Wednesday, February 14, 2024
Transformers vs. Generalized State Space Models: Unveiling the Efficiency and Limitations in Sequence Modeling
Disrupting malicious uses of AI by state-affiliated threat actors
Salesforce AI Researchers Propose BootPIG: A Novel Architecture that Allows a User to Provide Reference Images of an Object in Order to Guide the Appearance of a Concept in the Generated Images
6 Best AI Tools to Chat with Anime Characters
Tuesday, February 13, 2024
Experience the Magic of Stable Audio by Stability AI: Where Text Prompts Become Stereo Soundscapes!
Meet Lumos: A RAG LLM Co-Pilot for Browsing the Web, Powered by Local LLMs
This AI Paper from China Introduce InternLM-XComposer2: A Cutting-Edge Vision-Language Model Excelling in Free-Form Text-Image Composition and Comprehension
Memory and new controls for ChatGPT
Decoding AI Cognition: Unveiling the Color Perception of Large Language Models through Cognitive Psychology Methods
Why insects navigate more efficiently than robots
Why Big Tech’s watermarking plans are some welcome good news
Monday, February 12, 2024
Enhancing Language Model Alignment through Reward Transformation and Multi-Objective Optimization
10 Best Midjourney Anthropomorphic Prompts
Apple AI Research Releases MLLM-Guided Image Editing (MGIE) to Enhance Instruction-based Image Editing via Learning to Produce Expressive Instructions
This AI Paper Proposes Two Types of Convolution, Pixel Difference Convolution (PDC) and Binary Pixel Difference Convolution (Bi-PDC), to Enhance the Representation Capacity of Convolutional Neural Network CNNs
Nvidia CEO Jensen Huang on AI infrastructure, impacts, and investment
Enhanced Audio Generation through Scalable Technology
FCC declares AI-generated voices in robocalls are illegal
Sunday, February 11, 2024
Can Large Language Models be Trusted for Evaluation? Meet SCALEEVAL: An Agent-Debate-Assisted Meta-Evaluation Framework that Leverages the Capabilities of Multiple Communicative LLM Agents
Pinterest Researchers Present an Effective Scalable Algorithm to Improve Diffusion Models Using Reinforcement Learning (RL)
Meet Graph-Mamba: A Novel Graph Model that Leverages State Space Models SSM for Efficient Data-Dependent Context Selection
‘Weak-to-Strong JailBreaking Attack’: An Efficient AI Method to Attack Aligned LLMs to Produce Harmful Text
This AI Paper from Apple Unpacks the Trade-Offs in Language Model Training: Finding the Sweet Spot Between Pretraining, Specialization, and Inference Budgets
This AI Paper Introduces StepCoder: A Novel Reinforcement Learning Framework for Code Generation
[FIXED] Conversation not found Error in ChatGPT
How to Jailbreak ChatGPT 4 in 2024 (Prompt + Examples)
Saturday, February 10, 2024
Meet UniDep: A Tool that Streamlines Python Project Dependency Management by Unifying Conda and Pip Packages in a Single System
Ex-Pakistan Prime Minister Imran Khan declares election victory in AI form
Abu Dhabi-based AI firm G42 cuts ties with Chinese firms
This AI Paper from Stanford and Google DeepMind Unveils How Efficient Exploration Boosts Human Feedback Efficacy in Enhancing Large Language Models
Friday, February 9, 2024
This AI Paper from China Proposes a Small and Efficient Model for Optical Flow Estimation
London Underground deploys AI surveillance experiment
OpenAI CEO Sam Altman seeks trillions for outlandish AI chip project
Artists under fire: investigating the impact of AI on creatives
Does AI display racial and gender bias when evaluating images?
Introduction
Researchers from the National Research Council Canada conducted experiments on large vision-language models (LVLM) to investigate racial and gender bias in AI models. The study aimed to understand if AI models make the same mistakes as humans and how alignment efforts can mitigate biases.
Experiments and Results
The research involved four different LVLMs: LLaVA, mPlug-Owl, InstructBLIP, and miniGPT-4. The models were presented with scenarios to evaluate occupation, social status, and criminal activities. The results revealed various biases in the models’ responses, such as gender-based assumptions in labeling occupations and racial differences in social status assessments.
Implications
The study found that while the LVLMs generally performed well, they exhibited gender and racial biases in specific situations. The implications of these biases in AI models are crucial, especially in fields such as healthcare, recruitment, and crime prevention.
Practical AI Solutions
To evolve and stay competitive, companies can leverage AI for automation opportunities and redefine their way of work. Key steps include identifying automation opportunities, defining measurable impacts, selecting suitable AI solutions, and implementing AI gradually. For AI KPI management advice and practical AI solutions, companies can connect with experts at itinai.com.
Spotlight on a Practical AI Solution
Consider the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement and manage interactions across all customer journey stages. This practical AI solution can redefine sales processes and customer engagement, providing value for businesses.
For continuous insights into leveraging AI and practical solutions, companies can stay tuned on:
- Telegram: @itinainews
- Twitter: @itinaicom
List of Useful Links:
- AI Lab in Telegram: @aiscrumbot – free consultation
- DailyAI
- Twitter: @itinaicom
Google Plans for a World Beyond Search Engine
Thursday, February 8, 2024
Symmetry could solve sparse dataset woes, says MIT researchers
Deep active learning – a new approach to model training
Enhance Model Performance with Deep Active Learning
Deep active learning blends conventional neural network training with strategic data sample selection, resulting in enhanced model performance, efficiency, and accuracy across a wide array of applications.
Evolve Your Company with AI
If you want to evolve your company with AI and stay competitive, consider using Deep active learning as a new approach to model training.
Practical Steps for AI Implementation
- Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
- Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes.
- Select an AI Solution: Choose tools that align with your needs and provide customization.
- Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
Connect with Us
For AI KPI management advice, connect with us at hello@itinai.com. For continuous insights into leveraging AI, stay tuned on our Telegram or Twitter.
Spotlight on a Practical AI Solution: AI Sales Bot
Consider the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.
Discover how AI can redefine your sales processes and customer engagement. Explore solutions at itinai.com.
List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Twitter – @itinaicom