To me this is the weakest claim of the article. This claim been thrown around endlessly without proof.

https://fred.stlouisfed.org/series/IHLIDXUSTPSOFTDEVE

Software Engineer job openings for instance is at 2 year high (still far lower than covid dislocations though), but arguably all Enterprise AI was built or deployed in the last two years. We should have seen a crash in the job openings if the AI job replacement claim was correct.

This is something I've spend some time thinking about (personally written article, not AI slop): https://www.signalbloom.ai/posts/why-task-proficiency-doesnt...

Comments URL: https://news.ycombinator.com/item?id=47378806

Points: 2

# Comments: 0

1. The models/pricing page should be linked from the top perhaps as that is the most interesting part to most users. You have mentioned some impressive numbers (e.g. GLM5~220 tok/s $1.20 in · $3.50 out) but those are way down in the page and many would miss it

2. When looking for inference, I always look at 3 things: which models are supported, at which quantization and what is the cached input pricing (this is way more important than headline pricing for agentic loops). You have the info about the first on the site but not 2 and 3. Would definitely like to know!

@dang, if you read this, why don't we implement honeypots to catch bots? Like having an empty or invisible field while posting/commenting that a human would never fill in

Comments URL: https://news.ycombinator.com/item?id=47299261

Points: 2

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=47276425

Points: 5

# Comments: 6

Suppose you prompted the underlying LLM with "You are an expert reviewer in..." and a bunch of instructions followed by the paper. LLM knows from the training that 'expert reviewer' is an important term (skipping over and oversimplifying here) and my response should be framed as what I know an expert reviewer would write. LLMs are good at picking up (or copying) the patterns of response, but the underlying layer that evaluates things against a structural and logical understanding is missing. So, in corner cases, you get responses that are framed impressively but do not contain any meaningful inputs. This trait makes LLMs great at demos but weak at consistently finding novel interesting things.

If the above is true, the author will find after several reviews that the agent they use keeps picking up on the same/similar things (collapsed behavior that makes it good at coding type tasks) and is blind to some other obvious things it should have picked up on. This is not a criticism, many humans are often just as collapsed in their 'reasoning'.

LLMs are good at 8 out of 10 tasks, but you don't know which 8.

Comments URL: https://news.ycombinator.com/item?id=47002381

Points: 1

# Comments: 0

I am sure all of us have had anecdotal experiences where you ask the agent to do something high-stakes and it starts acting haphazardly in a manner no human would ever act. This is what makes me think that the current wave of AI is task automation more than measured, appropriate reactions, perhaps because most of those happen as a mental process and are not part of training data.

- Polls SEC continuously at small intervals

- Fetches all variants of the 13F since the last poll

- Resolves every filing to its effective manager (one filing can contain data for multiple filers or proxy statements)

- Resolves every ticker in each filing to its effective instrument

- Updates the holdings data for the filer (e.g. https://www.signalbloom.ai/13f/filer/point72-asset-managemen...)

- Updates the ticker's 'current view' (re-calculating the aggregate current ownership live) e.g. https://www.signalbloom.ai/13f/ticker/NVDA

- Majority of 13F filers are also registered investment advisers, it links them intelligently (e.g. Blackrock as a 13F filer https://www.signalbloom.ai/13f/filer/blackrock-fund-advisors vs Blackrock as Investment Adviser https://www.signalbloom.ai/investment-adviser/blackrock-fund...)

Reports for: Every single one of over 10k asset managers that files 13F

Completely Free to use for non-commercial uses! Would love to get your feedback as I just finished building this. Thank you!

Comments URL: https://news.ycombinator.com/item?id=46871519

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=46526336

Points: 2

# Comments: 0