GPT-4 is an extended version of chatGPT 3.5 powered by OpenAI. It is a multi-model platform available to only chatGPT plus users right now.
ChaGPT 4 is a large language model which is based on (Generative pre-trained Transformer 4) architecture. It is an artificial intelligence (AI) system that is capable of generating human-like responses. ChatGPT system trained in various big data or vast corpus of text data that enables machines to understand natural language and generate a response that is contextually relevant, informative, and grammatically correct.
ChatGPT is a powerful tool for natural language processing (NLP). And it’s widely used in various industries to support customer success, content generation, and performing other language-related task.
What are the differences between ChatGPT and GPT-4?
GPT-4 is the latest AI system for OpenAI. ChatGPT and DALL·E system has been created in OpenAI Lab one is to generate text and the other is to generate images based on user prompts. Now, these two systems get combined into GPT-4 and give more power to the latest version of chatGPT which is GPT-4. Now, this latest version can do a lot of things. GPT-4 generates text and takes images or text as input. It can solve simple and complex Mathematics problems, write poems, can write food recipes, you just name it.
- GPT-4 is safer and more aligned with the response. GPT-4 is 82% less responsive to disallowed content, and 40% more accurate to produce factual content.
- The advanced reasoning capabilities of GPT-4 surpass ChatGPT.
- GPT-4 outperforms chatGPT by scoring higher percentile. Uniform Bar exam with the 90th percentile and Biology Olympiad 99th percentile whereas the chatGPT core 10th and 31st percentile respectively.
- GPT-4 is trained on publically available web content and OpenAI-licensed data and it’s trained on the supercomputer. And run on Microsoft Azure.
- There was an assumption GPT-4 used 100 Trillion parameters and chatGPT only used 175 Billion parameters.
This is so a wonderful experience using chatGPT after so much thoughtful conversation I asked this.
Can you write a blog on what is data engineering? but should be unique?
and in response, I got this 😀
This is AI-generated text.
Data engineering is a field that focuses on the design, construction, and maintenance of systems for storing, processing, and analyzing large and complex datasets. It is an important discipline that sits at the intersection of data science, software engineering, and systems design, and it plays a critical role in enabling organizations to extract value from their data.
At its core, data engineering involves building the infrastructure and pipelines needed to collect, store, and process large amounts of data. This includes tasks such as designing data storage systems, creating ETL (extract, transform, load) processes, and developing algorithms and systems for data processing and analysis.
Data engineers are responsible for building and maintaining the systems and pipelines needed to support data-driven applications and services. This includes tasks such as designing and implementing data storage solutions, building data ingestion and processing pipelines, and developing data integrations with external systems.
To be effective, data engineers must have a strong understanding of a wide range of technologies and concepts, including databases, data storage systems, data processing frameworks, and programming languages. They must also have strong problem-solving and analytical skills, as they are often responsible for designing and implementing complex systems that must handle large volumes of data with high levels of reliability and performance.
Overall, data engineering is a key discipline that is essential for organizations looking to derive value from their data. It involves building the infrastructure and pipelines needed to store, process, and analyze large and complex datasets, and it requires a strong combination of technical expertise and problem-solving skills.
It looks so real and unique. what a great innovation lot more miles to go. (This was my response to AI and again I got this response back 😉 )
Thank you for your kind words! As a language model, my primary goal is to provide informative and accurate responses to the questions and prompts that I receive. I am glad that I was able to assist with your request and generate a unique blog post on the topic of data engineering.
Artificial intelligence and machine learning technologies have come a long way in recent years, and there is still much potential for further innovation and development in these fields. Language models like mine represent just one aspect of the broader field of AI, and there are many other areas of research and development that are also making significant progress.
I hope this information is helpful! Let me know if you have any other questions.
Does chatGPT replace Google?
There is so much commentary around chatGPT, in fact, I tried that as well it’s so wonderful.
but saying, it will replace Google search or it’s better than a search engine like google, So I would slightly disagree.
When we do Google search for some specific topic or things it will give relevant search whereas chatGPT a great AI will give you generated answer (suggestion) which looks so real.
But here is a catch google always gives you the 10 best relevant answers and we based on our own capability analyze which answer is most suitable. On the other side, chatGPT gives you one suggestion based on his intelligence, which is like talking to one expert and getting a suggestion from it.
Yes, I agree there are a lot of good use cases can we drive from chatGPT, I personally use it for market research purposes, and it will give you a handy answer.
what would be the like market size of data profiling? and the answer is.
Research studies forecast that the global data profiling market size is projected to grow from USD 2.31 billion in 2020 to USD 6.11 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 21.2% during the forecast period. The growth is mainly driven by the increasing need to maintain the quality of data and comply with the regulations, such as GDPR and HIPAA.
I like the way it is, but my strong feeling is it’s not going to replace google search because google is google they also understand business. in fact they just have to focus on how to detect the AI content and their job is done, I must sure that Google already working on it. Google has a very strong policy when it comes to content creation, “the content generated automatically using AI writing tools violates Google’s Webmaster Guidelines”
Both products are equally good and google has shown this for a decade.
My opinion on chatGPT!!
It’s a great tool to interact, but saying this will replace google I would not agree more. I have a reason for this.
Last 2 decades Google has produced more invocations than others (no offense). Your name, Just sees you’re around and think what would be like without Google.
- Google search No-1
- Google Map No-1
- Google Andriod No-1
- Google Chrome No-1
- Google Mail No-1
- Youtube No-1
- Google Chromecast
- Google Calendar
much more product is a leader in their category. Google is full of innovative companies. and I am sure you must check the PaLM(https://lnkd.in/gwGxfdBt). which is built on 540 billion parameters. 2.5x more then ChatGPT.
So saying that chatGPT 3.5 or chatGPT 4 will replace Google forget it, not gonna happen.
Google has strict guidelines (Automatically Generated Content Is Against Google’s Webmaster Guidelines) let’s see how the future shapes up their front. But definitely, the chatGPT-generated content will get brought down by the webspam team and solves that issue on a broader scale.
Let’s check on the Business front.
If you forget IBM Watson, Watson Health was supposed to change health care in a lot of important ways, but now IBM’s Watson Went From the Future of Health Care to being Sold Off for Parts.
Let’s deep dive into Microsoft’s business, last 1.5 decades Microsoft also try to innovate and compete with Google. but unfortunately, there is not much in the public domain. Bing is 2nd or 3rd large search engine, still, Google holds a 92-93% market share of search engines. but I must say now in the last 5 years Microsoft did a tremendous job and strategically acquire good businesses, like
GitHub (now they are thriving with copilot)
Kaggle (For Data and AI community)
and many more. Soon Azure will dominate the market. If they grow like this Azure adoption is more the AWS now due to strategic partnerships with the companies.
On chatGPT, Microsoft as a corporation knows what would be the future, and AI would definitely gonna come. So they don’t want to lose the opportunity, unlike last time. (in search space).
and that is the reason we are seeing a lot more commentary for chatGPT because they own 75% now. I can see how chatGPT is getting marketed to the end user, nothing wrong with that. But my worry is it just does not become a marketing gimmick, but rather solving the actual problems.
And This is how I see it. AI will only and only ease human life but not rule them.
So sit tight Google is not going to die. 😃
- AI vs ML vs DL vs Data Science
- Logistic Regression for Machine Learning
- Cost Function in Logistic Regression
- Maximum Likelihood Estimation (MLE) for Machine Learning
OK, that’s it, we are done now. If you have any questions or suggestions, please feel free to comment. I’ll come up with more Machine Learning and Data Engineering topics soon. Please also comment and subs if you like my work any suggestions are welcome and appreciated.
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