#050 - Too hot to handle
Insurance, AI, and where the two won't meet.
#049 - Looking for a grenade in a haystack
The meltdown of auto parts company First Brands may tell us about lurking problems in the genAI space.
#048 - Catching up on the news
Of AI browsers, circular deals, and token dealers
#047 - What's left after it all falls apart
If AI is indeed a bubble, what happens after the crash?
#046 - It's a long way down
genAI keeps digging a hole. Will it be able to climb out?
#045 - Tracing the connections
The key lesson from complex systems: when everything's connected, large players can pull others up and also drag them down.
#044 - Five light reads
Catching up on some end-of-summer AI news.
#043 - Taming the delightful chaos
What the computerization of Wall Street can teach us about AI
#042 - These broken machines
Remember: never let the machines run unattended.
#041 - Cashing in
Chasing momentum and Meta money.
#040 - All hammer, no nail
GenAI companies keep cooking up wild use cases. Here's how to spot the winners.
#039 - Small-batch, hand-crafted code
Hand-waving sometimes works, but sometimes it doesn't. Also: when people and machines write code.
#038 - Exploiting our weaknesses
When genAI chatbots and tools get into our human wiring.
#037 - Cranking out trash
On checking your genAI chatbot's work, and playing the blame game.
#036 - Relationship status: "it's complicated"
Our relationship with robots should be simple. Creepy, commercial GenAI has made it anything but.
#035 - This time, it actually is different
GenAI breaks away from the pack. And not in a good way.
#034 - Agent double-0 nothing
A look into agentic AI's hazy present. And possible future improvements. With some ideas from algorithmic trading.
#033 - GenAI is an executive's best friend
I'll emphasize: "best" friend. Not always "a good" friend.
#032 - What the machines don't know
Incomplete information can make AI models overly optimistic – even arrogant.
#031 - Deep secrets
LLMs remind us of a special kind of model error: inappropriate answers. Here are three lessons from a chatbot that knows when to clam up.
