Comparing OpenAI’s ChatGPT and Microsoft’s Copilot mobile apps

Comparing OpenAI’s ChatGPT and Microsoft’s Copilot mobile apps

by | May 19, 2024 | A.I

OpenAI’s ChatGPT and Microsoft’s Copilot are two powerful AI tools that have revolutionized the way we interact with technology. While both are designed to assist users in various tasks, they each have unique features that set them apart.

OpenAI’s ChatGPT

ChatGPT, developed by OpenAI, is a large language model chatbot capable of communicating with users in a human-like way¹⁷. It can answer questions, create recipes, write code, and offer advice¹⁷. It uses a powerful generative AI model and has access to several tools which it can use to complete tasks²⁶.

Key Features of ChatGPT

  • Chat with Images: You can show ChatGPT images and start a chat.
  • Image Generation: Create images simply by describing them in ChatGPT.
  • Voice Chat: You can now use voice to engage in a back-and-forth conversation with ChatGPT.
  • Web Browsing: Gives ChatGPT the ability to search the internet for additional information.
  • Advanced Data Analysis: Interact with data documents (Excel, CSV, JSON).

Microsoft’s Copilot

Microsoft’s Copilot is an AI companion that works everywhere you do and intelligently adapts to your needs. It can chat with text, voice, and image capabilities, summarize documents and web pages, create images, and use plugins and Copilot GPTs

Key Features of Copilot

  • Chat with Text, Voice, and Image Capabilities: Copilot includes chat with text, voice, and image capabilities/
  • Summarization of Documents and Web Pages: It can summarize documents and web pages.
  • Image Creation: Copilot can create images.
  • Web Grounding: It can ground information from the web.
  • Use of Plugins and Copilot GPTs: Copilot can use plugins and Copilot GPTs.

Comparison of Mobile App Features

Feature OpenAI’s ChatGPT Microsoft’s Copilot
Chat with Text Yes Yes
Voice Input Yes Yes
Image Capabilities Yes Yes
Summarization No Yes
Image Creation Yes Yes
Web Grounding No Yes

What makes the difference, the action button for the iPhone

The action button on iPhones, available on the iPhone 15 Pro and later models, is a customizable button for quick tasks. By default, it opens the camera or activates the flashlight. However, users can customize it to perform various actions, including launching a specific app. When set to launch an app, pressing the action button will instantly open the chosen app, such as the ChatGPT voice interface. This integration is further enhanced by the new ChatGPT-4.0 capabilities, which offer more accurate responses, better understanding of context, and faster processing times. This makes voice interactions with ChatGPT smoother and more efficient, allowing users to quickly and effectively communicate with the AI.

 

 

 

 

The ChatGPT voice interface is one of my favorite features, but there’s one thing missing for it to be perfect. Currently, you can’t send pictures or videos during a voice conversation. The workaround is to leave the voice interface, open the chat interface, find the voice conversation in the chat list, and upload the picture there. However, this brings another problem: you can’t return to the voice interface and continue the previous voice conversation.

Microsoft Copilot, if you are reading this, when will you add a voice interface? And when you finally do it, don’t forget to add the picture and video feature I want. That is all for my wishlist.

 

Understanding AI, AGI, ML, and Language Models

Understanding AI, AGI, ML, and Language Models

by | Dec 4, 2023 | A.I

Understanding AI, AGI, ML, and Language Models

Artificial Intelligence (AI) is a broad field in computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI encompasses various subfields, including machine learning, natural language processing, robotics, and more. Its primary goal is to enable computers to perform tasks such as decision-making, problem-solving, perception, and understanding human language.

Machine Learning (ML), a subset of AI, focuses on developing algorithms and statistical models that enable computers to learn from and make predictions or decisions based on data. Unlike traditional programming, where humans explicitly code the behavior, machine learning allows systems to automatically learn and improve from experience. This learning process is driven by feeding algorithms large amounts of data and allowing them to adjust and improve their performance over time.

One of the most notable applications of ML is in the development of Language Models (LMs), which are algorithms designed to understand, interpret, and generate human language. These models are trained on vast datasets of text and can perform a range of language-related tasks, such as translation, summarization, and even generating human-like text. Language models like GPT (Generative Pretrained Transformer) are examples of how AI and ML converge to create sophisticated tools for natural language processing.

Artificial General Intelligence (AGI), on the other hand, represents a level of AI that is far more advanced and versatile. While current AI systems, including language models, are designed for specific tasks (referred to as narrow AI), AGI refers to a hypothetical AI that has the ability to understand, learn, and apply its intelligence broadly and flexibly, much like a human. AGI would possess the ability to reason, solve problems, comprehend complex ideas, learn from experience, and apply its knowledge to a wide range of domains, effectively demonstrating human-like cognitive abilities.

The relationship between AI, ML, AGI, and language models is one of a nested hierarchy. AI is the broadest category, under which ML is a crucial methodology. Language models are specific applications within ML, showcasing its capabilities in understanding and generating human language. AGI, while still theoretical, represents the potential future of AI where systems could perform a wide range of cognitive tasks across different domains, transcending the capabilities of current narrow AI systems.

In summary, AI is a vast field aimed at creating intelligent machines, with machine learning being a key component that focuses on data-driven learning and adaptation. Language models are a product of advancements in ML, designed to handle complex language tasks. AGI remains a goal for the future, representing a stage where AI could match or surpass human cognitive abilities across a broad spectrum of tasks and domains.