nlpnerd

7 ms·

61.
by nlpnerd 1y ago
Ex quant researcher in an equity hedge fund.
62.
by nlpnerd 1y ago
Yup, doing that.
63.
by nlpnerd 1y ago
1) Workflow issues. A chatbot is not the best interface for accomplishing the typical tasks an investor or analyst needs to do. Our workflow are often start around a watchlist/portfolio and news. 2) Most LLM or agentic applications don
64.
Show HN: A Unique User-in-the-Loop Agent for Investment Research(vector.deepinsightlabs.ai)
3 points by nlpnerd 1y ago|2 comments
65.
Ask HN: How you network in NYC as a founder from out of town
2 points by nlpnerd 1y ago|4 comments
66.
by nlpnerd 1y ago
Definitely makes a lot less economic sense today. Takes easily months of full time work to raise from investors. That level of effort in the early days of a startup could put mean practically putting your pre-MVP/MVP on hold for months
67.
by nlpnerd 1y ago
Common failure mode is people. Most processes eventually fail when people start to slack on the little things, then the big things. Every part of knowledge management is tedious from capturing things to keeping them organized and discoverab
68.
Perplexity Finance Integrates SEC-Edgar(twitter.com)
1 points by nlpnerd 1y ago|1 comments
69.
by nlpnerd 1y ago
Perplexity just rolled out direct access to the SEC EDGAR database across all their interfaces (Search, Research, and Labs). That means retail investors and researchers now have LLM-friendly access to 10-Ks, 10-Qs, 8-Ks, etc., with real-tim
70.
Tariffs, Treasuries, and a Tumbling Dollar(deepinsightlabs.ai)
1 points by nlpnerd 1y ago|0 comments
71.
by nlpnerd 2y ago
I have always believed that Chain of Thought basically acts as a form of regularization. LLMs are fundamentally next token predictors without any form or notion of logic, reasoning etc and is as likely (as a probabilistic model) to produce
72.
Awesome AI Agents(github.com)
1 points by nlpnerd 2y ago|0 comments
73.
by nlpnerd 2y ago
That is a slight exaggeration, extrapolation on the author's part. What happened was that RL training led to some emergent behavior in R1-Zero (chain-of-thought, and reflection) without being prompted or trained for explicitly. Don&#x2
74.
by nlpnerd 3y ago
They don't. This is probably one reason why VCs invest in these companies. There is a natural moat since there is only a very finite number of people in the world has the right experience to raise, and only those who can raise can ever
75.
by nlpnerd 3y ago
Not a joke. It's fairly common in South East Asia and even has a name -- White Coffee.
76.
by nlpnerd 3y ago
Attitude matters more if we are talking about the longer term. 6 months to a year in the less credential-ed devs will probably be independent. The experienced but uninterested devs are unlikely to have become more interested.
77.
by nlpnerd 3y ago
Interesting perspective from the author. Insightful to note that VCs perhaps are not as smart as they would like investors and the public to believe (which I totally agree with, they only human...at least for now) or simply leveraging hype
78.
The Market for AI Companies(finbarrtimbers.substack.com)
1 points by nlpnerd 3y ago|1 comments
79.
by nlpnerd 3y ago
What did you guys do to bring down the latency so much?