From Watson to ChatGPT: AI chatbots and limitations
The launch of ChatGPT and the responses it provides brings Conversation AI back to the forefront and makes Conversation AI available to everyone through a simple web interface. We've seen many creative ways to use ChatGPT and how it might impact the future as well as questions surrounding whether it will replace the Google search engine and jobs.
Okay, let us solve this problem through the following analysis.
From the early Watson system to ChatGPT, conversational AI still has a basic problem.
Lack of domain intelligence.
While ChatGPT is undoubtedly an advancement in the field of conversational AI, I would like to mention the following from my book - Real AI: Chatbots (published in 2019).
“Artificial intelligence can learn, but it cannot think.”
Thinking about how to use the output of artificial intelligence systems is always left to humans. An AI system and its knowledge will always be limited to what it has learned, but can never generalize (like humans) where domain expertise and intelligence are required.
What is an example of domain intelligence?
As a simple example, you ask a conversational AI agent to “recommend outfits for shorts and saris.”
Fundamentally, any technical person will see them as two different options - match the outfit with shorts and match the outfit with a saree and either ask clarifying questions or imply that these options are not Intersecting, cannot be combined.
But for ChatGPT (or any general conversational AI), the response looks like this. Clearly trying to fill in some responses without understanding the domain and context. This is a very simple example, but the complexity increases exponentially because deep expertise and relevance are required – just like a doctor recommending a treatment plan. This is the exact reason why we see so many failures when using AI agents to solve health problems. They attempt to train general AI rather than build domain expert AI systems.
Another issue with this generative conversational AI system is the following:
Interpretability – allowing the AI output to explain how it arrived. I described this in my previous blog – Responsible And Ethical AI
Trust and Recommendation Bias – Correct Recommendation and Adaptability. I've explained this in my previous blog.
For more details, I explain this concept in my short e-book – Real Artificial Intelligence: Chatbots (2019).
You can find the book online at my website or sign up for a free video course.
The purpose of this blog is to educate people about ChatGPT and its current limitations. Any technology usually has a set of limitations, and understanding these limitations will help you keep them in mind when designing and developing your solution.
ChatGPT will undoubtedly advance the development of conversational artificial intelligence, and building it will take a lot of time and effort. However, enterprise adoption is still a long way off.
To make ChatPT relevant for enterprise adoption, we need the following:
- Domain Adaptability
- Domain Intelligence
- Explainability
- Transparency
- Unbiased
- Privacy
- Scalability - compute power for training and inference
- Reduce environmental footprint
In my opinion, ChatGPT and other AI chatbots will be similar to any other tool to help you get the information you need, you will use your mind and intelligence to Get the job done.
So, rest easy; the current version of ChatGPT does not replace anything that requires thought and deep expertise! !
The above is the detailed content of From Watson to ChatGPT: AI chatbots and limitations. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1387
52
ChatGPT now allows free users to generate images by using DALL-E 3 with a daily limit
Aug 09, 2024 pm 09:37 PM
DALL-E 3 was officially introduced in September of 2023 as a vastly improved model than its predecessor. It is considered one of the best AI image generators to date, capable of creating images with intricate detail. However, at launch, it was exclus
Bytedance Cutting launches SVIP super membership: 499 yuan for continuous annual subscription, providing a variety of AI functions
Jun 28, 2024 am 03:51 AM
This site reported on June 27 that Jianying is a video editing software developed by FaceMeng Technology, a subsidiary of ByteDance. It relies on the Douyin platform and basically produces short video content for users of the platform. It is compatible with iOS, Android, and Windows. , MacOS and other operating systems. Jianying officially announced the upgrade of its membership system and launched a new SVIP, which includes a variety of AI black technologies, such as intelligent translation, intelligent highlighting, intelligent packaging, digital human synthesis, etc. In terms of price, the monthly fee for clipping SVIP is 79 yuan, the annual fee is 599 yuan (note on this site: equivalent to 49.9 yuan per month), the continuous monthly subscription is 59 yuan per month, and the continuous annual subscription is 499 yuan per year (equivalent to 41.6 yuan per month) . In addition, the cut official also stated that in order to improve the user experience, those who have subscribed to the original VIP
Can fine-tuning really allow LLM to learn new things: introducing new knowledge may make the model produce more hallucinations
Jun 11, 2024 pm 03:57 PM
Large Language Models (LLMs) are trained on huge text databases, where they acquire large amounts of real-world knowledge. This knowledge is embedded into their parameters and can then be used when needed. The knowledge of these models is "reified" at the end of training. At the end of pre-training, the model actually stops learning. Align or fine-tune the model to learn how to leverage this knowledge and respond more naturally to user questions. But sometimes model knowledge is not enough, and although the model can access external content through RAG, it is considered beneficial to adapt the model to new domains through fine-tuning. This fine-tuning is performed using input from human annotators or other LLM creations, where the model encounters additional real-world knowledge and integrates it
To provide a new scientific and complex question answering benchmark and evaluation system for large models, UNSW, Argonne, University of Chicago and other institutions jointly launched the SciQAG framework
Jul 25, 2024 am 06:42 AM
Editor |ScienceAI Question Answering (QA) data set plays a vital role in promoting natural language processing (NLP) research. High-quality QA data sets can not only be used to fine-tune models, but also effectively evaluate the capabilities of large language models (LLM), especially the ability to understand and reason about scientific knowledge. Although there are currently many scientific QA data sets covering medicine, chemistry, biology and other fields, these data sets still have some shortcomings. First, the data form is relatively simple, most of which are multiple-choice questions. They are easy to evaluate, but limit the model's answer selection range and cannot fully test the model's ability to answer scientific questions. In contrast, open-ended Q&A
SOTA performance, Xiamen multi-modal protein-ligand affinity prediction AI method, combines molecular surface information for the first time
Jul 17, 2024 pm 06:37 PM
Editor | KX In the field of drug research and development, accurately and effectively predicting the binding affinity of proteins and ligands is crucial for drug screening and optimization. However, current studies do not take into account the important role of molecular surface information in protein-ligand interactions. Based on this, researchers from Xiamen University proposed a novel multi-modal feature extraction (MFE) framework, which for the first time combines information on protein surface, 3D structure and sequence, and uses a cross-attention mechanism to compare different modalities. feature alignment. Experimental results demonstrate that this method achieves state-of-the-art performance in predicting protein-ligand binding affinities. Furthermore, ablation studies demonstrate the effectiveness and necessity of protein surface information and multimodal feature alignment within this framework. Related research begins with "S
SK Hynix will display new AI-related products on August 6: 12-layer HBM3E, 321-high NAND, etc.
Aug 01, 2024 pm 09:40 PM
According to news from this site on August 1, SK Hynix released a blog post today (August 1), announcing that it will attend the Global Semiconductor Memory Summit FMS2024 to be held in Santa Clara, California, USA from August 6 to 8, showcasing many new technologies. generation product. Introduction to the Future Memory and Storage Summit (FutureMemoryandStorage), formerly the Flash Memory Summit (FlashMemorySummit) mainly for NAND suppliers, in the context of increasing attention to artificial intelligence technology, this year was renamed the Future Memory and Storage Summit (FutureMemoryandStorage) to invite DRAM and storage vendors and many more players. New product SK hynix launched last year
Laying out markets such as AI, GlobalFoundries acquires Tagore Technology's gallium nitride technology and related teams
Jul 15, 2024 pm 12:21 PM
According to news from this website on July 5, GlobalFoundries issued a press release on July 1 this year, announcing the acquisition of Tagore Technology’s power gallium nitride (GaN) technology and intellectual property portfolio, hoping to expand its market share in automobiles and the Internet of Things. and artificial intelligence data center application areas to explore higher efficiency and better performance. As technologies such as generative AI continue to develop in the digital world, gallium nitride (GaN) has become a key solution for sustainable and efficient power management, especially in data centers. This website quoted the official announcement that during this acquisition, Tagore Technology’s engineering team will join GLOBALFOUNDRIES to further develop gallium nitride technology. G
A new era of VSCode front-end development: 12 highly recommended AI code assistants
Jun 11, 2024 pm 07:47 PM
In the world of front-end development, VSCode has become the tool of choice for countless developers with its powerful functions and rich plug-in ecosystem. In recent years, with the rapid development of artificial intelligence technology, AI code assistants on VSCode have sprung up, greatly improving developers' coding efficiency. AI code assistants on VSCode have sprung up like mushrooms after a rain, greatly improving developers' coding efficiency. It uses artificial intelligence technology to intelligently analyze code and provide precise code completion, automatic error correction, grammar checking and other functions, which greatly reduces developers' errors and tedious manual work during the coding process. Today, I will recommend 12 VSCode front-end development AI code assistants to help you in your programming journey.
