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VERSION:2.0
PRODID:-//Palaner//palaner Single Event//EN
METHOD:PUBLISH
CALSCALE:GREGORIAN
BEGIN:VEVENT
UID:luma-46e5de0ed7@palaner.app
DTSTAMP:20260802T155821Z
DTSTART:20260809T113000Z
DTEND:20260809T130000Z
SUMMARY:The Human Code
LOCATION:Dots-In
DESCRIPTION:Saved in Palaner as: saved\n\nPalaner match: 25% · why: matches
  your usual pattern\n\nThe Human Code\nA working roundtable for developers
  building beyond correlation-based personalisation.\nLLMs understand langu
 age remarkably well. Understanding an individual is a different problem.\n
 Most personalisation systems still rely on patterns observed across a popu
 lation and map those patterns onto the person in front of the model. That 
 works—until shifting intent\, conflicting behaviour\, changing context\, o
 r individual causality breaks the assumption.\nThe Human Code brings toget
 her 30 developers\, ML engineers\, researchers\, and technical founders wh
 o have encountered that ceiling and want to work through it together.\nNo 
 stage. No keynote. No sales pitch. No product showcase.\nBring one real pr
 oblem. The room will work on it with you.\nWhat to expect\n5:00–5:15 PM — 
 Arrivals\nCheck in\, meet the room\, and settle in. We begin the working s
 ession at 5:15 PM sharp.\n5:15–6:00 PM — Live model comparison\nWe will ru
 n an LLM and an LBM—Large Behavioural Model—on the same individual-level i
 nference task.\nThis is not a polished demo reel. It is an open working se
 ssion.\nParticipants can challenge the assumptions\, introduce new inputs\
 , question the task design\, and attempt to break both approaches. If the 
 room believes the example is too convenient\, we will use a participant’s 
 problem instead.\n6:00–7:15 PM — The working roundtable\nEvery participant
  gets the floor.\nBring one specific use case where personalisation\, user
  modelling\, or individual-level inference is failing.\nFor example:\n“How
  do I model shifting intent when recent behaviour contradicts the user pro
 file?”\nis more useful than:\n“How should I improve personalisation?”\nThe
  room will examine each problem together. Participants working with causal
  methods\, graphs\, reinforcement learning\, state-based models\, memory s
 ystems\, embeddings\, or other approaches will have equal space to contrib
 ute.\nThis is a shared blackboard—not a Dots-In showcase.\n7:15–8:00 PM — 
 Patterns\, disagreements and open conversation\nWe will identify the probl
 ems that repeated across the room\, where different approaches converged\,
  and where they fundamentally disagreed.\nThe final part of the evening is
  left open for deeper conversations\, introductions\, exchanged notes\, an
 d possible collaborations.\nHow the room works\nCome with a problem\, not 
 a product pitch.\nThe strongest contributions will be specific\, technical
 \, and grounded in something you are currently building or researching.\nY
 ou do not need to arrive with an answer. You should arrive ready to explai
 n the problem clearly\, challenge assumptions respectfully\, and help othe
 rs examine theirs.\nFifteen minutes into the session\, nobody should care 
 who is hosting.\nWho this is for\nThis session is designed for:\nDeveloper
 s and ML engineers building products with LLMs\nTechnical founders working
  on personalisation or user modelling\nResearchers exploring behavioural\,
  causal\, graph-based\, state-based\, or reinforcement-learning approaches
 \nBuilders dealing with changing intent\, sparse individual data\, contrad
 ictory behaviour\, long-term memory\, or context-sensitive inference\nThis
  room may not be useful yet if you have never worked directly on these pro
 blems.\nIf you have\, you will probably recognise the questions—and the pe
 ople asking them.\nWhat you will leave with\nA new way to frame your probl
 em.\nA technical direction worth testing.\nA person you will call the foll
 owing week.\nIdeally\, all three.\nHosted by Dots-In\nHosted by Suraj Bisw
 as\, Founder and CEO of Dots-In.\nDots-In is building a Large Behavioural 
 Model focused on individual behavioural state\, causality\, memory\, and c
 ontext-aware personalisation.\nThe session is intentionally structured as 
 an open working roundtable rather than a product presentation.\nLogistics\
 nDate: Sunday\, 9 August 2026Time: 5:00 PM–8:00 PM ISTVenue: Dots-In HQ\, 
 27\, 4th Floor\, 501\, 2nd Cross Road\, KHB Colony\, 5th Block\, Koramanga
 la\, Bengaluru 560095Capacity: 30 participantsRegistration: Approval requi
 redEntry: FreeFood and refreshments: Provided\nPlease arrive on time. The 
 working session begins at 5:15 PM.\nThis event is part of Basecamp\, a com
 munity-powered tech week in Bengaluru bringing founders\, builders\, and o
 perators together. Basecamp is free for the community and powered by the c
 ommunity.
URL:https://luma.com/ugd3kdlf
CATEGORIES:palaner,saved
STATUS:TENTATIVE
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