ChatGPT, an advanced generative AI chatbot, has gained global attention for its powerful ChatGPT capabilities. OpenAI released it for public use in November 2022. Instantly, ChatGPT became a massive success, amassing over one million users within just five days. The AI tool continues to make headlines and attract more users each day.
With more than 25 million daily visits, ChatGPT dominates the generative AI market. But does it truly meet expectations? This post explores the technology behind ChatGPT capabilities, the improvements in GPT-4, and other emerging AI tools.
Understanding ChatGPT capabilities and how it works
ChatGPT stands for Generative Pretrained Transformer. It relies on the ‘transformer’ architecture to process large volumes of data efficiently. These models learn and perform natural language processing tasks with impressive accuracy. The model used by ChatGPT, derived from the GPT-3.5 series, boasts 175 billion parameters, making it the largest trained language model.
To function, GPT requires extensive training on a vast range of texts. For instance, GPT-3 trained on data comprising over 8 million documents and 10 billion words. Through this training, the model learns to recognise language patterns, generate coherent responses, and perform tasks effectively.
ChatGPT explains its own purpose as follows:
“ChatGPT is an advanced language AI model created by OpenAI. It generates human-like text based on input data and prompts, making it ideal for customer service, language translation, and content creation. Its ability to understand context and produce coherent responses sets it apart in the field of generative AI.”
Unpacking the advancements of GPT-4
GPT-4 introduced notable improvements and new features. One major change is its multimodal capability, which supports both text and image inputs. Unlike GPT-3.5, which only handles text, GPT-4 scans documents, understands images, and responds appropriately. For example, users can upload images or documents, and GPT-4 can generate insights or answers based on them.
Additionally, GPT-4 demonstrates greater creativity and better comprehension of nuanced language. It can now produce complex writing like poems, songs, and screenplays, while adapting to the user’s writing style. This capability enhances personalisation and enriches user experience.
ChatGPT capabilities in testing and coding
GPT-4 showcases impressive reasoning skills and passes standardised tests with higher accuracy. It now ranks in the top 10% of US students taking the Uniform Bar Examination. The model can even score a perfect five on Advanced Placement exams in subjects like calculus and psychology. Developers benefit from improved coding abilities, as GPT-4 can now understand, review, and generate code across multiple languages.
A significant feature for developers is the API’s “system” messages. This allows users to set style and task guidelines, accelerating development. OpenAI is rolling out this feature gradually, with priority access given to those on the waitlist.
Acknowledging the limitations of GPT-4
Despite its advancements, GPT-4 has limitations. It still produces “hallucinations,” or confident-sounding but factually incorrect outputs. These errors stem from inherent biases, outdated data, or an incomplete understanding of real-world events. Although GPT-4 performs 40% better in reducing hallucinations compared to GPT-3.5, challenges remain. OpenAI acknowledges that social biases and adversarial prompts need addressing.
Another current limitation is the image input feature’s restricted availability. OpenAI partners with specific organisations to test this feature before a wider release. For now, users can access GPT-4’s text capabilities through ChatGPT Plus, which costs $20 monthly. Microsoft’s Bing Chat, also powered by GPT-4, offers a free alternative.
Other notable generative AI tools
While ChatGPT capabilities are impressive, other AI tools are worth exploring. In March 2023, Microsoft launched GPT-4 in preview through Azure OpenAI Service. This service gives Azure users access to powerful models like GPT-3.5 and DALL·E 2, with enterprise-ready features like data security and compliance.
Microsoft’s GitHub Copilot also stands out. This tool, built on the Codex model (a variant of GPT-3), assists developers by generating code snippets and automating repetitive tasks. It boosts productivity and eases coding challenges.
Google entered the generative AI market with Bard, an AI chatbot using LaMDA models. Unlike ChatGPT, Bard sources its data from the web, offering a unique approach to providing real-time information. Although Bard’s public access is limited, interested users can join a waitlist for early access.
Amazon’s contribution, Bedrock, enables organisations to build scalable generative AI applications. This serverless service provides pre-trained models from various developers, including in-house Titan FMs. Bedrock’s flexible offerings make it suitable for customisation across different industries.
Transforming businesses with generative AI
AI tools are becoming essential for business growth and productivity. Generative AI technologies, such as those using transformer models, are advancing rapidly. The future promises more innovations, making 2023 a landmark year for enterprise-level AI solutions. Whether it’s ChatGPT, Bard, or Amazon’s Bedrock, businesses must adapt to harness the full potential of these tools.
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