Written when ChatGPT launched, with the GPT-3 model.
These models are massive:
"OpenAI didn't train GPT-3 on desktop computers.
They used very expensive supercomputers containing thousands of specialized AI processors, running for months on end."
Click to run World: Chat with GPT 3.5 at Ancient Brain.
Chat with GPT 3.5 model.
This is an open source JavaScript World to call the
OpenAI API to
talk to GPT 3.5 (2022).
GPT 3.5 was the model used by
ChatGPT
when it started in 2022, launching the AI revolution.
In these earlier GPT models there was a parameter called "Temperature".
Click to run World: Chat with GPT 5.6 at Ancient Brain.
Chat with GPT 5.6 model.
This version talks to
GPT 5.6 (2026).
This is the model ChatGPT uses as at 2026.
This has led to huge debate as to whether there will be no jobs for software engineers now,
or whether jobs in software will simply evolve.
Generative AI is especially good at short, self-contained functions. (Small context window.)
Things Stack Overflow
was brilliant for.
It is more of a challenge to build large systems with many files and inter-connecting parts,
and have AI keep track of all the context.
There is also a fundamental issue of risk
if you deploy production code that has never passed through a human brain.
Not just "code reviewed".
We mean, the human brain thought about it, invented it, removed parts, added parts, changed things,
and while doing so considered hacking injections, divide by zeros, null strings, and so on.
Vibe coding
is the idea of getting an AI to write your code by talking to it in human language.
True "vibe" coding is where you do not really look at or check the code, but just keep speaking to the AI
to fix any issues.
There is much debate on what "vibe coding" will do to the software industry:
On the one hand, it allows "creatives" who cannot code, but are good on user interfaces,
aesthetics, etc., to mock up beautiful prototypes.
On the other hand,
vibe coding by people who cannot code
is likely to generate code with many subtle bugs, issues, security holes, etc.
Artistic worlds like music and
fiction writing
struggle to know what to do with AI.
On the one hand, lack of a human creator seems wrong.
On the other hand, many of the products are beautiful, emotional and seem very human.
Because of course the training data is human output.
Ask another AI to generate some lyrics for a genre, like, say, "deep house".
Then give Suno "deep house" genre and those lyrics.
The result may be hard to distinguish from a human song.
Elysia Vale
seems to clearly be AI generated music.
And yet much of it is beautiful, emotional.
Videos get millions of views. So does it matter?
After all, some human decided to publish it.
