In biology, organisms draw on past experience to anticipate what their bodies will need. Energy use and cooling have to adjust together as demands change.
Biologists call this ๐ฎ๐น๐น๐ผ๐๐๐ฎ๐๐ถ๐. What could machines borrow from it?
We cover some thought experiments in this fascinating new blog post. ๐งต๐๐ฝ
https://t.co/8nMvlDX89u
1/5
Same ๐ญ. The brain has gotten habituated to feel like doing anything else (scrolling, opening X, etc.) when I'm waiting for my agents to finish their work. And then the constant switching between multiple agent sessions.
I think mindfulness meditation is the only way to go! ๐ง
I don't know who needs to hear this, but no matter who you are, the MOST important skill to train in the age of AI is critical thinking.
When you see (or are told) something in the real world, you should aim to question *why* it is what it is, rather than just looking at *what* it is. Understand how things work.
If one exercises critical thinking skills hard enough, you never stop (or tire of) learning. You just absorb new information like a sponge, and because you're always asking "why?" and "how?", you end up going wider and deeper than you ever did before you had AI. It was simply too hard to spend the time on that deep a study before. Now, you can.
So stoked for this one! It's such a fascinating topic to be speaking about, and I couldn't have found two better people to present with!
See you at @_odsc West in San Francisco next week!
7 days to go until ODSC AI West 2026! @_odsc
Our "Connected Intelligence" sessions in the new graph-enhanced AI track explore how AI can recall relevant experience, check it against current rules, and learn something useful for the next decision.
David Hughes and @tech_optimist are going to be in San Francisco with @hdclabs_ai and @amyhodler, from October 27-29. ๐งต๐๐ฝ
1/2
I think most people multi-tasking with agents could benefit from slowing down
most of the stuff you're doing wont really matter- what's your P0? what would it look like if you gave it your full attention?
@kushal_to It's always a smaller fraction of humanity that tends to value it, yep. But that's why education systems have to evolve, too. The way we learn, and the way we teach others how to learn, has to evolve. The problem is that change is happening too quickly for systems to evolve.
iโm becoming incredibly graph pilled lately.
i used to be dismissive of them, not seeing how they were actually useful over RAG or postgres.
but i now see a future where graphs are a central data structure for every companyโs world model
are you guys graph pilled yet?
That's a very broad question/comment that may have specific implementation details depending on the use case.
But in an upcoming demo I'm working on on, keeping a live context graph helps with provenance and validation, alongside other methods like vector search and ML/LLM inference
I know, right? I struggle to imagine what incremental improvement Opus 5.6 might bring over 5.5, with all the potential regressions. From what I gather, it's almost impossible to guarantee what these models learn during post training, and we still don't know what causes those regressions.
As a dataset grows, unrelated hypervectors get more chances to look accidentally alike.
In part 2 of our research study on the scalability limits of bundling, we use probability theory to estimate that risk, then test the predictions with controlled experiments. ๐งต๐๐ฝ
https://t.co/43w3pjeaFh
1/6
@communicable@sergical And to think they're trying so hard to get us to care to vote for the city elections. It doesn't seem to make the slightest difference, no matter who's in charge