioral strategies to test

SEO and PPC professionals are all in the business of driving more traffic to websites. But are you getting the most out of the visitors you already have? This is a critical question. And, often, the answer is “no.”  A solid search marketing strategy requires a customer experience plan as its core. Even if customer…

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Transformer architecture: An SEO’s guide

As we encounter advanced technologies like ChatGPT and BERT daily, it’s intriguing to delve into the core technology driving them – transformers. This article aims to simplify transformers, explaining what they are, how they function, why they matter, and how you can incorporate this machine learning approach into your marketing efforts.  While other guides on…

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Cerebras and G42 Break New Ground with 4-Exaflop AI Supercomputer: Paving the Way for 8-Exaflops

  As technology continues to advance at an astonishing pace, Cerebras Systems and G42 have just taken a giant leap forward in the world of artificial intelligence. In a groundbreaking partnership, they have successfully completed a 4-Exaflop AI supercomputer, marking a significant milestone in the quest for unprecedented computational power. This achievement also signifies the…

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Researchers from Waabi and the University of Toronto Introduce LabelFormer: An Efficient Transformer-Based AI Model to Refine Object Trajectories for Auto-Labelling

  Modern self-driving systems frequently use Large-scale manually annotated datasets to train object detectors to recognize the traffic participants in the picture. Auto-labeling methods that automatically produce sensor data labels have recently gained more attention. Auto-labeling may provide far bigger datasets at a fraction of the expense of human annotation if its computational cost is…

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