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I had the pleasure recently to participate in a lifelong learning session with a group of mostly current or retired educators at my nearby Lincoln Land Community College. The topic was AI in education. It became clear to me that many in our field are challenged to keep up with the rapidly emerging developments in AI.
The audience was eager to learn, however, many were unaware of the current models and capabilities of AI available to them. I had mentioned in the previous edition of “Online: Trending Now” that we are now in the third of a five-step development of AI as envisioned by the CEO of OpenAI, Sam Altman:
Level 1: Chat bots, AI with conversational language
Level 2: Reasoners, human-level problem solving
Level 3: Agents, systems that can take actions
Level 4: Innovators, AI that can aid in invention
Level 5: Organizations, AI that can do the work of an organization
Level 1, chat bots, are the question (prompt) and answer version that many users still think of as generative AI. Famously, on Nov. 30, 2022, OpenAI released GPT-3.5 featuring ChatGPT, an interactive, conversational AI trained with Reinforcement Learning from Human Feedback (RLHF) and fine-tuned safety measures, derived from the GPT-3.5 model. That became the inflection point for this technology that has rapidly spread around the world:
“ChatGPT stands out as the undisputed leader of this boom, capturing over 82.5% of the total traffic, with over two billion global visits and 500 million users each month. The pace of adoption is particularly noteworthy. ChatGPT set a record as the fastest-growing consumer software in history, reaching 100 million users just 64 days after the release of the updated ChatGPT3.5 in May 2023. It’s not alone in this surge; Baidu’s AI chatbot, ‘Ernie Bot,’ surpassed 200 million users within just eight months of its launch.”
Yet, this technology has, importantly, developed beyond earlier versions to stage 2, which Sam Altman called “reasoners,” such as the more recently released OpenAI o1 and OpenAI o3-mini. Every version of GPT engages in some form of text-based pattern recognition that can look like reasoning. The newer versions exhibit markedly stronger logical consistency, better multistep problem-solving and better handling of extended context. This is why Altman calls the latest iterations “reasoner” models: They integrate more advanced techniques, larger context windows and improved training methods to produce answers that seem more logically sound. Ultimately, these “reasoner” capabilities reflect the evolution of large language models toward more complex forms of textual analysis and response.
The newer model OpenAI o3-mini is available to all users (paid and unpaid). I encourage you test out this reasoner model. You are welcome to use the GPT I trained for higher education emphasis, Ray’s eduAI Advisor, or the general ChatGPT site. In either case, try running a deep, questioning prompt that requires interpretation and significant research in its response. You will be able to briefly view the thought process that o3 is taking flash onto the top of your screen. The model shares this thought process with you as it assesses your question and context, then gathers data and ultimately responds to your question. What is unique about this level of AI is that you can see how the application is thinking about your inquiry. This will give you hints as to how you might craft follow-up prompts to add insights and perspectives to your inquiry.
On Feb. 2, 2025, OpenAI announced a highly advanced application built upon 03-mini named “Deep Research,” saying:
“Today we are launching our next agent capable of doing work for you independently—deep research. Give it a prompt and ChatGPT will find, analyze & synthesize hundreds of online sources to create a comprehensive report in tens of minutes vs what would take a human many hours … Powered by a version of OpenAI o3 optimized for web browsing and python analysis, deep research uses reasoning to intelligently and extensively browse text, images, and PDFs across the internet. Deep Research is built for people who do intensive knowledge work in areas like finance, science, policy & engineering and need thorough & reliable research.”
While Deep Research is not available to the general public at this time, online demonstrations show that this very powerful tool conducts both reasoning and far-reaching analysis. In her podcast of Feb. 9, AI expert Julia McCoy reports that the release of Deep Research puts us on the cusp of artificial general intelligence (summarized by Gemini 2.0 Flash):
“The podcast talks about OpenAI’s new deep learning models, 03 mini and Deep Research. 03 mini is a groundbreaking reasoning Powerhouse that fundamentally changes how AI approaches problems. Unlike previous models, 03 mini actually thinks before it speaks, methodically working through complex tasks with unprecedented precision. Deep Research is an autonomous research assistant that can spend up to 30 minutes deeply analyzing information, something previously unheard of in AI systems. What makes Deep Research truly special is its ability to dynamically adapt its research path, combining multiple sources and presenting its findings in fully cited comprehensive reports in seconds. The podcast discusses how Deep Research can be used to provide medical diagnoses and treatment recommendations. It can also be used for other knowledge work, such as market research and product development. The podcast concludes by discussing the implications of these new models for the future of AI. The host believes that we will see AGI [Artificial General Intelligence] this year and ASI [Artificial Super Intelligence] possibly as soon as 2027.”
As I write this, Altman has just announced that the tools embedded in o3 mini and Deep Research will be fully merged along with new capabilities in a revised pathway of releases in the days and weeks ahead.
“We will next ship GPT-4.5, the model we called Orion internally, as our last non-chain-of-thought model. After that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks. In both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3. We will no longer ship o3 as a standalone model. The free tier of ChatGPT will get unlimited chat access to GPT-5 at the standard intelligence setting (!!), subject to abuse thresholds. Plus subscribers will be able to run GPT-5 at a higher level of intelligence, and Pro subscribers will be able to run GPT-5 at an even higher level of intelligence. These models will incorporate voice, canvas, search, deep research, and more.”
The funneling of all of the capabilities of OpenAI technologies into the GPT-5 track shows a maturing of the technology. The three levels of intelligence most likely point to true AGI in the higher levels that will be released with GPT-5 later this year! Clearly, advancements are taking place very rapidly.
In addition, with the advent of new competitors both here and abroad, we are seeing new options for open-source models and alternative approaches. As these become more efficient and reliable, prices are headed lower while features continue to expand. McCoy’s vision of AGI seems only months, not years, away.
How are these highly advanced tools being used by your university to enhance teaching, learning, research and other mission-centric tasks? Are most of your faculty, staff and administrators well versed on the recent developments and potential of AI? Are they prepared for the full release of GPT-5? What can you do to help your institution remain efficient, effective and competitive?
