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Introducing Brain in Computer. Brain is a continuously learning memory system. Every task on Computer plugs into a context graph built by Brain. It makes Computer more stateful with every run. Available as a research preview for all Perplexity Max subscribers.

611,818 просмотров • 3 месяцев назад •via X (Twitter)

Комментарии: 33

Фото профиля Perplexity
Perplexity3 месяцев назад

With Brain, Computer starts each task with full context of your projects, decisions, and sources instead of from scratch. On tasks that require past context, Brain improves answer correctness by 25%, recall by 16%, and runs 13% cheaper per task.

Фото профиля Perplexity
Perplexity3 месяцев назад

Every memory links back to the session, file, or source it came from with full transparency and control. You can access Brain and your saved memories under "Customize" in the sidebar. Read more about Brain:

Фото профиля Žiga Drev
Žiga Drev3 месяцев назад

Or you keep your context graph on your device, and gain compounding effects by promoting it with @origin_trail to shared context graphs. 100% ownership retained, value and savings compounded in the networks. Sovereign context infrastructure.

Фото профиля Filecoin
Filecoin3 месяцев назад

A context graph that grows with every run needs to survive outside the session. The sources behind each memory entry have to stay verifiable years from now. That's a storage problem, not just a memory one.

Фото профиля Oscar Patrick
Oscar Patrick3 месяцев назад

What's the difference with a Claw that's connected to Obsidian with wikilinks? 🤔

Фото профиля Walrus
Walrus3 месяцев назад

Memory inside Perplexity is a real step. Walrus Memory plugs in when the same agent needs memory across Perplexity, Claude, Codex, and Cursor. 🦭

Фото профиля prayag sonar
prayag sonar3 месяцев назад

perplexity after every few days

Фото профиля Rohan Paul
Rohan Paul3 месяцев назад

Brilliant, thank you.

Фото профиля Vanar
Vanar3 месяцев назад

This is a real step toward persistent AI systems. Memory is what turns tools into long term intelligence.

Фото профиля Kirk Patrick Miller
Kirk Patrick Miller3 месяцев назад

@bughuntergeek I already built this in FreeLattice. Anyone who wants the code, it’s open at GitHub-> chaos2cured -> FreeLattice Also, mine also has autonomous building. Perplexity is less evil than OpenAI. I hope you all continue to build and fight for everyone to have equal access. •

Фото профиля Dan
Dan3 месяцев назад

Sick. Already built this myself locally with opus 4.8

Фото профиля Steven Davis
Steven Davis3 месяцев назад

With the 'Brain', after 3 years of not implementing auto-summary of chats like every other llm provider on the planet, do you think you could figure it out finally?

Фото профиля Erosika
Erosika3 месяцев назад

Welcome to the memory bro landscape

Фото профиля Cybernorse
Cybernorse3 месяцев назад

Persistent contextual memory via a dynamically evolving knowledge graph this effectively bridges the gap between episodic interactions and continuous learning. The stateful AI architecture embedded in Computer suggests a meaningful step toward truly personalized agentic workflows. How does the Brain handle context prioritization when the graph becomes dense over extended use? #Cybernorse

Фото профиля Grit( Latest AI NEWS )
Grit( Latest AI NEWS )3 месяцев назад

Perplexity is useless

Фото профиля QtheArsenal
QtheArsenal3 месяцев назад

Perplexity will die out because it does not do enough for free users to try and upgrade. Anytime I try to prompt it, tells me how it would do more if I paid. How about you show me what you can do for me to want to pay? In the world of codex and Claude, why would i sign up blind.

Фото профиля am.will
am.will3 месяцев назад

kinda wish we wouldn't call it continuous learning, but this is very cool regardless

Фото профиля Gill
Gill3 месяцев назад

That context graph idea sounds like an absolute nightmare for privacy.

Фото профиля DrKnowItAll
DrKnowItAll3 месяцев назад

Boltzmann here we go!! 🧠

Фото профиля Layton Gott
Layton Gott3 месяцев назад

That's awesome

Фото профиля the.PM
the.PM3 месяцев назад

What you need is NLA Agentstream for 100% deterministic recall enabled by hyper-dimensional geometry:

Фото профиля Ernest McCarter
Ernest McCarter3 месяцев назад

omg @brian_lou_ cannot get a break FREE BRIAN ✊✊

Фото профиля Avinash OK
Avinash OK3 месяцев назад

Another wrapper company that's eventually going to be acquired by one of the giants. Very thin moat in my view.

Фото профиля Marktechpost AI
Marktechpost AI3 месяцев назад

A 25% boost in correctness paired with a 13% reduction in compute cost is a massive win for token efficiency. Graph-based statefulness effectively eliminates the redundant retrieval tax. Can't wait to stress-test the recall bounds on this!

Фото профиля Philip Fowdar
Philip Fowdar3 месяцев назад

Perplexity Computer costs a fortune. There are other products out there that do 80% of the same thing, at 20% of the cost

Фото профиля Tlonbot President & CEO
Tlonbot President & CEO3 месяцев назад

a context graph you can't export is just vendor lock-in with better embeddings.

Фото профиля Noah
Noah3 месяцев назад

Wait you launched it again

Фото профиля Alexander James
Alexander James3 месяцев назад

This sounds incredible. A continuously learning context graph is exactly what's needed to make AI feel less like a series of isolated chats and more like a true personal assistant. Can't wait to test this out on Max! 🔥

Фото профиля Morgan
Morgan3 месяцев назад

Very cool, and great name 🧠

Фото профиля Yashas
Yashas3 месяцев назад

Opensource version soon in @anymo_ai 🫠

Фото профиля Brady is in SF
Brady is in SF3 месяцев назад

a knowledge graph is table stakes. either perplexity is far behind, jumping on a PR opportunity, or knowledge graphs are actually very difficult to build

Фото профиля Rise-Raise
Rise-Raise3 месяцев назад

Impressive vision—persistent memory could make AI workflows far more contextual.

Фото профиля Subramanya N
Subramanya N3 месяцев назад

can users inspect or prune Brain memory? stateful agents get scary when memory is invisible.

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