Close your eyes and picture a world where your Google Search was conversational and the answers were complex, in-depth, and contextual. One where artificial intelligence can respond to more philosophical questions and offer unique viewpoints within minutes - something once thought to be a far-off possibility in the future.
Now open your eyes, because that time is happening right now.
OpenAI has developed ChatGPT 3, a new benchmark technology in internet search engines, content, coding, and much more. It’s far beyond a Google Search or your average Smart Home Device - it’s going to be a whole new way that users interact with the online world.
But what is ChatGPT 3 and how does it differ from an average Google Search? We go into more detail about this below but bear in mind that this technology is already evolving beyond what we have in this article.
ChatGPT 3 As An Artificial Intelligence Tool
ChatGPT3 is in essence an AI trained in large language processing and uses the data it is trained on to generate realistic, human-like answers to prompts from users. Add to this capability the efforts of humans in Reinforcement Learning with Human Feedback and this tool is able to learn, improve and iterate faster and with better quality than other chat-related AIs can.
In essence, ChatGPT 3 works with a deep learning algorithm that can understand the sentiment, meaning, and context of conversations and therefore take part in them much as a human can.
Large language processing makes use of huge datasets of language in order to extrapolate what might come next in a sentence. The more data you give it, the better the output you receive.
According to Stanford University:
“GPT-3 has 175 billion parameters and was trained on 570 gigabytes of text. For comparison, its predecessor, GPT-2, was over 100 times smaller at 1.5 billion parameters. This increase in scale drastically changes the behavior of the model — GPT-3 is able to perform tasks it was not explicitly trained on, like translating sentences from English to French, with few to no training examples. This behavior was mostly absent in GPT-2. Furthermore, for some tasks, GPT-3 outperforms models that were explicitly trained to solve those tasks, although in other tasks it falls short.”
What’s incredible is this is not the first AI project launched by OpenAI to take the internet by storm. Before ChatGPT 3, there was DALL-E.
OpenAI And DALL-E: The Company Behind ChatGPT 3
OpenAI is a company that has been all the rage in AI news over the past few months. OpenAI is an artificial intelligence research laboratory with for-profit and non-profit branches. The company conducts research in the field of AI with the stated goal of promoting and developing friendly AI in a way that benefits humanity as a whole. Based out of San Francisco, the company first became well-known for its text-to-image-generating technology known as DALL-E.
After an early version was released in 2021, the tool became viral just a few months after when it entered into a beta phase with invitations sent to 1 million waitlisted individuals. Now, DALL-E can generate imagery in multiple styles, including photorealistic imagery, paintings, and even videos. Pulling data from a wide range of visual sources, DALL-E is able to blend creative concepts, a trait that used to be considered limited to humans only.
And while there has been some pushback in terms of the ethicality of generating images and what it might mean for the design community as a whole, DALL-E is ultimately predicted to become a turning point for a future multi-trillion dollar industry.
Moving Beyond Content: The Capabilities of ChatGPT 3
ChatGPT 3 is not a search engine or chatbot, even though it can play the roles of both. With such huge datasets behind it, it’s difficult to encapsulate just how much this tool is capable of.
Much like DALL-E, ChatGPT 3 retains the ability to blend creatively - just with words instead of images. This means that beyond asking it to write essays or blog posts, ChatGPT 3 can also be used to:
- Write poetry, screenplays, and short stories
- Explain complex academic concepts in layman’s terms
- Create and improve on programmatic challenges
- Manage your online bookings and be a personal assistant
- Give personalized recommendations and advice
- Automate online tasks like scheduling calls
And that’s just the tip of the iceberg. Many of the abilities of the tool are still being explored, with the technology currently in its infancy. However, based on the rapid trajectory of DALL-E and the improvements between versions one and two, it’s fair to predict that ChatGPT 3 will follow the same speed of advancement.
Microsoft seems to think so too, having recently invested as much as one billion dollars into OpenAI in order to create an integration for Bing. This move could flip the table on Google’s monopoly of the search engine industry as we know it.
The Keys To Using ChatGPT 3
What most people miss about ChatGPT 3 is that it’s not your simple question-and-answer machine (you can just go ask Jeeves for that). What it is is a trainable model in which you can use your own data to train Chat GPT-3 to understand and respond to questions about specific topics.
This means the more you use ChatGPT 3 for your intended needs, the better and more accurate it will become at meeting those needs over time. It’s ultimately machine learning, and that means training is essential to getting the results that can be achieved if done correctly.
For venture studios, the capabilities of ChatGPT 3 are extremely exciting and important. Not only can they train the model themselves, but they can also then use this tool to improve their output and time to market all in one go.
The field of AI and ChatGPT 3 also represents a great new amount of business-building opportunities for venture studios that work in machine learning and AI. Not only is there a spate of new projects in this space, but it also gives the studio the chance to be at the forefront of a new wave of technology.
Building For ChatGPT 3 With A Venture Studio
Although ChatGPT 3 may be new to the public, its earlier versions and machine learning as a whole are deeply familiar to the venture studios like NineTwoThree that operate in these spaces.
After working on dozens of machine learning projects (and having a dedicated team), our machine learning scientists know how to train the models to uncover your problem. Our team is constantly testing "what's possible" and is willing to go the extra 1% in accuracy.
Our data scientists can handle all of your data-related requirements including software development, labeling, and modeling. After the algorithm is tested, we wrap the solution in a cloud infrastructure to deliver a fully functioning machine-learning solution.
We’re a big-picture studio meaning we do more than just AI. Our software analysts, engineers & project managers will build your entire solution for your entire business - whether that’s recommending AI services and tech that’s right for your business or building automated solutions that adjust in real-time based on users’ needs and wants. Work with us by reaching out today!