GPT-4 Launches Today: The Rise of Generative AI from Neural Networks to DeepMind and OpenAI

GPT-4 launch illustrated with Stable Diffusion (CC BY-SA 4.0)
GPT-4 launch illustrated with Stable Diffusion (CC BY-SA 4.0)

With today’s launch of OpenAI’s GPT-4, the next generation of its Large Language Model (LLM), generative AI has entered a new era. This latest model is more advanced and multimodal, meaning GPT-4 can understand and generate responses based on image input as well as traditional text input (see GPT-4 launch livestream).

Generative AI has rapidly gained popularity and awareness in the last few months, making it crucial for businesses to evaluate and implement strategies across a wide range of industries, including e-commerce and healthcare. By automating tasks and creating personalized experiences for users, companies can increase efficiency and productivity in various areas of value creation. Despite being in development for decades, it’s high time for businesses to apply generative AI to their workflows and reap its benefits.

Before you dive into GPT-4, let’s take a quick look back at the evolution of generative AI…

The history of generative AI begins in the late 1970s and early 1980s when researchers began developing neural networks that mimicked the structure of the human brain. The idea behind this technology was to assemble a set of neurons that could pass information from one to another with some basic logic, and together the network of neurons could perform complicated tasks. While minimal advances were made in the field, it remained largely dormant until 2010, when Google pioneered deep neural networks that added more data, hardware, and computing resources.

In 2011, Apple launched Siri, the first mass-market speech recognition application. In 2012, Google used the technology to identify cats in YouTube videos, finally reviving the field of neural networks and AI. Both Google and NVIDIA invested heavily in specialized hardware to support neural networks. In 2014, Google acquired DeepMind, which built neural networks for gaming. DeepMind built AlphaGo, which went on to defeat all the top Go players, a pivotal moment because it was one of the first industrial applications of generative AI, which uses computers to generate human-like candidate moves.

In 2015, OpenAI was founded to democratize AI and was established as a non-profit organization. In 2019, OpenAI released GPT-2, a large-scale language model capable of producing human-like text. However, GPT-2 sparked controversy because it could produce fake news and disinformation, raising concerns about the ethics of generative AI.

In 2021, OpenAI launched DALL-E, a neural network that can create original, realistic images and art from textual description. It can combine concepts, attributes, and styles in novel ways. A year later, Midjourney was launched by the independent research lab Midjourney. Also in 2022, Stable Diffusion, an open-source machine learning model developed by LMU Munich, was released that can generate images from text, modify images based on text, or fill in details in low-resolution or low-detail images.

OpenAI launched ChatGPT in November 2022 as a fine-tuned version of the GPT-3.5 model. It was developed with a focus on enhancing the model’s ability to process natural language queries and generate relevant responses. The result is an AI-powered chatbot that can engage in meaningful conversations with users, providing information and assistance in real-time. One of the key advantages of ChatGPT is its ability to handle complex queries and provide accurate responses. The model has been trained on a vast corpus of data, allowing it to understand the nuances of natural language and provide contextually relevant responses.

Today’s launch of GPT-4 marks a significant milestone in the evolution of generative AI!

This latest model, GPT-4, is capable of answering user queries via text and image input. The multimodal model demonstrates remarkable human-level performance on various professional and academic benchmarks, indicating the potential for widespread adoption and use. One of the most significant features of GPT-4 is its ability to understand and process image inputs, providing users with a more interactive and engaging experience. Users can now receive responses in the form of text output based on image inputs, which is a massive step forward in the evolution of AI.

Bing has already integrated GPT-4 and offers both chat and compose modes for users to interact with the model. With the integration of GPT-4, Bing has significantly enhanced its capabilities to provide users with more accurate and personalized search results, making it easier for them to find what they are looking for.

The disruptive potential of generative AI is enormous, particularly in the retail industry. The technology can create personalized product recommendations and content, and even generate leads, saving sales teams time and increasing productivity. However, the ethical implications of generative AI cannot be ignored, particularly in the creation of disinformation and fake news.

To sum up, generative AI is here to stay, and companies must evaluate and implement strategies swiftly. As generative AI technology advances, so do the ethical concerns surrounding its use. Therefore, it is critical for companies to proceed with caution and consider the potential consequences of implementing generative AI into their operations.

Are you already using generative AI for a more productive workflow?

What improvement do you expect from GPT-4 in this regard? I look forward to reading your ideas in the comments to this LinkedIn post:

Authenticity in Photography: Samsung’s Moon Shots Controversy and the Ethics of Synthetic Media

Side-by-side comparison of the original capture and the synthesized version
Side-by-side comparison of the original capture and the synthesized version: Generative AI technology adds texture and details on moon shots, blurring the line between real and synthesized images.

Generative AI has made waves around the world with its ability to create images, videos, and music that are indistinguishable from human-made content. But what happens when this technology is applied to photography, and the images we capture on our devices are no longer entirely real?

While Samsung claims that no overlays or texture effects are applied, a recent Reddit post suggests otherwise. The post provides evidence that Samsung’s moon shots are “fake” and that the camera actually uses AI/ML to recover/add the texture of the moon to the images.

The use of AI in photography is not new, as many devices already use machine learning to improve image quality. But the use of generative AI to create entirely new images raises ethical questions about the authenticity of the content we capture and share – especially when the photographer is unaware that their images are being augmented with synthesized content.

What do you think about the use of generative AI in photography? Is it okay for a phone to use this technology to synthesize a photo, or is it crossing a line?

Join the conversation on LinkedIn:

Decisively Digital is the #1 Best-Selling Computers & Technology Industry Book on Amazon

Decisively Digital is an Amazon Best Seller
Decisively Digital is an Amazon Best Seller

What a great start to the new year: I am absolutely thrilled and grateful that my book, Decisively Digital, is the #1 best-selling Computers & Technology Industry book on Amazon!

When I first started writing this book, I had a strong belief in the message that I wanted to share with the world. I wanted to share my insights and experiences on how businesses can harness the power of digital technologies to drive growth and success by interviewing thought leaders from a variety of industries.

I hope that Decisively Digital will continue to inspire and empower readers to embrace the digital age and harness the full potential of technology for their own businesses and organizations. Thank you again for all of your support, and I can’t wait to see what the future holds!

Feel free to spread the word:

#datamustread 2022 Essentials: How to Level Up In Your Data Journey

#datamustread 2022 Essentials

For some time now, I have been using the hashtag #datamustread on LinkedIn and Twitter to regularly recommend books that are essential for a data journey. At the end of this year, I would like to put together some absolute highlights that I consider to be absolute #datamustread books:

πŸ“– True or False by Cindy L. Otis
πŸ“– Info We Trust by RJ Andrew
πŸ“– Tools and Weapons by Brad Smith
πŸ“– Data Science for Business by Foster Provost and Tom Fawcett
πŸ“– Decisively Digital by 24 thought leaders interviewed by me

True or False: A CIA Analyst’s Guide to Spotting Fake News

True or False by Cindy L. Otis covers the entire spectrum of misinformation and disinformation, why we fall for it, and what we can do about it. Even though some concepts are familiar to me, I still learned quite a lot. The book contains a wealth of unexpected examples, current and from history, and is more relevant than ever in today’s world.

Get True or False on Amazon.

Info We Trust: How to Inspire the World with Data

Info We Trust by RJ Andrews is an inspiring journey of data storytelling, but it’s also written in an extremely entertaining way, making thisΒ #datamustread the perfect companion for relaxing days. RJ’s enjoyable writing style, by the way, has been a guiding light for my own books.
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Join the #bookaweekchallenge for a Chance to win a copy of Decisively Digital

Join the #bookaweekchallenge with 7 days of Decisively Digital
Join the #bookaweekchallenge with 7 days of Decisively Digital

My book Decisively Digital: From Creating a Culture to Designing Strategy (➑️Amazon) is guest at Christina Stathopoulos and her #bookaweekchallenge on LinkedIn. Join Christina as she reflects on her journey through the book with several LinkedIn posts.

Christina’s posts can be found further down this blog along with a variety of interesting comments and opinions. Feel free to join the discussion on LinkedIn! You also have the chance to participate in our raffle and win one of three copies of Decisively Digital! Good luck!

Now I’ll turn it over to Christina, who kicks off the challenge with the following introduction to Decisively Digital (day 1):

No one can argue that today’s business landscape is DIGITAL, you’ve got to stay ahead of the curve or you’ll quickly fall behind. It’s Digital or… Disappear.

Jam-packed with insights, this book includes 24 interviews with leaders of the digital revolution covering:

πŸ’» Digital Culture & Modern Work (day 2)
πŸ“Š Data Democracy & Analytics (day 3)
☁️ Big Data Processing & Cloud Computing (day 4)
πŸ€– Artificial Intelligence (day 5)
πŸ“³ Process Automation, Blockchain & IoT (day 6)

Plus:

πŸ’‘ Wrap-up and Raffle (day 7)
🎁 Announcement of Winners (day 8)

Day 1: πŸš€ Introduction to Decisively Digital

Day 2: πŸ’» Digital Culture & Modern Work

Continue reading “Join the #bookaweekchallenge for a Chance to win a copy of Decisively Digital”