What's Inside
Court Decides AI-Created Art Not Eligible for Copyright Protection
Salesforce's Case Study: Retailers' adoption of generative AI
Research in AI: Automated visual information seeking using large language models
Research in AI: Understanding Your Mind: Dr. Karl J. Friston Discusses the Free Energy Principle
AI Guides: Privacy, Security, And Compliance Strategies For AI
Court Decides AI-Created Art Not Eligible for Copyright Protection
A recent ruling by Judge Beryl A. Howell stated that AI-generated artwork cannot be copyrighted. This decision came in response to a lawsuit against the US Copyright Office by Stephen Thaler, who was denied copyright for an AI-generated image created using the Creativity Machine algorithm.
Thaler's attempts to obtain copyright were rejected multiple times. While acknowledging the evolving landscape of AI and copyright, the judge emphasized the need for human authorship in copyrightable works.
Despite the potential for AI-assisted art creation, questions about the required human input remain. Thaler plans to appeal, disagreeing with the interpretation of the Copyright Act. Ongoing legal battles reflect the growing intersection of AI and copyright law. Read More
Salesforce's Case Study: Retailers' adoption of generative AI
Retailers are embracing generative AI to adapt to shifting shopping trends, with significant usage for personalized marketing emails (56%) and creative assets (58%). This tech is also employed for personalized offers (54%) and auto-generated product descriptions (53%).
Though some are experimenting, many are leveraging generative AI for tasks like product recommendations (59%) and digital shopping assistants (55%). Surprisingly, 92% of retailers plan to increase AI investment this year. Shoppers show interest, especially in researching electronics (52%).
The study reveals that 57% of retailers can personalize using data, and multi-channel customer service, led by email (79%), plays a key role. Generative AI is being utilized to empower chatbots (54%), automate knowledge base articles (53%), and create case summaries (52%). The urgency stems from the fact that 74% of shoppers switch after three negative experiences. These insights are from Salesforce's global survey involving 2,400 shoppers and 1,125 retail leaders across 18 countries.
Research in AI (Google Blog): Automated visual information seeking using LLM
Progress in adapting large language models (LLMs) for multimodal tasks like image captioning and Visual question answering (VQA).
Current state-of-the-art visual language models (VLMs) struggle with visual information seeking datasets (e.g., Infoseek, OK-VQA) that require external knowledge.
"AVIS: Autonomous Visual Information Seeking with Large Language Models" presents a novel method for improved visual information seeking.
AVIS integrates LLMs with three tools: computer vision tools, web search tool, image search tool.
AVIS employs LLM-powered planner for tool and query selection, LLM-powered reasoner for analyzing tool outputs. Read More
Understanding Your Mind: Dr. Karl J. Friston Discusses the Free Energy Principle
Dr. Karl J. Friston, a renowned neuroscientist, is Chief Scientist at VERSES AI, focusing on Active Inference AI based on the Free Energy Principle (FEP).
FEP, recently validated by Japanese researchers, explains brain learning.
Traditional AI research relies on machine learning, which faces challenges like data loading, interpretability, and lack of actual reasoning.
VERSES AI's approach, involving Active Inference AI, FEP, and the Spatial Web Protocol, establishes a new cognitive architecture.
This architecture is self-organizing, self-optimizing, and self-evolving, while also being programmable, auditable, and aligned with human governance. Read More
Privacy, Security, And Compliance Strategies For AI
Product Launches
The Real-Time Payments Fraud Solution utilizes advanced machine learning techniques and predefined rules for detecting fraud in real-time payment scenarios.
It enables financial institutions to securely access instant payment technologies like The Clearing House and Zelle.
The growth of the U.S. real-time payments market poses an elevated risk of payment fraud due to reduced time for fraud detection.
The solution features an open SaaS orchestration platform for data consolidation, enrichment, and scalability.
It employs Unsupervised Machine Learning, Advanced Device and Behavioural Intelligence, a Robust Decision Engine, and Graph-Based Investigation Tools for efficient Fraud Detection and Prevention.
Cyabra introduces botbusters.ai to combat artificial intelligence-generated bots and spam accounts
Botbusters.ai is a tool that detects AI-generated texts, images, and fake profiles, all in one place.
Created to bring back trust, transparency and authenticity into the online realm.
Bots and other fake profiles have been manipulating social media for years, spreading disinformation, propaganda and other harmful content.
Recently, they have been weaponizing AI-generated texts and images to promote their agendas.
Identifies difference between machine-generated content and authentic, human-created content has become crucial
AI Meme of the Day:
ChatGPT: "If your wife said 8 then it 'must' be 8" 😂
A gem from Reddit: link
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