Summary: ChatGPT and Bard were rated as more helpful and trustworthy than Bing Chat in a diary study evaluating the three generative-AI bots. Bing Chat’s less favorable ratings were attributed to its richer yet imperfect user interface and poorer information aggregation capabilities.
Summary: Participants rated Bing Chat as less helpful and trustworthy than ChatGPT or Bard. These results can be attributed to Bing’s richer yet imperfect UI and its poorer information aggregation.
One of the benefits of generative-AI bots is that they save users the effort of searching for information themselves. They aggregate relevant information from various sources, making it easier for users to find what they need.
In a diary study that involved three bots, we discovered that people overwhelmingly found the conversations with these bots to be highly helpful and trustworthy. However, there were some discrepancies in the ratings for the three bots, which can be explained by their differing capacities and interfaces.
Our Research:
Action Items:
1. Conduct further research on the interface and information aggregation capabilities of ChatGPT, Bard, and Bing Chat to gain a deeper understanding of the differences mentioned in the meeting notes.
2. Analyze user feedback and ratings for ChatGPT, Bard, and Bing Chat to identify specific areas where improvements can be made.
3. Collaborate with the UI/UX team to address any issues related to Bing Chat’s user interface, aiming to make it more user-friendly and intuitive.
4. Explore ways to enhance Bing Chat’s information aggregation process to improve its effectiveness and accuracy.
5. Schedule a meeting with the development team to discuss potential updates or new features that can bridge any gaps and address the shortcomings highlighted in the meeting notes.
Assignments:
1. Research task (Action Item 1) – Assigned to [Researcher]
2. User feedback analysis (Action Item 2) – Assigned to [Data Analyst]
3. UI/UX improvements (Action Item 3) – Assigned to [UI/UX Designer]
4. Information aggregation enhancement (Action Item 4) – Assigned to [Development Team Lead]
5. Meeting scheduling and follow-up (Action Item 5) – Assigned to [Executive Assistant]Please review and let me know if any adjustments or clarifications are needed.
List of Useful Links:
AI Products for Business or Custom Development

AI Sales Bot
Welcome AI Sales Bot, your 24/7 teammate! Engaging customers in natural language across all channels and learning from your materials, it’s a step towards efficient, enriched customer interactions and sales

AI Document Assistant
Unlock insights and drive decisions with our AI Insights Suite. Indexing your documents and data, it provides smart, AI-driven decision support, enhancing your productivity and decision-making.

AI Customer Support
Upgrade your support with our AI Assistant, reducing response times and personalizing interactions by analyzing documents and past engagements. Boost your team and customer satisfaction

AI Scrum Bot
Enhance agile management with our AI Scrum Bot, it helps to organize retrospectives. It answers queries and boosts collaboration and efficiency in your scrum processes.
AI Agents
AI news and solutions
-
GPT-4 can solve math problems — but not in all languages
GPT-4 was tested in various experiments to solve math problems in 16 different languages.
-
UCSD and ByteDance Researchers Present ActorsNeRF: A Novel Animatable Human Actor NeRF Model that Generalizes to Unseen Actors in a Few-Shot Setting
Neural Radiance Fields (NeRF) is a neural network-based technique for capturing 3D scenes and objects from 2D images or sparse 3D data. It consists of two main components, “NeRF in” and “NeRF out” network. NeRF-based human…
-
Support Vector Machine with Scikit-Learn: A Friendly Introduction
Learn how to master SVM, a versatile model that every data scientist should have in their toolbox. Get a hands-on introduction to SVM in this informative article on Towards Data Science.
-
Neural Basis Models for Interpretability
The text discusses the introduction of a new interpretable model by Meta AI, with further information available in the article on Towards Data Science.
-
Google Researchers Introduce An Open-Source Library in JAX for Deep Learning on Spherical Surfaces
Researchers have developed an open-source library in JAX for deep learning on spherical surfaces. This new approach, utilizing spherical convolution and cross-correlation operations, shows promise in addressing challenges related to predicting chemical properties and understanding climate…
-
Meet Mistral-7B-v0.1: A New Large Language Model on the Block
Mistral-7B-v0.1 is a cutting-edge large language model (LLM) developed by Mistral AI. With 7 billion parameters, it is one of the most powerful LLMs available. This transformer model excels in natural language processing tasks such as…
-
AI language models could help diagnose schizophrenia
AI language models have been used by scientists to create new tools for analyzing speech patterns in patients with schizophrenia, allowing them to identify subtle signatures.
-
Researchers from the University of Manchester Introduce MentalLLaMA: The First Open-Source LLM Series for Readable Mental Health Analysis with Capacity of Instruction Following
Researchers from the University of Manchester have introduced MentalLLaMA, the first open-source series of large language models (LLMs) for interpretable mental health analysis. These models, including MentalLLaMA-chat-13B, outperform state-of-the-art techniques in terms of predictive accuracy and…
-
Class Imbalance: Exploring Undersampling Techniques
Undersampling techniques are used to address class imbalance in data. There are two main categories of undersampling: controlled and uncontrolled. Controlled techniques involve selecting a specific number of samples, while uncontrolled techniques remove points that meet…
-
Class Imbalance and Oversampling: A Formal Introduction
The text discusses the problem of class imbalance in machine learning and explores the use of resampling methods, specifically random oversampling, to solve it. It explains the concept of class imbalance, the impact it has on…
-
Adobe reveals its new Firefly Image 2 Model and related features
Adobe has introduced new AI image editing tools for Creative Cloud, including the Firefly Image 2 Model that can create more realistic images with added details. They have also integrated AI into Adobe Illustrator and Express,…
-
AI could consume the same energy as the Netherlands by 2027
A study predicts that the energy consumption of the AI industry could match that of the Netherlands by 2027. However, if AI growth slows, its environmental impact may be less severe. The study’s projections consider factors…
-
A New Machine Learning Research from MIT Shows How Large Language Models (LLMs) Comprehend and Represent the Concepts of Space and Time
Large Language Models (LLMs) like ChatGPT have gained popularity for their human-imitating capabilities in tasks like question answering, text summarization, and language translation. However, the extent to which these models truly understand the underlying data-generating process…
-
Meet the Air-Guardian: An Artificial Intelligence System Developed by MIT Researchers to Track Where a Human Pilot is Looking (Using Eye-Tracking Technology)
Researchers from MIT have developed a guardian system that improves the safety and performance of autonomous aircraft. The system uses visual attention to monitor both the pilot and itself during flight, and intervenes if attention discrepancies…
-
New – No-code generative AI capabilities now available in Amazon SageMaker Canvas
Amazon SageMaker Canvas is a service that allows business analysts and citizen data scientists to use pre-built machine learning models or build their own without writing code. It supports various use cases such as sentiment analysis,…
-
This AI Paper introduces FELM: Benchmarking Factuality Evaluation of Large Language Models
Large language models (LLMs) like ChatGPT have made significant advancements in generative AI, but they still struggle with generating inaccurate information. To address this, a benchmark called FELM has been created to evaluate factuality in LLM…
-
TimesNet: The Latest Advance in Time Series Forecasting
This text is about understanding and applying the TimesNet architecture for forecasting using Python.
-
Byte-Pair Encoding For Beginners
This text is an illustrative guide to the BPE tokenizer, explained in a plain and simple manner. It provides insights into the process and benefits of using BPE tokenizer for natural language processing.
-
How to Extend Pandas DataFrames with Custom Methods to Supercharge Code Functionality & Readability
This article provides a step-by-step guide on how to extend pandas DataFrames with custom methods. It includes examples of implementing probability and expectancy. Read more on Towards Data Science.
-
Dijkstra’s algorithm weighted by travel time in OSM networks
OSMnx 1.6 enables users to find the fastest and shortest route efficiently.