davidajackson

What are your favorite reasoning/compaction strategies for saving token spend, and why?

If you had to project what kind of pattern we'll see in inference cost v.s. time, what would you predict? Over the next 2, 5, 10+ years?

Prompts and prompt rot could potentially be solved by dynamic injection of relevant, embedded snippets to dynamically build prompts. Right now most company's prompts are too small to suffer from such bloat, but I'm guessing soon we'll see it.

Have any of you tried this? What was the LOE and did you benchmark it? What did you find?

Given a system with N components and M pairwise connections between said N components, there exists infinite sequences of [component, command, ...] for a series of operations. A component displays data and a command obviously executes a command.

Has anyone here done research on using an agant to select happy paths to test based on user intent? Is there literature on this? Seems like a cost, compute, intent optimization problem.

Assume latency is a restriction.

Seems like something some AI research folks here can chime in on. I have my own opinions but want to hear what the community thinks.

Does anyone here have a lot of knowledge on neuromorphic computing, or has worked in the space? What do you think of it? Also, do you see any ethical issues with this type of engineering...

In this thread I would like to discuss the interesting ways we've found to increase model accuracy when analyzing images. I have been learning about vision models and trying a few different strategies, to varying degrees of success, and would like to brainstorm a bit further.

To that end, I have a few questions for HN:

What's your experience with bounding boxes?

What's your experience with different models/what are your favorites?

What's your experience with triaging extraction errors while managing cost?

Wanted to have a brief discussion here as to whether you see A2A as the 'final state' for most AI automation. Are there any alternative patterns that you feel might be competitive, or better than A2A? Thoughts on A2E?

Do self driving cars ever make assumptions about the lack of desirability of a lane if there is no one in it? While counterintuitive, sometimes that is an indication that there might be a parked car not currently visible etc. This has struck me as a curious problem where cars would actually observe other car's decisions ahead to guess that 'something is up'.

I have had a theory for a while that economic growth or the economy in terms of CAGR will go to 0% or becomes linear with population as the population grows. This in my mind aligns with the opportunities for lifestyle improvements going to 0 (we already have the internet, we already have food, shelter etc.) so this is no new market to cover/no new businesses to invent?

Has this topic been discussed or debated anywhere? Has anyone with this same theory done any mathematical projections?

Is there evidence that understanding causality (action -> reaction, cause -> effect, etc.) is instinctive or does it need to be trained in humans? It seems obvious that humans need to be taught some forms of logic, like logical fallacies, but are there some that are instinctive? How has this been 'proved'?

Siri is a really bad product when compared to GPT. Why has it taken Apple so long to get AI right?

I see some different names thrown around for this concept. Names aside, will this be the future, or do we anticipate humans sticking with the current hardware path? What are the performance or space tradeoffs of the two different system approaches?

It's been entertaining reading about the OpenAI-Meta talent wars. I thought it would be an interesting discussion to ask some OpenAI employees here how they got an 'in' to one of the most challenging companies to join.

Obviously, with the levels of talent on here, many of us are more founder-oriented/already have great gigs, but I'm curious if there were any special processes or connections you had to get the job. No agenda here :) just want to hear more about this.

Any more details on uses here? I read a post from Stripe on this. Any other companies or any of you using these successfully?

FYI... has anyone here considered how to represent background information (background context) at the beginning of a transformer sequence? Specialized tokens that refer to user attributes (a token preamble, if you will...).

Micropayments? Uselessness? I'd like to hear some thoughts.