Well, saw that coming and too bad because for a moment and before notion took off, it had a chance. I gave up using it when critical notes I wrote in offline mode in the subway did not sync as I was lead to believe. Never touched it again.
The factual's don't matter in Politics, not when mad men are at the helm. Funny how Trump closed his address with thanking god, and the Iranians start theirs in the name of god. So different, yet the same.
The US posturing against Iran dates back to the Cold War era when Iran was tagged as “northern tier” state, and any nationalist moves inside looked like a Soviet opening, and a threat to the Anglo stronghold of Iran's Oil.
This keeps getting repeated all around the comments, but it's absolutely false.
Christians, Jews and Muslims are monotheistic and all claim to be the religion of the One God, yes.
But the Jews rejected the God the Christians believe in, and the Muslims describe/portray a god that is absolutely incompatible with the Christian God.
So essentially no, they can't possibly all believe in the same God.
That's cool! thanks for making it easy to fork and play with this!
I've just begun my own iteration of adding Nash Equilibrium (NECoRT?) and reframing the "prompt engineering" to be a multi-agent negotiation. Curious what others think?
https://github.com/faramarz/NECoRT/
my reasoning is that enterprise LLMs wont have any issue with the extra compute costs and would rather reconcile complex financials with various modeling optimizations.
I'm very new to public repo and contributions, and hope someone can point out if I'm doing it wrong.
my intention was to fork the ops codebase so I can test out my theory, and push as PR eventually
maybe they should focus on. growth stage startups? frankly, even incumbant who are perpetually trying to play catchup and are more startup like in their core teams via transformation maturity and have what startups don't have, market fit and deep pockets.
target the enterprise b2b orgs in private equity portfolios.
Just last night I took a similar approach to arriving a number of paths to take when I shared my desired output with a knowledge graph that I had populated and asked the AI to fill in the blank about the activities that would lead a user to my desired output. it worked! I got a few none-corralative gaps that came up as well and after some fine tuning, got included in the graph to enrich the contentious output.
I feel this is a similar approach and it's our job to populate and understand the gaps in between if we are trying to understand how these relationships came to existence. a visual mind map of the nodes and the entire network is a big help for a visual learner like myself to see the context of LLMs better.
anyway, the tool I used is InfraNodus and am curious if this community is aware of it, I may have even discovered it on HN actually.
The one thing to solve for imo is the initial attraction needs to be incentivized for being the early set in of users/contributors to arrive. On that note, make it possible for me as a product recommender to recommend someone else’s product if I want to, and that can be a separate bucket for recommendations.
Then what you have now is essentially digg and Reddit but for startups. It submission will be slow on day one, but hopefully ppl stick around if you capture their imagination and plant a seed for them to come back for.
A second tab by other recommendations by the user will always be buzzing as people will naturally want to hack their chances into being promoted to the LIST on the first tab and/or by being promoted, or feeling good about it, or helping a friend etc and the recommending submitter gets points that can be used for launching their own product and with greater placement or give them one vote for every 10 votes their reco gets on the other tab.
Anyway, I’m riffing but I’m also taking a break from working on a stratplan for my startup and winding down on the couch.
Love the simplicity. PH sold out.
P.s. instead of votes, give people satoshis’ and use as an opp to on-ramp more people onto crypto.
I sure hope they are already well into fixing the issues and that the resignation is just for posterity and shareholder appeasement, otherwise, any significant change will take half a year at minimum!
I’m now annoyingly used opening my Sonos app once, closing it, opening it again to get the damn ui to load current streams on any of the speakers.
So what is the suggestion at the end of the post? Did I understand correctly that a sandboxed-replica simulator with the fundamental training would harden the system design? Cool! Can you run the simulator based on the basic but complete input architectural drawing? I’d be curious to know if LLMs are able to go and abstract it all across the public network and come back with an attention for all possible known scenarios. Frankly, you can even serve the scenarios into financial forecast models to serve and move the right levers for appropriate actions.
These blind spots are exploits waiting to be discovered.
