OpenAI on the Brink of Extinction: Prepare to See Something New!
This Tool Has The Potential To Overpower All The AI Chatbots
AI race is at its peak right now and everyone wants to make the most advanced AI tools. Now another advanced AI tool had come into the market to defeat ChatGPT. I don’t think many people had known about this new AI tool which can completely eliminate ChatGPT from the market.
As we all know in the field of science and technology new discoveries, developments, and upgrades are essential because if you do not upgrade or advance your technology then someone else will overtake you and then you will fall behind. I have seen many times that people shift to other products because everyone like advanced and new things.
Today, in this article we are going to discuss 2 things: First is the hot rumor circulating in the market right now about the bankruptcy of OpenAI, and the second one is the new AI tool ORCA which has what it takes to defeat ChatGPT.
OpenAI
In July 2019, Microsoft gave $ 1 billion Funding to OpenAI and another $10 Billion in January 2023. After learning about this, I am sure that Microsoft must have seen something in OpenAI that’s why they were willing to fund this huge amount of money.
Bankrupt?
The possibility of dark clouds coming on the future of OpenAI company is increasing; I am not saying this, it is said by OpenAI’s founder Sam Altman himself. Sam Altman is saying we could be bankrupt by the end of 2024. Hearing this, everyone’s senses have flown like parrots.
I know, you may be thinking that Sam Altman is gone mad, seriously who fool announce to the public that his own company is going to bankrupt. But there are several reasons behind why Sam Altman had to announce that they will get bankrupt soon. The OpenAI ChatGPT tool costs roughly $700k per day including server maintenance, electricity, etc… to run; so to reduce this cost, OpenAI has introduced the premium tool GPT-4 version with a subscription.
However, even after monetizing GPT3.5 and GPT-4, the company is still running into losses. With this loss, it appears that the business has become profitable is just an illusion. The number of users has also decreased by 12%. There were 1.7 billion users in June and in the next month (July) the users decreased by 0.2 Billion to 1.5 billion.
For now, there is no problem because OpenAI received $10 Billion funding for Microsoft but for the long run they need to find a solution. I do not know if you already know or not but OpenAI announced a few months ago that the company will make $200 million in 2023 and $1 billion revenue in 2024, but considering how things are right now, I doubt they will be able to make that much money?
According to Sam, the company’s ability to train new models is being affected by the US-China tech competition and the lack of GPUs (Graphics Processing Units) on the market.
They cannot even launch their own IPO because the company is running in a loss and there is no profit so on what basis they would think about launching an IPO? No matter how wonderful the company’s business plan is, if it does not become profitable, it will collapse.
AI Industry
For many investors, chatbots are the form of a new revolution in technology investment. Microsoft is not working on new AI tools which can drive public interest in AI technology over the roof.
The name of this tool is ORCA. ORCA tool is many times faster than ChatGPT and accuracy is going to be very high. The purpose of Microsoft for developing this AI tool is to reshape the world of AI.
ORCA
Language Model — 30 Billion Parametric Model
ORCA develops its own ability by emulating and learning from the reasoning process of large languages
Let me explain it to you with a simple example, we all have seen many sci-fi movies. In some movies, robots comes from another planet on our earth and learn everything by overserving people, surroundings, and technology. After collecting all the data they put their knowledge in the program to develop its own capability.
I hope you now know what ORCA is and how it will work, you can also compare it to those alien robots we have seen in movies.
I was quite confused when I heard about this but If you understand the language model of ORCA, like me then I am sure it will be easier for you to understand the language model of ChatGPT.
ChatGPT
Language Model — Chat Generative Pre-Trained Transformer (Very Large Language Model)
There are 3 main steps in this structure of the ChatGPT model.
Step 1: Encoding
When we give any command in ChatGPT then it collects the data. Converts the collected data into numbers. The data set containing these numbers is made and kept prepared by labeling it, similar to how everything is kept in the cells in a large warehouse. In AI, Label is used for Reasoning.
Step 2: Trained Reward Model
By combining the collected data with the rest of the data, a combination will be made that which data matches the reasoning, that is, how many types of answers can be given to the question asked by the user.
Now ChatGPT compares all the produced answers to determine which answer is the best and justify the given prompt. Based on that they will do labeling and add it in the reward model.
Step 3: Decoding
In this step, AI will take the prompt sample from the database so it can give an answer. The reward model as we have explained in the previous step works on the basis of feedback of the provided answer.
The large language model of ChatGPT is made on the basis of the above-explained 3 steps, but the ORCA’s language model is completely different.
ORCA
Zero Shot language model. This model develops its own learning capability by collecting data from the Large Language Model and processing that data.
Example
If you want to make latte coffee but have no idea how to make it. So you just go to your friend and request him to teach you how to make Latte Coffee. Then he gives you an answer like:
Espresso in glass — Fill a jug with 1/3 milk — foam with microfoam — remove bubbles — pour milk into espresso — Keep foam on top — enjoy!
You have gathered all of the information on how to make latte coffee from your friend. When you were collecting this data, I was listening to everything as if I were a ghost. By listening to the data-gathering procedure of latte coffee, I am improving my ability to do my task.
In this case, you are the user, and your friend is ChatGPT. Here, I’ve become ORCA. I learned everything when I became ORCA.
Now I hope you have understood from this example how the ORCA will work.
On ChatGPT, people ask many different kinds of questions. From these many questions, ChatGPT provides multiple replies. Returns the output from the resizing process. All types of processes are multiplying in ChatGPT. The incredible part is that ORCA learns the entire procedure using a progressive learning technique.
ORCA AI
After hearing about the ORCA, I know all of you are very curious to know about how ORCA AI actually works. So just like OpenAI, ORCA AI works in 3 steps.
Step 1: Explanation Tuning
Whatever outcome the ChatGPT model provides, it learns from it and accumulates data from the reasoning process of deriving the conclusion. Trains itself using the obtained data points. These skills are similar to a clone.
Step 2: Scaling
ORCA collects the results of every task running in the ChatGPT model. Surprisingly, ORCA will only gather outputs with the maximum reasoning accuracy. You might be thinking that this ORCA is a clone that just copies the output of ChatGPT, however, this is not the case.
Here, ORCA uses the data from ChatGPT as a reference to develop its reasoning capability.
Step 3: Comprehensive Evaluation
Assume that 500 people asked ChatGPT how they can become rich quickly. At the time, ChatGPT provided 500 various forms of output based on the user’s writing style. The procedure for obtaining these 500 outputs is saved in the GPT database.
Now we put commands inside ORCA that how to get rich quickly, then these keywords were used earlier inside ChatGPT, so ORCA does not need to run different processes 500 times like ChatGPT.
ChatGPT has already run the process 500 times so ORCA will only access GPT’s database and run a comprehensive analysis inside it. This research shows that the reasoning accuracy of which prompt is great. After collecting data from this particular topic, ORCA will develop a new output and provide it.
Benefit
ORCA has a parametric language model with just 30 billion words, whereas ChaGPT has 175 billion words. Because ChatGPT is several times larger than ORCA, ORCA will be more powerful, faster, and more accurate than ChatGPT.
Although ChaGPT must do several operations in order to obtain the result, ORCA will automatically use all of the outputs that GPT produced. Responds by evaluating the outputs and combining self-taught knowledge.
Burn Less
The bigger the model and number of tasks, the more money is required to process those tasks on servers. The cost of running those servers is very high. If you have been reading this article till now from the beginning then you must have read that OpenAI is spending $700000 everyday. Now you must have understood where the money is going.
It will take several tasks to train ChatGPT to extract the output, but it will take only 1 task to train ORCA to do that.
For this reason, the cost of running ORCA is many times less than ChatGPT.
The major benefit of ORCA is that it is simple to scale because it is a small model.
Large language models are being developed by Google, StabilityAI, and OpenAI. Microsoft is funding these AI startups so they can build extensive language models. Microsoft is currently developing its own small model ORCA.
In the end, Microsoft is going to be the hero of the story without any kind of hardwork.
So keep learning because no one can tell, when; what will happen in AI. The world of technology is beyond our imagination.
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Disclaimer
I am not a Financial advisor. I am not affiliated with any of the websites or coins and also this is not financial and Investment advice. This article is meant only for educational purposes. I am just sharing my thoughts and analysis based on my many years of experience.