AI is taking the front stage and it is clear that there are no hurdles for technology. Just within the last year itself, it is quite remarkable how far AI research has advanced.
GPT-4 and Gemini 2.0 are now able to multi-task with decision making and problem solving which is AI-like, and an AI powered instrument has also secured the prestigious Nobel Prize in Chemistry.
These remarkable breakthroughs are more than enough to analyze what has happened so far, the reason behind all of this and the expected future.
Open AI launched GPT-4 in early 2024 which is one of the latest versions of LLM. Gemini 1 followed shortly after by Debmid’s Gemini 2.0: The AI model which relies heavily on vision and speech and is fully intertwined with each other.
These are not AI systems, rather, they are a smart set of programs that can plan, reason, summarize, translate, and code in and out of AI language. In fact, oftentimes, better than an average human would.
And here we have the hype: GPT-4 managed to clear professional exams such as the biology olympiad bar and SAT, gaining a sub average score during testing in comparison with many other candidates which is a great achievement in itself.
The introduction of Gemini 2.0 marked the addition of multimodal capabilities where it can now analyze text, images, and audio data together.
Remarkably, both models have been evaluated on advanced activities like writing algorithms, doing mathematics, or performing scientific tasks — and they have been excelling.
To put it differently, AI not only keeps up with expectations, but now outpaces many in specific domains, which previously required extensive human effort over many years of training.
The emergence of AI with capabilities beyond text: Multimodal systems
The difference between Gemini 2.0, GPT-4 Turbo, and their predecessors is their ability to be responsive to multiple modes of information. Their seeing, hearing, and reading abilities can be utilized all at once which enables them to conduct the following tasks.
Compose a summary after analyzing a chart.
Extract information from a PDF scanned document, comprehend it, and translate it into a database form.
View a video and recognize several objects as well as narrate what is taking place.
Such abilities elevate the role of AI from a mere text generator to a powerful multi purpose knowledge tool beyond words. They are expected to operate AI tutors, virtual doctors, legal aides and much more in the near future.
From an AI lab to an AlphaFold: A Nobel prize winning discovery
If you are impressed by the previous mention of language models, then let’s not forget about AlphaFold – an AI system developed by DeepMind (owned by Google) which single handedly tackles one of the toughest challenges in biology: predicting the protein structure.
A year after the award was given, in 2024, global attention was turned to the AlphaFold project as the team behind it accepted the Nobel Prize in Chemistry.
Now, Why Is This Important?
(proteins) Knowing their 3D shape helps scientists:
* Design better drugs.
* Understand how diseases work.
* Develop synthetic enzymes for industry and medicine.
Prior to AlphaFold, determining protein structures could take years. With deep learning AI, scientists are able to form shapes within minutes and with greater accuracy. The database provided by DeepMind changed the landscape of medicine, biology, agriculture, and bioengineering by holding predictions for over 200 million proteins.
AI That Approaches Human Intelligence
An abundance of articles proclaim the statement “AI has surpassed humans”. In reality, it is more complex than that.
These systems still struggle with:
* Understanding, planning and reasoning
* Long term planning
* Emotional understanding
They can conjure up lies (hallucinate).
Specialized, yes. General, not quite yet.
With every month that passes, benchmarks become easier to reach with the help of AI. Generating code, summarization, and solving complicated mathematical problems all came AI-powered, outperforming average professionals.
What Comes Next?
In the future, all models like Mistral and LLaMA 3 offer the public new-aged AI.
Personal devices and business applications will integrate with Multimodal AI in the near future.
The safety and regulation of AI technology will emerge as a key area of focus, especially as the level of autonomy and impact these systems possess increases.
Ending Thoughts
What we are seeing now is a foundational change. The productivity, creativity, and even scientific discovery are being redefined by tools such as GPT-4 and Gemini 2.0. The Nobel Prize awarded to AlphaFold is proof that AI is not only providing assistance; it’s taking the lead in domains traditionally considered human territory.
The period of assistive AI that has long awaited us has come to an end. We are now entering a new collaborative intelligence era, where humans and machines work hand in hand to build the future.
