For the past few months, the term ChatGPT has been trending on all possible online platforms and in the media. Its sudden rise in popularity has sparked numerous discussions and debates. Undoubtedly, the introduction of ChatGPT has marked a new chapter in the evolution of humankind, revolutionizing how we communicate with machines and creating new opportunities for businesses and individuals.
But what do we know about ChatGPT so far? Only so little. Understanding the mechanism behind ChatGPT will shed light on the AI technology used to create it and the magnitude of what it can do for us.
When we talk about ChatGPT, we actually refer to GPT – 3, which is a product of cutting-edge innovations in the field of artificial intelligence and natural language processing. Basically, ChatGPT is powered by GPT – 3, which is short for Generative Pretrained Transformer 3, developed by OpenAI, an American artificial intelligence research laboratory. This is the largest and most powerful language processing AI model to date that contains 175 billion parameters, which is more than ten times the number of parameters in its predecessor, GPT-2.
What GPT-3 can do is insane
It can generate human-like text with a wide range of applications such as language modeling, translation, generating text for chatbots, and much more.
Since its introduction to the world, it has been banned in some US, France, and India schools. Microsoft has used it to revolutionize its Bing search engine. GPT-3 has been used as a creative writing partner for composing chords for new songs. It has been used to draft legally-binding contracts sparking debates among lawyers and nonlawyers alike.
Recently, OpenAI company has expanded its set of offerings by launching a premium version called ChatGPT Pro. For a monthly subscription fee of $20 (or approximately £16), users can enjoy an array of enhanced features such as prioritized access and quicker loading times.
We have not had time to recover from the shock of GPT-3 as GPT-4 makes its loud entrance into the market, promising to handle “much more nuanced instructions,” according to its creators.
GPT-4 has been released this week. However, it is only available to Plus members for now.
In this article, we’ll look into GPT-4 and what to expect from it. But before that, let’s get to know GPT-3 a little bit better.
Overview of GPT-3 and its Place in the AI Landscape
Over the last few years, investments in the AI sector have been growing dramatically. Only in 2021, total AI investments reached a whopping $77.5 billion, completely smashing the previous year’s all-time high of $36 billion. Driven by breakthroughs and innovations in fields like machine learning and deep learning techniques, we have now entered a new era of a rapidly evolving landscape of AI technology. GPT -3 is a prime example of this technological advancement.
Undoubtedly, GPT-3 serves as a momentous quantum leap in the AI landscape due to its ultra-modern performance, great versatility, and ability to carry out zero-shot and few-shot learning. Its impact reaches much further than just technological progress, encompassing broader implications for the AI field and sparking conversations on pivotal things such as scalability, ethics, and safety, subsequently opening new doors to AI research and development, paving the way to new investigations and unlocking new potential uses across a plethora of industries.
How does GPT-4 improve upon GPT-3?
Probably the main differences between GPT-4 and GPT-3 are that GPT-4 is multimodal. It possesses the ability to interpret and understand visuals, allowing it to depict designs on garments, offer advice on utilizing fitness apparatuses, or translate labels in the user’s desired language merely by inspecting an uploaded picture.
The differences don’t end here.
In the words of Linas Beliunas, GPT-4 “passed basically every exam with flying colors, and its reasoning capabilities are far more advanced than ChatGPT.” On top of that, with a capacity to accommodate up to 25,000 words in context, it can encompass entire documents within a single prompt.
According to OpenAI, “GPT-4 outperforms ChatGPT by scoring in higher approximate percentiles among test-takers,” adding that “we spent six months making GPT-4 safer and more aligned. GPT-4 is 82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses than GPT-3.5 on our internal evaluations.”
The potential impact of GPT-4
GPT-4, the highly anticipated AI language model by OpenAI, is poised to be a game-changer, with the potential to take the world by storm and redefine the limits of what’s possible in artificial intelligence. Forget about GPT-3. GPT -4 is expected to leave its predecessors in the dust, outshining the earlier models with its superior language generation, understanding, and cognitive capabilities, setting new standards in the field of AI.
GPT-4 exploits deep learning methodologies to put together human-like text based on input data. Building upon the foundation laid by its predecessors—GPT-1, GPT-2, and GPT-3—it incorporates state-of-the-art algorithms and methods to enhance its ability to generate language that closely resembles human writing.
To achieve an exhaustive understanding of the subtle complexities of human language, GPT-4 will go through a wealth of data as pre-training encompassing text, audio, and visual inputs. By capitalizing on this knowledge, GPT-4 will produce text that emulates human writing, Establishing it as an indispensable resource for such tasks as content creation, chatbots, and virtual assistants.
It is believed that GPT-4 will impact a wide range of industries, including:
Marketing & advertising – it could create copy for ad campaigns, email marketing, and personalized content for targeted audiences. It is, however, too soon to say whether it will be able to engage people’s senses by crafting vivid descriptions, evoking emotions, and painting mental images that resonate with the audience.
Education & research – it could be an instrument for tutoring, answering questions, summarizing research papers, and providing personalized learning experiences.
Software development – it could generate code snippets from natural language descriptions, streamline programming tasks, and improve developer productivity
Entertainment – it could be employed in generating dialogues for video games, scripts for movies or TV shows, and creating interactive storytelling experiences.
Customer service – Chatbots and virtual assistants powered by GPT-4 could provide more accurate and human-like support, leading to enhanced customer experiences.
GPT-4’s abilities have been recognized by big firms. Morgan Stanley’s wealth management unit will use GPT-4 “to access, process, and synthesize content to assimilate MSWM’s own expansive range of intellectual capital in the form of insights into companies, sectors, asset classes, capital markets, and regions around the world.” As the exploration of its business applications expands, more companies are believed to follow suit and integrate GPT-4 in their operations.
GPT-4 Multimodals Model
Every media outlet or blog writing about GPT-4 praises its multimodal feature, but what does it actually mean?
GPT-4 is a large multimodal AI model, which means that it is, quote, “accepting image and text inputs, emitting text outputs, that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.” This basically signifies that GPT-4 comprehends both textual and visual data, an improvement over GPT-3.5, its predecessor, which only accepted text. This advanced AI model is able to not just caption but also read sophisticated images, such as recognizing a Lightning Cable adapter when showcasing an image of a connected iPhone.
Currently, the image recognition feature is made available to a select group of OpenAI clients, such as Be My Eyes, that have incorporated GPT-4 into their Virtual Volunteer function to assist users by answering queries about the images they submit. OpenAI has written about this collaboration here.
According to its creators, “ if a user sends a picture of the inside of their refrigerator, the Virtual Volunteer will not only be able to correctly identify what’s in it but also extrapolate and analyze what can be prepared with those ingredients. The tool can also then offer a number of recipes for those ingredients and send a step-by-step guide on how to make them.”
GPT-4’s steerability tooling is a game changer, opening up a whole new world of possibilities for developers. Picture OpenAI’s new API capability, “system” messages, as the rudder that steers the AI ship, guiding its style and tasks through clear-cut instructions. These system messages, soon to grace ChatGPT, set the stage and draw the line for the AI’s upcoming interactions.
Imagine a system message that paints this picture: “You are a tutor that always responds in the Socratic style. You never give the student the answer, but always try to ask just the right question to help them learn to think for themselves. You should always tune your question to the interest and knowledge of the student, breaking down the problem into simpler parts until it’s at just the right level for them.”
Despite this amazing, to say the least, feature, OpenAI acknowledges that GPT-4 is far from perfect. The AI still has inaccuracies and fumbles in reasoning, occasionally exuding strong confidence despite these missteps.
Key Features of GPT-4
GPT-4 is truly the cream of the crop, offering a plethora of cutting-edge features that put it head and shoulders above its predecessors:
Enhanced language generation capabilities
GPT-4 has made significant strides in producing coherent, contextually relevant, and fluent text. This improved skill set benefits various applications, from content creation to engaging conversations. GPT-4 generates concise and meaningful content, making it a dependable partner for those seeking an eloquent and accurate text.
Improved contextual understanding
GPT-4 has honed its ability to understand context, allowing it to engage in more meaningful interactions and provide accurate information. Embracing the idea that “knowledge is power,” GPT-4’s enhanced contextual understanding unlocks its potential to offer insightful and relevant responses. It actively participates in the conversation, ensuring that its contributions align with the topic at hand.
Multimodal learning capabilities
GPT-4 expands its capabilities beyond text, diving into the realm of visual data. As a versatile AI model, it can process and interpret images alongside the text, broadening the scope of potential applications. Its creators have managed to seamlessly integrate its multimodal learning abilities. It can now understand and interpret visual narratives, paving the way for new opportunities in AI applications.
GPT-4’s remarkable ability to adapt and undergo pre-training allows it to excel in a variety of specialized tasks. When GPT-4 is pre-trained on smaller, task-specific datasets, it can be fine-tuned to tackle particular challenges, such as language translation, text summarization, and question answering. This adaptive process molds the AI model to better serve specific purposes, transforming it into a versatile and valuable tool that caters to a wide range of applications. By harnessing the power of adaptation and pre-training, GPT-4 becomes a formidable ally in the quest for AI-driven solutions to an assortment of challenges in the world of text and data processing.
Ethical considerations and bias mitigation: OpenAI has taken the bull by the horns, tackling ethical concerns and biases that lurk within AI systems. GPT-4 strives to “do no harm” (as per Google’s Code of Conduct), minimizing biases to create a more reliable and responsible tool for users and paving the way for a more “fair and just” (according to Timnit Gebru) AI future. With great power comes great responsibility, and OpenAI recognizes the importance of ensuring that GPT-4 is not only a powerful tool but also an ethical one. By addressing biases and ethical concerns, GPT-4 is poised to make a positive impact on the world, forging a path toward a more equitable and transparent AI landscape.
Challenges and Limitations
There are no doubts that GPT-4 is great, but despite the impressive advancements in the technology, there are still several challenges and limitations that need to be addressed:
GPT-4 may sometimes generate content that contains inaccuracies or “hallucinated” facts, even when it appears to be confident in its responses. This limitation makes it essential for users to verify the information provided by the AI before relying on it.
Context understanding limitations
Although GPT-4 has made strides in contextual understanding, it may occasionally misinterpret the context or fail to address specific nuances of a user’s query, resulting in responses that could be irrelevant or not fully aligned with the user’s intent.
Ethical concerns and biases
As with any AI model, GPT-4 is susceptible to inherent biases present in the data it has been trained on. OpenAI has made efforts to mitigate biases and address ethical concerns, but it remains an ongoing challenge to ensure GPT-4 operates in a fair, unbiased, and ethical manner.
GPT-4 can sometimes be overly verbose in its responses, providing more information than necessary or repeating certain phrases or ideas. Striking the right balance between providing sufficient information and maintaining brevity is an area where further improvement is needed. Sharif Shameem, a user of GPT, comments that “adding small fine-tuned “summarization” model as a post-processing step would make ChatGPT conversations feel way more concise and natural.”
The challenge of steerability for GPT-4 lies in finding the right balance between providing useful, relevant content and adhering to specific user-defined constraints, goals, or styles. While GPT-4 has made significant strides in improving steerability, it can still be difficult to guide the AI model to generate precise, creative, or nuanced responses that align perfectly with user intent or desired style.
Some potential issues that may arise with steerability include:
Inability to consistently follow user instructions: GPT-4 might not always fully grasp or adhere to user-defined constraints or instructions, which could lead to outputs that don’t align with the intended goal or style.
Over- or under-steering: Striking the right balance between allowing the AI model to be creative and ensuring it follows the specified guidelines is a challenging aspect of steerability. Over-steering could limit the model’s potential, while under-steering might result in outputs that don’t meet user expectations.
Difficulty in addressing nuanced or complex tasks: GPT-4 might struggle to generate responses that require a deep understanding of context, subtle meanings, or complex tasks, making it challenging to steer the model toward the desired output effectively.
Balancing safety and usefulness: Ensuring that GPT-4’s output remains safe and within ethical boundaries while still being useful and informative is an ongoing challenge in the realm of steerability.
Resource consumption: GPT-4 is a large-scale model that demands considerable computational resources for both training and deployment. This can make it less accessible to individuals or organizations with limited resources and could contribute to increased environmental impacts due to energy consumption.
Despite these challenges and limitations, GPT-4 has shown significant potential in various applications, and ongoing research and development efforts aim to address and mitigate these issues to make the AI model even more robust, efficient, and useful.
In conclusion, GPT-4 represents a significant milestone in the field of artificial intelligence, showcasing remarkable advancements in language generation, contextual understanding, multimodal learning, domain-specific adaptation, and efforts toward addressing ethical concerns and biases. However, like any technology, it still has its limitations and challenges, including steerability, controllability, and occasional inaccuracies.
As we look to the future, we can expect continuous improvements in GPT-4, and its successors, as researchers and developers work to address these challenges.