4 ms·

I'm surprised there's not more discussion about potential inflection points here. When technology gets faster, it opens up whole new classes of UX that were har

I'm surprised there's not more discussion about potential inflection points here. When technology gets faster, it opens up whole new classes of UX that were hard to predict For example, faster internet didn't mean being able to view 100x as many HTML4 web pages. It brought SaaS, streaming media and interactivity. I'm not good at predicting, but some ideas: 1. All information gets augmented in real time with personalised context. 2. AI interaction seems more like find-as-you-type than a back and forth. 3. AI produces many outputs to pick from. Either the human, AI, or another system can do the deciding. Even if it's last year's model, speeding up LLM inference could open up all sorts of opportunities.

tybit 2mo ago
Yes, this is a great point and it’s even one that the Cerebras CEO spruiks for his own chips. Talaas has gone furthest on the spectrum here, so seems to have the most potential to evolve the use cases.
amelius 2mo ago
I think the most important direction will be: you spawn hundreds of agents at the same time, and let them work in a breadth-first search style. So you will not necessarily get your answers much faster, but they will be much more thoroughly researched. And if you do want faster responses, you can do that at the expense of quality.
- petra 2mo ago
  You could probably do real-time deep research using that method, and than summarize and ask questions about the results. That is a probably a significant jump in search quality for many queries, that people didn't take the time to research properly.
overfeed 2mo ago
4. Pervasive , distributed dragnet surveillance under the misrepresentation that it's not a search until a human pulls the data. But a small on-device "E2E preserving" "safety" model that runs on your phone and snitches when illegal communication content is suspected. Edit: also consider centralized Room-641A-type surveillance when models summarize and/or flag all calls processed by public telephony
- dave1010uk 2mo ago
  I hope this doesn't come to BCI.
  - bigyabai 2mo ago
    BCI will only arrive once this style of monitoring can be enforced.
bearjaws 2mo ago
You could quite literally make an OS that generates your software ahead of you, like this VibeOS demo but lightning fast. https://youtu.be/7NfyZhV1dKM?t=53 https://youtu.be/7NfyZhV1dKM?t=53 Imagine this demo but the apps render in real time generating real code. Obviously not valuable because we have OS today, but could be your companies "WorkOS"
dmead 2mo ago
robotic probes on mars could run science experiments and report results on their own. pacemakers could do deep analysis of heart signals and report problems.
barbazoo 2mo ago
Right, instead of just having more LLM conversations as they get faster and cheaper we'll find products having AI that never had it before. How about an actually smart thermostat that checks the weather and possibly makes decisions more like a human would i.e. tool calling, judgement, preference, history, personal plans. Sure we have thermostats and you can configure rules and data sources, hook up Google calendar, etc but it has to be all predetermined and breaks as soon as anything stops working. AI could make this less brittle. AI agents are more flexible.

tybit 2mo ago

Yes, this is a great point and it’s even one that the Cerebras CEO spruiks for his own chips. Talaas has gone furthest on the spectrum here, so seems to have the most potential to evolve the use cases.

amelius 2mo ago

I think the most important direction will be: you spawn hundreds of agents at the same time, and let them work in a breadth-first search style. So you will not necessarily get your answers much faster, but they will be much more thoroughly researched. And if you do want faster responses, you can do that at the expense of quality.

petra 2mo ago
You could probably do real-time deep research using that method, and than summarize and ask questions about the results. That is a probably a significant jump in search quality for many queries, that people didn't take the time to research properly.

overfeed 2mo ago

4. Pervasive , distributed dragnet surveillance under the misrepresentation that it's not a search until a human pulls the data. But a small on-device "E2E preserving" "safety" model that runs on your phone and snitches when illegal communication content is suspected. Edit: also consider centralized Room-641A-type surveillance when models summarize and/or flag all calls processed by public telephony

dave1010uk 2mo ago
I hope this doesn't come to BCI.
- bigyabai 2mo ago
  BCI will only arrive once this style of monitoring can be enforced.

bearjaws 2mo ago

You could quite literally make an OS that generates your software ahead of you, like this VibeOS demo but lightning fast. https://youtu.be/7NfyZhV1dKM?t=53 https://youtu.be/7NfyZhV1dKM?t=53 Imagine this demo but the apps render in real time generating real code. Obviously not valuable because we have OS today, but could be your companies "WorkOS"

dmead 2mo ago

robotic probes on mars could run science experiments and report results on their own. pacemakers could do deep analysis of heart signals and report problems.

barbazoo 2mo ago

Right, instead of just having more LLM conversations as they get faster and cheaper we'll find products having AI that never had it before. How about an actually smart thermostat that checks the weather and possibly makes decisions more like a human would i.e. tool calling, judgement, preference, history, personal plans. Sure we have thermostats and you can configure rules and data sources, hook up Google calendar, etc but it has to be all predetermined and breaks as soon as anything stops working. AI could make this less brittle. AI agents are more flexible.