The same labs that built ChatGPT and Claude are also quietly hatching chicks from 3D-printed eggshells (Colossal Biosciences did it this morning), wrangling fusion plasma with neural networks (Commonwealth Fusion Systems), designing proteins that have never existed (David Baker’s lab at the University of Washington), and recovering DNA from species that went extinct centuries ago. Every frontier runs on every other frontier in 2026, and the people building it are having the time of their lives.
If you only follow one of these fields, you are missing most of what is actually happening. This hub exists so a non-technical reader can hold the whole map in their head, then pick the corner that lights them up first. Each cluster below is its own deep dive. The point of this page is to show what we cover, where to start, and just how much fun all of it actually is.
Our promise to you
Three things, in this order. Hold us to them.
- Plain English. If we use a technical term, we either define it in the same sentence or link it to our Glossary. We never assume background. Even advanced concepts get taught at a beginner level.
- Pro-human first. Technology at its best enhances what you do. It does not replace the parts of your work that build you. Handwriting builds neural connections that typing skips. Sitting with a problem builds judgment that asking an LLM skips. We will write about every technology with that lens.
- Primary sources. When we cite a study, we link to the actual paper. When we cite a number, we link to the dataset. Nature, Science, NEJM, IEEE, ACM, arXiv, official company announcements. Never Wikipedia. Never AI-generated summary sites.
The map: what we cover
Click into any cluster below. Each one has its own master hub page, a flagship pillar to start with, and a growing set of spokes.
Where to start if you’re new
Three honest paths into the site:
- Start with AI. If you’ve heard about ChatGPT or Claude and don’t know how to start using them, our Start Here page is the right door.
- Start with a profession. If you want to know how AI fits your specific job, our profession-specific guides cover doctors, lawyers, teachers, real estate, design, HR, and 30+ other fields.
- Start with curiosity. Pick a colored card above. The two we recommend for a curious beginner are Biotech & Synthetic Biology (because the news is wild right now) and our Brain & Neuroscience anchor (because it changes how you think about every other tool you use).
The Beginners in AI position
BiA exists because the technology being built right now is going to make people’s lives better, and most introductions to it are written by people who either over-explain or assume background. We try to do neither.
And the second half of the promise matters as much as the first. Every technology we cover, we cover with the question, “what part of being human does this enhance, and what part does it threaten to replace?” The answer is rarely one or the other. A 2024 Norwegian EEG study showed that writing by hand builds wide brain networks that typing skips. That is a small, specific example of a much bigger pattern. We will keep finding examples, and we will write honestly about all of them.
Use the tools. Keep your hand on the wheel. And try to remember, every once in a while, that we are alive at one of the most interesting moments in human history. The least we can do is pay attention.
Frequently asked questions
Why is a site called Beginners in AI covering biotech, fusion, and quantum computing?
Because the same labs and companies that built AI are now pushing biology, energy, materials, and space. AI is one expression of the broader technology shift of the 2020s. A beginner-friendly site that ignores the rest of the field gives readers a partial picture. Our brand promise has always been to explain technology so people can have better lives. The brand fits.
What’s the publication cadence for these new hubs?
Deliberately slow. One hub at a time. Each hub launches with a master page and a flagship pillar post. After that, one or two news-driven posts per week per active cluster, never more. We are not in a race to publish. We are building reference material that will still be useful in five years.
How are the topics chosen?
By what’s actually happening, what beginners are asking about, and what we can write with original primary-source research. We avoid topics where we’d just be summarizing other people’s reporting. We avoid topics where the news doesn’t move enough to justify long-form coverage. We try to ship what a curious non-technical reader actually wants to know.
What sources do you use?
For biology: Nature, Science, NEJM, Cell, official lab announcements (NTNU, Stanford, Broad Institute, etc.). For physics and engineering: IEEE, ACM, arXiv, company white papers. For business and market data: Bloomberg, Reuters, the Financial Times, company press releases and SEC filings. For policy: government documents and OECD/UN reports. We never cite Wikipedia. We use our own AI Glossary for definitions and link out to the actual papers behind every claim.
Will the newsletter cover all of this?
Yes. The daily newsletter at beginnersinai.com is human-curated and human-edited. It already covers AI breakthroughs that touch biology, robotics, and the rest. The new hubs make that broader coverage more visible and more usable as reference material.
Sources for the brand promise
- AlphaFold, Google DeepMind: the AI that solved protein structure prediction and unlocked modern drug discovery
- Colossal Biosciences: de-extinction company, source for the artificial-eggshell story
- Commonwealth Fusion Systems: MIT-spinoff using AI for plasma control
- Van der Weel & Van der Meer (NTNU, 2024): the EEG study behind our handwriting / brain network coverage
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