The Future of AI with ChatGPT: Navigating the Risks and Rewards of GPT-3, Sparrow and Others.

ChatGPT news is on fire and is a piece of artificial intelligence that is exciting technology, BUT it is still in its research phase and can produce inaccurate information. It is compared to a teenager that is still finding its footing in the world. As with other emerging technologies, you have to be aware of the risks associated with AI and its current limitations. However, companies like Microsoft are investing billions of dollars in OpenAI, indicating that despite the risks, it is still considered to be a valuable technology.

In my recent travels as a practice leader for EisnerAmper Digital Transformation and the Co-Chair of the CompTIA AI Council, I have been asked by many about how these new AI technologies work. So, here we go...

What Does ChatGPT Do?

So what is ChatGPT? It's a natural language model developed by OpenAI that's taking the business world by storm. With its deep learning techniques, ChatGPT can generate human-like text that's so realistic, you'll have trouble telling it apart from the real thing. And it's not just about writing, ChatGPT can be trained on a wide range of tasks, from language translation to question answering and even conversation generation. Plus, its ability to understand and respond to natural language input makes it a powerful tool for automating tasks that involve human communication. But the real excitement is in the race for Artificial General Intelligence (AGI), and let me tell you, it's heating up. With the upcoming launch of Sparrow by Google subsidiary DeepMind set to compete against OpenAI's GPT-3, we're on the cusp of a new era in AI technology. GPT-3, a Generative Pre-trained Transformer 3, is a highly advanced generative artificial intelligence model that is trained on vast amounts of text data, allowing it to generate human-like text with minimal input while also being able to perform tasks such as language translation and summarization.?These models are pushing the boundaries of what's possible and represent a step towards AGI - ultimate goal of AI research. Imagine a machine that can perform any intellectual task that a human can and also improve itself. It's mind-blowing stuff and I can't wait to see what happens next.

AGI: The Future of AI, Pushed Forward by Sparrow and GPT-3

The competition is pushing the boundaries of what's possible with AI technology. Sparrow and GPT-3 represent a step towards AGI; if you didn't already know, AGI is considered the ultimate goal of AI research. DeepMind, the company behind Sparrow, is an AI company founded back in 2010 and acquired by Google in 2015. The company is creating advanced AI to solve complex scientific and real-world problems. Notable contributions from DeepMind include the development of AlphaGo and Alpha Zero. Sparrow is currently in the private beta phase and will launch in late 2023. The chatbot aims to answer questions and search the internet using Google and can cite sources through reinforcement training - a feature that GPT-3 currently lacks.

An AI system learns to make decisions through interaction with its environment and feedback in the form of rewards or penalties. This process is known as reinforcement learning. This type differs from traditional machine learning, where the AI system is trained on pre-labeled data. With reinforcement learning, the AI system learns through trial and error, similar to how we learn from our experiences in life.

Google's large language models for dialogue and conversation, such as Lambda and Flamingo, are an example of reinforcement learning in action. These models were trained to respond to user input through reinforcement learning. They received rewards for providing relevant and accurate responses and penalties for providing irrelevant or inaccurate answers, which allowed the models to learn and improve over time, ultimately leading to more effective conversational AI systems.

What is Conversational AI?

Conversational AI, also known as chatbot technology, is all about creating AI-powered systems that can hold human-like conversations. In other words, it's making computer programs that can talk to people like real people do. Sparrow is an excellent example of a conversational AI system. It can answer questions and search the internet using Google. It's like having a virtual personal assistant that can help you with anything you need, from finding information to booking a flight. The technology behind conversational AI is quite complex, but it involves using natural language processing and machine learning algorithms to understand and respond to human inputs. The goal is to make the interaction as seamless and natural as possible. Imagine being able to talk to your phone or computer the same way you talk to your friends and family and have it understand and respond accordingly. That's the power of conversational AI.?

What are Neural Networks?

Neural networks are a type of artificial intelligence modeled after the human brain's structure and function. They consist of interconnected nodes or "neurons" that work together to process information and make decisions. Neural networks are used in many areas of AI, including computer vision, natural language processing, and reinforcement learning. GPT-3, Sparrow, and many other AI models are based on neural networks. These networks can learn from large amounts of data and improve their performance over time, making them a powerful tool for solving complex problems.

What is Generative AI?

Generative AI is a type of AI that can generate new content, like text, images, or audio. Think of it like a machine that can write a story, create a piece of music, or even design a new product. It's pretty great stuff!

GPT-3 is one example of a generative AI model. It's a type of language model that has been trained on a large amount of text data, which allows it to generate text that is very similar to what a human might write. For example, if you give GPT-3 a prompt like "Write a story about a robot who saves the world," it can generate a coherent story and even plot, characters, and setting.

It's important to note that GPT-3 is not the only generative AI model out there, but it's one of the most advanced models currently available. It's also worth noting that GPT-3 could be better and can sometimes generate nonsensical or off-topic text. However, the ability of GPT-3 to generate human-like text with minimal input is what makes it so impressive, and it is being used in a wide range of applications such as chatbots, language translation and more.?

Final thoughts as AGI Race Heats Up

The competition for AGI is intensifying as major players in the tech industry are vying for a piece of the pie. 谷歌 subsidiary Google DeepMind 's upcoming launch of Sparrow is set to compete against OpenAI 's GPT-3, 微软 Azure Cognitive Service for Language, IBM Watson and Amazon Web Services (AWS) . This competition is not just about market dominance, but about pushing the boundaries of what's possible with AI technology and reaching the ultimate goal of AI research - AGI. Sparrow and GPT-3 are considered major players in the race towards AGI, with Sparrow excelling in providing plausible answers and supporting them with evidence, while GPT-3 is known for its ability to imitate intelligence on various subjects. Other technologies such as generative AI, conversational AI, reinforcement learning, and neural networks are also being developed and used to reach AGI. Accurate intelligence also requires moral understanding and the ability to cite sources, and Sparrow is said to be progressing in these areas. A public beta will soon be available for Sparrow, and it remains to be seen which company will come out on top. However, one thing is for sure, the race for AGI is heating up, and it will be exciting to see what the future holds for AI technology.

By the way, the image in this article has been created by DALL-E 2 a GPT-3 deep learning model created by OpenAI that produces digital images from descriptions in natural language. DALL·E 2 (openai.com)

You can find more information about me on www.eisneramper.com/jason-juliano/

Reference:

Building safer dialogue agents (deepmind.com)