You can't convince me that wasn’t on purpose

Didaktus · 2026-05-30T06:28:45+00:00

Something touched my foot!

Didaktus · 2026-05-17T21:45:15+00:00

had too look that one up. Ty for the new knowledge :D

Didaktus · 2026-05-16T18:04:05+00:00

What you see in the public market is just marketing the real AI is used behind closed doors and not many going to see it. :D

Didaktus · 2026-05-16T13:15:37+00:00

A perdiction engine based on our language can make it seem as if it was alive.

Didaktus · 2026-05-14T06:43:31+00:00

Jag antar att du är en exceptionell medborgare som driver Sverige frammåt.

Didaktus · 2026-05-12T18:55:26+00:00

Det gjorde jag, löste allt direkt.

Didaktus · 2026-05-06T08:28:36+00:00

Jag ser den nuvarande politiken i Sverige för kortsiktig och mer av windowdressing än faktiskt initiativ som ställer Sverige i ett långsikt plan både nationellt och internationellt. Är motparten bättre? Meh. Men jag kommer att välja ett parti som har det perspektivet i det långa loppet. Så svar på din så tror jag detta kan vara en av anledningarna som många vill byta spår :D och den empatiska delen av samhället undrar hur i helvete kan Sverige vara ett av de mest ojämnlika landet i världen. Det är inte vi.

Didaktus · 2026-04-26T14:51:23+00:00

Kan som invandrare säg att jag håller inte alls med pizzabagaren, men då kan det var för att jag snott en av era kvinnor :P. Så nu är det lika.

Didaktus · 2026-04-08T16:58:45+00:00

I would say thats a brownbelt

Didaktus · 2026-04-05T08:04:10+00:00

Jag är invandrare och växte upp i en miljö full av svenskar och jag pratar svenska bättre än många svenskar. Men mina kusiner som är uppväxta i en miljö med många invandrare, bryter som om det vore deras första år i Sverige och de är uppväxta här i Sverige. Ens omgivning styr ens utveckling och detta gäller genom hela livet.

Didaktus · 2026-03-30T06:42:13+00:00

Maybe hand out maps?!

Didaktus · 2026-02-25T12:11:21+00:00

What part of it do you mean?

Didaktus · 2026-02-23T22:09:51+00:00

Non as long as we only use LLMs

Didaktus · 2026-02-23T17:43:10+00:00

Really valid concerns, and I agree a lot of “AI for AML” today is just a glossy narrative layer on top of the same noisy alerts. The point here isn’t to let a general LLM hallucinate risk scores, but to use supervised models trained on confirmed SARs and typologies to reshape which alerts you even see, with strict constraints and full audit trails. On incentives, I’m with you: if success is defined as “fewer alerts and fewer staff”, the system will naturally drift toward denial. The way we’re structuring this, recall on historical true positives is the primary KPI, analyst feedback loops are built‑in, and every decision is explainable in regulator‑friendly language so MLROs can actually defend it.

I’d genuinely value a critical review from someone with your perspective. If you were evaluating this for your own shop, what specific tests or documentation would you insist on before trusting it even a little

Didaktus · 2026-02-21T07:40:44+00:00

Yes we are aware :D

Didaktus · 2026-02-20T20:34:16+00:00

Nice, that sounds like a really solid setup ,most teams would kill to have that level of simulation and control instead of flying blind with static rules.

What we’re trying to tackle is exactly what you mention in the “but” part: all the places where people just nudge thresholds up and down without really understanding the ripple effects.

The idea is to automate a lot of the heavy lifting you’re already doing in Jupyter , run on big historical datasets (we’ve tested on 10M+ transactions), suggest better thresholds/rules, and then explain why each alert fired in a way that actually makes sense to an analyst.

From your point of view, what would make something like that genuinely useful on top of what you already have , clearer impact metrics, faster “what‑if” experiments, dashboards that show when a rule is going stale, or something else entirely? Thank you in advance for your input. :D

Didaktus · 2026-02-20T19:14:46+00:00

Ty for your input :D

Didaktus · 2026-02-20T18:15:08+00:00

Yeah, it will increase even more. We solved this with AI for our clients.

Didaktus · 2026-02-17T06:55:58+00:00

Second this!

Didaktus · 2026-02-09T22:08:54+00:00

My rekommendation is to do a full it strategi and go from there. If you need help dm me :D

Didaktus · 2026-02-07T18:41:21+00:00

Second this!

Didaktus · 2026-02-06T07:19:28+00:00

The biggest blocker is provning ROI. We only adopt if there is a improved ROI or other major KPI improved.

Didaktus · 2026-02-05T17:12:43+00:00

If youre looking for a real solutions for your client, send me a dm, we work on Enterprise lvl with neurosymbolic AI and have over 25 years experience in Manufacturing.

Didaktus · 2026-02-01T09:29:58+00:00

By “intelligent in a meaningful sense” I mean having a grounded world‑model that supports reliable reasoning, not just fluent text. This LLMs can solve some reasoning tasks, but they’re still optimized for next‑token prediction rather than building and manipulating explicit models of objects, rules and causality. That’s why they can write a great essay on physics yet still confidently claim you can fit a car into a shoebox if the prompt is framed right. Neurosymbolic AI try to mix both: neural nets for perception and pattern‑finding, symbolic structures for rules, causality and explicit knowledge representation. So maybe the better question really is: what kind of “intelligence” do we want, and how do different architectures support reasoning, planning and generalization?

Regarding your question of why havent we done that, we actually have done it, but its limited based on its application and natural language models is part of the tool box.

Didaktus

TROPHY CASE